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• Published: 23 May 2024

Family communication patterns, self-efficacy, and adolescent online prosocial behavior: a moderated mediation model

• Weizhen Zhan   ORCID: orcid.org/0009-0003-8497-8611 1 &
• Zhenwu You   ORCID: orcid.org/0000-0003-1581-5264 1  

Humanities and Social Sciences Communications volume  11 , Article number:  658 ( 2024 ) Cite this article

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• Cultural and media studies

As technology has been developing by leaps and bounds, concerns regarding adolescent online behavioral patterns have garnered significant attention. Nevertheless, current research exhibits limitations in both perspective and depth. Consequently, this study introduces a moderated mediation model to investigate whether the mediating effect of self-efficacy and the moderating effect of emotional regulation strategies are valid in the relationship between family communication patterns and adolescent online prosocial behavior. A questionnaire survey encompassing 1183 adolescents across 12 schools in three cities of mainland China was conducted. The findings reveal that conversation orientation contributes to the augmentation of adolescents’ self-efficacy and online prosocial behavior, whereas conformity orientation follows a reversed trend. Furthermore, self-efficacy serves as a mediator in the relationship between conversation orientation and conformity orientation, influencing adolescent online prosocial behavior in both positive and negative manners. Additionally, this study underscores the significance of emotion regulation strategies; cognitive reappraisal not only reinforces the positive effects of conversation orientation, but also mitigates the adverse effects of conformity orientation, while expressive suppression demonstrates the inverse effect. This research yields a comprehensive and insightful understanding of adolescent online prosocial behavior, furnishing a valuable theoretical foundation for future research and practice in family education.

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Introduction.

The evolution of the internet has ushered in profound changes in the society people live in. As Negroponte ( 2015 ) succinctly put it, “Human learning, working, and entertainment methods, in short, human existence, have all become digitized.” The advent of the internet has introduced novel behavioral and communicative paradigms (Gosling and Mason, 2015 ). According to the 52nd China Internet Development Status Report, as of June 2023, 13.9% internet users in China are aged 10–19, which accounted for approximately 150 million (China Internet Network Information Center, 2023 ). It is evident that adolescents are highly active in online social behaviors, like online information dissemination and collective behaviors. Current research has primarily focused on negative online behaviors among adolescents, such as cyberbullying, online sexual harassment, and cyber violence (Festl and Quandt, 2016 ; Taylor et al., 2019 ; Soriano-Ayala et al., 2022 ). However, research on positive online behavioral of adolescents also emerged, where they engage in knowledge sharing, mutual assistance (Zulkifli et al., 2020 ), and emotional support (Saling et al., 2019 ).

In contrast to offline prosocial behaviors, online prosocial behaviors disseminate faster, utilize a more diverse array of communication channels, and cater to a broader audience. Online prosocial behaviors foster a conducive online environment: countering the adverse effects of cyberattacks and rumor dissemination, while promoting the well-being of others, thus it facilitates a positive social development (Fan et al., 2020 ). Some research indicates that adolescent online prosocial behavior is not expected to receive spiritual or material rewards from external sources. However, this does not rule out the intrinsic rewards such as the sense of pleasure, satisfaction, and the achievement of self-worth that individuals may experience from doing good deeds (Zheng, 2013 ). These behaviors not only foster positive psychological traits in adolescents (Zheng et al., 2018 ) but also bolster their subjective well-being and sense of purpose (Post, 2005 ). Thus, adolescent online prosocial behaviors benefit individuals, communities, and the society at large, contributing to social harmony and development (Lemmens et al., 2009 ). Consequently, this study aims to delve into the multifaceted factors influencing adolescent online prosocial behaviors and elucidate the underlying mechanisms, thereby fostering a comprehensive understanding of this phenomenon.

In the antecedent variables affecting adolescent online prosocial behavior, family environmental factors cannot be overlooked. Family functions as a significant reference group for individuals during the decision-making process (North and Kotz, 2001 ), and “nowhere is its influence on individual behaviors more profound than in the area of communicative behaviors” (Koerner and Fitzpatrick, 2002b ). Family dynamics imbue individuals with shared worldviews, values, and belief systems (Fitzpatrick and Ritchie, 1994 ; Reiss, 1981 ), which ultimately shape their perceptions, psychological states, and behaviors (Schrodt et al., 2008 ). Research indicates that parent-child communication significantly influences prosocial behavior. Deficient family communication patterns correlate with heightened problem behaviors among adolescents (Wang et al., 2004 ). Conversely, high-quality parent-child interactions not only fortify familial bonds but also instill a sense of life purpose, foster interpersonal relationships, and enhance social adaptability, thereby elevating individual prosocial levels (Jafary et al., 2011 ). Hence, family communication patterns serve as a promising avenue for investigating adolescent online prosocial behaviors.

Previous studies have highlighted environmental and individual factors as the primary influences of prosocial behavior. Family, as one of the primary socialization environments during adolescent development, particularly exerts significant influence on adolescent self-efficacy through the transmission of values and social norms by parents (Ajayi and Olamijuwon, 2019 ). Social cognitive theory underscores the critical role of self-efficacy in individuals’ self-assessment of their capabilities (Caprara and Steca, 2005 ). Therefore, in exploring the relationship between family communication patterns and adolescent online behavior, introducing self-efficacy can deepen our understanding of the mechanisms through which individual factors operate in this process. However, very few research examined the impact of both family communication patterns and self-efficacy on adolescent online prosocial behavior. Thus, this study seeks to explore the relationship between various family communication patterns and self-efficacy, along with their interactive effects, to elucidate how the family environment shapes adolescents’ perceptions of their abilities and consequently influences their online prosocial behavior.

Simultaneously, emotion, regarded as a core driving force in individual development (Campos et al., 1989 ), plays a pivotal role in influencing the adaptation to society and psychological well-being. Effective emotion regulation is imperative for maintaining individuals’ social functioning and fostering interpersonal relationships (Gross and John, 2003 ). Emotion regulation strategies, an internal factor of individuals, have garnered attention in the study of family environmental factors and prosocial behavior (Song et al., 2013 ). Denham ( 1998 ) pointed out that the interaction between caregivers and children is a fundamental factor influencing children’s emotional regulation, which is the root cause of individual differences in emotional regulation among young children. Parenting styles, such as communication patterns, significantly impact children’s emotion regulation development (LaFreniere, 2000 ). Additionally, research has also found correlations between emotion regulation and prosocial behavior (Kwon and López-Pérez, 2021 ), as well as self-efficacy (Liu et al., 2011 ). Hence, this study aims to explore the role of emotion regulation strategies in the relationship between family communication patterns and adolescent online prosocial behavior.

In conclusion, to comprehensively investigate the mechanisms underlying the influence of family environmental factors and individual factors on adolescent online prosocial behavior, this study endeavors to construct a moderated mediation model. It examines the influence paths of family communication patterns, self-efficacy, and emotion regulation strategies on adolescent online prosocial behavior, as well as the interactions among these factors. Compared to previous studies, the innovation of this paper mainly manifests in three aspects: First, it explicitly discusses the impact mechanism of different types of family communication patterns on self-efficacy and adolescent online prosocial behavior; Second, it investigates the influence of self-efficacy on adolescent online prosocial behavior from a holistic perspective; Third, it introduces emotion regulation strategies for examination and verifies their mechanism of action in adolescent online prosocial behavior.

Literature review and research hypothesis

Definition of online prosocial behavior.

Online Prosocial Behavior (OB) is a burgeoning phenomenon associated with the evolution of the Internet, particularly the widespread adoption of mobile devices such as smartphones and computers. Despite its increasing prevalence, the concept remains intricate with multiple interpretations. Scholars often delineate online prosocial behavior by drawing upon the unique characteristics of the Internet. For instance, Zeng et al., ( 2022 ) propose that, compared to offline environments, cyberspace affords users additional time and space to care for others. Similarly, Zheng et al., ( 2018 ) contend that the anonymity provided by the Internet can alleviate users’ social pressure, fostering a greater willingness to assist others. However, these perspectives emphasize the medium carrying online prosocial behavior and relatively overlook exploring the relevant elements and behavioral characteristics of online prosocial behavior itself.

To gain a profound understanding of OB, it is imperative to scrutinize the definition of prosocial behavior and subsequently delineate how OB diverges from it. In the 1980s, Eisenberg and Miller ( 1987 ) defined prosocial behavior as a voluntary action intended to benefit others, based on the outcome of the behavior. More recently, Pfattheicher et al. ( 2022 ) approach prosocial behavior from a motivational standpoint, characterizing it as actions intended to benefit others rather than oneself. In summary, this study defines OB as voluntary conduct in the online realm aimed at benefiting others, encompassing activities like offering comfort, sharing willingly, providing guidance, and so forth. In contrast to traditional prosocial behavior, OB not only retains the fundamental connotations of prosocial behavior but also extends its boundaries, presenting a more convenient alternative to offline prosocial behavior. Noteworthy instances during the COVID-19 pandemic spotlighted how adolescents globally shared experiences and offered emotional support through online platforms (Pavarini et al., 2020 ). Such positive initiatives by peers can contribute to positive emotions like adolescents’ social tolerance and self-confidence (Repper and Carter, 2011 ), suggesting that OB holds the potential to assist adolescents in navigating challenges encountered in their personal growth. However, the current body of research on adolescent online prosocial behavior remains limited, with most studies concentrating on online prosocial behavior in adult samples (Hong et al., 2023 ). Consequently, this paper deems it imperative to specifically explore the driving factors and behavioral mechanisms underlying adolescent online prosocial behavior.

Self-efficacy and adolescent online prosocial behavior

Prosocial behaviors are influenced by individuals’ assessment of their own abilities, such as self-efficacy (Zhan et al., 2023 ). “Self-efficacy,” (SE) originating from Bandura’s social cognitive theory, is a multidisciplinary phenomenon lacking a consistent definition (Drnovšek et al., 2010 ). For example, Bandura ( 1977 ) defines SE as “an individual’s belief in one’s capability to organize and execute the courses of action required to produce given attainments.” Bieschke ( 2006 ) suggests that SE is the ability to assess one’s capability in implementing specific behaviors to achieve expected outcomes. Thus, all psychological processes and behavioral functions are determined by individual mastery of conscious alterations (Maddux, 2013 ).

Social cognitive theory posits that individual behavior is influenced by both personal cognition and environmental factors, with the family being a significant environmental factor affecting individual behavior, and self-efficacy being a crucial cognitive force (Bandura, 2004 ). Personal cognition may impact preferences for knowledge acquisition, information processing, and decision-making. When individuals process information, they become aware of their ability to engage in action (self-efficacy) and the likelihood of engaging in action (intentions) (Barbosa et al., 2007 ). According to these views, individuals can control their thoughts, feelings, and actions, with this control heavily influenced by their SE. SE provides insight into the sources of efficacy judgments that subsequently influence behavior and goal attainment (Boyd and Vozikis, 1994 ). This close relationship between SE and behavior has been supported by abundant empirical evidence across various fields, such as start-up readiness (Adeniyi, 2023 ), and environmental conservation behavior (Merling et al., 2018 ).

From an agentic perspective, SE serves as a motivational factor for individuals’ prosocial behaviors (Li et al., 2022 ). Individuals with high SE are more self-aware, comparing their existing knowledge and experiences with the current situation, and believing they have sufficient capability to address issues positively, thus being more inclined towards engaging in prosocial behaviors (Gong et al., 2021 ). Deng et al. ( 2018 ) conducted a survey among 768 first to third-grade middle school students in Shandong and Chongqing provinces, indicating that SE was the most predictive factor influencing prosocial behavior. Patrick et al. ( 2018 ) found that SE could predict certain types of prosocial behaviors, such as public behaviors, which may provide confidence for adolescents to engage in prosocial behaviors. In the realm of digital media technologies, researchers have discovered that bolstering self-efficacy facilitates individuals’ engagement in online prosocial behavior (Leng et al., 2020 ).

Building upon these insights, this paper posits that SE significantly forecasts adolescent OB; specifically, adolescents exhibiting elevated levels of SE are more inclined to actively participate in OB. Consequently, this paper advances the following research hypothesis:

H1 The higher the level of self-efficacy is, the higher level of online prosocial behavior adolescents will exhibit.

Family communication patterns, self-efficacy, and adolescent online prosocial behavior

Since its inception in the 1970s by American scholars McLeod and Chaffe (1972, as cited in Ritchie and Fitzpatrick, 1990 ), the Family Communication Patterns Theory (FCP) has been extensively utilized by researchers to delve into the dynamics of family communication, with ongoing refinements and evolution to its foundational theory. In the 1990s, Fitzpatrick and Ritchie ( 1994 ) classified FCP into two dimensions: Conversation Orientation (CV) and Conformity Orientation (CF). Within families emphasizing CV, there exists a heightened level of interaction and discussion on diverse subjects, fostering an environment where children can openly articulate their thoughts. Members engage in communication without constraints, and parents exercise minimal influence over their children’s conduct and perspectives. Conversely, in families leaning towards CF, internal communication is limited, and children are expected to adhere strictly to parental expectations to avert discord within the family. Emphasis is placed on uniformity among family members, particularly regarding values and beliefs (Fitzpatrick and Ritchie, 1994 ). FCP posits that the predisposition of family communication patterns has the potential to shape the cognition and behavior of adolescents.

Current research findings suggest a negative correlation between CF and adolescent SE (Fu et al., 2022 ). Scholars elucidate the adverse impact of CF on SE, attributing it to its influence on adolescent psychological well-being. Studies reveal that adolescents in families with high CF are more prone to depression, hindering the development of positive beliefs and manifesting symptoms like heightened loneliness, self-deprecation, and diminished self-esteem (Zhou et al., 2022 ). Notably, not all family communication patterns impede adolescent SE. CV, for instance, is positively associated with adolescent SE (Matteson, 2020 ). Dorrance Hall et al. ( 2016 ) examination of FCP and their impact on students’ SE, stress, and loneliness in the United States and Belgium reveals that CV positively influences SE among American students. In Belgium, significant correlations between CV and student SE were identified through the quality of social suggestions. Further research underscores that, in contrast to CF, CV provides higher social support, quality advice, and self-efficacy for family members (Bevan et al., 2019 ). These enhancements contribute to improved academic and social performance among adolescents. For example, CV positively affects the athletic performance of student-athletes by boosting SE (Erdner and Wright, 2017 ). Adolescents raised in CV families demonstrate greater financial knowledge and enhanced financial self-efficacy (Hanson and Olson, 2018 ).

Building upon these theoretical foundations and empirical findings, this paper posits that family communication patterns influence adolescent self-efficacy. Accordingly, the following hypotheses are proposed:

H2a The more emphasis are placed on conversational orientation in families, the higher levels of self-efficacy adolescents will exhibit.

H2b The more emphasis are placed on conformity orientation in families, the lower levels of self-efficacy adolescents will exhibit.

In the process of adolescent growth, the family shoulders significant responsibilities in nurturing and guiding individuals. Previous research indicates that families favoring CV contribute to adolescents developing positive personality traits and projecting a more amicable demeanor in social interactions. For instance, a study conducted in the United States revealed that children raised in CV families displayed more prosocial behaviors compared to those from CF families (Wilson et al., 2014 ). Some scholars believe that FCP can affect adolescents’ prosocial behaviors because when a family tends toward high-quality communication, it can effectively enhance the affinity and resilience levels of family members (Afifi et al., 2020 ). Further analysis by researchers suggests that CV not only impacts face-to-face interactions among parents and children but also significantly enhances children’s interpersonal skills and the socialization process in technology-mediated online communication (Wang et al., 2018 ). Conversely, an increase in CF diminishes the quality of communication within the family, fostering disagreement and intensifying the marginalization of adolescents (EHall et al., 2022 ). This is detrimental to the development of adolescents’ personal competencies, particularly in problem-solving, social cognition, and prosocial behavior. Building on prior research, this paper posits that adolescents raised in families favoring CV are more likely to exhibit pronounced personal characteristics, such as friendliness and solidarity, potentially leading to higher levels of online prosocial behavior. Conversely, adolescents from families emphasizing CF may demonstrate lower levels of online prosocial behavior. Consequently, the following hypotheses are proposed:

H3a The more emphasis are placed on conversational orientation in families, the higher levels of online social behavior adolescents will exhibit.

H3b The more emphasis are placed on conformity orientation in families, the lower levels of online social behavior adolescents will exhibit.

In addition to direct influences, FCP can also indirectly affect adolescents’ OB through their SE. Social cognitive theory suggests that individual cognition, environment, and behavior are interconnected, mutually influencing one another (de la Fuente et al., 2023 ). On one hand, the family serves as a crucial environment for adolescent development, constituting a significant microsystem that influences their growth. As a fundamental aspect of the family system, interpersonal communication among family members serves as a primary socialization medium, imparting basic interpersonal skills and norms to adolescents by fostering a shared sense of reality (Koerner and Fitzpatrick, 2002 ; Ritchie and Fitzpatrick, 1990 ), thereby significantly influencing individual self-efficacy. On the other hand, individual behavioral choices are shaped by individual cognition, and changes in cognition lead to different behavioral decisions. Furthermore, attentional focus theory suggests that the situational context can alter individuals’ moods, consequently affecting their behavioral outcomes (Chen and Yang, 2020 ). Therefore, self-efficacy, resulting from individuals’ assessment and evaluation of their capabilities, is likely a proximal factor in determining individuals’ choices of online prosocial behaviors, while other environmental factors (such as FCP) may act as distal factors, influencing adolescents’ online prosocial behaviors through the mediating role of proximal factors. Specifically, adolescents nurtured in families favoring CV are likely to exhibit elevated SE levels, fostering a greater willingness to engage in OB. Conversely, adolescents from families with a preference for CF may experience lower levels of SE, potentially resulting in diminished participation in OB. Previous studies have also found that children raised in high CF families often manifest lower SE, leading to challenges in social integration. In contrast, those from CV families demonstrate heightened SE, and equip them with more flexible social coping skills, making it easier for them to live more actively and inspiring them to display increased prosocial behaviors both online and offline (Dorrance Hall et al. ( 2020 ); Segrin et al., 2022 ). Building on this premise, the paper proposes the following research hypotheses:

H4a Self-efficacy plays a positive mediating role between conversation orientation and adolescents’ online prosocial behavior.

H4b Self-efficacy plays a negative mediating role between conformity orientation and adolescents’ online prosocial behavior.

The moderating effect of emotion regulation strategies

Emotion regulation involves the process of individuals influencing which emotions they experience, when they experience them, and how they express these emotions (Gross, 1998 ). Within this process, individuals initially assess the generation, alteration, or response state of their emotions and subsequently employ diverse emotion regulation strategies to achieve specific objectives. Emotion regulation (ER) strategies primarily fall into two categories: Cognitive Reappraisal (CR) and Expressive Suppression (ES) (Gross and John, 2003 ). CR is a cognitive change strategy, involving individuals altering their interpretation of events or situations. This may entail viewing negative events from a more positive cognitive perspective or rationalizing the evaluation of events to regulate their emotions. For example, if a netizen doesn’t promptly respond to an urgent request for assistance, an individual might interpret this delay as the netizen being busy, thereby reducing feelings of disappointment or sadness. On the other hand, ES involves an individual suppressing or concealing emotional expression that is occurring or imminent. For instance, if someone feels anger toward another person, those employing the ES may avoid interacting with that person to conceal their true feelings.

Prior studies have demonstrated that emotions play a moderating role in the correlation between individual cognition and behavior (Cristofaro, 2020 ). Consequently, we posit that diverse emotion regulation strategies may yield distinct effects on the association between family communication patterns and adolescents’ online prosocial behavior. ES can reduce adolescents’ desire to share and express, leading to lower levels of social support, which negatively affects the socialization of adolescents, while CR can reduce negative emotions and enhance the psychological recognition and behavioral presentation of positive emotions, thereby having a positive effect on individuals’ interpersonal communication (Hein et al., 2016 ; Laghi et al., 2018 ). These research findings suggest, to some extent, that CR is more likely than ES to contribute to the manifestation of prosocial behavior in adolescents.

This paper endeavors to investigate the moderating role of ER strategies in the correlation between FCP and adolescents’ OB. Specifically, when adolescents from CV families face emotionally challenging events, employing the CR strategy enables them to perceive the causes and outcomes of stressful events with more positive emotions (Robazza et al., 2023 ), thereby stimulating their online prosocial behavior. Similarly, the CR strategy may buffer the negative impact of conformity orientation on adolescents’ online prosocial behavior. In other words, CR empower adolescents to make positive cognitive evaluations of stressful events, thereby reducing the occurrence of antisocial behavior. Furthermore, adolescents raised in high CF environments, where their emotional expressions and opinions are undervalued by parents, may further diminish their OB when employing the ES. Similarly, adolescents from CV families using the ES during stressful events might compromise their ability to express themselves actively and empathize (Li et al., 2020 ), resulting in passive behaviors like silence or avoidance.

In summary, this paper posits that emotion regulation strategies play a moderating role in the relationship between family communication patterns and adolescents’ online prosocial behavior. Building upon this premise, the paper proposes the following research hypotheses:

H5a Cognitive reappraisal enhances the positive effect of conversation orientation on adolescents’ online prosocial behavior.

H5b Cognitive reappraisal weakens the negative effect of conformity orientation on adolescents’ online prosocial behavior.

H5c Expressive suppression weakens the positive effect of conversation orientation on adolescents’ online prosocial behavior.

H5d Expressive suppression enhances the negative effect of conformity orientation on adolescents’ online prosocial behavior.

This paper also focuses on the moderating role of ER strategies in the relationship between FCP and adolescents’ SE. Adolescents raised in families where there is stronger parental control and emotional neglect may find the use of ES detrimental to establishing open and free communication relationships. This leads to an increased tendency towards depression and aggression in them, which in turn lowers their SE (Hong et al., 2018 ). In other words, they do not believe in their ability to handle negative emotions well when faced with stress (Di Giunta et al., 2022 ). Conversely, the positive association between CR and adolescents’ SE (Zyberaj, 2022 ) enhances individuals’ positive emotions and augments their adaptability to diverse environments. This can strengthen the cognitive levels of adolescents from families with a preference for CV, enabling them to interact more amicably with the others and the whole society, and thus reduce the occurrence of conflict events (Curran and Allen, 2016 ). Building upon this premise, the paper posits the following hypothesis:

H6a Cognitive Reappraisal enhances the positive effect of Conversation Orientation on adolescents’ self-efficacy.

H6b Cognitive Reappraisal weakens the negative impact of Conformity Orientation on adolescents’ self-efficacy.

H6c Expressive Suppression weakens the positive effect of Conversation Orientation on adolescents’ self-efficacy.

H6d Expressive Suppression enhances the negative effect of Conformity Orientation on adolescents’ self-efficacy.

Research design

Data sources.

The present study employed a questionnaire survey method to collect relevant data and to test the proposed research hypotheses. The sample of adolescent groups was selected through stratified cluster sampling. First, all provinces in China were classified into high, medium, and low levels based on the gross domestic product (GDP) rankings for the year 2022. From each level, one province was randomly selected from the eastern, central, and western regions, with Jiangsu Province, Henan Province, and Shaanxi Province chosen as samples. Then, the capital cities of these provinces, namely Nanjing, Zhengzhou, and Xi’an, were chosen as the study subjects. Secondly, from each city, one school was randomly selected from four categories: ordinary junior high school, key junior high school, ordinary senior high school, and key senior high school. Two classes were then randomly chosen from each school, ensuring a roughly equal number of junior high and high school students. In total, students from 24 classes across 12 schools were sampled. The questionnaires were distributed face-to-face by researchers during self-study classes, collected on the spot, with a total of 1300 questionnaires distributed, and 1183 valid questionnaires were recovered, resulting in a 91% response rate. Among the valid samples, there were 566 females, accounting for 47.8%, and 617 males, accounting for 52.2%, with a relatively balanced male-to-female ratio. Respondents ranged from 12 to 20 years old, with an average age of approximately 15 years old. 40.7% ( n  = 482) of the respondents’ parents did not received education beyond high school, 44.2% ( n  = 523) had one parent with education beyond high school, and 15% ( n  = 178) had both parents with education beyond high school.

Variable measurement

Independent variable: family communication patterns.

In this study, we referred to the Family Communication Patterns Instrument developed by Fitzpatrick and Ritchie ( 1994 ) and selected 17 items for measurement. This instrument includes two dimensions: Conversation Orientation (comprising 9 items, such as “My parents often say that every family member should have a say in decision-making.”), (M = 2.729, SD = 0.957); and Conformity Orientation (comprising 8 items, such as “My parents sometimes get angry when I disagree with them.”), (M = 3.370, SD = 0.996). Respondents answered using a Likert five-point scale (ranging from “strongly disagree” = 1 to “strongly agree” = 5). The scores for each item within the two dimensions were summed and averaged; higher scores indicate that the corresponding family characteristic is more pronounced.

Mediating variable: self-efficacy

In this study, the measurement of self-efficacy was based on the scale from the research by Kleppang et al. ( 2023 ), which contains 5 items such as “I am confident that I can handle unexpected situations” and “When faced with difficulties, I can stay calm because I know I can rely on my own abilities to solve them.” Respondents answered using a Likert four-point scale (ranging from “strongly disagree” = 1 to “strongly agree” = 4). We calculated the average of the sum of scores for these 5 items, with higher scores indicating a higher level of self-efficacy among adolescents (M = 2.510, SD = 0.718).

Moderating variable: emotional regulation strategies

In this study, the Emotional Regulation Strategies Scale developed by Gross and John ( 2003 ) was employed. The scale consists of 10 items and includes two dimensions: Cognitive Reappraisal (which includes 6 items, such as “When facing stressful situations, I am capable of thinking about it in a calm way.”), (M = 2.459, SD = 0.800); and Expressive Suppression (which includes 4 items, such as “I control my emotions by not expressing them.”), (M = 3.430, SD = 0.957). Respondents answered using a Likert five-point scale (ranging from “strongly disagree” = 1 to “strongly agree” = 5). Scores for each item within the two dimensions were added and averaged, with higher scores indicating a greater tendency of an individual to use a certain emotional regulation strategy.

Dependent variable: adolescents’ online prosocial behavior

The scale for measuring adolescents’ online prosocial behavior in this study is based on the research by Guo et al. ( 2018 ). We selected 13 items (e.g., “I share useful information such as my successful learning experiences and study insights with others online.”). Respondents answered using a Likert five-point scale (from “never” = 1 to “always” = 5). We added and averaged the scores of the 13 items for each respondent, with higher scores indicating a stronger level of online prosocial behavior among adolescents (M = 2.381, SD = 0.864).

Data analysis techniques

This study utilized Smart PLS 4 software to execute partial least squares structural equation modeling (PLS-SEM) and to assess all hypotheses. PLS-SEM is a non-parametric technique that leverages the explained variance of latent dimensions not directly observable. This method exhibits greater modeling flexibility, is suitable for small sample sizes, does not necessitate multivariate normal distribution for the research sample data, and can integrate two types of indicators—formative and reflective—without encountering model convergence issues. Therefore, Smart PLS-SEM is apt for predicting linear correlations and analyzing intricate structural models (Irma Becerra-Fernandez, 2001 ), particularly in directly obtaining R² to maximize the explanation of variance in the dependent variable, thus aligning closely with the data, enhancing analytical accuracy, and yielding results with robust explanatory and predictive capabilities (Avkiran and Ringle, 2018 ). In terms of software utilization, both SPSS 24.0 and Smart PLS 4 software were employed for all statistical analyses. Firstly, descriptive statistical analysis of the research sample was conducted using SPSS 24.0 software, with an examination of common method bias. Secondly, Smart PLS 4 software was utilized to assess the reliability and validity of the research sample, and to scrutinize the main effects, mediation effects, and moderation effects of this study.

Research results

Measurement model.

To evaluate the measurement model, we assessed indicator reliability, internal consistency, convergent validity, and discriminant validity (Hair et al., 2020 ) (refer to Tables 1 and 2 ). The values of Cronbach’s α, rho_A, and composite reliability for all variables in this study surpassed 0.70, indicating robust construct reliability (Hair et al., 2017 ). Regarding indicator loadings, all reported values in this study exceeded 0.7 for outer loadings. The average variance extracted (AVE) values for all constructs were above 0.50, providing support for convergent validity (Hair et al., 2022 ). Since the square root of the AVE for each construct in the model exceeded the correlations with other constructs (Fornell and Larcker, 1981 ), and all Heterotrait-monotrait ratio (HTMT) values were below 0.85, this study exhibited strong discriminant validity (Kline, 2011 ). Furthermore, this study conducted Harman’s single-factor test, which, under unrotated exploratory factor analysis, revealed 6 factors with cumulative explained variance of 36.277%, where the first factor’s explained variance did not surpass the 50% threshold. Consequently, this study did not demonstrate significant common method bias.

Structural model

First, we investigated collinearity within the structural model. All internal VIF values were below 5, indicating the model is unaffected by multicollinearity (Hair et al., 2019 ). Second, we assessed the weights of the path coefficients. As illustrated in Table 3 , all beta coefficients are statistically significant with high corresponding t-statistics. OB is significantly influenced by SE ( β  = 0.367, t  = 13.172, p  < 0.001), CV ( β  = 0.235, t  = 10.004, p  < 0.001), and CF ( β  = −0.190, t  = 7.574, p  < 0.001). SE is significantly influenced by CV ( β  = 0.403, t  = 17.793, p  < 0.001) and CF ( β  = −0.366, t  = 16.982, p  < 0.001). Therefore, hypotheses H1, H2a, H2b, H3a, and H3b are supported. Finally, we evaluated the effectiveness of the structural model using the coefficient of determination (R²), predictive relevance (Q²), and GoF. The R² values for OB and SE were 0.604 and 0.573, respectively, both exceeding 0.26, indicating strong explanatory power. The Q² values for OB and SE were 0.377 and 0.386, respectively, both greater than 0, suggesting good predictive relevance. Moreover, the overall goodness-of-fit index (GoF) of the PLS-SEM was calculated to be 0.561, surpassing the standard value of 0.36, indicating good model fit validity.

Mediation effects

We utilized the Bootstrapping technique to evaluate whether SE mediated the relationship between FCP and OB. When testing the mediating effects, it is crucial to initially ascertain the significance of each path coefficient and subsequently examine the variance accounted for (VAF) to determine whether the analysis indicates complete or partial mediation. The VAF index measurement is employed to determine the magnitude of the indirect effect relative to the total effect. (VAF < 0.2 indicates no mediation; 0.2 < VAF < 0.8 denotes partial mediation; VAF > 0.8 signifies complete mediation). As depicted in Table 3 , CV significantly indirectly influence adolescents’ OB through SE ( β  = 0.148, p  < 0.001, VAF = 0.386), indicating partial mediation. Similarly, CF significantly indirectly impact adolescents’ OB through SE ( β  = −0.134, p  < 0.001, VAF = 0.350), also indicating partial mediation. Therefore, research hypotheses H4a and H4b are supported.

Moderation effects

First, CR significantly moderates the relationship between CV and SE ( β  = 0.172, t  = 7.701, p  < 0.001), as well as OB ( β  = 0.115, t  = 5.563, p  < 0.001). This suggests that the stronger adolescents’ ability in CR, the greater the positive effect of CV on their SE and OB. Second, ES significantly moderates the relationship between CV and SE ( β  = −0.225, t  = 10.093, p  < 0.001), as well as OB ( β  = −0.134, t  = 6.577, p  < 0.001). This implies that the stronger adolescents’ ability in ES, the smaller the positive effect of CV on their SE and OB. Third, CR significantly moderates the relationship between CF and SE ( β  = 0.102, t  = 4.677, p  < 0.001). This indicates that the stronger adolescents’ ability in CR, the smaller the negative effect of CF on their SE. Fourth, ES significantly moderates the relationship between CF and SE ( β  = −0.135, t  = 6.175, p  < 0.001), as well as OB ( β  = −0.066, t  = 3.081, p  < 0.001). This implies that the stronger adolescents’ ability in ES, the greater the negative effect of CF on their SE and OB. Additionally, CR does not moderate the relationship between CF and adolescents’ OB ( β  = 0.009, t  = 10.354, p  > 0.05). Therefore, hypotheses H5a, H5c, H5d, H6a, H6b, H6c, and H6d are all supported, while H5b is not supported.

Conclusion and discussion

Main conclusions of the study.

Amidst the wave of digital socialization, online prosocial behavior among adolescents is gradually emerging as a pivotal element shaping their social interactions and self-development. This study explores the relationships among family communication patterns, self-efficacy, and emotional regulation strategies, while elucidating, through the analysis of 1183 valid questionnaires, how these factors interconnect to influence adolescents’ prosocial behavior in the digital social environment.

This study revealed a significant correlation between FCP and adolescents’ OB. These findings align relatively well with prior research (Carlo et al., 2017 ), emphasizing the pivotal role of the family environment in shaping adolescent social behavior and offering additional empirical support for family education and youth development. Specifically, FCP was subdivided into CV and CF, and the examination of prosocial behavior was extended online. The results indicate that adolescents from families emphasizing CV exhibit a higher frequency of OB compared to those from families with a CF. This implies that the proactive communication atmosphere in CV families offers adolescents more opportunities to express their opinions and feelings, thus cultivating a more open, confident social style, and a willingness to engage in prosocial behavior online. Conversely, in families leaning toward CF, where parents prioritize norms and subordination, adolescent social behavior may be constrained, resulting in lower levels of OB. Future research could delve deeper into guiding FCP to promote the healthy development of adolescents in the digital social environment.

The study has further identified that SE plays a mediating role in the connection between FCP and adolescents’ OB. In other words, whether the family emphasizes CV or CF, SE acts as a conduit, transferring the impact of the family environment to adolescents’ OB. Specifically, within CV families, where parents foster open communication and demonstrate comfort and assistance to their children, this supportive atmosphere contributes to the development of positive self-beliefs in children, thereby influencing their positive behavior. This aligns with previous research findings (Hesse et al., 2017 ), indicating that heightened SE translates into more proactive online prosocial behavior, such as sharing learning experiences and providing support to others. On the contrary, in CF families, where parents emphasize discipline and obedience, adolescents encounter the challenge of diminished SE. Influenced by stringent regulations, these children may question their social interaction abilities and independence (Horstman et al., 2018 ), thereby impacting their online social initiative. This suggests that a decrease in SE might make them more cautious or hesitant to engage in prosocial behavior. These findings offer insights for intervening in adolescents’ OB to better promote its development.

This study incorporates two ER strategies, CR and ES, expanding beyond prior research which predominantly focused on the influence of single-dimensional emotions on prosocial behavior (Davis et al., 2018 ). As a matter of fact, distinct emotional regulation strategies exhibit varying degrees of impact on individual attention and behavioral responses. First, the study reveals that in families that emphasize CV, CR exerts a positive moderating effect on adolescents’ SE and OB. This finding highlight that: with increased use of CR, adolescents from CV families can exhibit stronger SE. The mechanism of CR lies in empowering adolescents to reassess and reflect on their environment, thereby reinforcing their confidence in crisis management and boosting their SE levels. Guided by this ER strategy, a more flexible emotion adjustment ability of adolescents can also facilitate active integration into online social behaviors. Eventually, it will significantly increase their frequency of online prosocial practices. However, in the context of conformity orientation, the positive moderating effect of CR is relatively limited. While it alleviates the negative impact of CF on adolescent SE to some extent, its moderating effect on prosocial behavior is not significant. This may be attributed to CR. Functioning as an active self-perception framework, it emphasizes individual capabilities and autonomy (McRae et al., 2012 ). Moreover, it also enhances adolescents’ confidence in their abilities and mitigates the negative impact of CF on SE. Nevertheless, regarding prosocial behavior, individuals are influenced not only by CR but also by a combination of social motives (Hodge et al., 2022 ), like age, personality (Silvers et al., 2012 ), and other factors. Some studies suggest that when CR is combined with other effective interventions, its positive impact may not be significantly pronounced (Clark, 2022 ). This suggests that any ER strategy may not be universally beneficial or harmful, and subsequent research needs to consider the impact of cultural, environmental, and individual differences to enhance the universality of the findings.

Second, the study investigated the influence of ES on adolescent SE and OB within various family communication patterns. The results revealed that in families emphasizing CF, ES exacerbated the decline in adolescent SE and further restrained their engagement in online prosocial behavior. Specifically, ES reinforced negative emotions in adolescents from CF families, resulting in a diminished sense of self-worth (Tibubos et al., 2018 ), which subsequently lowers their self-efficacy levels. The utilization of this strategy also hindered adolescents’ inclination to express themselves, impeding their participation in OB. Moreover, ES diminished the positive effects of CV on adolescent SE and OB. Under the influence of ES, adolescents became inhibited and less confident, undermining their SE and instilling doubt in their abilities, particularly in terms of independence and problem-solving. This tendency increased the likelihood of avoiding problems or adopting extreme behaviors (McLafferty et al., 2020 ), negatively impacting their OB. In summary, these research findings underscore the distinct roles of different emotional regulation strategies within the family environment and highlight the divergent impact of CR and ES on adolescent SE and OB. This comprehensive understanding contributes practical insights, especially for the development of family education and youth support strategies.

Research contributions

Theoretical contribution.

This study contributes to three theoretical implications. First, while the impact of specific SE on prosocial behavior within particular tasks or situations has been established, our findings elucidate the multifaceted role of SE in a complex environment. By scrutinizing its influence on OB, we gain a nuanced understanding of adolescents’ performance across diverse social contexts, transcending specific tasks or situations. This holistic perspective integrates social cognitive theory into adolescent education, enhancing comprehension of self-efficacy’s overarching significance in the realm of adolescent internet socialization, thereby providing a more accurate explanation of their conduct in the online social sphere. Second, from an emotion management standpoint, the study explores individual differences in emotion processing by investigating the impact of two emotional regulation strategies, CR and ES, on adolescent OB. This theoretical extension deepens our insights into the role of emotions in family and online social interactions, offering more precise and actionable guidance for adolescents’ emotional education. Third, within the context of the internet era, the study investigates the direct effects of various FCP on adolescents’ OB. This broadens the research scope of family education and provides practical insights for steering adolescents toward positive OB.

Practical contribution

The practical significance of this study includes several aspects. First, in the adventure of the digital age, parents are the helmsmen guiding adolescents. The research results remind parents of the profound impact family communication patterns have on their children’s development and call for their active participation and guidance in children’s online behaviors. Parents should provide emotional support to make their children feel loved and respected, which is crucial for establishing a healthy, harmonious family environment and fostering socially skilled adolescents. Second, designers of online platforms can refer to this study to improve their applications. By understanding the impacts of different family communication patterns, self-efficacy, and emotional regulation strategies on adolescents, they can fine-tune platform design to encourage positive prosocial behaviors while developing effective mechanisms to maintain the safety and healthy development of the online community. Third, school education can also incorporate prosocial behavior and emotional education into the curriculum based on the study’s findings, including empathy, cooperation, conflict resolution, and emotion management, allowing students to learn these skills through extracurricular activities and role-playing. Additionally, schools can work closely with parents to create a warm and loving atmosphere for students’ growth, with both parties committed to cultivating positive and healthy digital citizens.

Research limitations and prospects

This study has three main limitations. First, this study is the predominantly localized nature of the research sample, which overlooks adolescents from regions characterized by lower levels of economic development and education. Consequently, the generalizability of the findings may be compromised. Future research endeavors could broaden the scope of the sample by encompassing a wider range of geographical regions, cultural contexts, and educational backgrounds. Second, although the research used self-reported data, self-reporting may be subject to subjectivity and bias from social desirability. Future studies could integrate objective data collection methods to enhance the credibility of the results. Third, this study mainly focused on online prosocial behaviors in the short term and did not consider long-term effects. Future research could examine how online prosocial behaviors evolve over time and whether the impact of factors such as family communication patterns diminishes with time.

Data availability

The datasets generated during and/or analyzed during the current study are not publicly available due to ongoing research and analysis, but are available from the corresponding author on reasonable request.

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Weizhen Zhan, and Zhenwu You: Conceptualization, Methodology, Software; Weizhen Zhan, and Zhenwu You: Data curation, Writing-Original draft preparation; Zhenwu You: Visualization; Weizhen Zhan: Investigation; Weizhen Zhan, and Zhenwu You: Software, Validation; Weizhen Zhan, and Zhenwu You: Reviewing; Weizhen Zhan, and Zhenwu You: Writing and Editing.

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Zhan, W., You, Z. Family communication patterns, self-efficacy, and adolescent online prosocial behavior: a moderated mediation model. Humanit Soc Sci Commun 11 , 658 (2024). https://doi.org/10.1057/s41599-024-03202-2

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Intertwining self-efficacy, basic psychological need satisfaction, and emotions in higher education teaching: A micro-longitudinal study

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• Melanie V. Keller   ORCID: orcid.org/0000-0003-2919-4470 1 ,
• Raven Rinas   ORCID: orcid.org/0000-0001-8907-0352 1 ,
• Stefan Janke   ORCID: orcid.org/0000-0003-1799-8850 2 ,
• Oliver Dickhäuser   ORCID: orcid.org/0000-0002-3126-8398 2 ,
• Markus Dresel   ORCID: orcid.org/0000-0002-2131-3749 1 &
• Martin Daumiller   ORCID: orcid.org/0000-0003-0261-6143 1  

Prior research has explored various factors to explain differences in teaching experiences and behaviors among school teachers, including self-efficacy, basic psychological need satisfaction, and emotions. However, these factors have predominantly been examined in isolation, and limited research has investigated their role in the context of higher education teaching. To address these research gaps, analyses on both the within and between teacher level are needed. The aim of the present study was therefore to investigate the interplay between these motivational and emotional constructs on both levels, as well as the relevance and applicability of prior research findings on school teachers to the context of higher education teaching at universities. In a micro-longitudinal study, 103 university teachers from Germany (49 female; average age: 41.4 years, SD  = 11.0) completed assessments of their self-efficacy in 748 sessions directly before their teaching sessions, as well as their basic psychological need satisfaction and discrete emotions directly after. Multilevel structural equation modeling revealed positive associations between self-efficacy and basic psychological need satisfaction. Self-efficacy was negatively associated with negative emotions, and positive indirect effects on positive emotions as well as negative indirect effects on negative emotions were identified through satisfaction of the needs for competence and relatedness. Basic psychological need satisfaction was positively related to positive emotions and vice versa—however, unexpected positive associations between relatedness and negative emotions emerged and require further research.

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1 Introduction

Motivation and emotion play crucial roles in fostering learning and achievement in school and higher education contexts—this holds true both for students and teachers. Accordingly, there has been significant growth in research investigating these constructs in educational contexts in recent decades (Hall & Goetz, 2013 ). Teaching, particularly in higher education, is a complex, emotion-laden profession that requires a high degree of self-control and self-management, making it important to understand teachers’ motivational and emotional experiences to support high quality instruction (Lin et al., 2005 ). Higher education teachers make valuable contributions to society through their research and scientific advancements (e.g., Javitz et al., 2010 ) as well as their teaching—which significantly impacts student outcomes such as engagement (BrckaLorenz et al., 2012 ) and learning (Pascarella & Terenzini, 2005 ). Recent studies have therefore expanded their focus to explore the role of motivation and emotion in higher education teachers (Daumiller et al., 2020 , Mendzheritskaya et al., 2019; Watt & Richardson, 2020 ). To describe and explain teachers’ experiences, including those in higher education, self-efficacy, basic psychological need satisfaction (BPNS), and emotions have emerged as widely used and meaningful theoretical constructs (Daumiller et al., 2020 ).

The primary aim of the present study was to integrate these theoretical foundations to paint a comprehensive picture of motivation and emotion in higher education teachers. To accomplish this, we examined teachers’ self-efficacy and the satisfaction of their needs for competence, autonomy, and relatedness as key motivational factors, along with their discrete emotions. Through teachers’ immediate assessments of their experiences during specific teaching sessions, we closely examined the intricate relations between these constructs. Moreover, our analysis encompassed both between and within person levels of interaction, while also considering indirect relationships. This detailed and context-specific approach provides nuanced insights into the dynamics between motivation and emotion in higher education teaching that can guide further research on higher education teachers and aid in the development of effective strategies to support successful teaching.

2 Higher education teachers’ self-efficacy, basic psychologcial need satisfaction, and discrete emotions

Higher education teachers’ motivation can be defined as the overall processes that give rise to initiating, sustaining, and regulating goal-directed behaviors (Daumiller et al., 2020 ). Within this conceptualization, self-efficacy and BPNS can be considered as core aspects of teachers’ motivation. Together, these two aspects serve as a powerful approach for describing teachers’ motivation within specific teaching situations, as they represent different lenses through which motivational dynamics can be understood. They are influenced by individual characteristics of the teacher (e.g., personal traits; person-specific) as well as by characteristics of the situational context (e.g., behaviors of others; context-specific), painting a holistic picture of motivation.

Self-efficacy for teaching represents beliefs that teachers hold about their teaching competence, while BPNS, as defined in Self-determination theory (SDT), considers how teachers’ needs are satisfied within a given teaching situation. From a theoretical perspective, these different aspects of motivation regulate teachers’ cognitions, behaviors, and affect, and within the affective component, are also related to experiences of emotions (Dresel & Hall, 2013 ). We conceptualize emotions as discrete emotions that are connected, but not identical to the term motivation. Specifically, following Pekrun and Stephens ( 2010 ), we view emotions as multifaceted phenomena including affective, cognitive, physiological, motivational, and expressive components, and focus on the discrete, affective component experienced within an achievement situation in the present study.

Prior research has highlighted the value of combining these three constructs to better understand individual experiences and behaviors. Sweet et al. ( 2012 ) combined self-efficacy and parts of SDT to explain health behaviors (i.e., physical activity) of university students and found that simultaneously examining and combining these constructs in a single model enhanced explanations of goal-directed behavior (Sweet et al., 2012 ). Bandura ( 1977 ) drew close links between self-efficacy and emotions in his theoretical framework, where beliefs about successfully managing and performing tasks are posited to influence emotional responses, and in turn, future beliefs. Moreover, Basic Psychological Need Theory, as one of the mini-theories within SDT (Vansteenkiste et al., 2010 ), is considered to be a part of functioning and well-being, with well-being, among other aspects, defined as experiencing more positive and less negative emotions (Ryan & Deci, 2017 ; Vansteenkiste et al., 2020 ), suggesting a link between BPNS and emotions. Empirical evidence in academic contexts, such as the work of Holzer et al. ( 2021 ), found consistent associations between positive emotions and satisfaction of all three of the basic psychological needs, further supporting the link between BPNS and emotions. Despite these encouraging findings, studies have yet to examine how self-efficacy and BPNS are related and how both constructs matter for teachers’ emotions in the context of higher education teaching.

2.1 Self-efficacy for teaching and its relevance for teaching

Self-efficacy refers to an individual’s beliefs about their ability to master situations and successfully overcome obstacles (Bandura, 1997 ). Previous research provides a wide range of evidence highlighting associations between self-efficacy and aspects of successful teaching. For instance, in the case of school teachers, high self-efficacy has been linked to effective teaching practices, the ability to cater to students’ individual needs and motivate them successfully, as well as greater persistence, enthusiasm, commitment, and positive affect (Allinder, 1994 ; Ghaith & Yagi, 1997 ; Klassen et al., 2011 ; Schwerdtfeger et al., 2008 ; Skaalvik & Skaalvik, 2007 ; Tschannen-Moran & Hoy, 2001 ). These findings underscore the significance of self-efficacy as a meaningful aspect of teacher motivation, which has implications not only for teachers themselves, but also for their students (Klassen & Tze, 2014 ).

Although less researched than in the school teacher context, self-efficacy has also been assessed in studies on higher education faculty, particularly in relation to the research domain (e.g., Hemmings & Kay, 2009 ; Pasupathy & Siwatu, 2014 ). The importance of self-efficacy for teaching in higher education has been illustrated in early descriptive research (Bailey, 1999 ) and in subsequent studies that have identified similar patterns as observed in school teachers. For example, in higher education, self-efficacy has been linked with teachers’ motivation to improve their teaching through professional development workshops (Young & Kline, 1996 ), higher job satisfaction (Ismayilova & Klassen, 2020 ), adaptive framing of negative events (Morris & Usher, 2011 ), more enthusiasm for teaching and the subject (Daumiller et al., 2016 ), as well as reduced stress levels (Yin et al., 2020 ). Concerning student outcomes, self-efficacy for teaching has also been linked to the use of content-related humor in teaching (Daumiller, Janke, Hein et al., 2019 ), teaching quality (Daumiller et al., 2019 ), and student learning and engagement (Daumiller, Janke, Hein et al., 2021 ; Fong et al., 2019 ). These findings indicate that the importance of self-efficacy for teaching found among school teachers is also applicable and relevant in the context of higher education.

Despite the existing research on self-efficacy in higher education teachers, there is still little understanding of how self-efficacy is intertwined with BPNS during teaching, and how it relates to discrete emotions during teaching in higher education. Importantly, the mentioned associations have mostly been looked at regarding teaching in general, potentially omitting nuanced insights that can only be captured by considering teachers’ experiences within specific teaching sessions and situations.

2.2 Basic psychological need satisfaction and its relevance for teaching

BPNS, as conceptualized in SDT (Deci & Ryan, 2000 , 2008 ), is relevant for understanding how features of the teaching context influence (higher education) teachers’ motivation through fulfillment of the needs for competence, autonomy, and (Stupnisky et al., 2018 ). In order to fulfill their basic psychological needs, teachers need to perceive themselves as effective and mastering (satisfaction of the need for competence), experience volition and willingness (satisfaction of the need for autonomy), as well as feel connected to and significant in the eyes of others (satisfaction of the need for relatedness, Vansteenkiste et al., 2020 ). Within SDT, it is assumed that high satisfaction of the needs for competence, autonomy, and relatedness contribute to effective functioning and well-being (Ryan & Deci, 2017 ; empirically validated in school contexts, e.g., by Taylor et al., 2008 ; Vansteenkiste et al., 2009 ). Research on SDT in higher education teachers, mainly in North America, has shown that satisfaction of basic psychological needs is connected to autonomous work motivation, teaching quality, and the use of best practices in teaching in higher education (e.g., Esdar et al., 2016 ; Stupnisky et al., 2016 , 2017 ). Additionally, studies on basic psychological need satisfaction and achievement goals have confirmed that BPNS of higher education teachers shows similar relations across different countries and institution types (Daumiller, Janke, Rinas et al., 2021 ; Stupnisky et al., 2018 ). These findings suggest that BPNS plays a significant role in shaping the teaching practices of higher education teachers.

2.3 The role of discrete emotions in teaching

Teaching is an inherently emotional task (Frenzel, 2014 ; Sutton & Wheatley, 2003 ), which also holds true for the higher education context (Gardner & Leak, 1994 ; Mendzheritskaya & Hansen, 2019 ; Postareff & Lindblom-Ylänne, 2011 ; Thies & Kordts-Freudinger, 2019 ). Research on school teachers has identified positive links between teacher enjoyment and effective instructional strategies, student performance, and engagement in informal learning activities (Frenzel et al., 2020 , 2021 ; Huang et al., 2020 ). In the higher education context, teachers’ emotions have also been closely linked to their perceived success (Stupnisky et al., 2019 ) as well as the value they attribute to teaching (Stupnisky et al., 2016 ). Furthermore, emotions experienced by higher education teachers have been associated with motivational constructs such as self-efficacy beliefs (Burić & Frenzel, 2019 ; Burić & Moe, 2020 ) and achievement goals (Rinas et al., 2020 ). This illustrates that teacher emotions play a central role in the nexus of teaching experiences and student outcomes (see also Frenzel et al., 2021 ).

Given the significance of emotions in teaching, gaining nuanced insights into teachers’ discrete emotions and their relationships with motivational constructs, such as self-efficacy and BPNS, represents a promising research direction for understanding teachers’ experiences. In the present study, we cover an array of discrete emotions, namely joy, pride, anxiety, anger, shame, and boredom, which encompass both positive/negative value and activating/deactivating object focus (see Pekrun et al., 2007 ). These specific emotions have been frequently reported in higher education teaching (Hagenauer & Volet, 2014 ; Keller et al., 2014 ; Thies & Kordts-Freudinger, 2019 ) and have been found to be related to perceived success in teaching (Stupnisky et al., 2019) .

2.4 Interplay between self-efficacy, basic psychological need satisfaction, and emotions in teaching

Understanding the interplay between self-efficacy, BPNS, and the discrete emotions experienced during teaching is crucial for gaining a deeper understanding of how motivation and emotions intertwine within the context of higher education teaching. In the following sections, we outline how, based on theoretical considerations and prior empirical findings, self-efficacy, BPNS, and emotions can be expected to be associated with one another. Specifically, we propose that self-efficacy for teaching in a specific lesson is directly linked to teachers' satisfaction of the needs for competence, autonomy, and relatedness. These core psychological needs, when fulfilled, can be expected to contribute to emotions experienced during teaching. Furthermore, we suggest that self-efficacy has both direct and indirect influences on discrete emotions, with the indirect impact being mediated through BPNS.

2.4.1 Interplay between self-efficacy and BPNS

Before describing the interplay between self-efficacy and satisfaction of the three basic psychological needs, it is important to acknowledge the similarity between self-efficacy and the experience of competence, as both focus on teachers’ perceived teaching competence. Nevertheless, we draw a clear differentiation between the two constructs: Self-efficacy for teaching, as it is perceived prior to a lesson, describes teachers’ beliefs about being able to successfully teach and overcome obstacles within a lesson, and is thus rooted in the teachers themselves and their previous experiences, but directed at an upcoming lesson. In contrast, satisfaction of the need for competence focuses on a retrospective view of a given lesson and how it went, assessing whether the teacher felt competent during their teaching. Thus, satisfaction of the need for competence is more contingent upon the circumstances of the specific lesson.

Regarding the interconnections between self-efficacy and BPNS, from a theoretical perspective, high self-efficacy facilitates confidence and better performance, which should lead to teachers feeling more competent during teaching. This expectation is supported by research that has found teacher self-efficacy to be associated with effective classroom processes and student academic adjustment (Ashton & Webb, 1986 ; Zee & Koome, 2016 ). Thus, we expect self-efficacy for teaching to be positively connected to satisfaction of the need for competence during a teaching session.

Furthermore, it stands to reason that teacher self-efficacy is positively related to satisfaction of the need for autonomy: According to the underlying theory (Bandura, 1997 ), teachers with high self-efficacy beliefs for teaching may be more capable of effectively navigating challenges in their teaching, leading to a sense of autonomy in their decision-making and responses. Conversely, teachers with lower self-efficacy may perceive themselves as less competent when encountering unexpected challenges, leading them to simply react to problems occurring during teaching rather than proactively addressing them and potentially undermining their sense of autonomy. Thus, teachers’ self-efficacy should be closely related to the extent to which their need for autonomy is satisfied during teaching.

Lastly and also according to Bandura’s theoretical conceptions of self-efficacy (Bandura, 1997 ), teachers with strong self-efficacy beliefs are expected to be more effective in engaging with and motivating their students, contributing to higher teaching quality (see Praetorius et al., 2018 ). Consequently, their satisfaction of the need for relatedness to their students may be supported by effectively engaging students in a lesson and thus enhance the feeling of connectedness to those students by enhancing interpersonal communication. In summary, we anticipate strong positive connections between self-efficacy for teaching and the satisfaction of the three basic psychological needs.

2.4.2 Interplay between self-efficacy and emotions

Emotions are often considered to be antecedents of self-efficacy beliefs (Pekrun et al., 2007 ), as supported by empirical findings such as those of Burić et al. ( 2020 ), who identified negative emotions as antecedents of lower teacher self-efficacy in a longitudinal study with school teachers. At the same time, emotions are influenced by an individual’s perception of their ability to achieve goals, which is captured by self-efficacy (Frenzel et al., 2009 ). In our study, we specifically aim to examine the relationship between self-efficacy for teaching prior to a lesson and the emotions experienced during that session, thus focusing on the relevance of self-efficacy for emotions.

For this relationship, control-value theory suggests that self-efficacy, which informs the teachers’ perceived control in a teaching situation, serves as one appraisal for emotions (Pekrun et al., 2007 ). Specifically, high self-efficacy for teaching implies perceptions of high control, favoring rather positive emotions depending on the situation’s value. Conversely, low self-efficacy for teaching implies rather low control over teaching situations, which favors experiencing rather negative emotions depending on the accompanying value.

Furthermore, self-efficacy can be expected to be positively associated with positive emotions such as joy and pride, and negatively associated with negative emotions such as anxiety, anger, shame, and boredom, based on the theoretical rationale that high self-efficacy promotes more effective teaching and better coping abilities (e.g., Skaalvik & Skaalvik, 2007 ; Tschannen-Moran & Hoy, 2001 ). Thus, teachers with higher self-efficacy are inclined to hold the belief that they can effectively navigate teaching challenges and are more likely to demonstrate successful problem-solving skills in practice. Consequently, these teachers may experience more positive emotions, such as joy and pride, and encounter less anger during their instructional activities, as they are better equipped to manage demanding situations.

In addition to dealing with actual problems that arise during teaching, the anticipation of teaching problems could already lead to emotional effects. For instance, if a teacher has low self-efficacy beliefs, they might be afraid of making mistakes and consequently experience increased anxiety during their teaching. Similarly, feelings of shame during teaching may arise from a perceived inadequacy in their ability to effectively handle difficult situations. Concerning boredom, teachers with high self-efficacy beliefs are more likely to engage in effective instructional strategies that promote student interest and engagement, reducing the likelihood of boredom in the classroom (e.g., Fong et al., 2019 ).

While there is limited empirical research examining the above-mentioned interconnections in higher education teachers, some studies have provided preliminary support for the proposed pattern of linkages (see Lobeck et al., 2018 , for results focused on emotions and self-concept). These findings, combined with the theoretical foundations highlighting their interrelatedness, indicate that self-efficacy may play a meaningful role in shaping the emotions experienced by higher education teachers. Nevertheless, there is a need for empirical testing and validation of this assumption.

2.4.3 Interplay between BPNS and emotions

Following SDT, satisfaction of the needs for competence, autonomy, and relatedness is closely connected to well-being, which encompasses both positive and negative affective experiences. In SDT, the positive and negative affect components of well-being can be further differentiated into finer grained emotional experiences (Ryan & Martela, 2016 ). Following this, we take a detailed approach by examining several discrete emotions that are relevant for achievement and teaching contexts (Pekrun et al., 2007 ; Stupnisky et al., 2016 ). Besides well-being, BPNS facilitates intrinsic motivation (as defined in SDT), which has been found to be positively associated with positive emotions, and negatively associated with negative emotions (Deci & Ryan, 2000 ). Accordingly, the same pattern of linkages can be proposed for the satisfaction of the needs for competence, autonomy, and relatedness. Guided by these broader theoretical notions, each of the basic psychological needs and their relations with the six discrete emotions examined (joy, pride, anxiety, anger, shame, and boredom) are described in the following sections.

Beginning with satisfaction of the need for competence, we draw upon the principles of SDT to propose that higher satisfaction of this need is positively linked to positive emotions. Specifically, when teachers feel more competent during their teaching, they are more likely to experience greater joy and a sense of pride in their teaching. Moreover, teachers who feel competent during teaching can be expected to be less likely to experience anxiety, anger, and shame in a lesson (e.g., when facing mistakes) and to be less bored during their teaching. A reason for this is that higher satisfaction of the need for competence is associated with more engaging teaching practices and teaching quality (see Esdar et al., 2016 ; Stupnisky et al., 2016 ) and teachers teaching successfully are less likely to encounter situations eliciting negative emotions.

Moreover, we propose that the associations between satisfaction of the need for autonomy and emotions follow the same underlying assumptions as for competence. Teachers who perceive themselves as autonomous during their teaching are more likely to experience joy and pride. This link may be further emphasized by the notion that teachers who have the autonomy to make their own decisions in teaching assume more responsibility for teaching outcomes and derive greater pride from their successes. Conversely, teachers whose need for autonomy is not fulfilled are more likely to experience negative emotions during their teaching, including anxiety, anger, shame, and boredom (Deci & Ryan, 2000 ), as the impression of being controlled by outer circumstances might lead to feeling pressure and annoyance. Empirical evidence supports this reasoning, demonstrating that university teachers’ sense of control over teaching situations is positively associated with positive emotions and negatively associated with negative emotions (Hagenauer & Volet, 2014 ).

Regarding satisfaction of the need for relatedness, teachers whose need for relatedness to their students is more satisfied may exhibit greater emotional investment in their teaching and their students’ learning. As a result, they may be more likely to experience positive emotions: Teachers who establish satisfying social connections with their students when teaching may experience higher levels of joy and pride, both in their own teaching and regarding their students’ learning experiences. Additionally, they can be expected to be less likely to feel anxiety, anger, shame, and boredom, as relatedness might be accompanied by a higher level of trust and ease. First empirical evidence supports these assumptions, with studies having found positive associations between social connectedness and enjoyment, as well as negative associations with anxiety and anger among teachers (Hagenauer & Volet, 2014 ; Klassen et al., 2012 ).

These theoretical and empirical foundations point to satisfaction of the needs for competence, autonomy, and relatedness being positively related to positive emotions and negatively related to negative emotions during teaching. We acknowledge that the reverse direction between BPNS and emotions is also plausible, however, from a SDT perspective, we expect a path from BPNS to emotions. Moreover, as previously argued, self-efficacy at the start of a teaching session might influence BPNS during the session by shaping how teachers perceive and interpret their experiences. Taken together, it stands to reason that self-efficacy for teaching matters for the emotions that teachers experience during teaching, directly and indirectly, through their BPNS.

2.5 Temporal and situational changes in higher education teachers’ motivation

How self-efficacious higher education teachers feel towards their teaching does not only vary between different teachers, but also from situation to situation within a teacher. For example, a teacher might hold higher or lower self-efficacy beliefs from one session to the next depending on the lesson topic. Additionally, recent evidence suggests that stable and session-specific aspects of self-efficacy may be differently relevant, with person-stable parts of self-efficacy having been found to matter more for student learning than session-specific self-efficacy (Daumiller, Janke, Hein et al., 2021 ). Besides that, it has been recommended that self-efficacy should be measured in a precise and context-specific manner, tailored to the specific teaching context (Bandura, 1986 ; Pajares, 1996 ). Thus, in the context of the present study, we focus on individual teaching sessions and seek to capture teachers’ experiences more accurately by assessing their self-efficacy for each session.

Next to self-efficacy, BPNS is highly context-specific given that the satisfaction of basic psychological needs heavily depends on the context itself (Deci & Ryan, 2008 ). Analogous to self-efficacy for teaching, it is thereby important to measure BPNS within the context relevant to the respective research questions. It is, for example, plausible that certain characteristics of a session facilitate different levels of satisfaction of the need for competence (e.g., depending on how well the lesson went), autonomy (e.g., depending on the lesson plan for the session), and relatedness (e.g., depending on how the students acted or responded in a particular session). In this light, employing session-specific assessments targets the experiences of teachers in a valid, fine-grained manner, directly addressing the specific context in which they operate.

Lastly, it is widely recognized that emotions vary within individuals and across different situations (Nett et al., 2017 ; Seo & Patall, 2021 ). This is particularly relevant for higher education teachers who often engage in various domains in their work beyond teaching (e.g., research, administration). Thus, to ensure more valid assessments of the emotional experiences of (higher education) teachers during teaching, emotions should be assessed closely to the teaching context and separately for different sessions (Thies & Kordts-Freudinger, 2019 ). By doing so, nuanced emotional experiences can be captured that account for specific teaching contexts and the unique experiences that emerge within them.

It is reasonable to expect differences not only in the motivational patterns between different teachers (i.e., at the between level), but also in the fluctuations of teachers’ motivation and emotion from session to session (i.e., at the within level). Some higher education teachers may generally experience higher levels of self-efficacy for teaching right before their sessions compared to other teachers. However, even among teachers with high overall self-efficacy, it is possible for them to feel less self-efficacious before a particular session, such as when testing out a new teaching concept and feeling unsure of its success. According to Goetz et al. ( 2016 ), “[…] most psychological theories focus on intraindividual psychological functioning, and the same holds true for educational theories of student learning.” These intraindividual connections can be, but are not necessarily, equivalent to interpersonal connections (Goetz et al., 2016 ; Schmitz & Skinner, 1993 ), implying that both interindividual and intraindividual aspects should be considered when testing assumptions grounded in psychological theories.

We expect that the same relationships will emerge between self-efficacy, BPNS, and emotions at both the between and within person level, i.e., both on the interindividual and on the intraindividual level. For instance, we expect that teachers who report high self-efficacy before their sessions will also report higher levels of joy compared to teachers with lower self-efficacy (at the between level). At the same time, we anticipate that a teacher who generally reports low self-efficacy but experiences higher self-efficacy before a specific session will also report higher levels of joy in that session compared to their other sessions. However, it is important to note that the interplay between self-efficacy, BPNS, and emotions may not be identical at both levels. Previous research by Goetz et al. ( 2016 ) showed that the relationships between emotions and achievement goals differ between the between and within levels in students. This illustrates that stable and generalizable associations found at the between level may not necessarily be perfectly reflected at the within level, highlighting the need for more research on situational relationships alongside overarching ones. Moreover, deriving accurate situation-centered interventions from the between level proves to be challenging. Therefore, it is necessary to examine and understand the interplay between self-efficacy, BPNS, and emotions at both the between and within levels in the context of higher education teaching.

3 Research question and hypotheses

The central research focus of the present study is to investigate the interplay between self-efficacy, BPNS, and emotions during teaching in higher education teachers. To this end, we combine previous empirical findings from related contexts (teaching in schools) and theoretical considerations to build hypotheses about the motivation and emotions of higher education teachers and condense them in an overall model (see Fig.  1 for an overview). For a thorough analysis of their interplay, we formulate mediation hypotheses and distinguish between within and between person effects.

Expected relations of self-efficacy, BPNS, and emotions. Note The arrows pointing from self-efficacy to the respective BPNS and emotions represent temporal directions from the beginning of each session to the end. Arrows from BPNS to emotions represent the theoretical notion that motivational aspects (BPNS) statistically predict emotions. However, we do not claim causal relations between them

Specifically, we expect high self-efficacy to be related to high satisfaction of the needs for competence, autonomy, and relatedness in a given teaching session (Hypothesis 1; H1). Furthermore, we hypothesize associations between self-efficacy for teaching at the beginning of a session and emotions experienced during teaching (H2). Extending prior research, we expect self-efficacy to be positively associated with joy (H2a) and pride (H2b), and negatively associated with anger (H2c), anxiety (H2d), shame (H2e), and boredom (H2f). These hypotheses are congruent with the theoretical assumptions regarding self-efficacy proposed by Bandura ( 1997 ).

Finally, based on theoretical considerations and previous research, we hypothesize associations between the respective BPNS during teaching and emotions experienced within a given session. Satisfaction of the needs for competence (H3), autonomy (H4), and relatedness (H5) are proposed to be positively associated with experiences of joy and pride (H3a/b, H4a/b, H5a/b), respectively, while anxiety, anger, shame, and boredom are proposed to be negatively associated with satisfaction of the needs for competence, autonomy, and relatedness (H3c/d/e/f, H4c/d/e/f, H5c/d/e/f). We expect these hypotheses to hold true on both the between as well as the within person level, i.e., both for differences between different teachers and for differences that a particular teacher experiences from session to session.

Additionally, we hypothesize self-efficacy to be related to discrete emotions via teachers' individual basic psychological needs (H6), i.e., self-efficacy for teaching right before a given session is expected to shape how teachers perceive and interpret their experiences, determining the extent to which their basic psychological needs for competence, autonomy, and relatedness are fulfilled during a given session. BPNS, in turn, is expected to be related to the emotions teachers experience during their teaching. Thus, we expect positive indirect effects of self-efficacy on positive emotions (joy, pride) and negative indirect effects on negative emotions (anxiety, anger, shame, boredom), with BPNS as a mediator, in our statistical model.

Following our aim to better understand how self-efficacy, BPNS, and emotions relate, we comprehensively tested all associations proposed in Fig.  1 in an overall model.

4.1 Procedure

A high-frequency micro longitudinal study was conducted among German higher education teachers to measure the constructs used to test our hypotheses. We assessed session-specific data on self-efficacy, BPNS, and emotions in five consecutive teaching sessions of each course. Each teacher could participate with as many of their courses as they wanted. If a teacher participated with more than one course, we conducted our study separately for each course, resulting in five datapoints for each course. In these five consecutive sessions of every course that the teachers agreed to participate with, the teachers were asked to complete a short paper-and-pencil questionnaire. Directly before the start of their session, they made assessments regarding their self-efficacy beliefs concerning that session. Directly at the end of the session, they reported on their degree of satisfaction of their needs for competence, autonomy, and relatedness as well as their discrete emotions experienced during that session. The questionnaires were distributed and collected by a research assistant right before and after each session to minimize the disruptive impact on the higher education teachers’ teaching. The time between two measurement points was generally one week, with a few shorter or longer exceptions when a course was taught twice a week or if one session was cancelled (e.g., due to illness). In cases like the latter, we continued the study the week after.

Higher education teachers from two average-sized universities in southern Germany were asked to participate on a voluntary basis. In total, we collected 1090 session-specific assessments in 218 different courses (ranging from lectures to seminars) from 103 higher education teachers (49 female, age M  = 41.4 years, SD  = 11.0, 21 full professors, 38 academic staff members with PhD, 41 academic staff members without PhD). As the first session we assessed was the first meeting in the semester and thus rather atypical (e.g., taking a third of the time of a regular lesson), we excluded the first datapoint ex post, resulting in four data points for each course. This resulted in a total of 748 session-specific datasets with 3.7 measures per course on average. Teachers were recruited from a broad range of subjects, for example, educational sciences, American studies, physics, and music, which were taught in seminars and lectures of different sizes.

4.3 Measures

The measures used for the questionnaires consisted of adapted scales that have been established in research on higher education teachers. Internal consistency for all assessed variables was high (with Cronbach’s Alpha / McDonald’s Omega values ranging between 0.72 and 0.91, See Table   1 for details). As we calculated a multilevel model, we additionally used ICC2 values to assess whether our measures are reliable on the person level (Marsh et al., 2012 ). All ICC2 values were high, ranging between 0.75 and 0.96. In general, we aimed to keep the questionnaire short to be minimally disruptive and to reduce the load of items that had to be answered right before the start and right at the end of the lessons. As this dataset is part of a larger project, additional measures were also included within the surveys to assess separate research questions outside of those focused on in the present study. Footnote 1

4.3.1 Self-efficacy

Self-efficacy for teaching was measured with an adapted, German version of the scale developed by Nie et al. ( 2012 ) that has been used in past research on higher education teachers’ motivation (Daumiller et al., 2016 ). The scale includes three subscales that assess self-efficacy regarding instruction, classroom management, and student motivation. We used one item to assess each subscale, and as such, self-efficacy for teaching was measured by three items with a focus on the specific upcoming teaching session (e.g., “What do you think, how well will you be able to present alternative explanations or examples today if students do not get something immediately?”). The answers were measured using a Likert-type scale ranging from 1 ( not true at all ) to 8 ( completely true ).

4.3.2 Basic psychological need satisfaction

To measure basic psychological need satisfaction within a given session, a scale by Janke and Dickhäuser ( 2018 ) was used. Two items were used to assess each of the basic psychological needs on an eight-point Likert-type scale ranging from 1 ( not true at all ) to 8 ( completely true ). Similar to the self-efficacy scale, the item stems of the items were adapted to refer specifically to the session that had just ended, for example, “In today’s session, I felt like I was able to manage my teaching in a good and competent way” (competence), “In today’s session, I felt like I was free to shape my teaching by myself” (autonomy), and “In today’s session, I felt like I was socially involved with my students” (relatedness).

4.3.3 Emotions

The six selected discrete emotions (joy, pride, anxiety, anger, shame, and boredom) were measured with single items, as single items have been found to be suitable for measuring motivational-affective constructs like emotions in situational contexts (Goetz et al., 2016 ; Gogol et al., 2014 ). After reading the item stem (“In this session, I experienced …”) participants rated the different emotions on an eight-point Likert-type scale ranging from 1 ( do not agree at all ) to 8 ( fully agree ).

4.4 Analyses

We tested our hypotheses in the model shown in Fig.  1 by estimating two-level structural equation models using Mplus 7.1 (Muthén & Muthén, 2017 ), which allowed us to examine the proposed relations on both the within level and the between level. Specifically, this analysis distinguishes within person relations that are focused on changes within teachers from session to session (level 1) and between person differences that are focused on the differences between the individual teachers (level 2). The session-specific assessments were nested within courses, and courses were nested within teachers. This data was strictly hierarchical, meaning that each session and course had only one teacher. We grouped our multilevel model by teacher and analyzed mechanisms between and within teachers (scripts for the full analyses are available in an open repository: https://osf.io/vgxrd/?view_only=a87a197c3ed84350bc569e9ebf4eadfd ). We did not conduct analyses on the course level as teachers participated with 2.18 courses on average, with a third of the teachers only participating with one course, which did not result in enough courses per teacher to yield satisfying power.

We modeled self-efficacy as well as each of the basic psychological needs as latent variables using the individual items as indicators. Moreover, we modeled indirect effects between self-efficacy, BPNS, and emotions using the “model indirect” command. MLR was used as an estimator to account for potential non-normal data distribution. Missing values were handled using full information maximum likelihood (FIML). Missing values on item level were less than 3% in all cases where teachers answered at least one item. Missing cases (less than 16%) were not systematically related to any of the variables of interest and were thereby considered missing at random (MAR). We interpreted the model fit based on the following cut-off values following the recommendations by Schermelleh-Engel et al. ( 2003 ) and Hu and Bentler ( 1998 ): CFI > .90, TLI >  .90, RMSEA ≤ .08, and SRMR ≤ .10. To additionally check for robustness, we calculated separate models where we only included one of the three aspects of BPNS each, and tested for indications for potential suppression effects.

5.1 Preliminary results

First, we calculated the measurement model as a multilevel confirmatory factor analysis, which resulted in an acceptable fit: χ 2 ( df  = 102, n  = 748) = 186.410; p  < .001; CFI = .967; TLI = .931; RMSEA = .033; SRMR within  = .029; SRMR between  = .041. Descriptive results on both the within and between level as well as latent correlations on both levels can be found in Table  1 . In addition, manifest bivariate correlations are provided in the supplementary materials (Table S1 ).

The mean values for self-efficacy and basic psychological need satisfaction were relatively high. Concerning the discrete emotions, while a high mean was observed for joy and pride, we found low means for anxiety, anger, shame, and boredom compared to the theoretical mean of the scales. Regarding these mean values, it is worth noting that the teachers participated voluntarily in our study, potentially leading to a highly motivated sample. Nevertheless, results included the full theoretical range of the scale for all emotions aside from shame, indicating variability in responses (as also reflected in the substantial standard deviations). None of the motivational or emotional aspects were highly correlated to demographic variables. Regarding correlations between constructs, we found the expected positive correlations between BPNS and self-efficacy. Moreover, the pattern of positive emotions being positively correlated, and negative emotions being negatively correlated with both BPNS and self-efficacy also became apparent at the within level, i.e., within individual teachers. At the between level, an exception was observed for the satisfaction of the need for relatedness, which was surprisingly positively correlated with the negative emotions of anxiety, anger, and shame.

Intraclass correlations (ICC1) are reported in Table  1 . It is notable that for self-efficacy, the proportion of variability located on the person level was rather high. For BPNS, approximately two thirds of variability was located at the within person level, with satisfaction of the need for relatedness descriptively showing the highest person-specificity. The intraclass correlations of the six discrete emotions varied, with pride being the most stable emotion on a within person level ( ICC1  = .54) and boredom being the least stable ( ICC1  = .28). Despite this variation, the intraclass correlations showed substantial variability both from session to session within one teacher and between different teachers. Together with the high ICC2 values, this shows that two-level structural equation modeling is a fitting analytical approach.

5.2 Structural equation modeling

Overall, our results of the two-level SEM showed an acceptable model fit: χ 2 ( df  = 108, n  = 103) = 214.05; p  < .001; CFI = .958; TLI = .918; RMSEA = .036; SRMR within  = .037; SRMR between  = .044. In Fig.  2 , all statistically significant regression coefficients are presented on within and between levels; the complete model results for both levels can be found in Table  2 .

Results of multilevel structural equation modeling with self-efficacy, BPNS, and emotions. Note : N  = 748 sessions (within level), N  = 103 teachers (between level). Regressions that are statistically significant at the p  < .001 level are denoted by ***, p  < .01 with ** and p  < .05 with *. The model yielded a satisfactory model fit (χ 2 ( df  = 108, n  = 103) = 214.05; p  < .001; CFI = .958; TLI = .918; RMSEA = .036; SRMR within  = .037; SRMR between  = .044). For clarity, only statistically significant relations are shown, and indicators of the latent variables (self-efficacy, BPN) are not displayed. Residual correlations are included but not depicted

Self-efficacy was strongly and positively related to satisfaction of the needs for competence, autonomy, and relatedness, both on the within level and on the between level, as proposed in H1 (within level: β = .56 –.82, p  < .001; between level: β = .56–.87, p  < .001). On the within level, there were no statistically significant relations between self-efficacy and any emotions, which did not confirm H2a-f. Thus, teachers who felt more self-efficacious than usual in one session did not, for example, report statistically significantly more joy than usual in the respective session. However, we did find statistically significant relations between self-efficacy and anxiety and shame on the between level (β = –0.78 / –.54, p  < .05). Both were negative, aligning with our assumptions (H2c and H2e). Thus, teachers who reported higher self-efficacy than others also reported less anxiety and less shame than their fellow participants.

For the associations between BPNS and emotions, differences emerged between the within level (variation within teachers from session to session) and the between level (variation between different teachers). On the within level, all statistically significant links between BPNS were positive with positive emotions and negative with negative emotions. Consistent with our expectations, teachers who experienced more satisfaction of their need for competence in a session experienced more joy (β = .30, p  < .05; H3a) compared to other sessions. Similarly, teachers who had a greater sense of satisfaction of their need for autonomy in a session experienced more joy (β = .24, p  <.001; H4a) and pride (β = .19, p  <.01; H4b) and less anger (β = –.40, p  < .001; H4d) and boredom (β = –.28, p  < 0001; H4f) compared to other sessions. Furthermore, teachers who felt a stronger sense of satisfaction of their need for relatedness in a session also experienced more joy (β = .31, p  <.05; H5a) and pride (β = .21, p  <.001; H5b) and less anger (β = –.30, p  < .001; H5d) and boredom (β = –.26, p  < .001; H5f) compared to other sessions. Notably, not all basic psychological needs were found to be significantly associated with all emotions on the within level.

On the between level, we found a different pattern of associations between BPNS and emotions compared to the within level. There were no statistically significant associations between satisfaction of the need for competence or autonomy with any emotions, implying that teachers who experienced more satisfaction of the need for competence or autonomy did not feel more positive or less negative emotions than teachers who experienced less satisfaction of the need for competence or autonomy. However, our results imply that teachers who felt that their need for relatedness was satisfied during teaching experienced more pride (β = .43, p  <.001; H5b), but also more anxiety (β = .38, p  <.01; H5c), more anger (β = .38, p  <.05; H5d), and more shame (β = .34, p  <.01; H5e) during their teaching sessions than teachers whose need for relatedness was less satisfied.

Table 3 depicts the indirect effects of self-efficacy on emotions via the respective basic psychological needs. In summary, there were statistically significant indirect effects of self-efficacy via the satisfaction of all three basic psychological needs on emotions (for pride, anxiety, and anger), especially on the within level, while on the between level, satisfaction of the need for relatedness mediated the link between self-efficacy and experienced emotions (for pride, anxiety, and shame).

6 Discussion

The present study contributes to painting a clearer picture of higher education teachers’ motivation and emotion by combining established constructs that have primarily been examined independently from each other in research on primary and secondary education teachers. Specifically, the aim of this study was to investigate the interplay between self-efficacy, BPNS, and discrete emotions of higher education teachers during teaching. For this purpose, we tested hypotheses regarding their interrelations based on theoretical considerations and previous empirical findings using session-specific, longitudinal data from higher education teachers in four consecutive teaching lessons. In our model, we considered indirect effects from self-efficacy via BPNS on emotions and examined both the variance between teachers and the variance between sessions within each teacher (i.e., the between and the within teacher level, respectively). The results largely confirmed our hypotheses, with notable exceptions, and suggest that combining these constructs can help facilitate a better understanding of motivation and emotion of higher education teachers during teaching. Furthermore, our investigation of the associations between self-efficacy, satisfaction of the need for relatedness, and discrete emotions revealed significant differences when comparing both levels, i.e., regarding their interplay in differences between teachers compared with changes within teachers from session to session.

6.1 Interplay between self-efficacy, BPNS, and emotions

6.1.1 discussion of descriptive statistics.

Descriptively, we found rather high means of self-efficacy and BPNS. This was to be expected as we asked higher education teachers to participate on a voluntary basis which may have led to a rather motivated sample. For discrete emotions, prior studies found rather high means for positive emotions during teaching in higher education, especially for enjoyment, and rather low means for negative emotions, aligning with our results (e.g., Frenzel et al., 2016 ; Klassen et al., 2012 ; Thies & Kordts-Freudinger, 2019 ). Thus, the pattern of descriptive statistics found within our study lies within the expected range. Notably, the ranges and standard deviations of the scales used in our study suggest that there were substantial differences between teachers in their motivational and emotional experiences during teaching.

6.1.2 Stability of higher education teachers’ self-efficacy, BPNS, and emotions

Teachers’ self-efficacy for teaching was rather stable across sessions for individual teachers, as illustrated by high intraclass correlations. This stands in line with the theoretical reasoning that self-efficacy is a rather stable construct (Bandura, 1997 ), which has been documented in several studies on primary and secondary school teachers (e.g., Schwarzer & Warner, 2014 ).

More than two thirds of the variability of satisfaction of the need for relatedness could be attributed to the teacher level, as well as almost two thirds of the variability of satisfaction of the needs for competence and autonomy, illustrating that BPNS is not exclusively determined by the context, but is also dependent on how the specific teacher experiences the context. It is notable that satisfaction of the need for relatedness emerged as being more person-specific than satisfaction of the other two needs. Seemingly, whether teachers feel that their need for relatedness is satisfied depends less on contextual factors than whether teachers feel that their need for competence and autonomy is satisfied during a given session.

The proportion of variability in the discrete emotions that could be located at the teacher level differed, with joy, pride, and anxiety being more person specific, while for anger, shame, and boredom, only about a third of the variability could be traced back to the individual teacher level. In previous studies, discrete emotions in the academic context were found to have equally temporally stable and variable parts, paralleling our results for joy, pride, and anxiety (see, e.g., Nett et al., 2017 , who investigated the same emotions, apart from shame, in students). These findings emphasize the significance of considering both levels of analysis, as a substantial portion of the variability in the constructs can be attributed to both the between teacher and within teacher levels.

6.1.3 Interplay of self-efficacy, BPNS, and emotions

Overall, we found that higher education teachers’ self-efficacy, BPNS, and emotions were intertwined, with associations between BPNS and emotions partly differing between the within and the between level. We also observed indirect relationships between self-efficacy for teaching and emotions, mediated by BPNS. Generally, our structural equation modeling results emerged as relatively robust when compared with the additional models calculated with one of the three aspects of BPNS each (see Tables S2–S4 in the supplementary material). We first discuss the results on the within level, followed by the between level, and contrast both.

6.1.3.1 Interplay of Self-efficacy, BPNS, and emotions within teachers from session to session

On the within level, our findings mirrored the presumed positive associations between teaching self-efficacy regarding an upcoming session and satisfaction of the needs for competence, autonomy, and relatedness (in line with H1). This means that if teachers reported higher than usual self-efficacy in one session, they also reported higher than usual BPNS in that session. Thus, even though higher education teachers’ self-efficacy seems to be rather stable, as the intraclass correlations suggest, changes in their self-efficacy for teaching right before teaching sessions were relevant for BPNS in the respective session.

Regarding the direct relations between self-efficacy and emotions, we did not find any statistically significant results at the within level. However, our results on total and specific indirect effects partly supported our theoretical assumption of mediation through BPNS. Specifically, when teachers’ self-efficacy for teaching was higher than their usual level immediately before a session, it was associated with experiencing more joy and pride, as well as less anger and boredom in that session compared to other sessions. These relationships were statistically mediated by the satisfaction of teachers’ needs for competence, autonomy, and relatedness, with the satisfaction of competence only mediating the relation to joy.

While we could only identify a statistical mediation from the satisfaction of competence to joy but not to the other emotions, the effects on pride, anger, and boredom were also mediated by the satisfaction of the needs for autonomy and relatedness. It should be kept in mind that we proposed and tested this mediation based on theoretical considerations, but BPNS and emotions were measured at the same time, so, based on the empirical findings and the statistical results we cannot depict a causal mediation here. Indeed, it is also possible that the emotions experienced during teaching might influence to which degree the needs for competence, autonomy, and relatedness of teachers were satisfied. However, our considerations are supported by empirical research with designs that allow for causal inference, such as the study by León and Núñez ( 2013 ) who found casual relations from BPNS to well-being. Additionally, there are strong theoretical grounds for the direction that we tested: This finding supports the theoretical notion that self-efficacy for teaching can shape how teachers perceive and interpret their teaching experiences. Following our hypothesis, self-efficacy determines the extent to which teachers’ basic psychological needs for competence, autonomy, and relatedness are fulfilled during the session. It stands to reason that when teachers have high self-efficacy, they are more likely to have motivationally favorable appraisals of their teaching experiences, similar to the reasoning proposed by Jerusalem and Schwarzer ( 1992 ) regarding self-efficacy and stress appraisals. These positive appraisals, in turn, contribute to a higher level of BPNS.

Direct associations between BPNS and emotions were found for all three aspects of basic psychological need satisfaction on the within level. In specific sessions where teachers felt that their needs for competence, autonomy, and relatedness were more satisfied than in other sessions, they also experienced more joy than in other sessions, paralleling the theoretical mechanisms proposed in SDT (Deci & Ryan, 2000 ) and aligning with prior evidence (Klassen et al., 2012 ). Next to that and in line with our expectations, satisfaction of the need of autonomy was significantly positively associated with pride. As reasoned before, teachers are more likely to feel proud of their achievements in a given session compared to other sessions if they believe they are responsible for their success, i.e., they felt autonomous in making the decisions that led to successful teaching. Similarly, the connection between satisfaction of the need for relatedness and pride is also in line with our expectations, as teachers may experience a greater sense of pride in a specific session when they not only take pride in fostering connections with their students (see Praetorius et al., 2018 , for relatedness as a measure of teaching quality), but also when they feel proud of the students they have formed a meaningful connection with. Surprisingly, satisfaction of the need for competence was only connected with joy, which did not align with our hypotheses (see H3).

Concerning the negative emotions, for changes within teachers from session to session, satisfaction of the need for autonomy and the need for relatedness were negatively related to anger and boredom. Again, this did not extend to teachers’ satisfaction of the need for competence. The pattern of satisfaction of the needs for autonomy and relatedness being negatively related to negative emotions during teaching aligns with our hypotheses as well as with prior research (Hagenauer & Volet, 2014 ). Elucidating the source of the discrete emotions might explain why, against our hypotheses, the relations with satisfaction of the needs for autonomy and relatedness were more prevalent than relations with satisfaction of the need for competence. Concerning, for example, anger, the anger that teachers experience might not be rooted in being angry about their own performance (i.e., not feeling competent), but rather in the external circumstances that restricted them (i.e., not feeling autonomous), or students not participating as they were supposed to in this particular session. This notion is corroborated by prior research: Hagenauer and Volet ( 2014 ) conducted interview studies on the emotions of higher education teachers during teaching and identified student engagement and a lack of control over teaching situations as overarching factors influencing teachers’ emotions, pointing to the satisfaction of the needs for relatedness and autonomy, but not to satisfaction of the need for competence. Burić and Frenzel ( 2019 ) obtained similar findings for anger in quantitative studies, pinpointing student behavior, but also parental involvement and organizational factors (i.e., factors that can reduce autonomy) as primary antecedents of anger among primary and secondary education teachers. However, in our study, teachers did not provide detailed explanations of what specifically elicited their emotions. Therefore, future studies could extend this line of research by combining session-specific assessments of emotions with retrospective interviews, wherein teachers can elaborate on the sources of the discrete emotions they experienced during teaching. The latter might also explain why, in our study, the negative emotions anxiety and shame were not statistically related to BPNS at all, even though we expected them to be related based on theoretical assumptions and prior evidence (see H3c,e; H4c,e; H5c,e).

It should be kept in mind that even though self-efficacy was assessed before each session and BPNS and emotions were assessed after the session ended—implying a temporal direction from self-efficacy to BPNS and emotions—this study design does not unambiguously allow for causal interpretation, and the described directions could also work in the reverse direction. For example, from a theoretical perspective, positive emotions can also foster self-efficacy, representing the opposite direction Pekrun et al., 2007 ).

6.1.3.2 Interplay of self-efficacy, BPNS, and emotions between different teachers

Similar to the within level, we found that teachers who reported higher self-efficacy than their colleagues also reported higher satisfaction of the needs for competence, autonomy, and relatedness than their colleagues. Thus, comparing the results on both levels, teachers who generally held higher self-efficacy beliefs than their colleagues experienced higher BPNS, and at the same time, as elaborated before, if a teacher held higher self-efficacy beliefs than usual right before a session, their needs for competence, autonomy, and relatedness were more satisfied in that session.

Concerning the relations between self-efficacy and emotions, in line with our expectations, teachers with higher self-efficacy for teaching experienced less anxiety and shame during teaching compared to their colleagues (see H2c,e). These direct relations between self-efficacy and emotions were not apparent when looking at differences within teachers from session to session. This difference on both levels supports the notion that self-efficacy is a rather stable construct that can act as a protective factor against the experience of negative emotions (see Schwerdtfeger et al., 2008 ). However, this line of reasoning raises the question of why anger and boredom were not statistically significantly related to self-efficacy at the between level. In our context, this could be due to anxiety and shame being more closely tied to session-specific appraisals of competence, while anger or boredom might be influenced by contextual elements like malfunctioning technical infrastructure or repetitive topics in teaching. Regarding anger, this line of reasoning is supported by the earlier findings of Burić and Frenzel ( 2019 ), who identified various sources of anger in teaching beyond competence appraisals. Regarding boredom, various antecedents during teaching can be discerned following control-value theory, some of which are unrelated to one’s abilities (e.g., repetitive topics; Pekrun, 2000 ).

Regarding our hypotheses (H2a,b), we would have expected self-efficacy for teaching to be additionally connected to the positive emotions of joy and pride, as suggested by both self-efficacy theory (Bandura, 1997 ) and control-value theory (Pekrun et al., 2007 ). While on a bivariate level, self-efficacy was in fact positively associated with joy, the missing connections to pride are puzzling. Following control-value theory, teachers’ experiences of pride might, to a large extent, be based on students’ success in the classroom, e.g., students raising interesting questions or understanding challenging topics. These student achievements might not necessarily be connected to teachers’ perceptions of their own achievement in teaching, i.e., not with their self-efficacy for teaching. As we only asked teachers about their emotions in general (i.e., to rate the statement “In this session, I felt pride”), what they felt proud about remains a question of interpretation. Again, this informs future studies to include the reason or source for emotions when assessing them, allowing to test the interpretation given here.

In addition to these direct associations between self-efficacy and emotions, our results suggest indirect positive associations via relatedness on pride, anxiety, and shame. Regarding the indirect effect on pride, similar to the session-to-session differences, high levels of self-efficacy probably led to more positive appraisals of their teaching abilities, which, in turn, resulted in higher satisfaction of their need for relatedness. By feeling a sense of connection with their students, these teachers may subsequently experience greater pride in their students’ achievements compared to teachers who have a lower level of satisfaction of their need for relatedness. This line of reasoning is supported by the idea that teachers reported pride as being proud of their students instead of pride as an achievement emotion concerning teachers’ own achievement. However, it is worth noting that our further findings on indirect effects deviate from our initial expectations, as teachers reporting higher levels of self-efficacy also reported experiencing higher levels of anxiety and shame instead of fewer negative emotions, which raises theoretical questions discussed in the next paragraphs.

We did not find any significant associations between differences in teachers’ satisfaction of the needs for competence and autonomy during their teaching and their experience of positive or negative emotions compared to their colleagues. However, our results indicated that teachers who reported a stronger sense of relatedness to their students experienced higher levels of pride, anxiety, anger, and shame during their teaching in comparison to their colleagues. These findings align with our expectations concerning pride, as it is theoretically expected that the satisfaction of basic psychological needs is positively linked to positive emotions. However, the positive association between relatedness and negative emotions is not in line with the theoretical assumptions of SDT (Deci & Ryan, 2000 ).

One explanation for these unexpected findings of satisfaction of the needs of relatedness, self-efficacy, and negative emotions could be that satisfaction of the need for relatedness could go hand in hand with how socially invested teachers are in their teaching: For example, higher education teachers might experience more anger towards students during a session if they feel more socially connected to them, in contrast to feeling more indifferent, and teachers might be more anxious about making mistakes or be more ashamed of mistakes they might make when they feel a social connection to their students in contrast to being indifferent to them.

In summary, teachers who do not have their need for relatedness satisfied during teaching may exhibit a general sense of distance and lower emotional investment in their teaching, resulting in weaker emotional experiences. If teachers experience differences in their satisfaction of their need for relatedness in just some sessions, they might still be emotionally invested (within level), but teachers who generally experience low levels of satisfaction of their need for relatedness during teaching sessions (between level differences) might emotionally engage with their students less overall. Accordingly, these differences in emotional investment become especially apparent in between person comparisons (as reflected by the indirect positive relations between self-efficacy and anxiety/shame via relatedness becoming visible only at the between level). This is also supported by our finding that the satisfaction of the need for relatedness may be more specific to individual teachers, while satisfaction of the other two needs may be more session-specific (slightly higher ICC1 values for relatedness than for competence and autonomy). At the same time, we observed the expected positive associations with positive emotions and negative associations with negative emotions when examining the associations between emotions and satisfaction of the need for relatedness (and self-efficacy) within one teacher across different teaching sessions, aligning with the theoretical assumptions of SDT (Deci & Ryan, 2000 ). This composition shows that both levels are relevant and need to be included when analyzing teachers’ motivation and emotion, as they seem to follow somewhat different theoretical processes.

Overall, the above-mentioned findings imply that teacher-student-relationships are an integral part of explaining differences in the emotional experiences of different teachers during teaching. For future research on motivation and emotions of higher education teachers during their teaching, it is therefore advisable to consider student–teacher-relationships when aiming to explain differences between teachers’ motivation and emotion. Furthermore, the unique results observed at the within teacher and between teacher levels regarding the relationship between self-efficacy, satisfaction of the need for relatedness, and discrete emotions suggest that solely considering between level associations may not be sufficient when testing theoretical assumptions. It is important to acknowledge that mechanisms and dynamics can differ across different levels of analysis. Therefore, future studies should incorporate both within teacher and between teacher analyses to gain a more nuanced understanding of the complex interplay between individual factors and contextual variables that shape teachers’ emotional experiences.

6.2 Strengths, limitations, and implications

Although limited to the German higher education system, our study’s sample covered universities of two states and a broad variety of subjects, and thus, the influence of bias based on organizational structure is lowered. The micro-longitudinal design allowed for multilevel analyses covering different teachers and sessions, contrasting effects on the between and within teacher level and making different connections on the levels visible. Moreover, our sample size was considerably high with variation in gender, age, and academic positions of higher education teachers, contributing to the generalizability of our findings. In addition to collecting data regarding several lessons, our design provided a session-based approach. As a result, the higher education teachers’ answers may not have been as affected by memory biases and may more accurately reflect their self-efficacy, BPNS, and discrete emotions in their teaching.

Despite the strengths of our study, several limitations should be considered when interpreting our findings. First, our session-specific approach may have influenced the data by disturbing the natural procedure of a session, given that the teachers had to complete a short questionnaire right at the beginning and at the end of each session. Nevertheless, to reduce these effects, student assistants were present to help organize and support the teachers when answering the questionnaires. Additionally, as a result of our study design, the scales within the questionaires needed to be very short, which partly limits interpretation—for example, our single-items for measuring emotions do not provide information about why the participants experienced these emotions, and thus, sources of emotions cannot be detected.

Moreover as we did not obtain a sufficient number of courses per teacher for an analysis on three levels, we chose the more conservative approach of analysing two levels. However, it would also be an interesting research direction to assess further control variables, such as the frequency of the course or number of participants, which might influence how related higher education teachers feel towards their students. Finally, our study only used self-reported data of teachers; it could be fruitful, however, to also include student reports concerning student motivation and their perception of the lesson. This could allow for further insights into whether the connection between BPNS of school teachers and students (see Roth et al., 2007 ) can also be found in the higher education context, or if the connection between motivation of teachers and teaching quality can be replicated.

Despite these limitations, our findings indicate that self-efficacy, BPNS, and emotions are interrelated within higher education teachers’ teaching experiences. Thus, identifying practical methods to support these factors in higher education teaching can be considered an important direction. As self-efficacy has proven to be rather stable across teaching sessions, it seems to be more feasible to influence contextual features that in turn lead to favorable BPNS which could support teachers to experience more positive and less negative emotions during teaching. For example, identifying specific aspects of teaching in higher education that promote and limit autonomy, through methods such as interview studies, could be a promising approach to enhance satisfaction of the need for autonomy. Additionally, since satisfaction of the need for relatedness was particularly linked to positive emotions on the within level, fostering a sense of relatedness between higher education teachers and their students, for instance, by implementing personal introductions in their teaching or through informal counselling hours (Averill & Major, 2020 ), may help establish a sense of relatedness and support positive emotional experiences for both teachers and students. However, it is important to note that the effects of satisfaction of the need for relatedness on negative emotions at the between level appear contradictory. Further research is needed to replicate and clarify the positive effects of satisfaction of the need for relatedness on negative emotions when examining differences between teachers. It might also be an important line of research to assess whether the experience of negative emotions during teaching is problematic. Feeling ashamed due to students’ failures might be as important as feeling proud of their successes, and both might contribute to teachers’ investment in and development of their teaching.

6.3 Conclusion

In this study, we successfully applied the theoretical constructs of self-efficacy, BPNS, and emotions to the context of teaching in higher education. We found them to be prevalent in higher education teachers during teaching sessions and to be interconnected, showing relations regarding more stable differences between teachers as well as changes within teachers from session to session. Our results suggest that self-efficacy might influence emotions indirectly via satisfaction of the needs for competence, autonomy, and relatedness. As expected, high self-efficacy was positively associated with positive and negatively associated with negative discrete emotions; satisfaction of the need for autonomy and the need for relatedness were linked to favorable emotions. However, differences emerged regarding within and between teacher levels: While the satisfaction of the need for relatedness seemed to be a protective factor against negative emotions in regard to specific sessions, teachers whose need for relatedness was generally more satisfied experienced both more positive and more negative emotions than colleagues whose need for relatedness was less satisfied.

Based on this, combining several motivational theories appears to be a promising approach to better understand how they work in specific situations. However, we untangled unexpected positive associations between satisfaction of the need for relatedness and negative emotions on the between level that require further research. In terms of practical implications, providing contexts that, besides fostering high self-efficacy for teaching, help satisfy basic psychological needs appears to be critical for promoting positive emotions during teaching. Within this, especially autonomy and relatedness seem to be important for favorable motivation and emotions in teaching in higher education.

The dataset used for this paper was part of a larger study, where in addition to self-efficacy, basic needs, and emotions, other psychological constructs were assessed that were used in other published works without any overlap, namely Daumiller et al. ( 2021a , 2022 ), Hein et al. ( 2020 ), and Schwab et al. ( 2022 ). One publication (Daumiller et al., 2023 ) used the same emotion scales as in the publication at hand, investigating the stability and context specificity of achievement goals and emotions. The hypotheses and associations investigated in this article were not a part of any of these prior articles.

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This work was supported by the German Research Foundation (DFG; Deutsche Forschungsgemeinschaft) under Grant DR 454/8-1 awarded to Markus Dresel, and Grant DI 929/5-1 awarded to Oliver Dickhäuser.

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Keller, M.V., Rinas, R., Janke, S. et al. Intertwining self-efficacy, basic psychological need satisfaction, and emotions in higher education teaching: A micro-longitudinal study. Soc Psychol Educ (2024). https://doi.org/10.1007/s11218-024-09888-1

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Relationships between academic self-efficacy, learning-related emotions, and metacognitive learning strategies with academic performance in medical students: a structural equation model

• Ali Asghar Hayat 1 ,
• Karim Shateri 2 ,
• Mitra Amini 1 &
• Nasrin Shokrpour 3  

BMC Medical Education volume  20 , Article number:  76 ( 2020 ) Cite this article

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Recognition of the factors affecting the medical students’ academic success is one of the most important challenges and concerns in medical schools. Hence, this study aimed to investigate the mediating effects of metacognitive learning strategies and learning-related emotions in the relationship between academic self-efficacy with academic performance in medical students.

The present study was carried out on 279 students of medicine studying at Shiraz University of Medical Sciences. The students filled out three questionnaires: academic emotions (AEQ), metacognitive learning strategies, and academic self-efficacy questionnaires. The data were analyzed using SPSS and Smart PLS3.

The results of structural equation modeling revealed that the students’ self-efficacy has an impact on their learning-related emotions and metacognitive learning strategies, and these, in turn, affect the students’ academic performance. Moreover, learning-related emotions influence the metacognitive learning strategies, which in turn mediate the effect of emotions on academic performance.

The results of this study revealed that metacognitive strategies and learning-related emotions could play a mediating role in the relationship between students’ self-efficacy and academic performance.

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Academic success and obtaining good grades are among the main goals in all levels of education while having positive outcomes both for the learners and educational systems. Therefore, identifying the factors influencing the students’ academic success has ever been one the most important concerns of the researchers and educational psychologists [ 1 ], and also one of the challenges faced by medical schools [ 2 , 3 ]. To this end, researchers have focused on recognition of the role of motivation, learning strategies, and academic emotions in the students’ learning and performance [ 4 , 5 , 6 , 7 ].

However, most of the researches have been conducted using correlation analysis [ 6 ], qualitative methods [ 4 ], and experimental approaches [ 8 ]; they have revealed a positive and simple relationship between these variables and academic performance [ 9 ] and have not shown direct and indirect effect of these variables on each other. Moreover, most of these studies have been carried out in the field of psychology, social sciences, and education [ 10 , 11 ], and the results of these studies cannot be generalized to the medical context. Since the nature of the academic field is supposed to affect the students’ learning strategies [ 12 ], there may be a difference between medical students’ learning approaches in comparison with those of other students in higher education [ 13 ]. Moreover, students in different academic settings and environments have revealed to experience different emotions. By implication, emotions might be different across these contexts [ 5 ]. As Artino et al. noted, these emotional factors had almost been neglected in medical education literature. Instead, medical education literature tends to focus mostly on cognitive factors such as prior academic achievement, which do not explain much of the variance in academic outcomes [ 2 ]. Yet, a large body of medical literature on emotions indicates that many medical students experience stressful situations during their education resulting in depression and anxiety. There has been very little attempt to look at how these emotions influence the students’ self-regulating learning (SRL) [ 2 ]. As to the Iranian context, since the physicians have a very high income, most students are eagerly competing to be admitted in this major, so the smartest students with the highest potential get accepted to continue their studies in this major.

On the one hand, there is still limited knowledge about the effect of motivation and emotions on the students’ academic outcomes both in the classroom and clinical settings [ 2 , 14 ]. On the other hand, most of the studies have been conducted in western countries [ 15 ], and generalizing their findings to other countries, especially developing ones, has been criticized [ 16 ]. Therefore, this study was conducted to investigate the effect of self-efficacy, learning-related emotions, and metacognitive learning strategies on medical students’ academic performance. More specifically, it was attempted to determine how metacognitive learning strategies can mediate the relationship between self-efficacy and positive learning-related emotions and academic performance.

The effect of positive academic emotions on academic performance

Emotion is a subjective status accompanied by physiological reactions and responses to some conditions, actions, and events. Pekrun (2006) defines academic emotions as those which are directly related to achievements, activities, and outcomes [ 17 ]. This term was first used by Pekrun et al. (2002) in the field of education [ 4 ] classified into positive (enjoyment, pride, hope); negative (boredom, anger, anxiety); activating (joy, pride, anger); and deactivating (shame) emotions [ 5 , 17 ]. Emotions have complex associations with cognitive, motivational, and behavioral processes, especially in the classroom and educational settings [ 4 , 5 , 14 , 17 , 18 ], in all educational situations (before, during, and after attending the classroom, studying and testing) [ 4 , 10 ], and in clinical settings [ 2 , 14 ], as experienced by the students.

Moreover, some researchers have considered emotions as a significant factor directly or indirectly associated with learners’ achievements; satisfaction; physical and mental health; motivation; learning strategies; cognitive sources; self-directed learning; quality of teacher-learner interactions; class education; concentration; information processing, storing, retrieving, and learning; and consequently academic achievement [ 1 , 2 , 4 , 5 , 10 , 17 , 19 , 20 ]. Pekrun (2006) indicated that pleasant positive emotions like enjoyment positively influences on academic achievement. On the contrary, unpleasant deactivating emotions like boredom can reduce our motivation and disturb data processing, showing the negative effect of such emotions on academic achievement [ 17 ].

Chin et al. (2017) found a significant relationship between the students’ positive emotions and their performance [ 21 ]. Pekrun et al. (2009) revealed that positive activating emotions like enjoyment, hope, and pride have a significant relationship with the students’ midterm exam scores [ 10 ]. Generally, previous research showed that positive emotions such as enjoyment, hope, and pride are predictors of academic achievement [ 4 , 5 ].

The effect of academic self-efficacy on academic performance

Academic self-efficacy is one of the important factors influencing academic performance. Academic self-efficacy refers to the students’ beliefs and attitudes toward their capabilities to achieve academic success, as well as belief in their ability to fulfill academic tasks and the successful learning of the materials [ 22 , 23 ].

Self-efficacy beliefs lead to the individuals’ excellent performance through increasing commitment, endeavor, and perseverance [ 24 ]. The learners with high levels of self-efficacy attribute their failures to lower attempts rather than lower ability, while those with low self-efficacy attribute their failure to their low abilities [ 25 ]. Therefore, self-efficacy can influence the choice of tasks and perseverance while doing them. In other words, students with low self-efficacy are more likely to be afraid of doing their tasks, avoiding, postponing, and give them up soon [ 22 , 23 ].

In contrast, those with high levels of self-efficacy are more likely to rely on themselves when faced with complex issues to find a solution to the problem, as well as being patient during the process, making more efforts, and persisting longer to overcome the challenges [ 9 , 23 , 26 ]. Therefore, it seems that self-efficacy is one of the most important factors in the students’ academic success. For example, Chemers and Garcia found that the students’ self-efficacy in the first year of university is a strong predictor of their future performance [ 27 ].

Alyami et al. (2017) conducted a study on 214 university students and revealed that academic self-efficacy has a positive and significant effect on their academic performance [ 28 ]. Other studies have shown that academic self-efficacy has a considerable effect on the students’ learning, motivation, and academic performance [ 9 , 18 , 29 , 30 , 31 ].

The effect of metacognitive learning strategies on academic performance

In the recent years, self-regulated learning and especially metacognitive learning strategies [ 32 ] have received a great deal of attention, and many studies are being conducted in this field [ 33 ]. Predominantly, metacognitive strategies are among the key components of self-regulated learning, enabling learners to plan, monitor, and regulate their cognition [ 34 , 35 ]. Today, it is believed that learners using more metacognitive learning strategies effectively have better study plans, more efficiently monitor and evaluate their learning and perception of the materials, are more responsible, find and solve their problems, and try hard to learn deeply [ 36 , 37 ]. They certainly succeed more than their peers with no skills in the use of such strategies [ 38 ]. In this regard, it has been confirmed that metacognitive learning strategies have a main role in academic success, as shown by the theories and researches [ 1 , 4 , 23 , 24 , 35 , 38 ].

Conceptual framework and hypotheses

The control- value theory of achievement emotions is a comprehensive framework for analysis of the effects of emotions on the students’ academic performance. As hypothesized by Pekrun, in this theory, positive emotions influence the students’ achievement indirectly through the mediating role of cognitive, metacognitive, and self-regulating behaviors [ 17 , 19 ].

Generally speaking, emotions can influence the students’ achievement through two main pathways of cognitive and motivational and four mechanisms. In the cognitive pathway, emotions can influence one’s performance through three mechanisms, including mood-dependent memory, and cognitive and metacognitive learning strategies, and the use of cognitive sources [ 14 , 39 ].

In contrast, positive emotions resulting from the use of deep, flexible, and complex learning strategies and self-regulation facilitate the individuals’ learning [ 4 ], so that the students who experience positive emotions utilize deeper strategies and more metacognitive processing [ 4 , 40 ], that, in turn, enhances the students’ achievement. Therefore, the effect of emotions on academic performance can be mediated by the use of metacognitive learning strategies.

Based on Pekrun’s control-value theory [ 17 , 40 ], cognitive assessment is supposed to be one of the significant antecedents of academic emotions categorized into control assessments (perceived control) and value assessments (perceived value). Control assessments are related to the individuals’ perception of the controllability of achievement activities and their consequences. These assessments are shown through our expectations and perception of competence, such as self-efficacy. Therefore, academic self-efficacy (as a cognitive assessment) can influence academic emotions [ 1 , 4 , 14 ]. On the other hand, many researchers have investigated the role of self-efficacy in academic achievement since the introduction of the concept of self-efficacy by Bandura (1977) [ 9 , 18 , 30 , 31 ]. Bandura’s (1977) social cognitive theory discusses self-efficacy as the main construct, which affects both performance and motivation [ 26 ].

Some researchers believe that a part of the relationship between self-efficacy and academic achievement can be attributed to metacognitive learning strategies [ 35 , 41 ]. More specifically speaking, evidence shows that students with higher self-efficacy (as an expectancy component) show more endeavor and perseverance when faced with challenging situations [ 23 ]. Despite the positive effect of self-efficacy on the amount of attempt, evidence shows that the quality of the efforts of self-efficacious students is different as well; such students use various deeper cognitive and metacognitive processing strategies compared to their peers with lower self-efficacy. This leads to better learning and academic achievement [ 35 , 38 ]. On the contrary, students with low self-efficacy seek easier tasks to avoid failure and use superficial strategies while disregarding deep learning [ 6 ].

Therefore, as shown in other studies, self-efficacy and metacognitive learning strategies are closely related [ 35 , 42 ]. As stated by Pintrich, self-efficacy becomes a key determinant of whether learners adopt these strategies or not. According to self-regulated learning theories, apart from being aware of the cognitive and metacognitive strategies, students should be motivated to enthusiastically use these strategies to succeed [ 35 ]. In this respect, the general expectancy-value theory of motivation [ 35 , 43 ] suggests that there are three motivational components that might be associated with the components of self-regulated learning like metacognitive strategies: (a) an affective component, which involves emotional reactions of students to the task (pride, anger, etc.), (b) an expectancy component, including the students’ beliefs about their capability to do a task (self-efficacy), and (c) a value component, including the students’ goals and beliefs about the importance and interest of the task. Prior research reveals that the expectancy, value, and affective components are positively associated with the self-regulated learning components [ 35 , 44 ].

In short, the studies conducted in this field have shown a positive association between self-efficacy and metacognitive learning strategies [ 35 , 36 , 42 , 45 ]. On the other hand, many studies have indicated that metacognitive learning strategies are one of the most important predictors of the students’ academic success [ 4 , 9 , 24 , 35 , 38 , 46 ]. Therefore, as shown in some studies, metacognitive learning strategies mediate the effect of self-efficacy on academic performance [ 47 ]. There has been some progress in research in this area. According to the review of the literature, although many studies have been conducted on direct effect of variables as academic emotions, academic self-efficacy, metacognitive learning strategies and their roles in academic achievement, few studies have focused on direct and indirect relationship among these variables and investigated the role of emotions, self-efficacy, and metacognitive learning strategies together as predictors of academic achievement in a structural equation model. Previous studies have either investigated the effect of the above-mentioned variables on each other separately [ 2 , 36 , 42 , 48 ], or they have focused on fields other than medical education [ 1 , 4 , 10 , 28 , 32 , 46 ]. Therefore, according to the control-value theory [ 40 ], the expectancy-value theory of motivation [ 43 ], the social cognitive theory and review of the literature, the present study was designed to test the following research hypotheses and conceptual model (see Fig.  1 ):

The conceptual model

H1: Academic self-efficacy has a direct effect on academic performance.

H2: Positive academic emotions have a direct effect on academic performance.

H3: Metacognitive learning strategies have a direct effect on academic performance.

H4: Academic self-efficacy has a direct effect on positive academic emotions.

H5: Academic self-efficacy has a direct effect on metacognitive learning strategies.

H6: Positive academic emotions have a direct effect on metacognitive learning strategies.

H7: Metacognitive learning strategies mediate the relationship between academic self-efficacy and academic performance.

H8: Metacognitive learning strategies mediate the relationship between positive academic emotions and academic performance.

H9: Positive academic emotions mediate the relationship between academic self-efficacy and academic performance.

Participants and procedures

This cross-sectional study was conducted on 279 (64.5% females and 35.5% males) medical students studying in their first to fifth semesters (basic sciences period) in the 2018–2019 academic years at Shiraz University of Medical Sciences, Iran. The response rate of the participants was 279/350 (79%).

In general, the course of medicine lasts for 7 years in Shiraz University of Medical Sciences, divided into four periods, including basic sciences, physiopathology, externship, and internship. Each year about 200 medical students enter Shiraz Medical School straight after graduation from high school. Students’ major courses were investigated in each semester. In this study, the pathology, anatomy, cardiovascular system, digestive system, urinary tract, glands, reproductive system, blood, musculoskeletal system, neurology, respiration, and head and neck anatomy courses were selected. The mentioned courses are presented both theoretically or integration of theory and practice.

The students aged between 18 and 35 years old (mean 19.6, SD 3.2). Although a sample size of over 200 is satisfactory for conduction of Structural Equation Modeling (SEM), some researchers have suggested 20 subjects for each variable [ 49 , 50 ]. Our sample size satisfied both views. Of course, the advantage of Partial Least Square (PLS) approach is that it requires a smaller sample size in comparison with other approaches such as LISREL and AMOS. PLS is more suitable for real applications, especially in the case of more complex models, the use of this approach is more satisfactory.

The subjects were selected using the convenience sampling method. Since this study was conducted on humans, first, it was approved by the Research Ethics Committee of Shiraz University of Medical Sciences with the code of IR.SUMS.REC.1397.595. Also, the students were assured that their information would remain confidential. Before commencement of the study, written informed consent was obtained from all the students.

They were asked to fill out the forms anonymously. Participation in the study was completely voluntary, and those who were willing to participate filled out the questionnaires. The questionnaires were distributed among the students, and they were asked to answer the questions about how they experienced these emotions during the semester. Also, the questionnaires of metacognitive learning strategies and academic self-efficacy were simultaneously distributed.

In the current study, three types of questionnaires were applied.

Academic emotions questionnaire (AEQ)

AEQ developed by Pekrun et al. is a valid and reliable questionnaire measuring the students’ academic emotions [ 5 ]. It consists of 3 parts measuring the emotions related to the classroom, learning, and exams separately. In this study, an adapted version of AEQ was used to evaluate the students’ experienced positive emotions while studying (positive learning-related emotions).

This subscale includes three positive emotions related to learning (enjoyment, pride, hope) with 22 questions answered in the form of a 5-point Likert scale ranging from completely disagree [ 1 ] to completely agree [ 5 ]. Pekrun et al. have reported a good validity and reliability coefficient for this questionnaire [ 5 ].

Metacognitive learning strategies questionnaire

Motivated Learning Strategies Questionnaire (MLSQ) is a valid and reliable questionnaire used for evaluation of the students’ motivational orientations and self-regulatory learning strategies [ 44 ]. This questionnaire contains two subscales of motivation and self-regulated learning and has been used in many studies in medical and other fields [ 2 ]. In this study, metacognitive learning strategies subscale consisting of 12 items was used, in which results are scored using 5 -point Likert scale. Pintrich et al. have reported a Cronbach’s alpha of 0.79 for this subscale [ 44 ].

Academic self-efficacy questionnaire

The self-efficacy for learning and performance is one of the subscales of the above-mentioned questionnaire (MLSQ). It contains 8 questions evaluating the students’ beliefs regarding their abilities and performance.

These items are scored using a 5 -point Likert scale. Pintrich et al. also reported a desirable validity and reliability for this instrument [ 44 ], and it has been used in many studies [ 6 , 9 ].

• Academic performance

To assess the students’ academic performance, their final exam scores in that semester were considered. Scores in a course which are obtained on the midterm and final exams and also semester-work component consisting of a term paper, quizzes, and assignments were all considered as indicators of academic performance. The assignments include class presentation individually or in group, review of a book or paper, group discussions which are done as a part of the course requirements. Also, some of the lecturers assign some research projects which are conducted are conducted and presented by students in the class. In addition, in the context of Shiraz University of Medical Sciences, the students are assessed through formative and summative multiple-choice tests.

We used SPSS version 21 to calculate the mean and standard deviation and correlation coefficients between the variables. Also, we used Smart-PLS 3 to determine the validity and reliability and also the path coefficients between the variables. There are two types of structural equation modeling (SEM) namely covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). For the current study, PLS-SEM applying smart-PLS software was selected which empowers the researchers to estimate very complex models with many constructs and indicator variables, especially when prediction remains the main goal of the analysis. PLS-SEM basically offers more flexibility regarding data requirements and specification of the associations between the constructs and indicator variables [ 51 ]. PLS-SEM focuses on two processes, including the measurement model and structural model [ 52 ].

The matrix correlation results showed that, self-efficacy has a significant and positive relationship with academic performance (r = 0.46, p  ≤ 0.01), metacognitive learning strategies (r = 0.59, p  ≤ 0.01), and positive learning-related emotions (r = 0.65, p  ≤ 0.01). In addition, findings showed that, positive learning-related emotions have a positive and significant correlation with metacognitive learning strategies (r = 0.55, p  ≤ 0.01) and academic performance (r = 0.48, p  ≤ 0.01). Also, as shown in Table 1 , a significant and positive correlation was found between metacognitive learning strategies and academic performance (r = 0.45, p  ≤ 0.01).

The measurement model

The measurement model in PLS was evaluated in terms of internal consistency reliability, convergent validity, and discriminant validity. Internal consistency reliability measures the degree to which the items measure latent construct (Hair et al., 2006), assessed through composite reliability scores. Composite reliability of 0.7 or greater is considered acceptable. Results showed that the CR scores of all constructs exceeded the recommended criterion of 0.7, demonstrating appropriateness of the scales used in the current study.

Next, the factor loadings and Average Variance Extracted (AVE) were assessed to determine the convergent validity of the constructs. Individual item loadings greater than 0.7 are considered as adequate. Based on the results of the measurement model (Table 2 ), all the construct items exhibited loadings exceeding 0.7 with adequate AVE ranging from 0.68 to 0.79. Results also showed adequate discriminant validity as all the square roots of AVE were higher than the inter-correlation value between the constructs (Table 3 ). Therefore, the reliability and validity of the research constructs were confirmed.

The structural model

Structural model assessment was used to test hypothesized theoretical relationships in the suggested conceptual framework, which included the relationship between positive emotions, self-efficacy, metacognitive learning strategies, and academic performance (Figs. 1 , 2 ). The coefficient of determination (R 2 values) and path coefficients (beta values) were the parameters used to determine how well the data supported hypothesized relationships. Also, PLS path-analysis of bootstrapping was applied to find the path correlation between the research variables to understand whether the path coefficient is significant for hypothesized relationships.

SEM depicting relationships between metacognitive learning strategies, positive learning-related emotions and academic self-efficacy with academic performance. ** indicates statistically significant at p  < 0. 01 level and * shows statistically significant at p  < 0. 05 level. Values for each arrow indicate the standardized path coefficients

Figure 2 shows the path coefficients estimated from the PLS analysis. According to the results, hypotheses H1, H2, H3, H4, H5, H6, H7, H8, and H9 were all supported (Table 4 ). To determine significance of all the relationships in the model, bootstrapping procedure as a re-sampling technique was applied. Based on the estimated path coefficients showed in Fig. 2 and the t-test statistics scores indicated in Fig. 3 , self-efficacy demonstrated a direct, positive, and statistically significant effect on academic performance (H1 p < 0.05), positive learning-related emotions (H4 p < 0.001), and metacognitive learning strategies (H5 p < 0.001). Similarly, positive emotions had a direct, positive, and statistically significant effect on academic performance (H2 p < 0.001) and metacognitive learning strategies (H6 p < 0.001). Also, as hypothesized, metacognitive learning strategies had a direct, positive, and statistically significant effect on academic performance (H3 p < 0.001) (Figs. 2 and 3 ).

Path analysis of bootstrapping shows T-test scores related to path coefficients depicted in Fig. 2 . T-test scores that are higher than 1.96 are significant at 0.05 level, and T-test scores that are higher than 2.58 are significant at 0.01 level

Moreover, the mediation test indicated an indirect effect of self-efficacy on academic performance through metacognitive learning strategies (H7) (b = 0.09, t = 3.77, p  < 0.001), and positive learning-related emotions (H9) (b = 0.168, t = 3.50, p  < 0.001). Similarly, the mediation test indicated an indirect effect of positive learning-related emotions on academic performance through metacognitive learning strategies (H8) (b = 0.063, t = 3.27, p  < 0.001).

The goodness-of-fit R 2 of latent endogenous variables can be applied to assess the utility of the proposed model. In the proposed model, 30% of the variance in academic performance was explained by self-efficacy, positive emotions, and meta-cognitive learning strategies. Moreover, results indicated that 40% of the variance in metacognitive learning strategies was explained by self-efficacy and positive emotions. Furthermore, findings showed that 43.2% of the variance in positive emotions was explained by self-efficacy.

Hair et al. (2014) also suggested reporting on predictive relevance (Q 2 ) besides basic parameters. According to Fornell and Cha (1994), the model has predictive quality if the cross-redundancy value is found to be more than 0; otherwise, predictive relevance (Q 2 ) of the model cannot be achieved. Based on the results obtained using Smart PLS 3.0 software, obtained cross-validated redundancy was found to be 0.289, 0.422, and 0.389 for academic performance, positive emotions, and meta-cognitive learning strategies, respectively.

According to Pekrun et al. (2007), in control-value theory, it is supposed that the students’ cognitive appraisal, like self-efficacy affects positive emotions as a personal factor, which also impacts the students’ academic achievement through a cognitive path (metacognitive strategies).

Our results strongly supported predictive links among academic self-efficacy, positive emotions, metacognitive learning strategies, and academic performance.

First, the findings of the study demonstrated the influence of academic self-efficacy on positive emotions. As mentioned above, based on Pekrun’s control-value theory [ 17 , 40 ], cognitive assessment is supposed to be one of the significant antecedents of academic emotions categorized into control assessments (perceived control) and value assessments (perceived value). Control assessments are related to the individuals’ perception of the controllability of achievement activities and their consequences. These assessments are shown through our expectations and perception of competence, such as self-efficacy. Therefore, academic self-efficacy (as a cognitive assessment) can influence academic emotions [ 14 ]. It can be expected that, when the students believe in their ability to perform their tasks successfully, they will enjoy the learning process more; also, it seems reasonable that these individuals experience more feelings like hope and pride compared to the students with low self-efficacy. The findings of some studies indicated a positive relationship between academic self-efficacy and positive emotions [ 1 , 5 ].

The second finding of this study was the influence of academic self-efficacy on metacognitive learning strategies. One of the key determinants of the use of metacognitive learning strategies by the learners is their self-efficacy. Despite the positive effect of self-efficacy on the amount of attempt, evidence shows that the quality of the efforts of self-efficacious students is different as well; such students use deeper various metacognitive processing strategies compared to their peers with lower self-efficacy [ 6 ]. Previous studies have revealed that self-efficacious students use more metacognitive learning strategies compared to their peers [ 9 , 35 , 36 , 37 , 42 , 45 ]. Pintrich and De Groot believe that the students who trust in their abilities are more likely to be self-efficacious and try to recognize their academic tasks and plan for their educational affairs. Quality of the efforts and the use of a variety of deep cognitive and metacognitive learning strategies are different in such students compared to their peers [ 35 ].

The findings of other studies revealed a significant relationship between positive academic emotions and metacognitive learning strategies. Specifically, control-value theory predicts that achievement emotions influence the use of metacognitive learning strategies [ 17 , 40 ]. Pekrun et al. believed that positive emotions resulted from the use of deep, flexible, and complex learning strategies and that self-regulation facilitated the individuals’ learning [ 4 ], so that the students who experience positive emotions utilized deeper strategies and more metacognitive processing [ 4 , 40 ]. This, in turn, enhances the students’ achievement. The results of some studies have confirmed a positive association between positive academic emotions and cognitive and metacognitive learning strategies [ 1 , 4 , 6 , 48 ]. As assumed in our model, positive academic emotions positively predicted academic performance. This is in line with the results of previous studies [ 1 , 2 , 4 , 6 , 10 , 21 , 30 , 46 ]. Pekrun et al. stated that emotions are involved in almost all aspects of the teaching and learning process [ 40 ]. Positive emotions related to learning can influence the learners’ performance through effects on the quality of the learning process, quality of teacher-learner and peer-peer relationships in the classrooms, and effective teaching [ 19 ]. In this regard, Meinhardt and Pekrun stated that learning is continuously accompanied by emotions and emotions influence concentrating, processing, storing, and retrieving of the information [ 20 ]. In summary, emotions deal with four types of essential mental processes including attention, concept formation, and allocation of cognitive and metacognitive sources which are necessary for learning. Evidence shows the effect of emotions on cognitive performance. Also, based on Pekrun’s control-value theory, emotions can influence the individuals’ academic performance through their effect on some mediating factors such as academic motivation, memory, and cognitive and metacognitive sources [ 40 ].

Another finding of this study was a significant relationship between metacognitive learning strategies and academic performance. Scholars believed that the students who use more effective metacognitive learning strategies have better study plans, monitor, and evaluate their learning and perception of the materials more efficiently, assume their responsibility, detect and solve their problems, and try hard to learn deeply [ 36 , 53 ]. They surely achieve more than their peers who are not skillful in the use of such strategies [ 38 ]. In this respect, the role of metacognitive learning strategies has been well confirmed in academic success by the theories and researches [ 1 , 4 , 23 , 24 , 35 , 38 , 41 , 46 ]. Finally, as assumed in our model, findings showed that the influence of self-efficacy on academic performance depends on multiple relationships and interplay of positive emotion and metacognitive learning strategies. In particular, self-efficacy positively influences academic performance when it is mediated by positive emotion and metacognitive learning strategies. Based on the control-value theory, self-efficacy can act as an antecedent of emotion, meaning that academic emotion can mediate the effect of self-efficacy on academic performance [ 14 , 17 ]. Thus, it seems reasonable to assume that the students who believe in their own capabilities to learn and perform some of their scientific tasks enjoy learning new materials more than the others. Since these students believe that they have the necessary abilities to learn their materials, they have a sense of pride while learning. Also, since they believe in their abilities, they are optimistic about their learning and also the materials to be learned. Therefore, it is concluded that highly self-efficacious students experience more positive emotions while studying and learning, which can, in turn, lead to better academic performance.

Results also showed a significant indirect effect of positive emotions on the students’ academic performance, so that metacognitive learning strategies mediated the relationship between the students’ positive academic emotions and their academic performance. This finding is consistent with the results of other studies [ 1 , 4 ]. Also, based on Pekrun’s control-value theory, emotions can influence the individuals’ academic performance through their effect on some mediating factors such as metacognitive sources [ 14 , 40 ]. For instance, King and Areepattamannil (2014) found a significant and positive relationship between positive emotions and metacognitive learning strategies (planning, monitoring, regulating) [ 48 ]. Somehow the students who experience positive emotions in the learning process are more inclined to use flexible, complex, and self-regulatory learning strategies; in general, emotions bring about more involvement, and the use of deeper processing strategies consequently leads to better performance [ 4 ]. Therefore, positive emotions are not enough to guarantee academic achievement by themselves since metacognitive learning strategies are also necessary.

In conclusion, our theoretical model implies the antecedents and consequences of positive academic emotion, especially metacognitive learning strategies and academic performance. Our results revealed that the students who believed in their abilities and had more positive emotions used more metacognitive learning strategies, resulting in better academic performance.

Limitations

In general, this study can be regarded as evidence regarding the direct and indirect effects of self-efficacy and positive academic emotions on the medical students’ academic performance; it also supports the control -value theory and other studies conducted in this field. Despite these strengths, this study had some limitations. First, this study was a cross-sectional quantitative study, so it was not possible to precisely show the cause and effect relationship between the variables. Second, in this study, self-report questionnaires were used that raises the possibility of response bias. However, the use of self-report questionnaires enables us to elicit the participants’ beliefs and personal perceptions toward their learning process. Lastly, convenience sampling method was used, which does not reveal random sampling features and makes generalization of the results impossible.

Implications

Teachers in medical schools can reduce the students’ stress through providing supportive and calm environments since competitive and stressing contexts influence the students’ self-efficacy; they can invigorate positive emotions in the students by giving appropriate, positive, and supportive feedbacks, creating interactive approaches in the classrooms, and encouraging the students to cooperate in class discussions instead of competition. Since the teacher’s enthusiasm, positive feedback to success, cooperation, sense of belonging to class are positively related to the students’ enjoyment of learning and hope for success in learning.

Results of the study also suggest that teachers in medical schools should take measures in order to create a peaceful environment where the students feel comfortable and secure since positive feeling toward the learning climate and environment can increase positive emotions like enjoyment, pride, and hope in the students while learning, leading to academic success.

In addition, creating a climate in which the students experience freedom and respect would make them enjoy their presence in the class and learning which in turn leads to involvement in teaching, more academic engagement, and the use of deeper learning strategies.

Moreover, some factors can influence academic emotions indirectly. For example, quality of teaching in the classroom can directly influence the students’ dominance, perceived academic control, and self-efficacy, which in turn influences their emotions indirectly. Thus, behavior in the class, expressed emotions, and the teachers’ quality of teaching can influence the students’ learning which, in turn, can be a significant factor in raising the students’ positive emotions and self-efficacy.

Availability of data and materials

The datasets used during this study are available from the corresponding author on reasonable request.

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Hayat, A.A., Shateri, K., Amini, M. et al. Relationships between academic self-efficacy, learning-related emotions, and metacognitive learning strategies with academic performance in medical students: a structural equation model. BMC Med Educ 20 , 76 (2020). https://doi.org/10.1186/s12909-020-01995-9

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The influence of general self-efficacy on the interpretation of vicarious experience information within online learning

• Natalie Wilde 1 &
• Anne Hsu 1  

International Journal of Educational Technology in Higher Education volume  16 , Article number:  26 ( 2019 ) Cite this article

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An individual’s general self-efficacy affects their cognitive behaviours in a number of ways. Previous research has found general self-efficacy to influence how people interpret persuasive messages designed to encourage behavioural change. No previous work has looked into how general self-efficacy affects the interpretation of vicarious experience information and how this affects self-efficacy in being able to complete a set task within a career skills online learning environment. The study presented considers this gap in knowledge, analysing the effect of six different types of vicarious experience information on the self-efficacy of online workshop participants to complete a set task. In analysing the results, each participant’s general self-efficacy was considered.

Results showed individuals with low general self-efficacy to find vicarious experience information significantly less beneficial for their self-efficacy in completing a set task when compared to others with high general self-efficacy. Those with low general self-efficacy were more likely to make negative self-comparisons to the vicarious experience information, restricting its potential to increase their self-efficacy. In contrast, participants with high general self-efficacy found many of the vicarious experience information presented to be beneficial to their self-efficacy to complete the set task as they were more likely to dismiss any information they interpreted to be negative. Results from this study highlight the importance of more research into how vicarious experience information can be designed and presented in a way that ensures benefit to the task-specific self-efficacy of all individuals, regardless of their general self-efficacy beliefs at the time.

Introduction

Self-efficacy (SE) refers to an individual’s belief that they are able to succeed given any task that they encounter (Bandura, 1977 ). SE can be general or task specific, allowing individuals to have a range of SE beliefs about themselves at any one time. An individual’s beliefs surrounding their own levels of SE can have an impact on how they feel, think and motivate themselves. This can lead to significant contrasts in behaviour between individuals with differing levels of SE. Those with a strong or high sense of SE believe in their own capability deeply, seeing challenges as tasks to be mastered rather than threats to be avoided (Bandura, 1977 ). They also engross themselves into tasks and exert strong commitment. Any setbacks they encounter are easily recovered and learned from. These factors can all lead to enhanced personal well being by reducing stress, resulting in the individual being less likely to experience depression. Others with a weak or low sense of SE have major doubts over their own capabilities (Bandura, 1977 ). This can lead to a total avoidance of challenges as they see them as threatening situations. These individuals can spend a lot of time focussing on their previous failings and this can lead to setbacks being difficult to recover from. For this reason, these individuals can be more vulnerable to depression and stress (Bandura, 1977 ).

Levels of SE are not static and have the ability to be increased through exposure to influential information sources, one of which is vicarious experience information (VEI). VEI is argued by Gist and Mitchell ( 1992 ) to have the most instant and direct effect on an individual’s SE. If we read information about someone which implies that they have succeeded at a certain task, it raises our own belief that we too can succeed at the same task. This belief is further increased if we observe an individual that we consider to be similar to ourselves (Schunk, 1987 ). Previous studies have not considered how an individual’s level of general SE affects how they interpret VEI and the benefit to their task-specific SE that they get from this information.

Bandura ( 1994 ) explains how an individual’s current general SE can shape their behaviours and this may influence how they interpret and perceive information (Gist & Mitchell, 1992 ), which could include VEI. Due to individuals with low general SE being more likely to be brought down by information and to dwell upon previous negative experiences, they may not interpret VEI or pay it as much attention when compared to others with higher levels of general SE (Bandura, 1994 ). This puts them at a disadvantage, as this may lead to low general SE individuals not finding the VEI as beneficial on their SE. The study presented in this paper considers how an individual’s general SE influences how they interpret VEI and the effect this information has on their task-specific SE. This effect is considered within the context of a career skills online learning environment (OLE). In this study an OLE is defined as ‘a virtual environment that allows individuals to access learning material’ (Ally, 2004 ).

The study works with two types of SE beliefs, general and task-specific SE, with distinct differences between the two. General SE beliefs mirror the definition provided by Bandura ( 1977 ), ‘the belief in one’s capabilities to organize and execute the courses of action required to manage prospective situations’. General SE concerns an individual’s self-belief that they are able to complete any set task at any time and are not specific. Task-specific SE beliefs, in the study presented in this paper, will refer to an individual’s self-belief that they are able to complete a specific set task presented online. Results of this study will provide knowledge on whether an individual’s general SE should be considered in the design of VEI to use within future online learning processes.

General SE and its effect on VEI interpretation

When considering the influence of VEI on an individual’s SE, previous researchers have suggested the consideration of an individual’s general SE levels (Bandura, 1994 ; Bandura & Wood, 1989 ). Bandura ( 1994 ) outlines how behaviours of those with low general SE, when compared to others with higher levels of SE, differ in four major psychological processes: c ognition, selection, motivation and affect .

With regards to cognitive processes , those with higher levels of general SE find it easier to visualise success scenarios (Bandura, 1994 ). In contrast, those with lower levels of general SE are more likely to visualise scenarios in which they fail to successfully complete the required task. Selection processes also vary between those with high and low general SE. Those with high general SE have selection processes that allow them to feel more open to trying new tasks (Bandura, 1994 ). Others with low general SE are more likely to have narrower selection processes which causes them to shy away from any new ventures that they haven’t completed successfully in the past. Higher levels of general SE are also linked to higher motivation in goals, allowing greater effort and persistence in the face of difficulties (Bandura, 1994 ; Bandura & Wood, 1989 ). Finally, affective processes differ, with individuals who have higher levels of general SE being able to deal with threats easier than others with low general SE (Bandura, 1994 ). When faced with a threat, those with low general SE dwell on their coping deficiencies and this can lead to anxiety. This anxiety can lead to them fearing their environment and worrying about the worst outcomes from situations (Bandura & Wood, 1989 ).

Considering the behaviours described above, people with varying levels of general SE may be affected differently when presented with VEI. Firstly, due to their inability to visualise success and their susceptibility to be brought down by both negative or positive social comparisons, VEI may be less effective in helping individuals with low general SE. Also, the hesitance and shying away from new ventures that those with low general SE demonstrate could limit how open they are to the positive influence of certain types of VEI. Past experiences could also influence how an individual interprets VEI. If an individual has low general SE because they have experienced failures in related tasks that have been set before, it could be difficult for VEI to increase their SE in being able to attempt completing the task again. This could be due to the prevailing negative memories that gave rise to the individual’s current low level of general SE. Finally, individuals with low general SE may be more cautious towards potential threats and less likely to be able to deal with the stress caused by these effectively.

Previous work

During a literature search, we were unable to find any previous work conducted which examined how the effects of VEI for promoting task-specific SE in OLE’s were moderated by general SE. However, we did find previous studies that considered the moderating effect of different types of SE (both general and task-specific) on an individual’s interpretation of other types of persuasive messages designed to encourage behavioural changes. The work presented is based upon these types of previous work.

A series of previous studies have supported the key role that SE can play in shaping recipients behavioural responses to health messages with a particular focus on ‘framed messages’ (Riet, Ruiter, Werrij, & De Vries, 2008 ; Riet, Ruiter, Werrij, & De Vries, 2010 a; Riet, Ruiter, Smerecnik, & De Vries, 2010 b; Yang, Chen, & Wang, 2016 ). Two equivalent pieces of information can be framed in either a positive or negative way (Block & Keller, 1995 ), named ‘gain-framed ‘or ‘loss framed’ respectively (Yang et al., 2016 ). Gain-framing presents the positive outcomes of adherence to the message communicated, for example ‘If you reduce your daily sugar intake, you reduce your risk of developing tooth decay’. Loss-framing communicates the negative consequences of non-adherence to the message communicated, for example ‘If you don’t reduce your daily sugar intake, you increase your risk of developing tooth decay ‘.

Riet et al. ( 2008 , 2010 a, 2010 b) conducted a series of studies looking into the influence that an individual’s SE has on how they interpret loss and gain framed health messages. In Riet et al. ( 2008 ), researchers studied the effect of message framing on helping individuals to quit smoking. They found that when an individual had high SE in being able to quit, loss-framed messages were more beneficial in encouraging them to take the behavioural steps to stop smoking. For others with lower levels of SE in being able to quit, they found neither loss or gain framed messages to be of any benefit on their behavioural intention to stop smoking. The researchers suggest that individuals with high SE are able to avert the threats presented in loss framed messages more effectively than others with lower SE. This was one of the earliest studies to present the moderating effect that an individual’s SE can have regarding the effect of message framing on persuading behavioural change.

Following on from this, Riet et al. ( 2010 a) conducted another study looking into the effect of skin cancer detection messages among university students. The SE described in this study was that of being able to perform a skin cancer self-examination. Once again, this study supported the benefit of using loss framed over gain framed messages for students with higher levels of SE, as these messages were found to increase their intention to perform skin examinations. Also, similar to the earlier study, neither type of framing was found to be of benefit to those with lower SE and their intentions to perform future skin examinations. The researchers suggest that for those with lower SE, the loss framed message presents a great sense of threat. For some this may lead to lower levels of message acceptance, as they are likely to engage in defensive avoidance (e.g. ‘That won’t happen to me’ ) or message derogation processes (e.g. ‘This doesn’t apply to me’ ) (Witte, 1992 ).

In a third study Riet et al. ( 2010 b) explored whether an individual’s SE in being able to decrease their salt intake had any influence on the effect of gain and loss framed messages that promoted a low salt diet. The results of this study supported the earlier two studies. As a result, the researchers suggested that loss framed messages may be more effective than gain framed messages in decreasing salt intake, but this is only for individuals that already had a high SE to do so.

Yang et al. ( 2016 ) conducted a study investigating the effect of message framing on individuals decisions about undergoing treatment in the form of therapeutic exercise. All of the participants in this study suffered with some form of chronic pain and during the study were shown either loss or gain framed messages about therapeutic exercise. The mediating effect of an individuals SE in being able to complete therapeutic exercise was considered, with the effect on individuals with low and high SE being analysed. Results of this study differed slightly to the earlier studies outlined by Riet et al. ( 2008 , 2010 a, 2010 b) as they found both low and high SE individuals to be positively influenced by the loss framed message. The researchers put this new result regarding low SE individuals down to self-affirmation. If a low SE individual felt good about themselves generally, this may have reduced the perceived threat of the information and may have lead to them acting in less of a defensive way towards it (Sherman, Nelson, & Steele, 2000 ).

Previous literature has highlighted the differences between the behaviour of those with low and high SE when interpreting certain types of persuasive message. However, there has not been any previous work regarding the interpretation of VEI. Due to the difference in behaviour between those with low and high general SE (Bandura, 1977 ), it could be assumed that VEI being presented within an OLE may also be interpreted in different ways dependant on the general SE of the individual at the time.

Research purpose and hypotheses

The effect of an individual’s general SE and how it influences the benefit of VEI on task-specific SE within an OLE is an area where little previous work has been conducted. This study will focus on the effects that different forms of VEI have on the task-specific SE beliefs of individuals within an online learning process. Analysis will compare these effects between individuals with low and high levels of general SE. For this study, the following three hypotheses are proposed:

Hypothesis 1: Individuals with low general SE will find VEI less beneficial for increasing their task-specific SE compared to those with high general SE.

Hypothesis 2: Individuals will find VEI demonstrating high levels of success to be more beneficial on their task-specific SE when compared to VEI demonstrating lower levels of success, regardless of their general SE.

Hypothesis 3: Individuals with high general SE will not experience any negative effect on their task-specific SE when exposed to any type of VEI whereas individuals with low general SE will experience negative effects on their task-specific SE as a result of some VEI types.

The results of previous studies have shown individuals with low general SE to find persuasive messages less effective in encouraging behavioural changes (Riet et al., 2008 , 2010 a, 2010 b). Hypothesis 1 predicts, based upon these previous studies, that individuals with low general SE will not find VEI as beneficial on their task-specific SE when compared to others with high general SE.

Hypothesis 2 expects VEI types demonstrating a high level of success to be more beneficial to an individuals task-specific SE than VEI demonstrating lower levels of success. Bandura ( 1977 ) suggests that VEI that conveys a clear level of success is more likely to improve an individual’s SE more so than information where the success level is unclear or low. Considering this previous literature, this study will investigate the effect of using VEI demonstrating a clear success and whether this is more beneficial on an individuals task-specific SE within a career skills OLE.

Bandura ( 1994 ) also outlines characteristics of individuals with high general SE. Hypothesis 3 is based upon these characteristics predicting those with high levels of general SE to be more resilient and therefore less likely to be faulted by negative information, such as VEI demonstrating low levels of success. Because of this, it is expected that no VEI types will have a negative effect on the task-specific SE of individuals with high general SE. In contrast this hypothesis suggests that the task-specific SE of individuals with low general SE may be affected in a negative way by some types of the VEI presented in this study. This is based on characteristics of individuals with low general SE outlined by Bandura ( 1994 ) and Bandura and Wood ( 1989 ). Those with low general SE may experience anxiety or threat when presented with VEI portraying low levels of success, which could have a negative impact on their task-specific SE.

Methodology

Participants.

Participants were recruited using Amazon mechanical turk. They received a small monetary reward for completing the study. All participants were native english speakers and actively looking for a job at the time of the workshop. One hundred and thirty-six participants took part in the study. Of those that provided demographic information, the sample was 50% male and 50% female. Participant age ranged from 20 to 67 ( M  = 36, SD  = 11.4). Most participants were in some form of employment: full time (38%), part-time (12%) or self-employed (8%) at the time of completing the study. The full demographic information of the study participants is shown in Table  1 .

Before starting the analysis, we grouped participants based upon their general SE beliefs. The data population was split into two halves: low and high general SE groups. Participants were grouped, depending on their general SE score provided in the pre-workshop questionnaire. Those in the low SE group had a general SE scale score lower than the total population mean of 31 ( N =  68). Participants in the high SE group had a general SE scale score of 31 or above ( N =  68).

Research design

We used a between-groups experimental design, with each participant only being shown one type of VEI. In this study, the independent variable was the VEI type that the participant had read. Other variables included in the study include participant general SE, VEI type and benefit of the VEI on participants task-specific SE.

In order to analyse the data with reference to Hypothesis 1, significance testing looked for a main effect between a participants level of general SE and the benefit found to their task-specific SE from the information they had read, regardless of what VEI type it was. For Hypothesis 2 analysis, significance testing looked for a main effect between the level of success demonstrated in the VEI (low or high) and the benefit found to a participants task-specific SE after reading the VEI. But further to this, analysis also observed to see if there was an interaction effect between the level of success demonstrated in the VEI and an individuals general SE on how beneficial the VEI is for their task-specific SE. In this case, it is assumed that no significant interaction effect would be present.

Analysis for Hypothesis 3 was conducted in two halves. Firstly, the mean effect of each of the VEI types on the task-specific SE of participants with low and high general SE was calculated. A one sample two-tailed t-test was then conducted to find differences from the mean rating of 3, ‘no effect’. Once these significant differences were found, they were sorted into either significantly positive effects or significantly negative effects on task-specific SE. These significant effects on participants with low and high general SE were then considered when analysing for Hypothesis 3.

There were three types of VEI; a percentage completion statement, a previous answer and a testimonial. For each of these VEI types there were versions demonstrating low and high levels of success, resulting in six different types of VEI altogether. The different types of VEI represented different ways of conveying information about more or less successful completion of tasks by previous participants. All of the VEI forms created were fictitious and were created for the purpose of the study.

The first VEI type conveyed completion directly through a statistic, via a percentage completion statement (See Fig.  1 ). This statement described the percentage of individuals that had completed the task before them and the percentage that had failed to complete it. The first version of this VEI type stated that a low percentage of participants had completed the workshop successfully (45%) and the second version stated a high percentage of previous workshop participants (95%) had been successful in completing the set task. This type of VEI was chosen because it was considered the most direct way of communicating levels of success to the reader.

Percentage completion statement (High level of success version)

The second type of VEI demonstrated more or less successful completion of the task indirectly via an example of a previous participant’s answer (See Fig.  2 ). This type of information had been used in a previous study but was not found to lead to increases in SE beliefs (Newman & Tuckman, 1997 ). The first version was an answer that would have scored low according to a mark scheme that was provided earlier on in the workshop. The second version was an answer that would be scored highly according to the markscheme. This type of VEI conveyed not only success in completing the task but gave information about how to complete the task well through the good and bad examples.

Previous participants answer (Low level of success version)

The last type of VEI conveyed success of completion through a testimonial from a previous workshop participant (See Fig.  3 ), a type of VEI that has also been used in previous studies (Kelly, 2017 ). The first version was a testimonial in which an individual described how they were unsuccessful in completing the set task. In contrast, the writer of the second testimonial describes how they were able to successfully complete the task set. This type of VEI included the subjective opinions from previous participants about the experience of doing the task.

Participant testimonials (High level of success version)

Data was collected using questionnaires at two points during the study: the pre-workshop questionnaire and the VEI response questionnaire .

The pre-workshop questionnaire obtained participants demographic data including their age, gender and current employment status. Participants initial levels of general SE were assessed in this questionnaire using the ten item general SE scale (Schwarzer & Jerusalem, 1995 ). Evidence of this scales validity has been found in a variety of domains (Grammatopoulou et al., 2014 ; Mystakidou, Parpa, Tsilika, Galanos, & Vlahos, 2008 ). In this scale, participants were presented with ten statements and asked to state how true of themselves they feel each statement is. They indicated their answer on a four-point likert scale, ranging from 1 ( Not at all true ) to 4 ( Exactly True ). One to four points were awarded for each item based on their scale response, with exactly true having the highest four points awarded and not at all true having the lowest one point awarded. All 10 item points are totalled up to create an overall general SE score, out of a possible 40. During analysis it was assumed that the higher the score, the higher the participants general SE beliefs were at the time.

During the VEI response questionnaire , participants were asked what effect they felt reading the VEI had on their task-specific SE. Participants provided answers on a five-point likert scale, ranging from 1 ( Strongly decreased ) to 5 ( Strongly Increased ). An open ended question followed directly after this question which asked participants to explain why they felt the VEI had the effect on their task-specific SE that it did. This question would provide qualitative data which would help offer insight into participants reasoning for their earlier answer.

During the study, participants were guided through an online workshop entitled The Career Skills Workshop . The workshop focussed on career skills, providing information on the STAR principle. The STAR principle outlines a structure commonly used to answer competency based questions in job interviews. Competency based questions are where an interviewer asks the interviewee to provide evidence of a particular skill they are looking for in an employee. The workshop was created using the Google forms platform.

Before beginning the workshop, participants were asked to fill in the pre-workshop questionnaire which collected their demographic data and starting general SE levels. The workshop started initially by presenting the participant with a number of pages to navigate through. These pages included information about the STAR principle, including an explanation of what it is and how to use it correctly. After reading the workshop material, participants were presented with a small quiz. The quiz contained three multiple choice questions, asking them to recall what they had just read. Anyone who scored 33% or less in the quiz was discounted from the dataset, as it was concluded that they had not effectively read the information presented to them up to this point.

After completing the quiz, participants were shown a task to complete, the exact task set is outlined in Fig.  4 . This task drew upon the skills learnt in the first section of the workshop, asking them to answer an example job interview question using the STAR principle. Participants were shown a mark scheme (see Fig.  5 ) which outlined the aspects that would make up a high scoring answer. At this point, participants were randomly exposed to one of the six VEI types created. After exposure to the VEI, participants completed the VEI response questionnaire to gauge their reactions to the single VEI they were presented with and the effect it had on their task-specific SE. After this, participants were left to complete the task if they wished. In this study, actual performance on the task was not considered as it was not relevant to the hypotheses posed.

The set task that participants were asked to complete in the online workshop

Mark scheme shown to participants

Effect of participants general SE

The results outlined in this section address Hypothesis 1 directly, considering the effect an individual’s general SE has on how much of a boost they experience to their task-specific SE from reading the VEI presented. Figure  6 presents a comparison of the main effect of participant general SE level on the benefit to their task-specific SE when considering all VEI types combined. Testing found that overall, participants with high general SE found the VEI presented to have a more positive effect on their task-specific SE ( M  = 3.7, SD  = 0.80) when compared to the low general SE group ( M  = 3.2, SD  = 0.81), F (1, 124) = 15.8, p  < .001.

A comparison of the mean effect of VEI on task-specific SE between participants with low and high levels of general SE

VEI level of success

The results in this section address Hypothesis 2, considering the benefit on task-specific SE of VEI demonstrating low and high levels of success. There was a main effect found of the level of success demonstrated in the VEI presented on the benefit of the information to an individuals task-specific SE. Figure  7 presents a comparison of the effect on task-specific SE between VEI showing low and high levels of success. VEI showing a high level of success was found to have a more positive effect on an individuals task-specific SE ( M  = 3.6, SD  = 0.68) when compared to VEI showing a lower level of success ( M  = 3.3, SD  = 0.95), F (1, 124) = 6.7, p  = .01. No interaction effect was found between the level of success communicated in the VEI and participants general SE on how beneficial they found the VEI for their task-specific SE, F (1, 124) = 0.49, p  = .48.

Comparison of the mean effect on task-specific SE of VEI showing low and high levels of success

A three-way ANOVA found a significant two-way interaction between VEI type (percentage statement, previous answer or testimonial) and level of success (low or high) on participants’ task-specific SE (Decreased, increased or no effect), F (2, 124) = 9.02, p  < .001.

Figure  8 shows a comparison of the interaction effect on benefit to an individuals task-specific SE of VEI type and level of success demonstrated. Significant differences were found when comparing the effect of low success and high success versions of each of the VEI types. The percentage statement demonstrating the high level of success was found to have a significantly more positive effect on participants’ task-specific SE ( M  = 3.7, SD  = 0.68) when compared to the percentage statement demonstrating the low level of success ( M  = 3.1, SD  = 1.12), t (41) = 2.18, p  = .03, d  = 0.64. The positive testimonial demonstrating a high level of success was also found to be more beneficial for task-specific SE ( M  = 3.7, SD  = 0.56) when compared to a negative testimonial demonstrating a low level of success ( M  = 2.9, SD  = 0.64), t (45) = 4.75, p  < .001, d  = 1.32. However, in the case of the previous answer, the version showing low levels of success was found to have a significantly better effect on task-specific SE ( M  = 4.0, SD  = 0.79) when compared to the good previous answer demonstrating high levels of success ( M  = 3.5, SD  = 0.72), t (41) = 2.26, p  = .03, d  = 0.66. This is in contrast to the relationship between levels of success communicated for the other two VEI types presented in the study.

Comparison of means - VEI type vs Level of success communicated

When considering the effect in the other direction, a one-way ANOVA considered the benefit of each of the low success VEI types against each other and there was a significant difference found, F (2,64) = 10.9, p  < .001. Post hoc testing found significant differences between the effect on task-specific SE of the low percentage statement and the poor answer. Two sample t-testing showed the bad answer to have a significantly more beneficial effect on task-specific SE ( M  = 4.0, SD  = 0.72) when compared to the low percentage statement ( M  = 3.1, SD  = 1.12), t (33) = 3.01, p  = .004, d  = 0.96. The bad answer was also found to be significantly more beneficial on an individuals task-specific SE when compared to the unsuccessful testimonial ( M  = 2.9, SD  = 0.64), t (38) = 5.45, p  < .001, d  = 1.61. No differences were found between the effects of the unsuccessful testimonial and the low percentage statement on individuals task-specific SE, t (28) = 0.76, p  = .45. The ANOVA found no significant differences when comparing the benefit of the three successful VEI types against each other, F (2,66) = 0.9, p  = .4.

Potential negative effect of VEI on participants with low vs. high general SE

To address Hypothesis 3, the presence of significant negative effects on the task-specific SE of each of the separate VEI types was calculated for those with low and high general SE. A one sample two-tailed t-test was conducted for differences from the mean rating of 3, ‘no effect ‘.

Figure  9 shows the mean effect of each VEI type on the task-specific SE of individuals with low general SE, with an asterisk highlighting the effects to task-specific SE (both negative and positive) that were found to be significantly different to the known mean of 3 (‘no effect ‘). In Fig.  9 , there is a horizontal dotted line through the Y axis at ‘No effect ‘, representing the boundary between negative and positive effect on task-specific SE. Significant differences to the known mean were found for four of the six VEI types: the high percentage statement, the poor answer, the unsuccessful testimonial and the successful testimonial.

Mean effect of each VEI type on the task-specific SE of individuals with low general SE. An asterisk (*) indicates a mean significantly different from 3 (‘No effect ‘)

The effect of the high percentage statement ( M  = 3.3, SD  = 0.5) was found to be significantly different from the known mean, indicating that this type of VEI was significantly beneficial on the task-specific SE of those with low general SE, t (10) = 2.3, p  = .04, d  = 0.6. The poor answer ( M  = 3.5, SD  = 0.72) was found to be significantly beneficial on task-specific SE of this group also, t (8) = 2.29, p  = .05, d  = 0.69. Finally, the successful testimonial ( M  = 3.6, SD  = 0.52) was found to have a significantly positive effect on the task-specific SE of individuals with low general SE, t (7) = 3.42, p  = .01, d  = 1.18. In contrast, the unsuccessful testimonial ( M  = 2.7, SD  = 0.47) was found to have a significantly negative effect on the task-specific SE of individuals with low general SE, t (13) = 2.28, p  = .04, d  = 0.64.

Figure  10 shows the mean effect of each VEI type on the task-specific SE of individuals with high general SE, with an asterisk highlighting the effects to task-specific SE (both negative and positive) that were found to be significantly different to the known mean of 3 (‘no effect ‘). There is a horizontal dotted line through the Y axis at ‘No effect ‘, representing the boundary between negative and positive effect on task-specific SE. One-sample t-tests found significant differences to the known mean for four of the six VEI types (the high percentage information, the poor answer, the good answer and the successful testimonial), with all of them being significantly more beneficial than the known mean.

Mean effect of each VEI type on the task-specific SE of individuals with high general SE. An asterisk (*) indicates a mean significantly different from 3 (‘No effect ‘)

The effect on task-specific SE from the high percentage information ( M  = 4, SD  = 0.68) was found to be significantly higher than the known mean t (13) = 5.5, p  < .001, d  = 1.5. This was also the case when considering the poor answers ( M  = 4,4, SD  = 0.5) effect on participants task-specific SE, t (10) = 8.9, p  < .001, d  = 2.8. The good answer ( M  = 3.6, SD  = 0.81) was found to significantly benefit the task-specific SE when compared to the known mean, t (10) = 2.6, p  = .03, d  = 0.74. Finally, the last type of VEI found to have a significantly positive effect on task-specific SE when compared to the known mean was the successful testimonial ( M  = 3.8, SD  = 0.60), t (12) = 4.62, p  < .001, d  = 1.33.

Qualitative analysis on influence of VEI types

Further to the quantitative data outlined above, we collected qualitative data during the study which outlining participants thoughts on how the type of VEI they were presented with affected their task-specific SE beliefs. The aim of this analysis was to get a more in depth understanding of possible reasons why each of the VEI types presented affected participants task-specific SE either positively, negatively or not at all. We analysed the qualitative data from the open ended question asked during the study using thematic analysis (Braun & Clarke, 2006 ). Common themes mentioned within responses to each VEI type were identified and are outlined below. Themes were sorted by the effect they had on participants task-specific SE (positive, negative or no effect) as well as by whether the participant had low vs. high general SE.

Reasons for positive effect on task-specific SE

With regards to the positive effects on task-specific SE stated, four main themes were identified which are explained for each VEI form below: self-comparisons, reassurance, reducing task difficulty and gaining of knowledge.

With regards to the high completion statement, participants in both groups made positive self-comparisons after reading the information. They believed if 95% had been successful in completing the task then they could also be successful. These beliefs had a positive effect on individual ‘s task-specific SE, ‘I feel I’m with the 95%. If so many can do it, I certainly can’. The fact that so many others had completed it also lead to some participants perceiving the task to be less difficult. This in turn had a positive effect on their task-specific SE, ‘ Knowing that a very high percentage of participants were able to complete the task lets me know that completing the task must not be that difficult to do’.

Some participants also conducted positive self-comparisons to the bad answer and felt that they could do better, ‘ The information was not that great and I believe my abilities are beyond what was shown to me’. The bad answer also appeared to reinforce participants awareness in their own ability which had a positive effect on their task-specific SE, ‘ My awareness of my own ability was reinforced and therefore increased my confidence and motivation to be able to perform effectively and therefore increased my self-belief’. Participants also felt they gained knowledge as the bad answer taught them about what not to do in their answers and this had a positive effect on their task-specific SE, ‘ It increased my self-belief as I could clearly identify what was lacking in the answer’.

Participants also felt that they gained knowledge from reading the good previous answer, as it provided an example which helped understanding, ‘I feel better about how I will handle the task at hand because I now have a better understanding of what is required of me and what form of answer is acceptable’. Some participants made positive comparisons between themselves and the testimonial writer. They felt that because the testimonial writer. Had been successful, they could be too, ‘ Seeing someone else accomplish this goal has made me think that I too can be successful’.

Positive self-comparisons were also made when participants read the unsuccessful testimonial and this was done by both the low and high general SE groups. Participants described how they felt they were more capable than the individual in the testimonial presented, ‘ My capability is not the same as this persons. What they feel they are capable of doing has no bearing on me’.

When reading the positive testimonial, participants in the high general SE group felt it increased their task-specific SE because they gained knowledge from it which included tips and examples, ‘ It gave me a good idea on what to do to solve the task’. Participants in both groups made positive self-comparisons which had a positive effect on their task-specific SE. They felt that if the testimonial writer could do it, then so could they, ‘ If someone else that was unsure was able to do it that I could too’. Participants in both groups stated that reading the testimonial decreased the perceived task difficulty which had a positive effect on their SE. Overall, participants appeared to find the positive testimonial reassuring and it had a beneficial effect on their task-specific SE, ‘ I feel like this person boosted my thoughts and ability to do the task at hand’.

Reasons for negative effect on task-specific SE

Two main themes were found within the negative effects the VEI had on participants task-specific SE, worry and negative self-comparisons. With regards to worry, the low percentage statement left many participants in the low general SE group questioning their own beliefs, leading to feelings of uncertainty and worry, ‘ I feel a little more worried about my ability to complete the task’.

S ome participants in the low general SE group made negative self-comparisons to the good answer presented. They felt that they wouldn’t be able to write something as good and this lead to a decrease in their perceived task-specific SE, ‘ A good answer puts me down because I realise that I wouldn’t be able to come up with something this easy’. For participants in both the low and high general SE groups, reading the negative testimonial also lead to negative self-comparisons. This resulted in some participants realising they shared the same views as the testimonial writer and this had a negative effect on their task-specific SE, ‘ Because we share same views and beliefs about the task, I believe I will underperform for the question’.

Reasons for no effect on task-specific SE

One key theme was highlighted in the comments of those participants of which the VEI had no effect and that was dismissal of the information. This theme was mentioned in participants responses regarding all of the VEI forms presented apart from the good answer. Much of the dismissal was down to participants already having established strong self beliefs, ‘ I am a very self-confident person, and being shown a percentage of those who complete a task or not does not change my self-confidence’. Others stated that they are never influenced by external information in cases like this, ‘ I believe in the talents that I have. I would never let outside forces influence my confidence to such a degree’.

Discussion and conclusion

Overall, the results of this study have highlighted the mediating effect that an individual’s general SE can have on the interpretation and effect of VEI when presented within an OLE. The first hypothesis suggested that based upon previous studies looking into the moderating effect of an individual’s general SE on their interpretation of persuasive messages (Riet et al., 2008 , 2010 a, 2010 b), individuals with low general SE beliefs would not find VEI to boost their task-specific SE as much as others with high general SE. Results of the study supported this hypothesis. A main effect was found of an individual’s general SE level on the boost felt to their task-specific SE from reading the VEI presented. Those with high levels of general SE found reading the VEI to increase their task-specific SE significantly more than participants with low levels of general SE. Results support this hypothesis and show participants with low levels of general SE to find VEI less beneficial for increasing task-specific SE compared to those with high general SE.

The qualitative results highlighted how those with low general SE were less likely to make positive self-comparisons to the VEI they were presented with when compared to the high general SE group. Those in the low general SE group were more likely to make negative self-comparisons to VEI presented, even if it communicated a high level of success. In the case of the good previous answer, some low general SE individuals made negative self-comparisons, feeling that they were not able to create an answer as good as the one they had just read. Results of this study support the mediating role of an individual’s general SE in the interpretation of persuasive messages, as suggested in previous studies (Riet et al., 2008 , 2010 a, 2010 b). But this study considered this previous work within the interpretation of persuasive messages in the form of VEI, an information type that had not been considered previously.

The results also supported Hypothesis 2, as a main effect was found of the level of success demonstrated in the VEI on its benefit to an individual’s level of task-specific SE. Results describe how study participants perceived the VEI demonstrating a high level of success to be significantly more beneficial to their task-specific SE when compared to VEI communicating low levels of success. Qualitative analysis offered some insight into why participants found VEI demonstrating high levels of success to be beneficial. For some individuals, successful types of VEI provided them with extra information which they felt increased their SE in being able to complete the task. For example, the good answer provided the participants with a guide of how to structure their task answers. Other participants felt successful VEI types encouraged positive self-comparisons. In this process, the participant would compare themselves to the information, which would lead to increases in task-specific SE. In reference to the positive testimonial, some participants felt that if the testimonial writer was able to complete the task successfully, then so could they. VEI demonstrating high levels of success lead to some participants perceiving the task to be less difficult, increasing their task-specific SE. Finally, some participants felt reassured in their own abilities by reading information regarding others successes, this was especially the case for the successful testimonial information.

The qualitative data collected also gave an indication as to why some individuals found VEI types demonstrating low levels of success to decrease their task-specific SE. When reading these VEI types, some individuals would conduct negative self-comparisons. This process would result in participants feeling that they were not similar at all to the individuals in the VEI presented. Because of this, some participants felt that they would not be able to complete the task. These comparisons would lead to worry, which was found to have a negative effect on individuals task-specific SE.

Where there was a main effect of VEI demonstrating a high level of success to be more beneficial to an individuals task-specific SE than low success VEI types, this was caveated by an interaction effect where the bad example answer VEI type was perceived as more beneficial by participants to their task-specific SE than the good example answer. Qualitative data provided by the participants that were presented with the poor answer was useful in understanding why it had a positive effect on some individuals task-specific SE. Some people made positive social comparisons to the poor answer, they felt that they were able to do a lot better and this increased their task-specific SE. For others it was reassuring seeing other people not do that well on the task, and reinforced their beliefs about their own skills and abilities. The characteristics of individuals with high general SE outlined by Bandura ( 1994 ) were considered in this hypothesis. As those with high levels of general SE are more resilient and less likely to be faulted by negative information, it was suggested that VEI demonstrating a low level of success would not have a negative impact on their task-specific SE.

Finally, the results presented support Hypothesis 3, as none of the VEI presented in this test had a significantly negative effect on the task-specific SE for individuals with high general SE, not even the VEI demonstrating low levels of success. Qualitative results offered some insight into the thought process of individuals with high general SE when presented with VEI communicating a low level of success. Many individuals in the high general SE group ‘dismissed ‘any low success VEI they were shown. Some individuals in the high general SE group stated that they already had strong self-beliefs that would not be affected by such information. Others explained how they were never influenced by external information. Overall these results support the resilience that Bandura ( 1994 ) suggests those with high general SE have when confronted with negative types of information within an OLE.

The second half of Hypothesis 3 was also supported, as not all VEI presented to those with low general SE had a positive effect on their task-specific SE. A one-sample t-test found the unsuccessful testimonial information to have a significantly negative effect on individuals task-specific SE when compared to the known mean (‘No effect ‘). Qualitative data collected helps to understand why this type of VEI might have a negative effect on the task-specific SE of individuals with low general SE. For some individuals, reading the negative testimonial lead to negative self-comparisons. This was a process in which some participants realised they shared the same views as the person they were presented with. This perceived similarity may lead to the individual believing that because they were similar to the testimonial writer, they too wouldn’t be able to complete the set task, leading to the information having a negative effect on their task-specific SE. These results support theory regarding the anxiety and threat an individual with low general SE feels when presented with a VEI demonstrating low levels of success (Bandura, 1994 ).

Overall, the results have supported all three hypotheses posed in the study, building upon previous work regarding the effect of an individual’s general SE on how they interpret persuasive messages. An individual’s level of general SE was found to be a mediating factor in the effect different types of VEI had on their task-specific SE within a career skills OLE. Results have shown VEI to be less effective in increasing the task-specific SE of individuals with low general SE beliefs within the context of an OLE. Results suggest a need for VEI to be designed and presented in a way that considers the behaviours of both individuals with high but in particular, low levels of general SE.

Results support the need for more research to be conducted to find the most effective way of presenting VEI so it increases the task-specific SE of all learners within an OLE, regardless of their general SE. Individuals with low general SE found the unsuccessful testimonial presented in this study to have a negative impact on their task-specific SE, so this type of VEI should be avoided for this group. In contrast, individuals with high general SE didn’t find any of the VEI presented to have a negative impact on their task-specific SE. Results show low general SE individuals to be a more sensitive influenceable group and because of this, care must be taken that their responses to VEI presented are considered differently than those with high SE.

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Abbreviations

Online learning environment

• Self-efficacy
• Vicarious experience information

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Acknowledgements

The authors would like to thank Dr. Antonios Kaniadakis and Claire Revell for their kind help in the dissemination of the workshop.

This work was funded by the Engineering and Physical Sciences Research Council (EPSRC) through the Media and Arts Technology Programme, a Research Councils UK Centre for Doctoral Training (EP/G03723X/1).

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NW led on writing of the paper with AS also contributing to the writing of the paper. All authors worked on the study design. NW carried out the data analysis, with results being discussed with AS. Both authors read and approved the final manuscript.

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Wilde, N., Hsu, A. The influence of general self-efficacy on the interpretation of vicarious experience information within online learning. Int J Educ Technol High Educ 16 , 26 (2019). https://doi.org/10.1186/s41239-019-0158-x

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• Published: 21 May 2024

The mediating role of perceived social support on the relationship between lack of occupational coping self-efficacy and implicit absenteeism among intensive care unit nurses: a multicenter cross‑sectional study

• Qin Lin 1   na1 ,
• Mengxue Fu 2   na1 ,
• Kun Sun 3 ,
• Linfeng Liu 4 ,
• Pei Chen 1 ,
• Ling Li 1 ,
• Yanping Niu 1 &
• Jijun Wu 5  

BMC Health Services Research volume  24 , Article number:  653 ( 2024 ) Cite this article

Metrics details

Implicit absenteeism is very common among nurses. Poor perceived social support of intensive care unit nurses has a negative impact on their mental and physical health. There is evidence that lack of occupational coping self-efficacy can promote implicit absenteeism; however, the relationship between lack of occupational coping self-efficacy in perceived social support and implicit absenteeism of intensive care unit nurses is unclear. Therefore, this study aimed to evaluate the role of perceived social support between lack of occupational coping self-efficacy and implicit absenteeism of intensive care unit nurses, and to provide reliable evidence to the management of clinical nurses.

A cross-sectional study of 517 intensive care unit nurses in 10 tertiary hospitals in Sichuan province, China was conducted, of which 474 were valid questionnaires with a valid recovery rate of 91.6%. The survey tools included the Chinese version of Implicit Absenteeism Scale, the Chinese version of Perceived Social Support Scale, the Chinese version of Occupational Coping Self-Efficacy Scale and the Sociodemographic characteristics. Descriptive analysis and Pearson correlation analysis were performed using SPSS version 22.0, while the mediating effects were performed using AMOS version 24.0.

The average of intensive care unit nurses had a total implicit absenteeism score of (16.87 ± 3.98), in this study, the median of intensive care unit nurses’ implicit absenteeism score was 17, there were 210 intensive care unit nurses with low implicit absenteeism (44.3%) and 264 ICU nurses with high implicit absenteeism (55.7%). A total perceived social support score of (62.87 ± 11.61), and a total lack of occupational coping self-efficacy score of (22.78 ± 5.98). The results of Pearson correlation analysis showed that implicit absenteeism was negatively correlated with perceived social support ( r = -0.260, P  < 0.001) and positively correlated with lack of occupational coping self-efficacy ( r  = 0.414, P  < 0.001). In addition, we found that perceived social support plays a mediating role in lack of occupational coping self-efficacy and implicit absenteeism [ β  = 0.049, 95% CI of (0.002, 0.101)].

Conclusions

Intensive care unit nurses had a high level of implicit absenteeism with a moderate level of perceived social support and lack of occupational coping self-efficacy. Nursing managers should pay attention to the nurses those who were within low levels of social support and negative coping strategies, and take measures to reduce intensive care unit nurses’ professional stress, minimize implicit absenteeism.

Peer Review reports

Intensive care unit (ICU) nurses play a critical role in providing round-the-clock care to critically ill patients. However, the nature of their work can be stressful and demanding, resulting in physical and emotional challenges. The COVID-19 pandemic has further exacerbated these challenges, leading to negative outcomes for ICU nurses [ 1 ]. These challenges can take a toll on the physical and emotional well-being of ICU nurses, leading to negative outcomes such as low self-efficacy and implicit absenteeism [ 2 ]. The impact of the COVID-19 pandemic on the mental health of ICU nurses has been highlighted in recent research, with studies reporting high levels of anxiety, depression, and post-traumatic stress disorder among ICU nurses [ 3 ]. ICU nurses during the COVID-19 pandemic have been dealing with elevated levels of stress and emotional exhaustion [ 4 ]. The constant exposure to critically ill patients, the fear of personal infection, and the emotional toll of witnessing high mortality rates have contributed to increased psychological distress among ICU nurses [ 5 ]. Research suggests that during the COVID-19 pandemic, social support has become even more crucial for the mental health and well-being of healthcare professionals. A study found that perceived social support was inversely associated with anxiety and depression among healthcare workers during the pandemic [ 6 ]. In addition to the direct impact on mental health, the increased workload and exposure to infectious patients during the COVID-19 pandemic may exacerbate existing issues related to job satisfaction and burnout among ICU nurses. A study by Labrague and de Los Santos revealed that high levels of stress and workload significantly contributed to burnout among healthcare workers during the pandemic [ 7 ]. Besides, implicit absenteeism among ICU nurses poses a critical challenge within the broader framework of health systems and infrastructure, significantly affecting patient care, exacerbating workforce shortages, and contributing to systemic inefficiencies. ICU nurses are already in short supply, and implicit absenteeism contributes to workforce shortages. Emotionally disengaged nurses are more likely to experience burnout and turnover, leading to increased strain on the remaining staff and further exacerbating staffing shortages in critical care settings [ 8 ]. Implicit absenteeism can compromise patient safety and the quality of care provided in ICU. High levels of emotional disengagement may lead to decreased vigilance, diminished responsiveness to patient needs, and an increased likelihood of medical errors [ 9 ]. Therefore, it is important to explore strategies to support the mental health and well-being of ICU nurses during and after the COVID-19 pandemic.

Self-efficacy refers to an individual’s belief in their ability to perform a specific task or achieve a goal, and it plays a critical role in how individuals approach and cope with challenging situations. ICU nurses often face highly stressful and complex work environments, which characterized by high acuity patient care, time-sensitive decision-making, and emotional intensity. Firstly, the nature of ICU nursing involves caring for critically ill patients with complex medical conditions, ICU nurses are required to monitor vital signs, administer intricate treatments, and respond rapidly to dynamic patient situations [ 10 ]. This high acuity patient care demands a heightened level of attention and can lead to chronic stress and fatigue. Secondly, ICU nurses face constant time pressures and are often required to make swift, critical decisions, the need for quick and accurate responses to changing patient conditions adds a layer of stress to their work environment. This time-sensitive decision-making is inherent to ICU nursing and contributes to the overall complexity of their role [ 11 ]. Thirdly, ICU nurses regularly witness suffering, mortality, and family distress, the emotional intensity of providing care in life-threatening situations can lead to moral distress and emotional exhaustion. The burden of managing these emotions can have lasting effects on the mental health and well-being of ICU nurses [ 12 ]. Therefore, ICU nurse self-efficacy is an important area of research as it can affect job performance and job satisfaction. One study found that higher levels of self-efficacy were associated with greater job satisfaction and lower levels of emotional exhaustion among ICU nurses [ 13 ]. Another study suggested that ICU nurses with higher self-efficacy were more likely to engage in proactive coping behaviors, which in turn were associated with lower levels of emotional exhaustion [ 14 ].

Research has shown that social support is a critical factor in promoting the well-being of ICU nurses. Studies have found that social support from colleagues and supervisors is associated with lower levels of stress and burnout in ICU nurses [ 15 ]. In addition, social support from family and friends has been found to be important in buffering the negative effects of job stress on mental health in ICU nurses [ 16 ]. One study found that perceived social support from colleagues was positively associated with job satisfaction and negatively associated with emotional exhaustion among ICU nurses [ 17 ]. Another study found that social support from supervisors was positively associated with job satisfaction and negatively associated with turnover intention among ICU nurses [ 18 ]. Despite the recognized importance of social support for ICU nurses, more research is needed to fully understand the specific mechanisms through which social support operates and to develop effective interventions to support ICU nurses in the workplace.

Implicit absenteeism refers to a state where employees may be physically present at work but are emotionally or mentally disengaged, resulting in decreased job performance and overall contribution to the workplace [ 19 ]. While this term may not be widely used in the literature, the concept aligns with the broader understanding of presenteeism, which involves employees being on the job but not fully engaged or productive [ 20 ]. It is a more subtle form of employee disengagement than explicit absenteeism, such as calling in sick or taking time off. Implicit absenteeism is often associated with mental health conditions such as stress, burnout, and emotional exhaustion. Employees experiencing these mental health challenges may find it difficult to fully engage in their work, leading to a state of absenteeism despite being physically present [ 21 ]. Chronic health conditions can also contribute to implicit absenteeism, as employees dealing with physical health issues may struggle to fully engage in their tasks. This may manifest as reduced productivity, lack of focus, and an overall decline in job performance [ 22 ]. Implicit absenteeism can also impact nurses’ performance in the workplace, such as reduced patient interaction, reduced awareness of occupational protection, and lack of participation in professional development [ 23 , 24 , 25 ]. Research has suggested a negative relationship between nurse burnout, a concept closely related to implicit absenteeism, and job performance. For instance, a study by Van Bogaert et al. found that nurse burnout was significantly associated with lower perceived performance in various dimensions, including clinical care, teamwork, and job satisfaction [ 26 ]. One study found that high levels of job stress and low job control were associated with increased levels of implicit absenteeism among ICU nurses. The study suggested that interventions aimed at reducing job stress and increasing job control could be effective in reducing implicit absenteeism in this population [ 27 ]. Moreover, another study found that perceived organizational support was negatively associated with implicit absenteeism in ICU nurses. The study suggested that providing ICU nurses with a supportive work environment, such as opportunities for professional development and recognition, could reduce the occurrence of implicit absenteeism [ 28 ]. Moreover, a study on Chinese ICU nurses showed that implicit absenteeism were negatively correlated with perceived social support ( r =-0.390, P  < 0.05) and positively correlated with lack of occupational coping self-efficacy ( r  = 0.478, P  < 0.05) [ 29 ]. The Job Demand-Resource (JD-R) Model is a theoretical framework in occupational and organizational psychology that was developed to understand the impact of job characteristics on employee well-being and performance. The model was initially proposed by Arnold Bakker and Evangelia Demerouti in the early 2000s [ 30 ]. The JD-R Model is widely used to investigate the factors that contribute to employee engagement, burnout, and overall job satisfaction. This model suggests that job resources, including social support, can buffer the impact of job demands on employee well-being and performance. Based on the above-mentioned literature reviews, this study puts forward the following hypotheses: First, lack of occupational coping self-efficacy is related to the implicit absenteeism of ICU nurses (H1). Second, lack of occupational coping self-efficacy is correlated with perceived social support of ICU nurses (H2). Third, perceived social support is correlated with the implicit absenteeism of ICU nurses (H3). Finally, perceived social support plays a mediating role in the relationship between lack of occupational coping self-efficacy, and implicit absenteeism (H4). By investigating the specific mechanisms through which social support operates, and the impact of the COVID-19 pandemic on ICU nurses, this study can provide important insights into interventions aimed at improving the well-being and job performance of ICU nurses.

Study design and ethics

A cross-sectional study was conducted in March 2022 using a convenience sampling method to select ICU nurses from 10 tertiary hospitals of 5 cities in Sichuan province, China. This study was conducted in accordance with the Helsinki Declaration. The study protocol was approved by the Ethics Committee of People’s Hospital of Deyang (2021-04-056-K01). The questionnaires remain anonymous, the first page of the online questionnaire is the informed consent form, participants indicate their agreement to participate in the survey by clicking the “Agree” option in the online assessment, all data collected are confidential and all participants had informed consent.

Participants

A total of 517 questionnaires were issued and collected. 43 questionnaires were excluded due to evident patterns in the responses across various questionnaire items, and the surveys from the same hospital exhibited noticeable similarities. After eliminating 43 invalid questionnaires, 474 valid questionnaires were received, with a valid recovery rate of 91.6%.

The eligibility criteria were as follows: (1) registered nurses, (2) more than 12 months of ICU nursing experience, (3) willing to participate in the survey. The exclusion criteria were as follows: (1) training nurses or rotating nurses, (2) not working in the hospital during the survey period, such as long-term sick leave or maternity leave.

Survey tools

Sociodemographic characteristics.

Sociodemographic characteristics included age, gender, marital status, educational background, professional title, management position, working experience in ICU, employment form, turnover intention, physical pain, occupational stress, night shift experience and workplace violence.

The Chinese version of implicit absenteeism scale

The scale was developed by Koopman et al. [ 31 ] and translated and revised in to Chinese by Zhao Fang [ 32 ]. First, Zhao Fang and others translated, back-translated, and culturally adapted the scale. Subsequently, they conducted a survey on 935 staff members to validate the reliability and validity of the scale. The results indicated that the Cronbach’s α coefficients for each dimension of the scale ranged from 0.76 to 0.90. The structural validity revealed two latent factors, namely, work constraints and work vigor, with a cumulative variance contribution rate of 81.01%. The reliability and validity of the scale were deemed satisfactory. In another study, Liu Jia-wen et al. employed the same scale to conduct a questionnaire survey on 150 emergency department nurses in Nanchang, China, from September to October 2020 [ 33 ]. The Cronbach’s α coefficient for the scale was found to be 0.71, indicating good reliability. This scale consists of 6 items and the scale is used to estimate the employee productivity loss caused by the implicit absenteeism with a specific health status in the past month. This scale is based on a 5-point Likert scale, ranging from “completely disagree” to “completely agree”. The score for each item ranges from 1 to 5, and the total score ranges from 6 to 30, with higher scores indicating higher levels of productivity loss due to health status and the less effective attendance.

The Chinese version of perceived social support scale

The scale was developed by Zimet et al. [ 34 ] and translated and revised in to Chinese by Jiang Qian-jin [ 35 ]. In December 2019, Xiang Feng-ming and others employed this scale to conduct a questionnaire survey on 182 novice nurses in Wenzhou, China. The results showed that the Cronbach’s α coefficients for the overall scale and each dimension were 0.856, 0.803, 0.851, and 0.866, respectively [ 36 ]. The scale was used to measure perceived social support of ICU nurses. This scale consists of 3 dimensions and 12 items: 4 items for family support, 4 items for friends support, 4 items for other support. This scale is based on a 7-point Likert scale, 1 point stand for very disagree and 7 points stand for very agree. The total score ranges from 12 to 84, with higher scores indicating higher levels of perceived social support. The Cronbach’s alpha coefficient of this scale 0.90.

The Chinese version of occupational coping self-efficacy scale

The Chinese version of Occupational Coping Self-Efficacy Scale was used to measure the lack of occupational coping self-efficacy of ICU nurses. The scale was developed by Pisanti et al. [ 37 ] and translated and revised in to Chinese by Zhai Yan-xue [ 38 ]. First, Zhai Yan-xue organized researchers to translate and back-translate the scale. Subsequently, cultural adaptation was conducted by three experienced experts. Following this, modifications were made based on a preliminary survey of 50 nurses. Finally, a survey was conducted on 1172 nurses from five public hospitals to validate the reliability and validity of the scale. The results indicated a Cronbach’s α coefficient of 0.882, a test-retest reliability of 0.991, I-CVI of 0.833  ∼  1.000, S-CVI/UA of 0.889 and S-CVI/Ave of 0.981, demonstrating good reliability and validity of the scale [ 38 ]. This scale consists of 2 dimensions and 9 items: 6 items for professional burden, 3 items for difficulties in getting along with each other. This scale is based on a 5-point Likert scale, 1 point means “strongly disagree”, 5 points means “strongly agree”, and the total score ranges from 9 to 45, with higher scores indicating lower levels of occupational coping self-efficacy, means that the lack of occupational coping self-efficacy. The Cronbach’s alpha coefficient of this scale was 0.88, and the Cronbach’s alpha coefficients of the subscales were 0.79 and 0.87.

Data collection

We contacted the head nurses of ICU departments in 10 tertiary hospitals of 5 cities in Sichuan province, and distributed the online links of questionnaires to them to finish the survey. Voluntary and anonymity principle, inclusion and exclusion criteria were indicated on the first page of the online questionnaire. If ICU nurses clicked on the online link and submitted the questionnaire, it was informed consent by default. We set all answers must be filled out before submission. And two researchers checked the questionnaires to ensure the validity and integrity of the survey.

Data analysis

This study used SPSS version 22.0 and AMOS version 24.0 (IBM, Armonk, NY, USA) for statistical analysis of the data. Firstly, descriptive analysis was used to describe the sociodemographic characteristics and main variables of ICU nurses. Count data were expressed as percentage (%). Measurement data were expressed as (mean ± standard deviation), in addition, independent samples t-test and one-way ANOVA were used for comparison between groups. Pearson correlation analysis was performed to analysis the correlation of social support, lack of occupational coping self-efficacy and implicit absenteeism. Besides, we used lack of occupational coping self-efficacy as the independent variable and implicit absenteeism as the dependent variable to examine the mediating role of social support. In this study, we take α = 0.05 as the test standard.

Sociodemographic characteristics of ICU nurses

As detailed in Table  1 , a total of 474 ICU nurses were included in this study with a mean age of 32.19 years (range 21 to 56) and a mean year of ICU working experience of 8.07 years (range 1 to 36). Most of the ICU nurses were female (91.8%) and married (58.0%). In terms of educational background, 77.8% of ICU nurses have a bachelor’s degree. Besides, 82.7% of ICU nurses were in the authorized strength and contract system. Nearly 18% of ICU nurses were are experiencing physical pain. About 35% of ICU nurses admitted that they have high level occupational stress. In addition, 34.5% of ICU nurses have experienced workplace violence.

There were significant differences in the marital status, professional title, management position, working experience in ICU, turnover intention, physical pain, occupational stress, night shift experience and workplace violence between ICU nurses with high and low implicit absenteeism (all P  < 0.05). And no significant differences were found in the in the gender, age, educational background and employment form between ICU nurses with high and low implicit absenteeism (all P  > 0.05).

Scores of implicit absenteeism scale, perceived social support scale and occupational coping self-efficacy scale

As shown in Table  2 , the average of ICU nurses had a total implicit absenteeism score of (16.87 ± 3.98), indicating that ICU nurses had a high level of implicit absenteeism.

Previous research [ 39 ] has reported that more than half of nurses have implicit absenteeism and take the median of nurses’ implicit absenteeism score as the cut-off point to differentiate the high and low implicit absenteeism. In this study, the median of ICU nurses’ implicit absenteeism score was 17. Therefore, there were 210 ICU nurses with low implicit absenteeism (44.3%) and 264 ICU nurses with high implicit absenteeism (55.7%).

In addition, a total perceived social support score of (62.87 ± 11.61), indicating that ICU nurses had a moderate level of perceived social support, and a total lack of occupational coping self-efficacy score of (22.78 ± 5.98), indicating that ICU nurses had a moderate level of lack of occupational coping self-efficacy. The detailed information is shown in Table  3 .

Analysis of the correlation between implicit absenteeism, perceived social support and lack of occupational coping self-efficacy

The results of Pearson correlation analysis showed that implicit absenteeism was negatively correlated with perceived social support ( r = -0.260, P  < 0.001) and positively correlated with lack of occupational coping self-efficacy ( r  = 0.414, P  < 0.001), Table  4 .

Mediating effect of perceived social support between lack of occupational coping self-efficacy and implicit absenteeism in ICU nurses

Figure  1 ; Table  5 show the Structural Equation Model results. The standardized model paths are shown in Fig.  1 . The direct effect, indirect effect, and total effect are shown in Table  5 . The standardized model had a good model fit with the data (Table  6 ).

As shown in Table  5 , lack of occupational coping self-efficacy ( β  = 0.404, for total effect) had significant positive relationships with implicit absenteeism. The results also indicated that the indirect effect ( β  = 0.049) of lack of occupational coping self-efficacy on implicit absenteeism was significant as well as its direct effect on perceived social support ( β = -0.420). These findings show that higher occupational coping self-efficacy was related to lower implicit absenteeism and higher perceived social support, and that perceived social support partially mediated the relationship between lack of occupational coping self-efficacy and implicit absenteeism due to significant direct and indirect paths.

The mediating effect model of perceived social support between lack of occupational coping self-efficacy and implicit absenteeism in ICU nurses

Nursing workforce is critical in delivering quality care to patients in healthcare settings. However, absenteeism among nurses has become a significant concern for healthcare organizations globally. The phenomenon of nurse’s implicit absenteeism has been extensively studied in both China and other countries. A study found that the prevalence of nurse’s implicit absenteeism was 11.7% in China, and the factors influencing implicit absenteeism included age, working experience, and job satisfaction [40]. Similarly, a study conducted in Saudi Arabia reported that 24.7% of nurses experienced implicit absenteeism, with workload and job stress being the significant predictors [ 41 ]. Moreover, research conducted in the United States (US) and Europe also highlighted the problem of implicit absenteeism among nurses. A study in the US found that implicit absenteeism was associated with burnout, job dissatisfaction, and intention to leave the profession [ 42 ]. In addition, a study reported that implicit absenteeism was associated with workload, job demands, and role ambiguity [ 43 ]. Our study showed that the implicit absenteeism score of ICU nurses was (16.87 ± 3.98), which was similar to implicit absenteeism score of (17.25 ± 3.51) for ICU nurses in another study in China [ 44 ]. Similar research conclusions are also found in 200 ICU nurses from tertiary comprehensive hospitals in Beijing, where their implicit absenteeism score was (16.65 ± 4.69) [ 45 ]. This implies that ICU nurses in China generally experience implicit absenteeism, a result deserving attention from nursing managers. Analyzing this, it may be attributed to the global shortage of nursing personnel, where ICU nurses face a similar shortage of human resources. Given that ICU patients are often critically ill with rapidly changing conditions, the tasks of ICU nurses are less substitutable, making them prone to implicit absenteeism. Additionally, in the ICU team nursing model, team members taking sick leave may increase the workload for other members. Based on a sense of responsibility to colleagues, many tend to choose implicit absenteeism. Hence, healthcare organizations must develop strategies to manage and reduce implicit absenteeism among nurses to ensure quality patient care.

In recent years, research on perceived social support among ICU nurses has gained attention both in China and abroad. Perceived social support is the belief that one has access to individuals, groups, or networks that provide assistance and care in times of need [ 46 ]. ICU nurses are exposed to various stressors such as heavy workloads, long working hours, and critically ill patients, which can lead to emotional exhaustion, burnout, and turnover intention [ 47 ]. Therefore, perceived social support is crucial for their psychological well-being and job satisfaction. In China, several studies have investigated perceived social support among ICU nurses. For example, a study found that ICU nurses perceived low social support from their colleagues and supervisors, which was negatively associated with their job satisfaction [ 48 ]. Another study showed that ICU nurses who perceived high social support had lower levels of burnout and higher levels of work engagement [ 49 ]. Similarly, a study conducted in the Netherlands revealed that ICU nurses who perceived high social support from their colleagues had lower levels of emotional exhaustion and turnover intention [ 50 ]. Another study found that perceived social support from family and friends was positively associated with job satisfaction and negatively associated with emotional exhaustion among ICU nurses [ 51 ]. In this study, the perceived social support score of ICU nurses was (62.87 ± 11.61) points, which is lower than that of the research of Wu Peng [ 52 ] and Wang Li-jiao [ 53 ], indicating that nurses’ perceived social support had a moderate level in China. This suggests that the level of social support among ICU nurses in China is generally low. Previous research suggests a close correlation between nurses’ professional identity, job performance, and social support levels. Nurses who receive good support from family, friends, and other social networks often can maintain both physical and mental health, smoothly handle job responsibilities, accomplish tasks successfully, and experience higher job satisfaction [ 52 , 54 ]. With nurses being recognized as a high-risk profession, the social support received by nurses has been widely studied in the field of nursing human resources management. Concerningly, the level of social support for nurses in China and globally is not high. Our nurses are currently experiencing significant work pressure and physical fatigue, making it challenging for them to fully engage in their work. Therefore, it is important for healthcare organizations to develop interventions that enhance social support among ICU nurses to promote their well-being and reduce turnover intention. Overall, it is important for healthcare organizations to develop interventions that enhance social support among ICU nurses to promote their well-being and reduce turnover intention.

Occupational coping self-efficacy refers to an individual’s belief in their ability to effectively manage job-related stressors and challenges [ 55 ]. It is a crucial factor for promoting nurses’ occupational growth and sense of occupational benefit, as well as improving patient outcomes. Studies have shown that ICU nurses have relatively low levels of occupational coping self-efficacy. For example, a study found that ICU nurses with higher levels of occupational coping self-efficacy reported lower levels of emotional exhaustion and depersonalization, and higher levels of personal accomplishment [ 56 ]. A study also found that occupational coping self-efficacy was positively associated with job satisfaction among ICU nurses in China [ 57 ]. Another study found that occupational coping self-efficacy was positively associated with job satisfaction and negatively associated with burnout among ICU nurses in Taiwan [ 58 ]. In addition, a study showed that ICU nurses in Saudi Arabia with higher levels of occupational coping self-efficacy reported lower levels of emotional exhaustion and higher levels of personal accomplishment [ 59 ].

The results of this study suggest that the total score of lack of occupational coping self-efficacy was (22.78 ± 5.98). This result suggests that the self-efficacy levels of the majority of ICU nurses in China need improvement. The findings of this study are consistent with a previous survey on the self-efficacy of ICU nurses in China [ 60 ], and compared to other clinical nurses in China, ICU nurses exhibit lower levels of self-efficacy [ 61 – 62 ]. Additionally, when compared to professions such as secondary school teachers and pilots [ 63 – 64 ], ICU nurses seem to experience more widespread lower self-efficacy levels. In China, most ICU nurses work an average of more than 8 h per day. Under the prolonged work pressures, ICU nurses have less time available for interpersonal relationships, family activities, rest, and sleep. Therefore, this may lead to occupational burnout, lower self-efficacy among ICU nurses, and potentially trigger work-family conflicts. The above results provide clear evidence indicating that nursing managers should pay closer attention to the self-efficacy levels of ICU nurses in the future, as it is closely associated with the professional development of ICU nurses.

Our correlation results show that implicit absenteeism of ICU nurses was negatively correlated with perceived social support and its various dimensions ( r =-0.212 ∼ -0.260, P <0.01). The lower the perceived social support, the higher the implicit absenteeism. The results of this study indicate a negative correlation between support from family and implicit absenteeism among ICU nurses, consistent with previous research [ 65 ]. Family support not only ensures the maintenance of a positive mood for ICU nurses but also contributes to their physical well-being and active engagement in work. Furthermore, support from friends is negatively correlated with implicit absenteeism among ICU nurses. Friends support allow ICU nurses to feel embraced, understood, and assisted from the outside, enabling them to confront life and work challenges positively and facilitating the completion of work tasks [ 66 ]. Lastly, support from other sources is negatively correlated with implicit absenteeism among ICU nurses. According to reports [ 29 ], having more organizational support enables nurses to better immerse themselves in their work, where their personal values are fully reflected in patient care. This leads to a more positive response to work and reduces the impact of compromised health productivity to a lower level. In contrast, implicit absenteeism of ICU nurses was positively correlated with lack of occupational coping self-efficacy and its various dimensions ( r  = 0.379  ∼  0.414, P <0.01). The higher the occupational coping self-efficacy, the lower the implicit absenteeism. These findings suggest that both perceived social support and lack of occupational coping self-efficacy are important factors in predicting implicit absenteeism among ICU nurses. Given the findings, it is important for healthcare organizations to prioritize interventions that can help to increase perceived social support and occupational coping self-efficacy among ICU nurses. For example, providing opportunities for social support, such as peer mentoring or support groups, can help to reduce feelings of isolation and increase job satisfaction [ 67 ]. Additionally, training programs that focus on developing coping skills and self-efficacy can help nurses to better manage the demands of their job and feel more confident in their abilities [ 68 ]. Here are some feasible approaches that healthcare organizations can consider to improve ICU nurses’ perceived social support. Firstly, establishing peer mentoring programs where experienced ICU nurses provide support and guidance to newer or less experienced colleagues. Encouraging regular interactions and check-ins to foster a sense of camaraderie and mutual support. secondly, creating support groups within the ICU setting, where nurses can share experiences, discuss challenges, and provide emotional support to each other. Facilitating group discussions led by mental health professionals to address common stressors and coping strategies. Thirdly, providing training on effective communication skills to enhance interpersonal relationships among ICU team members. Emphasizing active listening and empathy to create a supportive environment. The above strategies for social support are among colleagues within the ICU setting. ICU nurses’ social support from family and friends are different with colleagues support and may implement distinct strategies recognizing the unique dynamics of each relationship. For support from family and friends, interventions could involve educational sessions for family and friends to understand the demands and stressors specific to ICU nursing, encouraging open communication channels between nurses and their loved ones, and providing resources for family support. This might include counseling services or support groups for family and friends of ICU nurses. In addition, the healthcare organizations can improve the occupational coping self-efficacy of ICU nurses through the following measures. First of all, conducting workshops focused on enhancing specific coping skills, such as time management, stress reduction techniques, and conflict resolution. Encouraging ongoing professional development to build a sense of competence. Besides, implementing recognition programs to acknowledge the hard work and dedication of ICU nurses. Providing regular feedback and appreciation for their contributions to patient care. Finally, organizing team-building activities to foster a positive work environment and strengthen teamwork among ICU staff. Creating a culture that values collaboration and mutual support. Furthermore, the relationship between social support, self-efficacy, and absenteeism due to physical health is a complex interplay influenced by various factors. On the one hand, social support, whether from colleagues, friends, or family, can act as a buffer against ICU nurses’ stress. Lower stress levels are associated with improved physical health and a reduced likelihood of needing time off due to health issues. On the other hand, social support networks can provide practical assistance, such as help with ICU nurses’ childcare or transportation, which may mitigate the impact of physical health issues on absenteeism. Having a reliable support system may reduce the need for extended time off for health-related issues. Self-efficacy is associated with absenteeism due to physical health, which is reflected in the following aspects. First, high self-efficacy is associated with a greater likelihood of adopting and maintaining healthy behaviors, such as regular exercise and a balanced diet. Healthy lifestyles contribute to overall well-being and can reduce ICU nurses’ risk of absenteeism due to physical health issues. next, individuals with high self-efficacy often possess effective coping mechanisms to manage pain, discomfort, or chronic conditions. The ability of ICU nurses’ to cope with health challenges may reduce the severity and duration of illnesses, potentially minimizing absenteeism.

The results of our mediating role analysis show that ICU nurses’ the lack of occupational coping self-efficacy had a direct positive predictive influence on their implicit absenteeism and that perceived social support had a partial mediating effect between lack of occupational coping self-efficacy and implicit absenteeism. The higher the level of occupational coping self-efficacy, the better the perceived social support and the lower the implicit absenteeism. The reasons for this relationship may be as follows: firstly, as the level of perceived social support increases, ICU nurses are more likely to feel external support from family, friends, and other sources, which can be utilized to effectively solve their problems or difficulties [ 69 ]. Secondly, higher levels of perceived social support can help ICU nurses to redefine difficult situations and strengthen their ability to regulate feelings of distrust, anxiety, and fear, thereby enhancing their positive attitudes towards handling difficulties and reducing implicit absenteeism [ 70 ]. In addition, a higher level of occupational self-efficacy enables ICU nurses to have a correct understanding of the challenges they face at work, form positive professional identities and values, and increase their confidence in dealing with difficulties [ 71 ]. In the practice environments of many hospitals in China, issues such as workload overload, poor working conditions, and lack of adequate compensation may exist [ 72 ]. The working environment in the ICU is often characterized by its enclosed nature, and the workload is frequently higher than in other departments. This may explain why many ICU nurses may develop lower self-efficacy and lack social support. Social support has the potential to uplift the work enthusiasm and professional spirit of ICU nurses, fostering a positive professional attitude and encouraging them to contribute to patient health and the development of medical institutions. However, as observed in this study, when experiencing lower self-efficacy, ICU nurses exhibit compromised health productivity, refrain from making additional efforts for the medical institution, and develop a negative attitude towards their work. If the social support for ICU nurses diminishes due to lower self-efficacy, it is unsurprising that their sense of mission as “health guardians” diminishes as well, meaning ICU nurses may no longer see serving the health of patients as their mission. As mentioned in the Conservation of Resources theory, when ICU nurses lose their resources (similar to losing social support in this study), they may experience varying degrees of psychological stress and lose confidence in the organization. With increased separation, psychological or physical issues may arise, such as ICU nurses being physically unwilling to engage in work, emotionally reluctant to integrate into the work team, cognitively becoming less active, and concealing their feelings and thoughts, all of which signify the occurrence of implicit absenteeism. Moreover, it can further impact the attitudes, behaviors, and beliefs of ICU nurses towards their profession, negatively affecting professional identity and a sense of professional mission. Therefore, hospital nursing managers need to pay closer attention to the current status of self-efficacy and social support among ICU nurses, strengthening their professional attitudes from aspects of organizational support, colleague support, and material support to promote healthy practices in their profession.

On November 29th, 2021, the General Office of the People’s Government of Sichuan Province issued the Implementation Plan for Promoting the High-quality Development of Public Hospitals in Sichuan Province, which emphasized the reform of personnel management system and the increase of nurses’ equipment, so that the overall ratio of doctors to nurses in public hospitals gradually reached about 1: 2. In addition, the salary distribution system should be reformed to encourage the internal distribution of hospitals to be tilted towards high-risk and high-intensity posts. The above policies and programs provide strong external social support for ICU nurses. Identifying institutional gaps and proposing improvements to support the workforce involves a comprehensive examination of existing policies, practices, and organizational structures. Common gaps include limited mental health support with suggestions for comprehensive programs and manager training, inadequate work-life balance policies calling for flexible arrangements and clear remote work options, a lack of professional development opportunities necessitating ongoing training, mentorship programs, and support for continuous learning, and insufficient diversity and inclusion initiatives requiring diversity training, committees, and regular assessments. Other gaps encompass poor communication channels, suggesting enhancements to internal communication strategies and regular town hall meetings, limited health and wellness programs requiring initiatives addressing physical and mental health, and inadequate remote work infrastructure, calling for technology investment and clear policies. Additionally, the absence of recognition and rewards programs underscores the need for implementation alongside leadership training, regular employee surveys, clear career progression paths, encouragement of peer support networks, and continuous evaluation and adaptation of workplace policies for ongoing improvement. Addressing these gaps and implementing improvements necessitates a collaborative effort from leadership, human resources, and employees, emphasizing ongoing assessment, communication, and a genuine commitment to workforce well-being and development.

Limitations and recommendations

This research has some limitations that need to be acknowledged. Firstly, this study is a cross-sectional design, which cannot determine the causal relationship between variables.

Secondly, this study employed a convenience sampling method to select participants, which may result in meaningful differences in various sociodemographic categories. These differences among the population could limit the generalizability of the results to a broader population, introduce bias to the sample, and potentially act as confounding variables affecting the relationship between the independent and dependent variables. Therefore, in future research, efforts to enhance the representativeness of the sample will be a focus of our endeavors. Finally, this study was conducted during the COVID-19 pandemic, which may have led to higher levels of implicit absenteeism and lower levels of occupational coping self-efficacy being measured.

Despite these limitations, this study can provide valuable information for future research. For example, this study describes the occurrence of implicit absenteeism among ICU nurses from the perspectives of social support and self-efficacy and establishes a structural equation model, making the study of implicit absenteeism more comprehensive and richer. Additionally, this study confirms the mediating role of perceived social support in the relationship between lack of occupational coping self-efficacy and implicit absenteeism among ICU nurses, suggesting that increasing perceived social support and occupational coping self-efficacy can reduce implicit absenteeism, decrease negative emotions and psychological stress, improve ICU nurses’ job satisfaction and promote their mental health.

The results of this study indicate that there is a high prevalence of implicit absenteeism among ICU nurses, with 55.7% of ICU nurses evaluated as having a high level of implicit absenteeism and 44.3% evaluated as having a low level of implicit absenteeism. In addition, implicit absenteeism among ICU nurses is negatively correlated with perceived social support and positively correlated with lack of occupational coping self-efficacy. Perceived social support plays a significant mediating role between lack of occupational coping self-efficacy and implicit absenteeism among ICU nurses. In future departmental management, ICU managers need to pay attention to nurses with low levels of social support and negative coping strategies, and take measures such as providing peer support, forming work groups, and arranging work tasks reasonably to reduce nurses’ professional stress, minimize implicit absenteeism, and promote the development of high-quality nursing teams.

Data availability

All data generated or analyzed during this study are included in this published article.

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Acknowledgements

We strongly acknowledged the 517 ICU nurses who participated in the study.

This work was supported by Popularization and application project of Sichuan Provincial Health and Wellness Committee (Grant Number 19PJ042) and Sichuan Hospital Management and Development Research Center Project (Grant Number SCYG2019-33).

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Qin Lin and Mengxue Fu contributed equally to this work.

Authors and Affiliations

Shulan International Medical College, Zhejiang Shuren University, Hangzhou, 310000, China

Qin Lin, Pei Chen, Ling Li & Yanping Niu

Department of Rehabilitation, People’s Hospital of Jianyang, Jianyang, 641400, China

Intensive Care Unit, West China Hospital, Sichuan University, Chengdu, 610044, China

Department of Scientific Research, Sichuan Nursing Vocational College, Chengdu, 610100, China

Linfeng Liu

Department of Cardiology, People’s Hospital of Deyang, Deyang, 618099, China

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Q L, MX F, K S and L L designed and conducted research, Q L, MX F, LF L and P C contributed equally to the research analysis and interpretation of the data and drafting. K S, YP N and JJ W contributed to distribute and withdrew the questionnaires. P C, YP N and L L contributed to provide guidance from the perspective of statistics. JJ W supervised the project and contributed to conception of the research and critical revision of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Jijun Wu .

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This study was approved by the Ethics Committee of People’s Hospital of Deyang (2021-04-056-K01). All methods were carried out in accordance with the Declaration of Helsinki. Informed consent was obtained from all participants.

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Lin, Q., Fu, M., Sun, K. et al. The mediating role of perceived social support on the relationship between lack of occupational coping self-efficacy and implicit absenteeism among intensive care unit nurses: a multicenter cross‑sectional study. BMC Health Serv Res 24 , 653 (2024). https://doi.org/10.1186/s12913-024-11084-y

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Relationship between research self-efficacy and evidence-based practice in the medical students

Department of MPH, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

Alireza Salehi

1 MD, MPH, PhD Associate Professor of Epidemiology, Shiraz University of Medical Sciences Shiraz, Iran

Mitra Amini

2 Clinical Education Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

Hossein Molavi Vardanjani

Malihe sousani tavabe.

3 Research Center for Traditional Medicine and History of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

BACKGROUND:

Due to the rapid advancement of medical knowledge, promotion in research is necessary to have the best clinical practice. Research Self-efficacy (RSE) is the researcher's confidence in their ability to conduct a specific study. The Evidence-Based Practice (EBP) represents how to improve the quality of care and treatment of patients. RSE and EBP are the cornerstones of successful research and then efficacious medical practice. This study aims to evaluate RSE and acceptance of EBP and their correlation among medical students.

MATERIALS AND MEHODS:

This is a cross-sectional study designed on 600 clinical students at the medical school of Shiraz, using a census method in 2020. Students were invited to fill out the standardized Phillips and Russell's questionnaires about RSE (4 domains, 33 questions) and Rubin and Parrish's questionnaire of EBP (10 questions). The gathered data were analyzed through the SPSS at α = 0.05 using descriptive statistics, t -test, Chi-square, and multiple linear regressions.

There was a positive correlation between EBP and RSE score ( P < 0.05). The results of linear regression test showed that all variables had a significant effect on our response variables and their effect were significant ( P < 0.05). The highest mean score in RSE was shown in the subscale of writing skills (52.54). The lowest score was observed in the subscale of quantitative (student's subjective assessment of their ability to work with statistically related data and formulas) as well as computer skills (35.61).

CONCLUSIONS:

Students who participated in a research project, workshop, or Master of Public Health program got a higher RSE and EBP. Due to the positive correlation between RSE and EBP, we conclude that trained physicians who can research independently and use research evidence can find the best treatment approach for patients. These finding support the importance of integrating research education in medical curriculum to increase RSE and finally improvement of EBP among medical students.

Introduction

A successful academic system can train physicians with adequate clinical competencies and research ability to find valid and up-to-date evidence to deliver services to patients. Research plays a significant role in improving educational processes and the expansion of scientific services in society.[ 1 ] One of the critical topics in the research field is the researcher's beliefs and attitudes, especially about their self-efficacy.[ 2 ] For effective performance, acquiring skills and believing in performing those skills are required.[ 3 , 4 ] Research Self-efficacy (RSE) is the confidence of a researcher in their ability to conduct a specific study.[ 5 ] Individual researcher variables cause a substantial effect on research productivity.[ 6 ] There is an inverse relationship between RSE and researcher's anxiety; the lower the RSE in a researcher, the greater their anxiety in designing and conducting research.[ 1 , 2 , 7 ] Besides RSE, evidence-based practice (EBP) also represents an essential academic performance domain. On the other hand, for a better and evidence-based clinical practice, research-related abilities are crucial. Therefore, these two factors seem to be related.[ 8 ]

The EBP represents a way to increase the quality of care and treatment of patients. It is necessary for safe, high-quality, and ethical medicine.[ 9 ] More precisely, EBP integrates and efficiently utilizes the best present and up-to-date evidence, the physician's expertise, and patient preferences in clinical decision-making.[ 2 ]

With the rising demand in the healthcare industry, academic research and EBP are essential for the profession's future. EBP and the importance of RSE continues to influence education and medical practice. Medical educators should design curricular initiatives to facilitate critical thinking and improve the chances of adequately applying research skills in residency and beyond.[ 4 ] As Getenet Dessie Ayalew showed, most medical practice in low and middle-income countries is not evidence-based.[ 10 ] Therefore, understanding the extent and possible ways to improve research skills and EBP is essential for enhancing patient care quality. Several previous studies on EBP evaluated the barriers, awareness, and attitude. Lack of familiarity with effective research methods was one of the main obstacles to EBP.[ 6 , 8 , 10 , 11 ] Despite the importance of research and EBP in medicine, previous studies in medical students included a small sample size or directed in the medical-related field, including nursing.[ 11 , 12 , 13 , 14 ]

RSE and EBP are the cornerstones of successful research and then efficacious medical practice. They can be used to identify the disadvantages and weaknesses related to the research. The significance of research in clinical decision-making, especially for medical students, is often overlooked. This study aims to investigate RES and EBP in the large sample size of clinical students. By increasing RSE during the study period, future health professionals can improve their skills and motivation to use research evidence to expand clinical practice.[ 15 ] Since no similar study has been done in the Shiraz Medical School up to now, the results of the study can aid in educational planning to strengthen these factors in clinical medical students before their graduation. Furthermore, it may bridge the present gap between scientific research results and practice in future physicians.[ 8 ]

Materials and Methods

Study design and setting.

This is a cross-sectional study conducted on the clinical students of Shiraz Medical School. Shiraz Medical School is the part of Shiraz University of Medical Sciences (SUMS), a public medical school located in Shiraz, Iran. About 1660 students in different educational stages are studying at this university. In the period from March to December 2020, approximately 600 students entered the hospital clinical environment and involved in the clinical decision-making in this medical school.

Study participants and sampling

All students who agreed to participate in the study, those who were in the clinical stage and those who entered the clinical stage during March to December 2020 enrolled in this study. No sampling was performed from the target population, and we used a census method. The exclusion criterion was medical students in their 4 th year and below those who were not in the clinical stage because they had not entered the hospital or experienced a medical encounter. The total of 600 clinical students were invited to participate in the study. Five hundred and forty-eight students filled out the questionnaire with a response rate of 91.3%.

Data collection tool and technique

A total of 381 students have answered the self-declaration paper questionnaire, and for others, due to difficult access, the electronic questionnaire link was sent to each individual through email to complete.

Demographic characteristics of participants consisted of age, sex, university grade point average (GPA), and the clinical stages (Extern: represent students who enter this clinical stage at the 4 th year of medicine. This period lasts 12 months, has four main sections, and covers common issues in general medicine, including internal medicine, surgery, gynecology, and pediatrics. Intern: In the internship, students are responsible for examining patients, diagnosing and treating patients in the hospital, and putting the skills they have been trained to practical use. this stage is the last stage of medical education and lasts 18 months).

Research-related data included participation in research training workshops or research projects (as a principal investigator or members of the research team) or voluntarily participating in the Master of Public Health (MPH) course.[ 2 ]

Research workshops in Shiraz Medical School are held separately in the various aspects related to research and EBP, such as academic writing, study design, method of literature review, etc., in 1-day various workshops in the morning and evening all year round. The RSE questionnaire was used to measure RSE. Phillips and Russell designed the RSE questionnaire for the first time in 1994. Its validity and reliability have been checked in a previous study.[ 4 ] Roshanian and Aqazadeh translated it into Persian in 2012.[ 5 ] The validity of the questionnaire was 0.96. The overall Cronbach's alpha of different sub-domains was more than 0.80. The questionnaire consisted of 33 questions and four subscales, including practical research skills (eight questions), research design skills (eight questions), computer and quantitative skills (eight questions), and writing skills (nine questions). Each question is assigned a score of zero to nine. Zero indicates a lack of belief in the ability, and a score of nine shows sufficient confidence in the capacity to perform a specific research-related task. The range of possible scores varies from 0 to 297. Internal consistency and reliability are 0.96 and 0.94.[ 6 ] The subscales' reliability, including research design skills (0.776), practical research skills (0.688), computer and quantitative skills (0.813), and writing skills (0.891) confirmed, respectively, using Cronbach's alpha.[ 4 , 5 ] The EBP questionnaire was used to measure EBP. This questuinnare was first designed and used by Rubin and Parrish in 2010 to evaluate the level of EBP quantitatively. It assesses students' knowledge, attitude, and intention to implement EBP.[ 7 ] It was translated into Persian by Ashktorab et al . Experts confirmed the face validity of the EPB questionnaire, content validity, and the Scale-Content Validity Index in Persian was 0.98. The overall Cronbach's alpha was more significant than 0.80.[ 11 ] The questionnaire contains ten questions. It was measured using a 5-point Likert scale ranging from one (completely disagree) to five (completely agree). The scores range from10 from 50. The higher scores indicate higher EBP acceptance. Scores 10-16 mean low acceptance of the EBP, 17-33 signify intermediate acceptance, and scores above 33 reflect a high level of EBP acceptance.[ 7 , 11 ] The gathered data were analyzed through SPSS (PASW Statistics for Windows, Version 21.0, Chicago: SPSS Inc., USA) at α = 0.05 using descriptive statistics, t -test, Chi-square, and multiple linear regressions. We used multiple linear regressions to estimate the relationship between the RSE, EBP scores, and the demographic and research variables.

Ethical considerations

The goals of the investigation were explained to the students who participated in the study. Investigator assured the students that all their information would be maintained confidential, and all students signed the informed consent form. The Ethics Committee of SUMS approved the study under the code IR.sums.med.rec. 1400.169.

Five hundred and forty-eight individuals participated in the study. The participants' age average (standard deviation [SD]) was 26.6 (1.77), with a range of 19-38 years. Other demographic data and research-related data are summarized in Table 1 .

Demographic and research-related characteristics

Extern=5 th year medical student, Intern=6 th or last year medical students. SD=Standard deviation, GPA=Grade point average, MPH=Master of Public Health, MD=Medicine

The mean score (SD) of RSE was 171.10 (55.71). The higher RSE scores were detected in individuals who took part in the research workshops or research projects. Moreover, these groups obtained higher scores in the RSE domains. In addition, individuals who took part in the MPH program received significantly higher scores regarding RSE and all its domains (all P < 0.05), as shown in Table 2 .

Comparison of research self-efficacy score by variables

Extern=5 th year medical student, Intern=6 th or last year medical students. SD=Standard deviation

The overall score of RSE and all its domains was greater in men (181.49 ± 55.98) than women (161.72 ± 54.27) ( P < 0.05).

The mean score (SD) of EBP was 36.99 (4.33). Cross-tabulation analysis of intermediate and high acceptance of EBP score and demographic and research-related variables are summarized in Table 3 . Group data of low acceptance of the EBP were statistically unavailable as no one scored ≤16.

Cross-tabulation analysis of evidence based practice score and demographic and research related variables

EBP=Evidence based practice, MPH=Master of Public Health, MD=Medicine

The multiple linear regression tests were calculated to predict the RSE and EBP based on the participants' characteristics. There was a positive correlation between EBP and RSE score (0.343). The significance of all variables showed that the outcome of RSE is approximately eight times in women, 33 times in students who membership of a research project, 12 times in students who participated in the research training workshops, and 50 times in MD/MPH students. Moreover EBP is approximately two times in students who membership in a research project, 0.65 times in students who participated in the research training workshops, and 1.8 times in MD/MPH students. No significant difference was detected in the RSE and EBP scores of the students in the different clinical stages. GPA showed a positive correlation with EBP in the bivariate analysis ( p < 0.05), but not in the multiple linear regression [ Table 4 ].

Multiple linear regression. The predicting factors regarding research self-efficacy and evidence-based practice were assessed

a Based=Female, b Based=Yes, c Based=Yes 3 , d Based=Yes 4 . RSE=Research self-efficacy, EBP=Evidence-based practice, SE=Standard error, CI=Confidence interval, GPA=Grade point average, MPH=Master of Public Health, MD=Medicine

In the present study, there is a direct correlation between RSE and EBP. It means that medical students who are more confident in their research-related abilities claim to use more EBP in the hospital environment. They find it easier to catch the up-to-date evidence. This correlation may bridge the present gap between scientific research results and practice in future physicians. As in previous studies, this positive relationship has been expressed to some extent.[ 8 , 16 , 17 , 18 ]

Students who participated in a research project, workshop, or MPH program obtained a higher score in EBP and RSE. EBP is a teachable and learnable skill, and holding training courses promotes its acceptance, similar to any other part of medicine that can be improved by teaching.[ 13 , 19 , 20 , 21 , 22 , 23 ] It has been observed that active learning approaches improve students' attitudes and communication abilities. All of these can be associated with self-efficacy.[ 24 , 25 , 26 ] It is essential for the physicians to have the ability to conducting their personal research or appraising others' researches. It can help them to properly introduce scientific advances into clinical use and practices that are more evidence-based.

The statistical analysis revealed that the mean score of RSE was 171.10 in students of Shiraz Medical School which was lower than that in the other studies.[ 5 , 14 , 27 ] It was less than the average score obtained from assessing RSE in students of Phillips and Russell in America, which was reported as the RSE score in counseling psychology postgraduate students (190).[ 4 ] The differences observed in the RSE score can be due to differences in the students' field of study. Those studies were conducted on the postgraduate students of nursing school and the postgraduate students of psychology and Educational Sciences.[ 5 , 11 ] Through reviewing the medical school curriculum, we hypothesized that medical students may have limited free time due to several clinical tasks.[ 28 ] This may explain some of the differences, but comparative studies are needed to find the root cause.

Our analysis showed the student's highest mean RSE score in the subscales in writing skills. The lowest score was obtained in the quantitative and computer skills (based on the number of questions). These results are similar to other reports; the mean score in quantitative and computer skills was lower than other subscales.[ 4 , 5 , 14 ] When we review the questions of this subscale, contents such as selecting the appropriate statistical test and determining sample size, maintaining the research project documents, collecting data, defending the proposal, obtaining the necessary permissions, and attracting financial support had got lower scores. They require more attention for better training. Our study showed a statistically significant relationship between participation in research training workshops, being members of a research project, or participating in the MPH program and higher RSE subscales scores. These courses can improve the ability of the Trainees' self-efficacy in different domains of research. The results are in the same line with the prior study.[ 1 ] Short-term research training workshops helped increase the participants' self-efficacy for research, especially in methodology and communication skills.[ 12 , 29 , 30 ]

In this study, there was a high level of EBP acceptance among medical students. These results contrast the data obtained from previous studies that demonstrated a low level of awareness and use of EBP among physicians.[ 31 , 32 ] However, the studies on medical students showed increased EBP awareness and critical appraisal ability of articles after participating in the evidence-based training workshop.[ 8 , 13 , 14 , 15 ] The observed difference can be sufficient to hold various EBP training workshops and MPH courses for students. Having these multiple courses play a significant role in promoting EBP acceptance and awareness.[ 33 , 34 , 35 ]

There was a positive relationship between GPA and RSE. These findings are similar to those of previous studies.[ 14 , 36 , 37 ] One of the leading indicators of academic performance is GPA. Previous studies have shown that the higher the self-efficacy is positively associated with the higher the academic performance. Students who believe in their more remarkable ability have better academic performance.[ 38 , 39 ]

We showed that the male gender had higher RSE scores than the females despite the higher number of female participants. On the other hand, Bierer et al . revealed no sex difference in their study.[ 40 ] Other studies also did not show any significant difference in RSE scores according to gender.[ 4 , 14 , 41 , 42 ] This difference may be related to different university environments since men have more learning and support opportunities than women in some academic settings.[ 43 ] As with some previous researches, there was no gender difference in EBP.[ 44 , 45 ]

One of the strengths of this study is researching clinical medical students, especially final-year medical interns, in the large and significant sample size. The medical students' level of RSE and evidence-based performance abilities could play an important role, as they are a starting point for visiting and treating patients.

Limitation and recommendation

Among the primary limitations of this study, we can mention the lack of data to examine EBP and RSE barriers. Since the RSE and EBP are self-rated and subjective variables, they may be indented with other personality factors. It is recommended to designed longitudinal and cohort studies on medical graduates to find out the long-term effect of higher RSE and EBP at the time of graduation on clinical performance in the future. It is also suggested that research workshops be included as part of the medical training curriculum and their effects on the student's attitude and practice are evaluated from time to time.

Students who participated in a research project, workshop, or MPH program got a higher score in RSE and EBP. The overall score of RSE and all its domains was greater in men than women. Due to the positive correlation between RSE and EBP, we conclude that trained physicians who can research independently and use research evidence can find the best treatment approach for patients. These findings support the importance of integrating research education in the medical curriculum to increase RSE and improve EBP among medical students.

Financial support and sponsorship

This research was supported financially by Shiraz University of Medical Sciences.

Conflicts of interest

There are no conflicts of interest.

Acknowledgment and ethical moral code

This study was extracted from a MPH thesis written by Zahra Zia. The Ethics Committee of SUMS approved the study under the code IR.sums.med.rec. 1400.169. We would like to thank the students and professors who helped us in this research.

ORIGINAL RESEARCH article

Self-efficacy, satisfaction, and academic achievement: the mediator role of students' expectancy-value beliefs.

• 1 Developmental and Educational Psychology, Jaume I University, Castellón, Spain
• 2 Developmental and Educational Psychology, University of Valencia, Valencia, Spain

Although there is considerable evidence to support the direct effects of self-efficacy beliefs on academic achievement, very few studies have explored the motivational mechanism that mediates the self-efficacy–achievement relationship, and they are necessary to understand how and why self-efficacy affects students' academic achievement. Based on a socio-cognitive perspective of motivation, this study examines the relationships among academic self-efficacy, students' expectancy-value beliefs, teaching process satisfaction, and academic achievement. Its main aim is to identify some motivational-underlying processes through which students' academic self-efficacy affects student achievement and satisfaction. Student achievement and satisfaction are two of the most important learning outcomes, and are considered key indicators of education quality. The sample comprises 797 Spanish secondary education students from 36 educational settings and three schools. The scales that referred to self-efficacy and expectancy-value beliefs were administered at the beginning of the course, while student satisfaction and achievement were measured at the end of the course. The data analysis was conducted by structural equation modeling (SEM). The results revealed that students' expectancy-value beliefs (Subject value, Process expectancy, Achievement expectancy, Cost expectancy) played a mediator role between academic self-efficacy and the achievement/satisfaction relationship. These results provided empirical evidence to better understand the mechanism that mediates self-efficacy–achievement and efficacy–course satisfaction relationships. The implications of these findings for teaching and learning in secondary education are discussed.

Introduction

Based on a socio-cognitive perspective of motivation, the main purpose of this study is to integrate self-efficacy and expectancy-value beliefs into predicting students' outcomes at secondary schools. This has barely been studied in previous research and sometimes with contradictory results.

Self-efficacy is a key personal variable of Bandura's Social Cognitive Theory (SCT) Bandura's (1986) , defined as “an individual's belief in his or her own ability to organize and implement action to produce the desired achievements and results” ( Bandura, 1997 , p. 3). Educational researchers have paid plenty of attention to this construct (see Michaelides, 2008 , for a review). Prior studies have provided strong evidence that self-efficacy is a positive predictor of performance outcomes in different subjects ( Schunk et al., 2008 ; Usher and Pajares, 2008 ). For instance, Usher and Pajares ( 2008 , p. 751) argued that self-efficacy “predicts students' academic achievement across academic areas and levels.” Despite there being considerable evidence to support the direct effects of self-efficacy beliefs on academic achievement, studies that have explored the motivational mechanism which mediates self-efficacy–achievement relationship are scarce, and are necessary to understand how and why self-efficacy affects students' academic achievement, and will allow instructional actions and programs to improve academic achievement to be designed. One of the most solid proposals that integrate these variables is the social cognitive Expectancy-Value Model (E-VM) of achievement motivation, created by Eccles and her colleagues ( Eccles et al., 1983 ; Wigfield and Eccles, 1992 , Usher and Pajares (2000) based on Atkinson's (1964) expectancy-value model. This complex model includes multiple connections and components that can be classified into three main blocks/categories of variables, arranged in the following sequential order: social world, cognitive processes, and motivational beliefs. All these blocks of variables act directly or indirectly as predictors of students' achievement behavior, persistence, and choice. Centered on motivational beliefs, this model assumes that; first, expectancies for success (achievement expectancy is considered a component of expectancy for success) and subjective task values are directly related to achievement, task choices and persistence; and second, expectancies and task value are assumed to be influenced by individuals' goals and self-schemata. Self-efficacy or personal beliefs of competence is/are considered a salient aspect of self-schemata. Another model that shares similarities with E-VM is the Educational Situation Quality Model ( Doménech, 2006 , 2011 , 2012 , 2013 ; Doménech-Betoret et al., 2014 ; MOCSE is the acronym in Spanish) because: (a) both models are rooted in the social cognitive perspective of motivation; (b) they emphasize the important role that expectancy-value variables play in predicting students outcomes; (c) self-beliefs constructs (e.g., self-efficacy, self-concept, self-esteem, self-confidence, etc.) are considered important antecedents of expectancy-value variables.

Based on the aforementioned theoretical frameworks, the purpose of this study is to test the validity of a structural model by integrating self-efficacy (adolescent students' self-belief) and expectancy and value constructs into predicting and explaining academic achievement and course satisfaction at secondary school. To examine how these motivational beliefs are related and affect such important students outcomes, they are important to not only design actions and programs to improve teacher effectiveness and students' academic results, but to also contribute to clarify the relationship between self-efficacy and expectancy-value variables in predicting students outcomes, whose results available to date are limited and sometimes contradictory ( Williams, 2010 ).

The term “outcomes” may refer to cognitive and emotional variables. Regarding cognitive variables, learning achievements are considered the most important. As regards emotional variables, satisfaction with a course is an important outcome since it influences students' decisions to continue with or drop out of a course ( Levy, 2007 ). Satisfaction is also an important requirement for successful learning ( Sinclaire, 2014 ). The majority of the considered students' outcomes have to do with cognitive variables such as academic achievement (e.g., grades, test scores, etc.) or learning strategies. In the current study we have decided to include, besides academic achievement, an emotional dependent variable that has been less studied by authors in this tradition, such as, course satisfaction. Academic achievement and course satisfaction are considered two complementary learning outcome as the two face of the same coin. Teachers are interested in knowing not only if their student's progress, but also if they are satisfied with the T–L process followed. Both constructs are important indicators of the quality of the teaching-learning (T–L) process. Therefore, we believe that it would be interesting to test if the selected motivational variables differed in predicting and explaining both academic achievement and students' course satisfaction.

Regarding the relationship between self-efficacy and student satisfaction, Pajares and Schunk (2001) stated that a strong sense of efficacy enhances human well-being; for instance, self-efficacy beliefs influence the amount of stress and anxiety that people experience as they engage in an activity ( Pajares and Miller, 1994 ), and probably when students engage in a course. Self-efficacy also predicts course satisfaction in traditional face-to face classrooms ( Bandura, 1997 ). Although there is empirical evidence to support the positive effects of self-efficacy beliefs on students' well-being and course satisfaction ( DeWitz and Walsh, 2002 ), the motivational mechanisms that mediate the self-efficacy–students satisfaction relationship is still a problem to be solved. Very few studies have centered on examining the mechanism that mediates the self-efficacy–students' course satisfaction relationship, and are necessary to understand how and why self-efficacy affects students' course satisfaction. These findings could provide important clues to promote student satisfaction. Student satisfaction is related to improved academic performance and the decision to take additional classes ( Booker and Rebman, 2005 ). Moreover, satisfaction at school is fundamental for the judgments that students make of their own general well-being ( Cummins and Tomyn, 2011 ).

Students' Expectancy-Value Beliefs

The Expectancy-value theory is grounded in the social cognitive perspective of motivation. Psychologists in this tradition argue that individuals' choice, persistence, and vigor expended in performance can be predicted and explained basically by expectations of achievement and the value attributed to a task; i.e., by their beliefs about how well they will do in the task and the extent to which they value the task ( Atkinson, 1957 ; Wigfield and Eccles, 1992 ; Wigfield, 1994 ). Apart from the components noted above, some theorists from this tradition have introduced a third construct related to the feelings experienced by students when they do a task ( Pintrich and De Groot, 1990 ). We name this third construct “process expectancy.” In the course/subject matter context, we understood process expectancy to be the positive feelings that students expect to experience in their interaction with their teacher during the course (How will I feel studying this subject?). Indeed experience tells us that no-one starts something that is not worthwhile or when expectations of success are very poor because completing the task in such circumstances is considered a waste of time. Finally, nobody starts a task if they do not expect be feel well during the performance process. Hence these beliefs are considered three important indicators of students' motivation ( Pintrich and De Groot, 1990 ), which specify some underlying motivational mechanisms that lead to the initiation and maintenance of action ( Pintrich and Schunk, 1996 ). Centered on a course-subject and based on the above arguments, we herein used three types of beliefs that can make adolescent students decide on striving to learn a subject or not: (a) the subject value (What value does this subject have for me?), (b) the achievement expectancy (Will I be able to pass this subject?), and (c) process expectancy (How will I feel studying this subject?).

The modern Expectancy-value theory ( Eccles and Wigfield, 2002 ; Eccles, 2009 ) distinguishes four task-value components: attainment value, intrinsic value, utility value and cost. For the present study, which centered on a course subject, we used extrinsic value (which encompasses utility, importance, and interestingness) and cost-benefit components to assess the subject matter value. Eccles and Wigfield (2002) identified cost as a critical component of value, which was conceptualized as a negative determinant in engaging a task due, for instance, to performance anxiety and fear of failure, and to the amount of effort needed to succeed ( Eccles and Wigfield, 2002 ). However, when we centered on a course, we understood that being involved in a specific subject depends not only on the time and effort invested, but also on the benefits (e.g., in terms of results, reinforcements, enjoyment, etc.) that students can obtain. In short, the subject value items employed in this work refer to: (a) the extrinsic subject value, i.e., the perceived utility, importance, and interestingness of the subject (What value does this subject have for me?); (b) the expected cost-benefit relationship to pass the subject (Will it be worth the time and effort that I will have to invest to pass the subject?).

Students' expectancy-value beliefs may have been generated before classes began, from previous experiences, or may arise on the first days of class when students meet the teacher and find out about the study syllabus, evaluation requirements, teacher methodology, etc. ( Doménech, 2006 , 2011 , 2012 , 2013 ). This means that these beliefs can be evaluated at the beginning of the course after some days/week of class.

The Mediator Role of Expectancy-Value Beliefs between Self-efficacy and the Achievement/Satisfaction Relationship

Regarding the relationship between self-efficacy and expectancy-value beliefs.

When students face a new academic task, they ask themselves “Can I perform this task?” (self-efficacy) and “Why should I do this task?” (task value). If their answer to the first question is “yes,” they proceed to the next question ( Keskin, 2014 ). This reasoning suggests that self-efficacy is considered a predictor of task value, and not vice versa. Previous studies have demonstrated not only a positive relationship between both constructs ( Bong, 2001 ; Seo and Taherbhai, 2009 ), but also that self-efficacy is a direct predictor of task value ( Kozanitis et al., 2007 ; Azar et al., 2010 ; Keskin, 2014 ).

Prior research has also revealed significant and substantial direct effects of students' self-efficacy on academic expectations ( Chemers et al., 2001 ; Lent et al., 2008 ). According to these authors, students with high self-efficacy have greater academic expectations and display better academic performance that with low self-efficacy. These findings are consistent with what Bandura's postulated Bandura's (1997) when he argued that self-efficacy is causally prior to outcome expectancy as the results that individuals anticipate depend mainly on their judgments of how well they would be able to perform in a given situation ( Bandura, 1997 ). Therefore, it is assumed that self-efficacy (defined as the perceived capability to perform a given behavior) causally influences expected outcomes of behavior, but not vice versa.

In short, as regards the relationship between self-efficacy and the expectancy-value variables, the above-described findings support the notion that competence beliefs may drive students' expectations and task/subject values in the school context. However, more studies are needed to understand the connections between students' self-beliefs (e.g., self-efficacy, self-concept, self-esteem, etc.) and expectancy-value variables.

Regarding the Relationship between Expectancy-Value Beliefs and Achievement

Prior research has provided empirical evidence which indicates that expectancies and task-values are related to academic choices and achievement in specific domains, such as mathematics ( Marsh and Yeung, 1997 ; Spinath et al., 2004 ) and language arts ( Spinath et al., 2004 ). Recent cross-sectional and longitudinal studies have found that expectancy beliefs strongly influence achievement, whereas subject value considerably impacts choice, effort and persistence ( Nagengast et al., 2011 ; Gasco and Villarroel, 2014 ; Guo et al., 2015 ).

Regarding the Relationship between Expectancy-Value Beliefs and Satisfaction

Less is known about how students' expectancy-value beliefs relate to emotional outcomes, such as student satisfaction. Despite the findings being limited, they seem to support that satisfaction is well explained by task value ( Artino, 2008 ; Diep et al., 2016 ) and by grade expectancies ( Svanum and Aigner, 2011 ). Nonetheless, most authors highlight the teacher role and teacher–student interaction ( Wu et al., 2010 ) in relation to instructional and emotional supports as the main responsible factors of students' course satisfaction. Accordingly, process expectations, specifically related to the feelings that student experience during their interaction with the teacher, may play the most salient role to explain students' satisfaction. However, the process expectation formed by students can be influenced, in turn, by self-efficacy beliefs. Students with strong self-efficacy beliefs visualize success scenarios, which provide supportive resources, and guidance for performance ( Bandura, 1993 ). As a result, these students tend to experience more satisfaction with the teaching process than the students with low self-efficacy.

Finally, taken all de variables simultaneously, structural models tested in previous studies, based on the expectancy-value theory, provide additional and important evidence to support the mediator role played by motivational expectancy-value variables in the relationship between students' self-beliefs (e.g., self-efficacy, self-concept, self-esteem, etc.) and students outcomes. For example, the study conducted by Doménech-Betoret et al. (2014) in the university context revealed that students' academic self-efficacy had a significant and direct effect on achievement expectations, enjoyable learning expectations and expected dedication (cost) and, in turn, achievement expectation had a significant and direct effect on avoidance strategies (students' outcomes). In addition, subject value had a significant and direct effect on avoidance strategies (students' outcomes). In a similar vein, the study conducted by Bong et al. (2012) in the school context found that the task value and test anxiety significantly mediated the relationships of self-efficacy to achievement.

Based on the aforementioned empirical evidence, it is plausible to assume that the motivators beliefs which derive from the Expectancy-value theory may mediate the relationship between self-efficacy and learning outcomes; e.g., academic achievement and student satisfaction.

Objectives and Hypotheses

According to the aforementioned rationale, the main aim of this study was to examine if the motivational beliefs derived from the Expectancy-value theory play a mediator role between academic self-efficacy and learning outcomes (achievement and satisfaction). At the same time, another aim was to identify some of the motivational processes through which students' academic self-efficacy affects student achievement and satisfaction (see Figure 1 ). Accordingly, we hypothesized that expectancy-value beliefs would have a direct effect on academic achievement and satisfaction, whereas academic self-efficacy would have an indirect effect on academic achievement and satisfaction through expectancy-value variables. In other words, we predicted that expectancy-value variables would play a mediator role between self-efficacy and achievement (H1), and between self-efficacy and satisfaction (H2). The hypothesized connections were addressed and tested by the Structural Equation Modeling (SEM) procedure with the EQS program ( Bentler, 2006 ). Self-efficacy and expectancy-value variables were all measured in the first academic term after some weeks of class, and student achievement and satisfaction were all measured in the third and last terms of the course. This study can provide new data to improve the motivational theories that integrate self-efficacy, expectancy, and value constructs in the educational setting context, focused on a subject matter as a unit of analysis. It may also help identify the motivational connections that mediate between academic self-efficacy and students' achievement/satisfaction. Important implications for educational practice may derive from these findings since they can provide valuable information to design instructional actions and programs that can improve student achievement and satisfaction. Student achievement and satisfaction are two of the most important learning outcomes, and are also considered key indicators of education quality.

Figure 1 . Grafical representation of the study. *Underlying Motivational Mechanisms (UMM) are partially operationalized by the following questions: What value does this subject have for me?, How much time and effort will I invest to pass the subject?, Will I be successful in this subject?, and How will I feel studying this subject?.

Materials and Methods

Participants and procedure.

The sample consisted of 797 Spanish secondary education students from 36 classes with different subjects, of whom 404 were male (50.7%) and 393 were female (49.3%), and they were aged between 12 and 17 years. Most of their teachers ( N = 23, 63.88%) also participated in the study, of whom 11 were males (average experience = 29 years) and 12 were females (average experience = 32 years). About 80% of the participating students were Spanish, while the parents of the rest had come from other counties (the majority from Romania, Ecuador, and Morocco) to Spain as emigrants some years ago. One private and two state secondary schools located in east Spain took part in this study, which was carried out at the first four levels of compulsory secondary education: 1st ESO (12–13 years old), 2nd ESO (13–14 years old), 3rd ESO (14–15 years old), and 4th ESO (16–17 years old; ESO is the Spanish acronym for Educación Secundaria Obligatoria—Compulsory Secondary Education). Table 1 displays sample distribution according to levels of education and centers. This study was approved by the Ethics Committee of the Regional Valencian Government, Spain. Consent for students to participate was required from students' parents or legal tutors. Confidentiality and personal data protection were guaranteed in accordance with current Spanish law.

Table 1 . Characteristics and sample distribution according to courses and centers.

The scales used to measure the variables considered herein have been reviewed and refined in previous studies ( Doménech, 2006 , 2012 , 2013 ; Doménech-Betoret et al., 2014 ). As most had been designed for university students, they had to be adapted to secondary education in order to use them herein. The scales that referred to self-efficacy and expectancy-value beliefs were administered at time 1 (halfway through the first term), and student satisfaction and achievement were measured at time 2 (halfway through the third term). See Table 2 for item examples.

Table 2 . Summary of the factor analysis, internal consistency and item example of the scales.

Students' General Academic Self-Efficacy Scale (25 Items, α = 0.86)

This scale is based on the original scales created by Bandura (1990) and by Pastorelli et al. (2001) . This scale was used to assess students' self-perception of how competent they were in the academic field. Students indicated their level of agreement within the 1 (very bad) to 4 (very good) range.

Expectancy-Value Scale (13 Items, α = 0.78)

This scale comprises 13 items and was designed to measure expectancy-value constructs at the beginning of the teaching-learning process. It was structured and designed according to the Motivational Theory proposed by Pintrich (1989) and Pintrich and De Groot (1990) . Students indicated their level of agreement on a 5-point Likert scale within the 1 (I am absolutely unconvinced) to 5 (I am absolutely convinced) range.

Satisfaction of the Teaching Process Scale (5 Items, α = 0.81)

The original scale was designed by Doménech (2011 , 2012) to assess university students' satisfaction with the teaching process followed in the classroom for a specific subject matter. The scale used herein was composed of five items and is a short version of the original teaching process scale adapted to secondary education. Students indicated their level of satisfaction with the teaching process, and opinions were viewed on a 4-point Likert scale within the 1 (unsatisfied) to 5 (very satisfy) range. Finally, student achievement was measured with the marks obtained by students for the first and second academic terms. The mark expected for the third term was also required. Achievement scores ranged from 1 (minimum) to 10 (maximum).

Statistical Analyses

The hypothesized connections were tested by the SEM procedure. The ML and ML robust method of estimation (if the assumption of multivariate normal distribution was violated), developed by Satorra and Bentler (1988 , 1994) , was used with the EQS program ( Bentler, 2006 ) to calculate the fit indices of the hypothesized models. Since the Chi-square test is sensitive to sample size, using relative fit indices like CFI, the NNFI, and RMSEA is highly recommended ( Bentler, 1990 ). Values below 0.05 for RMSEA indicate a good fit, whereas values up to 0.08 denote an unacceptable fit ( Browne and Cudeck, 1993 ). NNFI- and CFI-values above 0.90 ( Hoyle, 1995 ), or even 0.95 ( Hu and Bentler, 1999 ), were fixed as the cutting-off point.

Validity of the Measurement Model of Latent Variables

Hypothesized covariance structure models represent only approaches of reality because the obtained indices may be driven by the sample characteristics on which the model was tested ( Cudeck and Browne, 1983 ). One approach to mitigate this limitation is to employ the cross-validation strategy ( Byrne, 2012 ). To apply this strategy, the total sample ( N = 797) was randomly split into two equivalent subsamples (the calibration sample and the validation sample), following the recommendations of Cudeck and Browne (1983) . First, with subsample 1 ( n = 399), a separate explorative factor analysis (EFA), using the principal component method with varimax rotation, was conducted on all the scales to estimate their factorial structure. Second, by taking the factors extracted in the EFA as the observational variables, a separate confirmatory factor analysis (CFA) was performed with subsample 2 ( n = 398) to test the goodness of fit and stability of the measurement models of these scales. These two-handed factorial analyses (exploratory and confirmatory) approach provide strong evidence for the reliability of the factors used as latent variables, and improve the validity of the measurement model ( Cudeck and Browne, 1983 ). Finally, the total sample ( N = 797) was then used to examine the structural model; i.e., the relationships among the latent variables (see Table 2 for details). When data analyses were performed, the initial sample slightly reduced because 23 students did not complete the entire scales. Missing values were not calculated given the large number of participants.

Students' General Academic Self-Efficacy Scale (25 Items)

Exploratory Factor Analysis (Sample 1). Seven factors that corresponded to the seven academic skills included on the scale were extracted, which accounted for 62.17% of total variance. Cronbach's alpha values ranged between 0.82 (maximum) and 0.61 (minimum).

Confirmatory Factor Analysis (Sample 2). The fit indices values obtained using the ML (χ 2 = 573.459; p = 0.000, d.f . = 254; χ 2 / d.f . = 2.257; NFI = 0.831; NNFI = 0.878; CFI = 0.897; GFI = 0.892; AGFI = 0.861; RMSEA = 0.056) and ML Robust (Satorra-Bentler scaled χ 2 = 478.366; p = 0.000, d.f . = 254; χ 2 / d.f . = 1.883; NFI = 0.823; NNFI = 0.890; CFI = 0.907; IFI = 0.909; MFI = 0.754; RMSEA = 0.047) estimation methods indicated that the model fitted the data.

Expectancy-Value Scale (13 Items)

Exploratory Factor Analysis (Sample 1). Four factors, which corresponded to the four scale constructs, were extracted, and accounted for 77.06% of total variance. Cronbach's alpha values ranged between 0.90 (maximum) and 0.79 (minimum).

Confirmatory Factor Analysis (Sample 2). The fit indices values obtained using the ML (χ 2 = 136.238; p = 0.000, d.f . = 94; χ 2 / d.f . = 1.449; NFI = 0.963; NNFI = 0.985; CFI = 0.988; GFI = 0.960; AGFI = 0.942; RMSEA = 0.034) and ML Robust (Satorra-Bentler scaled χ 2 = 117.663; p = 0.000, d.f . = 94; χ 2 / d.f . = 1.251; NFI = 0.963; NNFI = 0.990; CFI = 0.992; IFI = 0.992; MFI = 0.971; RMSEA = 0.025) estimation methods indicated that the model fitted the data.

Satisfaction with the Teaching Process Scale (5 Items)

Exploratory Factor Analysis (Sample 1). One factor referred to satisfaction with the teaching process (α = 0.81), and was extracted and accounted for 56.05% of total variance. The confirmatory factorial analysis (Sample 2) was not applicable because only one factor was extracted.

Procedure for Testing Mediation

The structural equation analysis was carried out with the whole sample to firstly test the mediation role of the expectancy-value beliefs between the self-efficacy–achievement relationship, and secondly the mediation role of the expectancy-value beliefs between the self-efficacy–satisfaction relationship. The procedure followed to test the mediation effect of the expectancy-value beliefs between self-efficacy and achievement, and also between self-efficacy and satisfaction, was conducted in two steps: first by testing the significant direct effects of latent variable self-efficacy on latent variables achievement (M1A model) and satisfaction (M1S model); second by testing the mediated role of the latent variable expectancy-value beliefs on the self-efficacy–achievement relationship (M2A), and also on the efficacy–satisfaction relationship (M2S). In this case we considered the direct and indirect effects between self-efficacy and achievement/satisfaction simultaneously.

Testing the Mediation Effect of Expectancy-Value Beliefs between self-Efficacy and Achievement (H1)

The M1A model was first tested (direct effects) for the mediation role of the expectancy-value beliefs between self-efficacy and achievement. The fit indices values obtained by the ML method (χ 2 = 194.52; p = 0.0000, d.f . = 34; NNFI = 0.93; CFI = 0.95; GFI = 0.92; RMSEA = 0.078) and the ML Robust method of estimation (χ 2 = 173.19; p = 0.0000, d.f . = 34; NNFI = 0.93; CFI = 0.95; RMSEA = 0.073) indicated that the model satisfactorily fitted the data. According to the data, academic self-efficacy had a significant effect on achievement. So this prerequisite for mediation to exist was met ( Baron and Kenny, 1986 ).

Next the mediated model M2A was tested. The fit indices values obtained by the ML method (χ 2 = 329.77; p = 0.0000, d.f . = 74; NNFI = 0.92; CFI = 0.94; GFI = 0.94; RMSEA = 0.067) and the ML Robust method of estimation (χ 2 = 293.87; p = 0.0000, d.f . = 74; NNFI = 0.92; CFI = 0.94; RMSEA = 0.062) indicated that the model fitted the data well. According to the data, latent variable academic self-efficacy had a significant effect on expectancy-value beliefs, which, in turn, had a significant effect on achievement. On the contrary, the path between academic self-efficacy and achievement was not significant. See Figure 2 for details.

Figure 2 . M2A model (direct and indirect effects). Relationship among students' academic self-efficacy, expectancy-value beliefs, and achievement. The structural configuration and standardized coefficients of the model are displayed. *Significant ( p < 0.05), n.s., not significant.

Testing the Mediation Role of the Expectancy-Value Beliefs between the Self-Efficacy–Satisfaction Relationship (H2)

The M1S model was first tested (direct effects) for the mediation role of the expectancy-value beliefs between self-efficacy and satisfaction. The model was optimized when a covariance between two variable errors (E10–E12) from the self-efficacy latent variable was introduced, following the recommendations of the Wald and Lagrange test in the EQS program. Then the model was tested again. The fit indices values obtained by the ML method (χ 2 = 197.88; p = 0.0000, d.f . = 52; NNFI = 0.926; CFI = 0.942; GFI = 0.959; RMSEA = 0.060) and the ML Robust method of estimation (χ 2 = 163.57; p = 0.0000, d.f . = 52; NNFI = 0.931; CFI = 0.946; RMSEA = 0.053) indicated that the model fitted the data well. According to the data, Academic Self-Efficacy had a significant effect on teaching process satisfaction. So this prerequisite for mediation to exist was met ( Baron and Kenny, 1986 ).

Second the mediated model M2S was tested. The model was optimized when a covariance between two variable errors (E10–E12) from the self-efficacy latent variable was introduced, following the recommendations of the Wald and Lagrange test in the EQS program. Then the model was tested again. The fit indices values obtained by the ML method (χ 2 = 399.86; p = 0.0000, d.f . = 100; NNFI = 0.891; CFI = 0.909; GFI = 0.938; RMSEA = 0.062) and the ML Robust method of estimation (χ 2 = 343.17; p = 0.0000, d.f . = 100; NNFI = 0.894; CFI = 0.912; RMSEA = 0.056) indicated that the model fitted the data well. According to the data, the latent variable academic self-efficacy had a significant effect on expectancy-value beliefs which, in turn, had a significant effect on teaching satisfaction. On the contrary, the path between academic self-efficacy and teaching satisfaction was not significant. See Figure 3 for details.

Figure 3 . M2S model (direct and indirect effects). Relationship among students' academic self-efficacy, expectancy-value beliefs, and teaching process satisfaction. The structural configuration and standardized coefficients of the optimized model are displayed. *Significant ( p < 0.05), n.s., not significant.

The description and fit indices of the tested models are provided in Table 3 , which summarizes the structural equation analyses results.

Table 3 . Fit indices of the tested models ( N = 797).

Based on a socio-cognitive perspective of motivation, this study examines; first, the mediator role played by expectancy-value beliefs in the relationship between students' academic self-efficacy and student achievement; second, the mediator role played by expectancy-value beliefs in the relationship between students' academic self-efficacy and student satisfaction with the teaching process. Achievement and satisfaction were considered dependent variables in two separate models as indicators of teaching practice quality.

For the mediator role played by the expectancy-value beliefs in the relationship between students' academic self-efficacy and student achievement, and following the recommendation by Baron and Kenny (1986) for testing mediation, the prediction capacity of students' academic self-efficacy on student achievement was examined first by testing the M1A model; second the mediator role played by expectancy-value beliefs in the relationship between students' academic self-efficacy and student achievement was examined by testing the M2A model. According to the M1A model, the structural analyses indicated a direct, positive and significant effect of the latent variable academic self-efficacy on achievement. According to the M2A model, the obtained fit indices supported the hypothesized connections. This means that the expectancy-value beliefs mediated the relationship between students' academic self-efficacy and student achievement. These results indicated that students' academic self-efficacy affects student achievement, but only indirectly; i.e., by fulfilling the latent variable expectancy-value beliefs.

For the mediator role played by expectancy-value beliefs in the relationship between students' academic self-efficacy and student satisfaction with the teaching process, and following the recommendation by Baron and Kenny (1986) for testing mediation, the prediction capacity of students' academic self-efficacy on student satisfaction was examined first by testing the M1S model; second the mediator role played by expectancy-value beliefs in the relationship between students' academic self-efficacy and student satisfaction was examined by testing the M2S model.

In accordance with the M1S model, the structural analyses indicated a positive and significant direct effect of students' academic self-efficacy on the latent variable teaching process. According to the M2S model, the obtained fit indices supported the hypothesized connections. This means that the expectancy-value beliefs mediated the relationship between students' academic self-efficacy and student satisfaction. These results suggested that students' academic self-efficacy affects student satisfaction, but only indirectly; i.e., by fulfilling the latent variable expectancy-value beliefs.

Given the remarkable variance explained in both models (M2A and M2S), it can be stated that general academic self-efficacy has a strong effect on expectancy-value beliefs. These findings indicated that the level of activation and quality of students' expectancy-value beliefs during the first weeks of the teaching-learning process (after some weeks attending class) depended to a great extent on the evaluation that students made of their own academic skills/capabilities (self-beliefs); e.g., study techniques, planning study, team work skills, coping with new technologies, memorization capacity, oral and written communication, and coping with exam situations. In the light of the obtained results, academic self-efficacy can be considered an important internal source of motivation that is capable of activating students' motivation in the first stage of the behavioral process; i.e., academic self-efficacy contributes to a great extent to activate student students' motivation from the first weeks of the teaching-learning process undertaken with a specific subject. Therefore, it is important to take into account students' academic self-efficacy when they face a new educational setting. These findings are similar to others obtained in previous research. Thus, the study conducted by Doménech-Betoret et al. (2014) revealed the key role played by academic self-efficacy in explaining students' expectations (achievement expectations, enjoyable learning expectations, and expected dedication according to the subject value). In a similar vein, the structural model tested by Bong et al. (2012) revealed that self-beliefs (self-efficacy and self-concept) are good predictors of task value.

Expectancy-value beliefs had a direct positive and significant effect on student achievement/satisfaction. These findings suggested that expectancy-value beliefs (Achievement expectations, Value of the subject matter, Process expectations with the teacher, Expected cost to pass the subject), which were evaluated some weeks after the course began, would be capable of satisfactorily explaining and predicting student achievement and their degree of satisfaction with the teaching process followed with a specific subject matter. The observational variables with higher loadings (Achievement expectations, Value of the subject and Satisfaction expectations with the process) on the latent factor expectancy-value beliefs suggested that these motivational variables were the most important predictors of student achievement and satisfaction. These findings fall in line with previous studies that used the variables from the Expectation-value theory ( Guo et al., 2015 ). The structural model tested by these authors evidenced that Math self-concept (construct used to assess students' expectancy of success) and the Math utility value had a significant and direct effect on students' academic achievement and educational aspirations.

All these findings moved in the expected direction. Academic self-efficacy, considered a general domain variable ( Boekaerts, 1999 ), predicted and explained students' specific expectancy-value beliefs in connection with a specific educational setting. In turn, these specific expectancy-value beliefs predicted/explained students' outcomes (academic achievement and satisfaction). These results were coherent with what Bandura postulated when claiming that specific measures of beliefs were more closely related to behavior ( Bandura, 1997 ).

Based on the obtained results, the following conclusions can be drawn:

(a) Expectancy-value beliefs, understood as the anticipatory previsions and forecasts that students make in an attempt to anticipate their actions, emotions and results in a new educational situation, were well measured and operationalized by the four motivational selected factors that derived from the Expectancy-value theory: Value of the subject, achievement expectancy, satisfaction expectancy with the process, and the expected cost to pass the subject.

(b) Students' expectancy-value beliefs, generated/activated during the first weeks of the teaching-learning process, were well explained by the perception or idea that students form about their own basic academic skills. These findings also fall in line with previous studies ( Doménech-Betoret et al., 2014 ).

(c) Four motivational variables, which mediate the relationship between academic self-efficacy and students' achievement/satisfaction, were identified. These findings fall in line with previous studies, which examined the mediator role of motivational variables in the relationship between self-efficacy and achievement ( Bong et al., 2012 ).

(d) These findings shed light to better understand the relationship between self-efficacy and expectancy-value beliefs in predicting students' outcomes in secondary education.

(e) This study allows advances to be made in explaining students' emotional outcomes, such as course satisfaction, which has barely been studied in previous research in the expectancy-value theory context.

(f) Important educational implications can be derived from the socio-cognitive perspective of motivation acquired from the results obtained to improve students' achievement and satisfaction from a preventive point of view.

Educational Implications

Based on the results obtained in this study, the following educational implications can be made:

First, the expectancy-value beliefs generated during the first weeks of the course are capable of predicting student achievement and their satisfaction with the teaching process followed throughout the course. Therefore, we wish to stress the importance of making a diagnostic evaluation at the beginning of the course of secondary students' expectancy-value beliefs in order to: (a) detect possible shortcomings that students may present in relation to students' expectancy-value beliefs formed at the beginning of the course, after some days of class; (b) design an action plan to overcome or improve these shortcomings.

Second, the obtained results provide evidence that general academic self-efficacy is capable of explaining to a great extent the expectancy-value beliefs formed by secondary students about a specific subject some days after the course starts. Therefore teachers should also take it into account at the very beginning of the course. Accordingly, implementing actions and programs at schools is recommended to improve students' academic skills to, in turn, improve academic self-efficacy. These programs should include a variety of components that fall in line with the sources of self-efficacy beliefs proposed by Bandura (1997) in academic contexts. According to Bandura (1997) , self-efficacy beliefs are developed when individuals interpret information from four major sources, such as mastery experience, vicarious experience of observing others, social persuasions that students receive from others, and emotional and psychological states. In the school context, mastery experience refers to the way students interpret and evaluate obtained results, and self-beliefs of competence are revised and created according to these interpretations. Accordingly, teachers should provide instructional scenarios in which students are able to succeed in challenging tasks. Students' judgments of competence are also created by vicarious experience; i.e., by evaluating their capabilities in relation to other students' performance. Another source of self-efficacy is the social persuasions that students receive from others. Accordingly, a supportive message from parents and teachers is important to empower students' self-confidence. Finally, students' self-efficacy is created by their emotional and psychological states as students tend to interpret negative psychological states (stress, anxiety, bad mood, depression, etc.) as evidence for lack of skills, and positive psychological states as indicators of personal competence. Accordingly, promoting students well-being and reducing negative emotional states strengthen students' self-efficacy. For more details about sources of self-efficacy, see the review by Usher and Pajares (2008) . In short, the actions and programs that aim to develop students' self-efficacy should be based on these four sources.

We defend the notion of quality education based on a preventive view. Accordingly, we suggest secondary school teachers taking specific actions on the first days of the T–L process to improve adolescent students' beliefs as regards academic self-efficacy (self-beliefs), achievement expectancy, process expectancy and subject value.

(a) It is important for teachers to strive to transmit the idea that all the students in class are capable of passing the subject matter. This relates with students' psychological need of competence ( Deci and Ryan, 1985 , 2000 ).

(b) From the very beginning of the course, improve students' perception of their own capacity, specifically the general academic skills required to improve progress made at school; e.g., taking actions to bridge some basic gaps in training that some students may still have from former courses, and are necessary to make progress in the subject; or evaluate and recognize the progress made by students since the evaluative feedback that students receive contribute to develop their competence. This point relates with students' psychological need of competence ( Deci and Ryan, 1985 , 2000 ).

(c) Explain to students the value of the subject matter when presenting the subject matter syllabus, and also throughout the course. Inform students about the importance and usefulness of the subject matter (present or future) at the personal, academic and professional levels.

(d) From the very beginning of the course, promote and take care of the teacher–students interpersonal relationship; e.g., show closeness, respect, and empathy with students throughout the course. This relates with students' psychological need of relatedness ( Deci and Ryan, 1985 , 2000 ).

Limitations and Suggestions for Future Research

Although the results obtained herein are satisfactory, some limitations and suggestions for future research should be pointed out.

First, the results were obtained from schools located in a specific socio-cultural context. Thus, replicating this study in other educational and cultural contexts is recommended to generalize the findings.

Second, extending the tested model should be considered first by introducing other types of self-efficacy, such as metacognitive self-efficacy ( Moores et al., 2006 ) or emotion regulation self-efficacy ( Gross and John, 2003 ); second by including other motivational variables as mediators. Regarding the motivational process, Bandura (1986) distinguished three types of cognitive motivators: (a) causal attributions; (b) outcomes expectations; (c) goals, whose corresponding theories are Attribution theory, Expectancy-value theory, and Goal theory. Accordingly, including new variables as mediators in future research, such as, goal orientation ( Pintrich, 2000 ) or achievement goals, would be interesting ( Liem et al., 2008 ).

Third, although academic self-efficacy and expectancy-value beliefs were measured in the same data collection wave, we provide enough evidence and theoretical support to consider general academic self-efficacy as an antecedent of the students' expectancy-value belief generated in the classroom context.

Fourth, according to Wigfield and Cambria (2010) , most of the measures used by researchers to assess motivational beliefs are student self-report measures. However, self-report measures can be problematic, especially for young children or for students who state that school is not important to them. Consequently, we wish to emphasize the importance of combining quantitative and qualitative methods to reduce biases and to obtain more complete information about students' belief.

Ethics Statement

This study was carried out in accordance with the recommendations of the Ethics Committee of the Regional Government of Valencia, Spain, with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki.

Author Contributions

All authors made substantial contributions to design the work, analysis and interpretation of the data, drafting and revising the work, final approval of the version to be published, and finally agreement to be accountable for all aspects of the work in insuring that questions related to the accuracy or integrity of any aspects of the work were appropriately investigated and resolved (FD, LA, and AG).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: self-efficacy, expectancy-value theory, expectancy beliefs, value beliefs, academic achievement, student satisfaction

Citation: Doménech-Betoret F, Abellán-Roselló L and Gómez-Artiga A (2017) Self-Efficacy, Satisfaction, and Academic Achievement: The Mediator Role of Students' Expectancy-Value Beliefs. Front. Psychol . 8:1193. doi: 10.3389/fpsyg.2017.01193

Received: 01 May 2017; Accepted: 30 June 2017; Published: 18 July 2017.

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Copyright © 2017 Doménech-Betoret, Abellán-Roselló and Gómez-Artiga. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Fernando Doménech-Betoret, [email protected]

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