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• Published: 14 August 2024

Effectiveness of biofeedback on blood pressure in patients with hypertension: systematic review and meta-analysis

• Sian Jenkins   ORCID: orcid.org/0000-0003-1963-4495 1 , 2 ,
• Ainslea Cross 3 ,
• Hanad Osman   ORCID: orcid.org/0000-0001-7404-1276 1 , 2 ,
• Farah Salim 4 ,
• Dan Lane 4 ,
• Dennis Bernieh 4 ,
• Kamlesh Khunti 2 &
• Pankaj Gupta   ORCID: orcid.org/0000-0001-9481-6067 4 , 5  

Journal of Human Hypertension ( 2024 ) Cite this article

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• Hypertension

Hypertension is the leading modifiable risk factor for cardiovascular disease, but less than 50% have their blood pressure controlled. A possible avenue to support hypertension management is a holistic approach, using non-pharmacological interventions. Since hypertension is mediated in part by dysregulation of the autonomic nervous system (ANS), biofeedback may help improve hypertension management by targeted self-regulation and self-awareness of parameters that regulate the ANS. This systematic review aimed to assess the effectiveness of biofeedback on blood pressure in hypertensive patients. The review was pre-registered on PROSPERO and followed the PICO strategy. A total of 1782 articles were retrieved, 20 met the inclusion criteria. Sample sizes ranged from 15 to 301 participants; with a median age of 49.3 (43.3–55.0) years and 45% were female. There was a significant effect of biofeedback on systolic (−4.52, Z = 2.31, P  = 0.02, CI [−8.35, −0.69]) and diastolic blood pressure (−5.19, Z = 3.54, P  = 0.0004, CI [−8.07, −2.32]). Six different biofeedback modalities were used, with biofeedback delivered by psychologists, trained therapists and research assistants. There was no publication bias, heterogeneity was rated as substantial and data quality was rated to be poor. This review demonstrated that biofeedback had a significant effect on blood pressure. However, this should be viewed in the context of included studies being limited by heterogeneity and dated literature, meaning the research does not reflect the current biofeedback technology such as wearable devices. Future research should incorporate these technologies with robust methodology to fully understand the effect of biofeedback on hypertension.

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Introduction.

Hypertension is the leading modifiable risk factor for cardiovascular disease, stroke and premature death [ 1 ]. Globally, 1.2 billion people have hypertension, a figure that doubled between 1990 and 2019 [ 1 ]. Worldwide hypertension control remains poor with only 21% of men and 18% of women achieving blood pressure targets [ 1 ]. This is despite the availability of cheap and effective medications. Hence it would be useful to consider non-pharmacological therapies that, in conjunction with medications, may help improve blood pressure in a more holistic manner.

It is accepted that hypertension is in part due to a derangement in the regulation of the autonomic nervous system (ANS). The sympathetic nervous system leads to increase in heart rate and blood pressure, whereas the parasympathetic nervous system relaxes the body and decreases blood pressure [ 2 ]. Hypertension is also linked to impaired baroreceptor regulation with interrelationships between baroreflex sensitivity and autonomic dysfunction [ 3 ]. There is evidence that non-pharmacological treatments such as lifestyle interventions and weight loss have a positive impact on the ANS [ 2 ]. Therefore, improved regulation in the ANS, especially an increase in parasympathetic activity, can improve blood pressure and biofeedback may help to achieve this [ 4 ].

Biofeedback improves ANS control as it promotes self-regulation, induces a ‘relaxation response’ and reduces cognitive avoidance (i.e., avoiding thoughts of undesirable situations through distraction, thought suppression or worry [ 5 ]) through increasing awareness of physiological processes [ 6 ]. Biofeedback uses instruments to measure physiological responses such as heart rate variability, sharing this with the user in real time with the aim to increase awareness and health [ 7 ]. Biofeedback is often paired with interventions that address behaviour, emotion and thoughts, which can benefit physiological processes [ 7 ]. Frank et al. [ 8 ] described biofeedback as “training not treatment” highlighting the level of motivation and practice required by the user to achieve the benefits of biofeedback. Ultimately, the goal is that these learned processes become automatic and individuals do not require device feedback to achieve the desired outcomes.

Over the years, the field of biofeedback has progressed with advances in technology. Available devices are user friendly and wearable [ 9 , 10 , 11 , 12 ], making biofeedback a more accessible intervention. Additionally, using a wearable device gives insight into an individual’s physiology and response to stress and daily life on a continuous basis. This is more representative than data provided by a static clinic blood pressure measurement. With the improvement of technology, accessibility to biofeedback and progressions in artificial intelligence (AI), it is important to understand the existing literature and how we can progress knowledge and implementation of biofeedback to improve health and wellbeing. This review aimed to assess the effectiveness of biofeedback in patients with hypertension. The main outcome assessed was a change in blood pressure.

Eligibility criteria

This review was pre-registered on PROSPERO (ID: CRD42021285875) and follows PRISMA 2020 reporting guidelines [ 13 ]. Inclusion criteria were as follows: assessment of biofeedback (all modalities e.g., neurological, cardiovascular, physical) on systolic and/or diastolic blood pressure, randomised control trial, published in English, adult participants aged 18 and over, with a diagnosis of hypertension (office reading of systolic blood pressure (SBP) ≥ 140 and/or diastolic blood pressure (DBP) ≥ 90 mmHg or home blood pressure readings of SBP ≥ 135 and/or DBP ≥ 85 mmHg) [ 14 ]. There was no specification for patients to be on specific types of hypertension treatment. Systematic reviews, editorial letters and conference abstracts were excluded.

Study selection

The following electronic bibliographic databases were searched: PubMed, MEDLINE, PsycINFO, Embase, CINAHL and Cochrane Central Register of Trials. There was no date limit and all sources were last searched on January 16th, 2024. The search strategy followed the PICO criteria and was adjusted according to each database. The MEDLINE search strategy can be viewed in the Supplementary Material. Mendeley Desktop Reference Manager was used to store retrieved results and remove duplicates. Abstracts were reviewed in the first stage screening, which was completed by one review (S.J.), with a random 10% of abstracts screened by a second reviewer (A.C.). Disagreements were resolved after discussion between the two reviewers. The second stage screening reviewed the full text of articles and was completed by one reviewer (S.J.).

Data extraction

Extracted data was retrieved and collated into an Excel spreadsheet by one reviewer (S.J.). Outcomes retrieved included participant characteristics, intervention design, study design, pre/post intervention measurements and conclusions. Please see the Supplementary Material for the list of outcomes and variables retrieved. The effect measure for all main outcomes was mean (±standard deviation).

Synthesis methods

Studies were included in the meta-analysis if the mean and standard deviation was reported for a change in SBP and/or DBP. If reported, raw data and standard errors were converted to standard deviations and included. Authors were emailed for missing data and if there was no response, papers were excluded from the meta-analysis and assessed narratively.

The meta-analysis and forest plot diagrams were completed in Review Manager (version 5.4). A random effects model was used to assess systolic and diastolic blood pressure. Publication bias and Egger’s test was conducted in RStudio (version 2023.12.0 + 369).

A meta-regression was conducted on age and sex to explore possible causes of heterogeneity. However, there was insufficient data to conduct a reliable meta-regression for biofeedback modality. The meta-regression was a mixed effects model conducted in RStudio (version 2023.12.0 + 369).

Data quality assessment

Papers were assessed for bias with the Cochrane Risk of Bias assessment [ 15 ], assessing for selection, reporting, performance, detection, attrition, and other sources of bias. The Risk of Bias 2 Tool [ 16 ] was used to input assessment, calculate summary data and figures, and to check inter-rater agreement.

The overall quality of evidence from reviewed studies was assessed with the GRADE assessment [ 17 ], which reviewed individual study limitations, inconsistency of results, indirectness of evidence, imprecision, and publication bias. The quality of evidence was rated from high to very low.

Figure  1 details the PRISMA flowchart. The search generated 1782 articles, with 244 potentially eligible articles identified during the title and abstract screening. The full text screen identified 20 articles that met the inclusion criteria for the review. Of these articles, 18 were from peer-reviewed journals and two were PhD theses. The main reasons for exclusion were study design not meeting the inclusion criteria (31%), articles not in English (18%), or outcomes outside of the inclusion criteria (14%).

Flowchart in line with PRISMA guidelines indicating the number of articles originally identified, screened, excluded and included within the systematic review.

Participant characteristics

The overall characteristics of the 20 included studies are summarised in Table  1 . The mean demographics are reported in Table  2 . The studies were published between 1975 and 2013, from 10 different countries. There was a total of 988 participants and sample sizes ranged from 15 to 301 participants. The age ranged from 28 to 70 years, with 45% female participants. Ethnicity was reported in 3 articles, of these, 96% were Caucasian. The mean baseline SBP was 149.3 ± 7.8 mmHg and the mean DBP 93.0 ± 6.9 mmHg. Five studies [ 18 , 19 , 20 , 21 , 22 ] did not report data such as sex or age and were omitted from the above summary but were included in the main analysis as they reported key outcomes.

Types of biofeedback modalities

There were six different biofeedback modalities used across the 20 studies (Table  3 ). The type of biofeedback device used varied across studies and modalities, including finger or forehead electrodes [ 22 , 23 , 24 , 25 ], sphygmomanometer [ 18 , 26 , 27 ], finger blood pressure machines [ 28 , 29 ] and compact disk (CD) players [ 30 , 31 ]. No studies used a wearable device.

Blood pressure biofeedback was used by six studies and was measured with either a non-invasive beat to beat finger arterial pressure measurement [ 29 ] or an automated blood pressure device [ 18 , 20 , 26 , 27 , 32 ]. Blood pressure biofeedback was typically received by the participant visually (e.g., a screen) [ 18 , 26 , 28 , 29 , 32 ] and/or auditorily (e.g., a beep) [ 22 , 23 ]. For example, participants in the study by Tsai et al. [ 29 ] performed self-regulation techniques, such as deep breathing, and observed their blood pressure on a display.

Electromyographic (EMG) biofeedback detects changes or contractions in muscle. All six studies using EMG biofeedback gave auditory feedback, with some using the tone pitch and frequency to indicate EMG changes [ 19 , 20 , 22 , 24 , 33 ].

Galvanic skin response (GSR) biofeedback focuses on sweat gland activity and was used by five studies. As an example: Patel et al. [ 25 ] delivered the GSR feedback tone in one headphone and played a relaxation tape through the other headphone. The tone grew fainter as the participant relaxed and GSR activity reduced.

Thermal biofeedback was used in four studies. The intervention by Blanchard et al. [ 34 ] aimed to teach participants to increase temperature of their hands or feet, therefore strengthening deep-muscle relaxation.

RESPeRATE, a branded auditory based biofeedback device, was used in two studies [ 30 , 31 ]. It involves listening and breathing in time with a melody to guide slow breathing [ 30 ].

Achmon et al. [ 35 ] was the only study to use heart rate biofeedback. It used ear lobe capillary pulsations to guide heart rate reductions in normal and tension-provoking situations.

Intervention characteristics

Table  3 details the biofeedback intervention characteristics of the included studies. Biofeedback was mostly delivered one-to-one, with four studies delivering biofeedback to groups of 3–13 participants [ 19 , 28 , 33 , 34 ]. Studies varied in the biofeedback session length (12–75 min) and number of sessions (4–48 sessions). The post-study follow up ranged from 2 weeks to 12 months, with ten studies not reporting any follow up. Biofeedback training was delivered by psychologists in four studies [ 27 , 34 , 36 , 37 ] and by a trained nurse or therapist in two studies [ 32 , 35 ]. Three studies used an experimenter or research assistant to deliver biofeedback [ 18 , 20 , 24 ], with the remaining eleven not detailing who delivered biofeedback training.

There were eight different control conditions used across studies, the most common were self-recorded blood pressure measurements and placebo. Six studies [ 22 , 24 , 26 , 34 , 35 , 38 ] had multiple comparison groups (i.e., biofeedback and treatment as usual, placebo biofeedback, normotensive comparators). For data extraction, the treatment as usual group was prioritised as a comparator, followed by placebo biofeedback.

There was large variation across intervention design making it difficult to compare different designs and understand the most effective biofeedback intervention.

In terms of measuring how intervention delivery corresponded to the protocol, only two studies [ 29 , 34 ] detailed methods that suggested fidelity checks, including a therapist remaining with the group throughout the intervention and a trained nurse implementing biofeedback under supervision of a qualified biofeedback practitioner. Only five studies [ 18 , 25 , 28 , 31 , 36 ] reported the use of power calculations to inform the sample size.

The methods used for blood pressure measurements varied across studies; seventeen [ 18 , 19 , 20 , 22 , 23 , 24 , 25 , 27 , 28 , 29 , 30 , 31 , 33 , 35 , 36 , 37 , 38 ] used clinic readings, and three [ 26 , 32 , 34 ] used home measurements. In the ten studies [ 19 , 20 , 23 , 24 , 27 , 30 , 31 , 32 , 35 , 36 ] reporting medication use, 55% of participants were on anti-hypertensive medications. Medication status was not reported in three studies [ 25 , 33 , 37 ], whilst seven [ 18 , 22 , 26 , 28 , 29 , 34 , 38 ] studies reported participants were not taking any medications.

A total of seventeen studies detailed information regarding participant withdrawal or exclusion, with the remaining three studies [ 22 , 26 , 38 ] not reporting if any participants withdrew from the study. Overall, 111 participants withdrew, 44 were excluded and 2 participants died during the study time period. Reasons or details of participant withdrawal was limited, with 4 studies [ 19 , 27 , 33 , 36 ] detailing if participants withdrew from the control or biofeedback group, and six studies detailing the specific stage participants withdrew at i.e., before or after baseline measurements [ 27 , 37 ], after randomisation [ 30 , 33 , 35 ] or “within 2 weeks” [ 32 ]. Nine studies [ 18 , 19 , 20 , 23 , 24 , 28 , 29 , 34 , 36 ] did not detail at what stage participants withdrew. Reasons for participant exclusion included overly high blood pressure [ 28 , 34 ], medication changes [ 23 , 36 ], hypertrophy [ 18 ], failure in randomisation [ 25 ] and Olsson et al. [ 37 ] reported issues with biofeedback installation, commuting for the study and blood pressure not meeting hypertension criteria.

Meta-analysis of suitable studies

A meta-analysis was conducted for SBP with twelve studies and DBP with eleven studies, since the remainder did not have adequate data as detailed in the methods section. The studies included in the meta-analysis had six different control conditions (please see Table  3 ).

The meta-analysis showed that biofeedback had a significant effect on SBP −4.52 (Z = 2.31, P  = 0.02, CI [−8.35, −0.69]) and a significant effect on DBP −5.19 (Z = 3.54, P  = 0.0004, CI [−8.07, −2.32] (Fig.  2 ). The forest plot shows heterogeneity was high for SBP I 2  = 75% (Tau 2  = 27.80; Chi 2  = 43.15; P  < 0.0001). The DBP forest plot can be seen in Fig.  3 , also highlighting the high heterogeneity I 2  = 76% (Tau 2  = 15.46; Chi 2  = 41.46; P  < 0.00001).

The forest plot demonstrates a significant effect of biofeedback on systolic blood pressure.

The forest plot demonstrates a significant effect of biofeedback on diastolic blood pressure.

Notably, Nakao et al. [ 32 ] and Achmon et al. [ 35 ] had substantial mean differences between the biofeedback and control group, with a mean difference in SBP of −23.00 mmHg in Nakao et al. [ 32 ] and −23.93 mmHg in Achmon et al. [ 35 ] studies. Within the papers there were limited reasons for the large decreases. Despite the large mean difference, neither paper was given a heavier weighting within the forest plot compared to other studies, with Nakao et al. [ 32 ] allocated 5.6% and 9.4% and Achmon et al. [ 35 ] allocated 6.7% and 10.0% for systolic and diastolic blood pressure respectively.

Additionally, it is noticeable that Pandic et al. [ 30 ] had a SBP mean difference of 7.68 mmHg in favour of the control group. The control group had a larger reduction in blood pressure compared to the RESPeRATE intervention group. The authors reflected on previous literature that showed relaxing music played to the control group can decrease blood pressure. Publication bias was assessed with Egger’s test and was non-significant for both SBP (−0.34, 95% CI [−2.22–1.54], P  = 0.73) and DBP (−1.1, 95% CI [−3–0.75], P  = 0.27). Corresponding funnel plots can be found in the Supplementary Material (Supplementary Figs.  S1 and S2 ).

Of the eight studies excluded from the meta-analysis, only two showed significant findings in favour of biofeedback [ 19 , 33 ] (Supplementary Tables  S1 and S2 ). Across the 20 included studies, the pooled blood pressure difference in biofeedback groups was −9.5 mmHg SBP and −6.7 mmHg DBP, compared to −3.4 mmHg SBP and −1.9 mmHg DBP in control groups (Supplementary Table  S3 ).

Meta-regression

A meta-regression was conducted for age and sex on systolic and diastolic blood pressure. There was no significant association between participant age and effect of biofeedback on systolic (β = 0.49, SE = 0.40, 95% CI [−0.29, 1.26], p  < 0.22) or diastolic (β = 0.44, SE = 0.26, 95% CI [−0.07, 0.96], p  < 0.09) blood pressure (Supplementary Figs.  S3 and S4 ).

There was no significant effect of sex on biofeedback outcomes, with no effect of participants being male on systolic (β = 0.00, SE = 0.05, 95% CI [-0.10, 0.11], p  < 0.97) or diastolic (β = 0.01, SE = 0.04, 95% CI [−0.06, 0.07], p  < 0.87) blood pressure, or being female on systolic (β = 0.01, SE = 0.07, 95% CI [−0.12, 0.15], p  < 0.87) or diastolic (β = 0.01, SE = 0.05, 95% CI [−0.08, 0.10], p  < 0.80) blood pressure (Supplementary Figs.  S5 – 8 ).

Quality assessments

The Cochrane risk of bias assessment identified there were “some concerns” (Supplementary Table  S4 ). This was affected by 65% of papers not specifying randomisation allocation sequences or blinding of researchers or participants. All papers were raised to “some concerns” due to lack of pre-specified analysis plans.

The GRADE assessment showed data to have a “low certainty” of evidence, meaning further research is likely to change the estimate and have an important impact on confidence in the effect estimate. The certainty was downgraded from “high” to “low” due to inconsistency in evidence identified by heterogeneity and the risk of bias score. See Supplementary Material (Supplementary Table  S5 ) for assessment ratings.

This was the first systematic review since 2009 to assess the effect of biofeedback in patients with hypertension (≥140/90 mmHg). The review and meta-analysis demonstrated that biofeedback significantly improved SBP and DBP. However, these results should be interpreted with caution given the limitations of included studies, such as heterogeneity, low study quality and limited details regarding randomisation, blinding and intervention delivery. The meta-regression analyses demonstrated that participant age or sex did not account for the heterogeneity seen within the meta-analysis.

The heterogeneity across biofeedback rendered it difficult to conduct modality specific analysis. Follow up ranged from 2 weeks to 12 months, with 10 studies not reporting if a follow up was conducted. Given the requirement of continued practice to benefit from biofeedback it is important to understand the longevity of the intervention [ 8 ].

Studies included in this review reporting using different instructors to deliver biofeedback to participants, including a psychologist, a trained therapist or nurse, a research assistant or experimenter. Eleven studies did not detail who delivered biofeedback. Although this review was unable to statistically compare delivery personnel and biofeedback outcomes, both studies which used nurse delivered biofeedback demonstrated a significant effect on blood pressure [ 32 , 35 ]. For biofeedback to be a feasible and affordable intervention, the method and personnel delivering the intervention need to be considered. For services such as the NHS in the United Kingdom, it may benefit from biofeedback that is formulated to be delivered by a healthcare assistant or another allied health professional as this would be cheaper and scalable. More innovative solutions for delivery of biofeedback such as the use apps or videos need to be considered.

The results of this review are partly supported by the meta-analysis from Vital et al. [ 39 ] who included nine studies and found a significant reduction in DBP only. The current review differed from Vital et al. [ 39 ] as they included pre-hypertensive patients (SBP measuring 130–139 mmHg). The current review only included patients with SBP ≥ 140/90 mmHg because inclusion of patients with low-mild hypertension can lead to floor effects, with only small reductions possible [ 40 ]. An earlier review by Greenhalgh et al. [ 40 ] found no consistent evidence that demonstrated the benefits of biofeedback. However, they included thirty-six studies, some of which were excluded from the current systematic review based on low blood pressure readings (<140/90 mmHg), and missing or unclear outcomes. The inclusion of more studies, some of which did not meet the criteria for this review, may explain the higher heterogeneity and lack of consistent evidence in comparison to the present review.

This review is limited by heterogeneity and the number of studies included. This made it difficult to identify the most effective intervention design including, number of sessions, intervention length, and biofeedback modality. Despite the meta-analysis demonstrating a significant effect of biofeedback on SBP and DBP, the quality of data was low, especially relating to limited details on randomisation, blinding, missing pre-analysis statistical plans, and whether patients were on antihypertensive medications. The missing details regarding randomisation, blinding and key demographic data is a limitation that if submitted for publication in the current day, papers would not meet research guidelines. Limited details reported about interventions meant it was difficult to understand why some interventions worked, whilst others did not. Additionally, the lack of details regarding at what stage participants withdrew from the study make it difficult to understand if withdrawal was due to the requirements of biofeedback, or for another reason. Similarly, the wide variation in control conditions add difficulty to understanding the effect of biofeedback. This poor quality of data is similar to the findings of by previous reviews, highlighting the need for improved methods and reporting in future studies.

The included studies have several limitations that may affect the reliability of outcomes. These include wide variations in sample size, which may result in findings that do not reflect real patients. In line with representation, the mean age of the included participants was 51.7 ± 8.7 years, which does not reflect the mean age of patients with hypertension, which largely affects patients aged over 65 [ 41 ]. Only 25% of articles reported any power calculations. No studies reported measurements of medication adherence, which can significantly affect blood pressure control [ 42 , 43 ]. Furthermore, ten studies used participant populations that were either partly, or not on any medication. Similarly, intervention adherence was reported in only four studies, and two studies reported the use of fidelity checks. Consequently, it is difficult to ensure the biofeedback intervention was implemented as planned in the majority of studies.

A significant issue in this review is that the dated studies do not represent the availability of current technologies. The majority of studies were published between 1970 and 1999, with only one study published after 2010. Since then, biofeedback technology has improved dramatically and is more user friendly, with the ability to practice independently at home. This has been further supported by the progression with AI, which can further support the development and integration of biofeedback in the healthcare field. It has already been incorporated in biofeedback research in virtual reality exposure therapy for anxiety [ 44 ] and eXtended Reality training scenarios [ 45 ]. The use of machine learning in biofeedback can support tailored feedback and identify scenarios and stimuli that increase physiological responses, which can increase user awareness of their health. Biofeedback devices now include wearables, such as a wristband that continuously records blood pressure and displays results in an app on the user’s phone [ 11 ]. This contrasts with examples from included studies where biofeedback was conducted in the clinic in the presence of researchers [ 29 , 34 ] and using techniques not suitable for home use, such as a researcher manually plotting blood pressure biofeedback on a graph [ 20 ]. The dated technology is reflected in methods of blood pressure measurement.

We believe that biofeedback has a potential role to play in the management of hypertension. New research should incorporate robust methodology, updated biofeedback technology such as wearable devices, and incorporate the use of innovative techniques to support large scale delivery of biofeedback.

To conclude, this meta-analysis showed that biofeedback significantly reduces systolic (-4.52 mmHg, P  = 0.02) and diastolic blood pressure (−5.19 mmHg, P  = 0.0004), with the pooled blood pressure decrease in biofeedback groups reaching clinical significance. However, the low quality of evidence and heterogeneity across studies mean results should be interpreted with caution. Importantly, the dated nature of existing studies means they do not represent the current climate of biofeedback and the availability of current technologies. But future research especially featuring wearable devices using robust methodology are needed to provide evidence of a practical and scalable approach to biofeedback that is clinically deliverable and acceptable to patients.

What is known about the topic

Hypertension is a leading modifiable risk factor for cardiovascular disease. However, despite the availability of medication, hypertension control remains suboptimal in approximately 50% of patients.

Autonomic nervous system dysregulation in part mediates hypertension, highlighting a possible target for interventions aiming to improve blood pressure.

Biofeedback can increase self-regulation and self-awareness of parameters that regulate the autonomic nervous system, suggesting a suitable intervention to support patients with hypertension

What this study adds

The meta-analysis demonstrated that biofeedback had a significant effect on blood pressure, with a reduction in both systolic (−4.52, Z = 2.31, P  = 0.02, CI [−8.35, −0.69]) and diastolic blood pressure (−5.19, Z = 3.54, P  = 0.0004, CI [−8.07, −2.32]).

The weaknesses of the study not only make it difficult to determine the most effective intervention but also affect the ability to draw conclusions about the effect of biofeedback on blood pressure.

Future studies need to incorporate robust methodology and updated technology such as wearable devices, to improve understanding of the role of biofeedback in hypertension.

Data availability

All data generated or analysed during this review are included in this published article [and its supplementary information files].

Zhou B, Perel P, Mensah GA, Ezzati M. Global epidemiology, health burden and effective interventions for elevated blood pressure and hypertension. Nat Rev Cardiol. 2021;18:785–802.

Mancia G, Grassi G. The autonomic nervous system and hypertension. Circulation Res. 2014;114:1804–14.

Article   CAS   PubMed   Google Scholar  

Milic M, Sun P, Liu F, Fainman C, Dimsdale J, Mills PJ, et al. A comparison of pharmacologic and spontaneous baroreflex methods in aging and hypertension. J Hypertens. 2009;27:1243.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Lehrer PM, Vaschillo EG, Vidali V. Heart rate and breathing are not always in phase during resonance frequency breathing. Appl Psychophysiol Biofeedback. 2020;45:145–52.

Article   PubMed   Google Scholar  

Sagui-Henson SJ. Cognitive avoidance. In: Encyclopedia of personality and individual differences. Springer International Publishing. 2017. pp. 1–3.

De Witte NA, Buyck I, Van Daele T. Combining biofeedback with stress management interventions: A systematic review of physiological and psychological effects. Appl Psychophysiol Biofeedback. 2019;44:71–82.

Kondo K, Noonan KM, Freeman M, Ayers C, Morasco BJ, Kansagara D. Efficacy of biofeedback for medical conditions: an evidence map. J Gen Intern Med. 2019;34:2883–93.

Article   PubMed   PubMed Central   Google Scholar  

Frank DL, Khorshid L, Kiffer JF, Moravec CS, McKee MG. Biofeedback in medicine: who, when, why and how? Ment health Fam Med. 2010;7:85.

PubMed   PubMed Central   Google Scholar  

Khazan IZ. The clinical handbook of biofeedback: A step-by-step guide for training and practice with mindfulness. John Wiley & Sons; 2013.

Konstantinidis D, Iliakis P, Tatakis F, Thomopoulos K, Dimitriadis K, Tousoulis D, et al. Wearable blood pressure measurement devices and new approaches in hypertension management: the digital era. J Hum Hypertens. 2022;36:945–51.

Burnier M, Kjeldsen SE, Narkiewicz K, Oparil S. Cuff-less measurements of blood pressure: are we ready for a change? Blood Pressure 2021;30:205–7.

Matsuoka R, Akazawa H, Kodera S, Komuro I. The dawning of the digital era in the management of hypertension. Hypertension Res. 2020;43:1135–40.

Article   Google Scholar  

Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int J Surg. 2021;88:105906.

Williams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology (ESC) and the European Society of Hypertension (ESH). Eur Heart J. 2018;39:3021–104.

Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.

Higgins JT, Savović, J., Page, M. J., Sterne, J. A. C. Revised Cochrane risk-of-bias tool for randomized trials (RoB 2). 2019. Available from: https://www.riskofbias.info/welcome/rob-2-0-tool/current-version-of-rob-2 .

Schünemann H, Brożek J, Guyatt G, Oxman A, editors. Handbook for grading the quality of evidence and the strength of recommendations using the GRADE approach. 2013. Available from https://gdt.gradepro.org/app/handbook/handbook.html

Hunyor SN, Henderson RJ, Lal SK, Carter NL, Kobler H, Jones M, et al. Placebo-controlled biofeedback blood pressure effect in hypertensive humans. Hypertension. 1997;29:1225–31.

Hafner RJ. Psychological treatment of essential hypertension: a controlled comparison of meditation and meditation plus biofeedback. Biofeedback Self Regul. 1982;7:305–16.

Blanchard EB, Miller ST, Abel GG, Haynes MR, Wicker R. Evaluation of biofeedback in the treatment of borderline essential hypertension 1. J Appl Behav Anal. 1979;12:99–109.

Shoemaker JE, Tasto DL. The effects of muscle relaxation on blood pressure of essential hypertensives. Behav Res Ther. 1975;13:29–43.

Fray JM. Implications of electromyographic feedback for essential hypertensive patients. Lubbock: Texas Tech University; 1975.

McGrady AV, Yonker R, Tan S, Fine TH, Woerner M. The effect of biofeedback-assisted relaxation training on blood pressure and selected biochemical parameters in patients with essential hypertension. Biofeedback Self Regul. 1981;6:343–53.

Billion L. The effect of EMG biofeedback, relaxation, and sham EEG alpha training on blood pressure of essential hypertensives. University of Virginia; ProQuest Dissertations & Theses, 1980.

Patel C. Biofeedback and self-regulation. In: Complementary health therapies: a guide for nurses and the caring professions. Beckenham, Kent: Croom Helm; 1988.

Goldstein IB, Shapiro D, Thananopavarn C, Sambhi MP. Comparison of drug and behavioral treatments of essential hypertension. Health Psychology, 1982;1:7.

Paran E, Amir M, Yaniv N. Evaluating the response of mild hypertensives to biofeedback-assisted relaxation using a mental stress test. J Behav Ther Exp psychiatry. 1996;27:157–67.

Henderson RJ, Hart MG, Lal SK, Hunyor SN. The effect of home training with direct blood pressure biofeedback of hypertensives: a placebo-controlled study. J Hypertens. 1998;16:771–8.

Tsai P-S, Chang N-C, Chang W-Y, Lee P-H, Wang M-Y. Blood pressure biofeedback exerts intermediate-term effects on blood pressure and pressure reactivity in individuals with mild hypertension: a randomized controlled study. J Alternative Complement Med. 2007;13:547–54.

Pandic S, Ekman I, Nord L, Kjellgren KI. Device-guided breathing exercises in the treatment of hypertension–perceptions and effects. CVD Prev Control. 2008;3:163–9.

Google Scholar  

Landman GW, Drion I, van Hateren KJ, van Dijk PR, Logtenberg SJ, Lambert J, et al. Device-guided breathing as treatment for hypertension in type 2 diabetes mellitus: a randomized, double-blind, sham-controlled trial. JAMA Intern Med. 2013;173:1346–50.

Nakao M, Nomura S, Shimosawa T, Yoshiuchi K, Kumano H, Kuboki T, et al. Clinical effects of blood pressure biofeedback treatment on hypertension by auto-shaping. Psychosom Med. 1997;59:331–8.

Patel C. Yoga and biofeedback in the management of hypertension. J Psychosom Res. 1975;19:355–60.

Blanchard EB, Eisele G, Vollmer A, Payne A, Gordon M, Cornish P, et al. Controlled evaluation of thermal biofeedback in treatment of elevated blood pressure in unmedicated mild hypertension. Biofeedback Self Regul. 1996;21:167–90.

Achmon J, Granek M, Golomb M, Hart J. Behavioral treatment of essential hypertension: a comparison between cognitive therapy and biofeedback of heart rate. Psychosom Med. 1989;51:152–64.

Elavally S, Ramamurthy MT, Subash J, Meleveedu R, Venkatasalu MR. Effect of nurse-led home-based biofeedback intervention on the blood pressure levels among patients with hypertension: Pretest–posttest study. J Fam Med Prim care. 2020;9:4833.

Olsson EM, El Alaoui S, Carlberg B, Carlbring P, Ghaderi A. Internet-based biofeedback-assisted relaxation training in the treatment of hypertension: a pilot study. Appl Psychophysiol biofeedback. 2010;35:163–70.

Canino E, Cardona R, Monsalve P, López B, Fragachan F. A behavioral treatment program as a therapy in the control of primary hypertension. Acta Cient Venez. 1994;45:23–30.

CAS   PubMed   Google Scholar  

Vital JEC, de Morais Nunes A, New BSdAC, de Sousa BDA, Nascimento MF, Formiga MF, et al. Biofeedback therapeutic effects on blood pressure levels in hypertensive individuals: a systematic review and meta-analysis. Complement Ther Clin Pract. 2021;44:101420.

Greenhalgh J, Dickson R, Dundar Y. The effects of biofeedback for the treatment of essential hypertension: a systematic review. Health Technol Assess. 2009;13:1–104.

NHS. Health Survey for England, 2021 part 2 2023 [Available from: https://digital.nhs.uk/data-and-information/publications/statistical/health-survey-for-england/2021-part-2/adult-health-hypertension .

Kolandaivelu K, Leiden BB, O’Gara PT, Bhatt DL. Non-adherence to cardiovascular medications. Eur Heart J. 2014;35:3267–76.

Cutler RL, Fernandez-Llimos F, Frommer M, Benrimoj C, Garcia-Cardenas V. Economic impact of medication non-adherence by disease groups: a systematic review. BMJ Open. 2018;8:e016982.

Rahman MA, Brown DJ, Mahmud M, Harris M, Shopland N, Heym N, et al. Enhancing biofeedback-driven self-guided virtual reality exposure therapy through arousal detection from multimodal data using machine learning. Brain Inform. 2023;10:14.

Blackmore KL, Smith SP, Bailey JD, Krynski B. Integrating Biofeedback and Artificial Intelligence into eXtended Reality Training Scenarios: A Systematic Literature Review. Simul Gaming. 2024;55:10468781241236688.

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This study is funded by the National Institute for Health Research (NIHR) Applied Research Collaboration East Midlands (ARC EM). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. HO is funded by Servier Affaires Medicale. The views expressed are those of the author(s) and not necessarily those of Servier Affaires Medicale. KK is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration East Midlands (ARC EM) and the NIHR Leicester Biomedical Research Centre (BRC). DL is supported by the John and Lucille van Geest Foundation and the NIHR Leicester Biomedical Research Centre (BRC).

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A systematic literature review of education for Generation Alpha

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• Volume 3 , article number  125 , ( 2024 )

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Generation Alpha are the first to grow up immersed in digital technology and presumed to be wired differently than previous generations. This systematic review synthesizes the research literature on what has been learned so far and broadly answers the following question: What is happening in the education and training of Generation Alpha? The literature review was conducted based on guidelines outlined by The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Titles of 2,093 studies, abstracts of 603 studies, and 335 full-text studies were evaluated for inclusion criteria. A total of 83 studies were included into the literature review. The studies were sorted into four major categories: (1) the role of teachers, (2) the role of new approaches to education, (3) the role of teaching tools, and (4) the role of blended/online learning. Despite frequent use of the term “Generation Alpha” in the research literature, relatively few studies report generational differences that reveal how children of this generation are characteristically different from previous generations. There is simply a strong assumption that Generation Alpha is different. A major concern is that the use of technology by Generation Alpha has decreased opportunities for social-emotional development and increased mental health problems. There are digital educational tools and online strategies being developed and tested but none have emerged to be dominant.

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1 A systematic literature review of education for generation alpha

Generation Alpha has received a lot of attention by scholars seeking to understand how current advances in technology may impact their learning. The underlying assumptions are that Generation Alpha students differ qualitatively from students from other generations and that there should be corresponding changes to education based on these differences. To date, these assumptions have not been systemically examined, though there have been reviews in related areas (e.g., [ 39 ]). Accordingly, a systematic review of education literature is necessary to discover whether and how Generation Alpha should be considered by educators. The significance of this review is to guide future educational efforts designed to target specific cohorts like Generation Alpha.

The term “generation” can be used to classify people based on year of birth, age, location, similar values, and/or important events and usually spans about 20 years [ 47 ]. The first use of the term “Alpha Generation” is credited to Mark McCrindle who in 2005 coined the term to describe the cohort following Generation Z [ 103 ]. While there is general agreement that the Millennial Generation are classified as those born between 1980–1994, and GenZ/iGen are classified as those born between 1995–2012, there are some differences in the literature identifying the starting date for Generation Alpha. This report follows most of the literature which uses 2010 as the starting date []. Table 1 presents different generations and significant technical milestones.

Generation Alpha and those immediately preceding generations could all be understood to be digital generations with the only difference being the quantity and quality of digital opportunities that were available while growing up. All future generations will be considered true digital natives with Generation Alpha simply being the first to be so immersed in digital technology. For comparison, members of Generation Alpha are unlikely to carry a wallet or take a written exam [ 76 ]. When all members of this generation have been born, they are expected to number almost two billion [ 99 ].

Despite their large numbers, research on characteristics of Generation Alpha is limited. The assumption that Generation Alpha is qualitatively different than Generation Z is largely untested (Nagy & Kolcsey, [ 81 ]) and sometimes disputed [ 59 ]. There are very few direct comparisons between generations measuring the nature and extent of digital fluency or competence. Perhaps the only certainty is that for this generation, the everyday role of digital devices is not perceived as a “tool” or “instrument” to augment life, but as a normative and necessary means to interact with the world. This chief characteristic has important developmental implications, most notably in the construction of identity and social-emotional learning (SEL). Still, there are some research findings that suggest that Generation Alpha can be distinguished from previous generations.

2 Personal characteristics

In a rare study comparing generational differences, Apaydin and Kaya [ 14 ] identified characteristics of Generation Alpha from the perspective of pre-school teachers. Using a qualitative design with a small sample (n = 12) they found Generation Alpha to:

Exhibit behaviors such as being more curious, free from any rules, being more ill-tempered, more mobile and more self-centered than Generation Z; moreover, they also had high self-esteem, and they were more emotional and more conscious. In terms of communication, Generation Alpha was also determined to be more closed and behave more individually than Generation Z. Considering classroom management techniques, preschool teachers were found to use the reconstructive approach for the alpha generation and traditional classroom management techniques for Generation Z. (p. 123)

The above quote from the study by Apaydin and Kaya [ 14 ] is frequently cited in the Generation Alpha literature and the basis for most of the generation’s characteristic assumptions. dos Reis [ 33 ] found similar findings of cognitive flexibility and dynamism and inferred that Generation Alpha will be employed in jobs characterized by decision-making autonomy. This may lead to Generation Alpha being more entrepreneurial (Ziatdinov & Cillers, 2021). Similarly, Selvi et al. [ 100 ] notes Generation Alpha to lack qualities such as “loyalty, thoughtfulness, compassion, open-mindedness, and responsibility” (p. 273).

3 Family dynamics

Few researchers have examined how family dynamics such as family structure and roles of family members interact with Generation Alpha learning. For example, the research looking at family dynamics is almost exclusively concerned with marketing. The marketing industry is especially interested in how Generation Alpha may exert more influence on parental buying decisions because of increased media exposure [ 45 , 63 , 89 , 109 ]). In one study of 206 parents in India, the critical factors in the selection of educational toys for Generation Alpha were found to be brand recognition, brand attributes (e.g., safety) and product appeal [ 92 ].

4 Social media

The use of social media through mobile devices is a chief characteristic of Generation Alpha. The continuous rise in mobile internet use by Generation Alpha is blurring traditional boundaries between news, information, entertainment, socializing and research. Over 80% of parents of Generation Alpha say their children watch videos or play games on a mobile device daily [ 24 ] and on average spend 7–8 h on screen [ 111 ]. As early as kindergarten, children’s individual consumption of digitally streamed movies drives their classroom social interactions (Kaplan-Berkeley, [ 54 ]).

There are ongoing concerns that the rise in interpersonal communication through text will result in a loss of oral communication skills and that a reliance upon social media influencers to learn about current events will result in less critical thinking. Although there is much written about the potential and real harms of social media, there is little research from which to speculate how the impact on Generation Alpha will be different [ 38 ].

5 Social emotional development

The increased use of technology has resulted in a decline in opportunities for social-emotional development. Moreover, the increased use of social media has led to an increase in mental health problems as children who spend more time on screens experience more mental health challenges [ 112 ]. The potential good news is that because Generation Alpha are children born to late Millennials or members of Generation Z, these parents often spend more time and are more engaged with their children’s lives [ 26 ], 32 ). Thus, parents and other adults may be able to mediate harmful effects of social media use. In a rare study of adult–child interaction with 100 parents and children, Mariati et al. [ 73 ] found that “When social media and online games are introduced into a child’s environment, it has been demonstrated that they mediate their conceptualization of learning and cognitive development,... through the interactions between teachers, children, and technology, children conceptualize higher mental functions such as continuous and ongoing problem-solving dispositions, as well as language acquisition and social learning” (p. 95).

More research is needed to understand the optimal conditions to provide social-emotional learning opportunities with parents and teachers. Settings are also important. Schools also might be designed with embedded instruction of non-cognitive skills and opportunities for interpersonal skill development [ 67 ]. Not only schools, but also informal educational settings such as afterschool programs can be reimagined to provide more “edutainment” for Generation Alpha to increase social-emotional development [ 94 ].

6 Worldwide concern

There is widespread concern for the social-emotional and mental health of Generation Alpha and role of teachers and parents. In Slovakia, there is concern for the lack of emotional intelligence in Generation Alpha [ 53 ]. In Romania, based on the results of a previous investigation carried out in the same locations during the period of 2015–2016, exploratory qualitative research concluded that young children in Romania have a low level of digital literacy due to their parents’ and educators’ lack of technology knowledge and skills. Additionally, issues like online privacy and security are rarely of adults’ concern: parents worry more about their children’s eyesight and social isolation (Bako & Tokes, 2018).

In Indonesia, Zulkifli et al. [ 119 ] note “The results of the study [from 25 kindergarten principals] indicate that the role of preschools in the use of gadgets in digital native generation children in Pekanbaru City is included in the low category. Only a few preschools have organized parenting education for parents. There are almost no rules governing children's use of gadgets at home, and few preschools educate children on how to use gadgets properly. It is expected for teachers and preschools to add special programs in the curriculum to provide information about positive gadget use and parenting programs that discuss digital native generation and collaborate with parents to establish rules such as frequency, duration and content of children using gadgets” (p. 1).

In Malaysia, Fadzil et al., [ 35 ] concluded “This study showed that more than half of the respondents (parents and kids) surveyed felt very dependent upon gadgets. Parents need them as kids control, while kids need them for their pleasure and entertainment tools. They feeling the need to have their phones on them 24 h or using their phones every day. This will have caused them to feel anxious, disconnected, or even upset if they did not use and utilize it in their future and daily live” (p. 621). Finally, in Russia, [ 16 ] found that preschool children with prolonged immersion “in virtual leisure and limited social contacts with other people contribute to a decrease in the level of self-esteem and increase in the level of anxiety and social distancing from parents” (p. 11).

This review synthesizes the research literature on what has been learned so far and seeks to accomplish the following goals: (1) Identify the roles of teachers in the education of Generation Alpha; (2) Identify novel educational strategies in the teaching of Generation Alpha; and (3) Identify the roles blended or hybrid learning played in the education of Generation Alpha. There is a growing body of literature focused on answering the question: What is known about learning practices of Generation Alpha?

The systematic review of the Generation Alpha literature was conducted based on guidelines outlined by The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement, updated in November 2021 [ 85 ]. Figure  1 illustrates the PRISMA review.

Systematic literature review

In November 2022, searches were conducted using the following databases and search engines: ERIC, APA PsycArticles, APA PsycInfo, ProQuest One Academic, Google Scholar, and Clemson Library (a search engine that includes Scopus and 724 other databases). These databases were selected as they include research focused on education, psychology, and other related areas commonly used in the field of education. The databases covered peer-reviewed articles as well as dissertations. Table 2 illustrates the detailed search strategy for this literature review and provides information about the specific search terms used in the specific databases with numbers of searched returned publications. No filters were used, nor were there language or date restrictions while searching the literature.

The literature search identified a total of 3,067 studies. We retrieved all the records and exported them as a Research Information Systems (RIS) file into Mendeley Reference Manager, where duplicate records were identified and removed from the searches [ 65 ]. Subsequently, the records were reviewed, and 974 duplicates were identified. After deleting the duplicates, we exported 2093 records into an Excel document for further review and coding of titles, abstracts, and full texts.

In the first stage of screening, the titles of 2093 records were evaluated to identify the relevant literature and 1,490 studies were excluded. Studies that were older than 2011 were excluded as not applicable to Generation Alpha (children born from 2010 to 2024). Exclusion criteria were applied to titles that clearly indicated topics unrelated to education of Generation Alpha. Excluded studies: (1) were in a language other than English; (2) focused on disciplines unrelated to education (e.g., finances, marketing, medicine); (3) focused on different generations (e.g., Gen X); (4) focused on school leadership; (5) focused on religious education or Sunday church schools; or (6) focused on homeschool education or family education. While topics such as school leadership and religious education other than formal education may seem relevant, the reviewed titles did not indicate any direct connection to education of Generation Alpha (e.g., they were models of religious education or leadership development and styles).

Titles that were included focused on: (1) education; (2) digital education; (3) digital games in education; (4) virtual reality in education; (5) technology use in education; (6) social media use in education; (7) language development; (8) employment skills; (9) generational differences in the workplace; and (10) labor market trends. Studies with titles that were not descriptive enough to apply the inclusion or exclusion criteria were also included for further review.

In the second stage of screening, the abstracts of 603 records were read to identify the relevant literature and 268 studies were eliminated. Because many titles of papers were not specific, an overabundance of abstracts were read to determine if they applied to Generation Alpha. Publications without abstracts were also included in the full text review to ensure that all essential publications for our review were included. After further review, abstracts were eliminated because they focused on: (1) different generations or different age groups; (2) different disciplines (e.g., medicine, investments, economics, technology outside education); (3) different types of education (e.g., character education, citizenship education, religious education); or (4) soft skills. Abstracts that were included focused on: (1) characteristics of Generation Alpha; (2) curriculum development; and (3) technology and specific teaching tools usage in education.

In the third stage of screening, the full text of 335 records were reviewed to assess them for eligibility. From this stage of review, 84 studies were excluded because: (1) the focus was on different generations or different age groups; (2) the focus was from different disciplines (e.g., investments, architecture, marketing); (3) the language of the publication was other than English; and (4) the publication was not available or was available only after purchase. During this stage, we sorted the studies by the country of origin, type of publication, original research, methods/samples, focal point of the paper (e.g., students, teachers, parents).

In the final stage of screening, the full text of 251 publications were extensively reviewed and 168 studies were excluded from the literature review. The publications were excluded due to the following: (1) lack of empirical research, such as being theoretical or without a data-driven analysis; (2) insufficient sections of the publications, such as studies that lacked clear analysis, had insufficiently detailed data collection description, or had an unclear method section that did not distinguished between empirical research and a literature review; (3) had a focus on different generations; (4) had a focus on non-formal education (e.g., out of school educational settings).

The systematic review concluded with 83 relevant publications that could be analyzed and coded for the literature review. We utilized an indictive coding approach, when the codes, categories, and themes naturally emerged from reading and analyzing the articles. The coding process was performed continuously, starting from the title screening stage and repeated throughout the abstract and the full text review phases. Codes were revisited and refined at each step of the literature review to ensure that the thematic structure accurately represented the data. The result of this coding process, including codes, categories, and themes, are summarized in Table  3 . Four major themes concerning the education of Generation Alpha emerged from the coding process: (1) the role of teachers (18 studies), (2) the role of new approaches to education (12 studies), (3) the role of teaching tools (43 studies), and (4) the role of blended/online learning (10 studies).

Publications came from around the world, with a majority from Indonesia (33 studies), Malaysia (17 studies), followed by the United States (11 studies). Figure  2 . shows the distribution of publications by country, darker color indicating more studies.

Distribution of publications by country

The four themes derive from research that was conducted from around the world and describe common points of emphasis to accomplish the following goals: (1) Identify the roles of teachers in the education of Generation Alpha; (2) Identify novel educational strategies in the teaching of Generation Alpha; and (3) Identify the roles blended or hybrid learning played in the education of Generation Alpha.

9 The role of teachers

If Generation Alpha is special, then the expectation is that teachers would be the first to be impacted by the need for innovative teaching strategies. A synthesis of the 18 studies that focused on teachers confirms the gradual impact of an increased technology expertise needed to teach Generation Alpha. Perhaps unsurprisingly, the research tells a story of how teachers struggle to keep up with technology, recognize the importance of staying updated and innovate to teach Generation Alpha. To tell this story, seven publications were from Asia, five publications were from Europe, three from the United States, two from the Middle East, and one from Brazil.

9.1 Teachers struggle

For teachers (and most others), the speed of technological advances generally outpaces the ability to stay current on the latest educational innovations. The gap between teachers’ and students’ digital competence is dependent upon both teacher training and teacher commitment to staying updated. Regarding teacher training, a study conducted by Galindo-Domínguez and Bezanilla [ 40 ] showed only a medium level of digital competence among 200 future teachers enrolled in educational degrees in universities in Spain. Once in the classroom, whether or not teachers use social media may depend on attitudes toward its usefulness. In a dissertation, Turnbull [ 110 ] explored reasons for the low integration of social media into higher education classroom assignments in the United States. Professors who integrated social media into assignments believed that social media is an important part of students’ present lives and future employability. Professors who did not integrate social media into assignments believed that social media is not relevant to their class and not useful for learning. These professors were also older and unfamiliar with social media. Similarly, Adnan et al. [ 5 ] investigated teachers’ content development utilizing innovative teaching and learning technologies among tertiary teachers in Malaysia. The results showed that after training, very few teachers created interactive learning materials (e.g., virtual reality) on their own. The results affirm the necessity of offering opportunities for teachers to master new digital technologies throughout their careers.

9.2 The need for training for teachers

In educational institutions around the world, there is a growing acknowledgment that teacher training needs to be responsive to the assumed growing digital divide between teachers and students. In Brazil, future teachers were able to identify Generation Alpha’s use and ease with digital technologies but also recognized that their courses did not sufficiently prepare them to teach this new generation [ 25 ]. Similarly, future teachers in the Czech Republic believed that information and communication technology could support classes such as mathematics and elementary science but reported that for their own learning, they prefer textbooks and notes from lectures rather than the internet [ 113 ]. Finally, Aditya et al. [ 4 ] found that although early childhood education teachers in Indonesia had positive attitudes toward the use of information and communication technology, the lack of technical support and training led to difficulties with integrating technology in their online activities.

Even if proper teacher training is possible, how to train teachers is an important challenge. In a longitudinal case study dissertation, Mullen [ 78 ] investigated teachers’ jobs, administrative technology, education technology, and self-reported educator self-efficacy from the beginning of their employment through orientation and the first 60 days of an onboarding process in the United States. Unfortunately, the results showed that the onboarding intervention resulted only in minor changes in teachers’ self-efficacy.

Can the presence of older more experienced teachers from other generations make a difference? In a dissertation, Teske [ 108 ] exanimated generational differences of Baby Boomers, Generation Xers, and Millennials regarding educational and workplace values among American public-school teachers. Differences were found among the generations in work ethic, ability to establish positive relationships, utilization of technology, willingness to change, patience, and respect for hierarchy. Similarities between generations were found in motivation and types of leadership. In general:

The Baby Boomer generation perceived themselves resisting and experiencing difficulties when making changes . . . Millennials were identified by the other generations and perceived themselves as being flexible and open-minded to change, which was classified as a positive value. Generation Xers felt they aligned with the Baby Boomers’ difficulty to accept change, while the other two generations believed Generation Xers adapted well to change. (p. 174-175)

Overall, the findings suggest that it may be difficult to teach digital skills (see also, [ 60 ]).

As a model for understanding teachers’ preparedness, in Indonesia, there is significant national effort directed at measuring teachers’ capacity and competence with scientific literacy and digital technology. A national initiative creates teacher profiles through measures of a teacher’s ability to plan and integrate technology, pedagogy, and content knowledge for effective teaching to support student learning. Known at TPACK (Technological Pedagogy Content Knowledge), the framework has proved useful [ 60 ]. For example, Fakhriyah et al. [ 36 ] found that TPACK ability was good among future teachers and the factors that contributed the most to the abilities were the pedagogic component and the content knowledge component. Recommendations are for schools to improve teachers TPACK scores through individualized teacher training because group trainings fail to consider teacher characteristics. Following this recommendation, Churiyah et al. [ 28 ] evaluated a program that aimed to train and assist Indonesian vocational high school teachers in developing learning media and models that can accommodate the creativity skills of students. The results showed that teachers who took part in the program had skills in developing media and implementing learning models that support the students’ creative skills.

In addition to preparing teachers based on pre-existing competencies, specialized training can increase the chance of digital competence. For example, Karacan and Polat [ 55 ] examined the factors that predict Turkish pre-service English teachers’ intentions to use augmented reality in their classes. The pre-service teachers attended a training on augmented reality in language classes and a workshop to create augmented reality experiences. The results indicated that the pre-service teachers who perceived the augmented reality useful were more likely to adopt the augmented reality in their future classes. In addition, pre-service teachers’ self-efficacy beliefs also positively affected their adoption of augmented reality.

Training with the use of flipped classrooms had mixed results. Hashim and Shaari [ 44 ] examined Malaysian primary and secondary school teachers’ perception of flipped classrooms. Teachers perceived the flipped classroom as useful and believed it can improve their knowledge and skills. However, the teachers faced some challenges during the implementation, most of them believed that their students do not like watching short, flipped videos and they are not interested in the educational material in flipped classrooms.

Competencies other than mastering technologies are still important. Fauyan [ 37 ] conducted a study that investigated the roles and competencies of millennial teachers in Indonesia. The results showed that teachers had roles of agents of transferring the knowledge, managers, learning agents that created active and creative learning environment, motivators who encourage students’ involvement by using multimethod, multimedia, and multisource. Additionally, the following competences were found crucial: planning, implementing, and evaluating. Those roles and competencies showed teachers’ readiness in implementation of the latest technology during remote teaching in the COVID-19 period. In summary, there appears to be increasing efforts to understand how best to improve teacher competencies.

9.3 Teachers are Innovating

Teachers have been innovating and experimenting with new teaching methods for Generation Alpha with mixed success. In Ukraine, Morze et al. [ 77 ] examined competences required for critical evaluation of internet resources among future primary school teachers. The results showed that most future teachers have faced different types of fraud online and all teachers were aware of cybersecurity measures carried out at the national level. Most of the future teachers believed that critical evaluation of Internet resources should be developed in the computer science classes. The future teachers believed that the following techniques should be used most often in the development of future teachers’ internet critical thinking: project activity, effective use of digital tools, and collaboration in groups. Based on the findings, the authors designed a model of the system of formation of internet resource critical evaluation skills of future primary school teachers.

In another effort to improve Generation Alpha’s reading skills, Aberšek and Kerneža [ 2 ] examined Slovenian primary teachers’ attitudes towards an Internet Reciprocal Teaching (IRT) method that aims to improve students’ functional literacy competence when using the internet and screens. Research with previous generations suggest that paper-based reading produced better learning outcomes than screen-based reading [ 31 ]. Teachers believed that the IRT method is suitable for developing functional literacy in digital learning environment among students 9–11 years old and should be modified for younger students. There was an acknowledgement that there was no going back to paper-based reading.

Games and robots are also making inroads into Generation Alpha curriculums. Masril et al. [ 74 ] found that the use of robotic technology (Lego Mindstorms Ev3) as a learning resource by Indonesian elementary school teachers had a positive effect on behavior and was perceived as a learning tool that should be used in the elementary school curriculum. In Turkey, Akkaya et al. [ 9 ] found that most teachers considered themselves competent in using technology and they used digital games mostly in mathematics classes. Teachers believed that although there are many educational benefits, the usage of games could lead to physical health problems, communication problems, focusing problems, mental disorders, and excessive time loss.

In summary, the experimentation with novel approaches has some promising results, but there was no single innovation that has been replicated or scaled to an extent to be seen as universally effective.

10 The role of new approaches to education

New approaches to education are occurring at every level. Twelve studies focused on rethinking curriculums and programs for Generation Alpha. Five studies were from Indonesia, two studies were from Europe, two from the United States, one from Turkey, one from Algeria, and one from Kuwait.

10.1 Rethinking national approaches

In some countries, researchers are discovering how best to train teachers at the national level. In Croatia, Jukić and Škojo [ 51 ] conducted interviews with 10 information and communication technology (ICT) experts and 10 university professors to assess the future and integration of technology. Reflecting their orientation, the ICT experts perceived that teachers have insufficient training, their computer literacy is lower than students, and schools do not have adequate equipment. According to the ICT experts, teaching must be more dynamic and should be gamified as future occupations will be related to highly developed technology and artificial intelligence. The professors raised concerns about challenges associated with insufficient social interactions, problems of socialization, and insufficient development of social competencies and communication skills. In other words, social-emotional learning was important. The professors also agreed that the teaching process must be updated to be more interesting, teaching methods need to be multimodal with visualization of the teaching content, the teaching process must be more dynamic with active learning and interactive teaching, and the curriculum must be attractive with elective subjects.

When countries do innovate to meet the needs of Generation Alpha, it is important to evaluate the effectiveness of the approach. In Algeria, Sarnou [ 97 ] investigated the reasons of unsuccessful technologization of schools and universities and found the major reasons for the failure of an effective integration of ICT into the classrooms were social, cultural, economic, and educational factors. Specifically, there were deeply rooted regional differences in culture, politics, and financing within the country that made integration of ICT difficult. The ineffective integration of ICT was also found to negatively influence the relationship between teachers and students.

In summary, although a few articles depict efforts to understand how best to educate Generation Alpha, the results have not yet translated into national policies.

10.2 Rethinking language programs

An important goal in many educational systems is to improve language proficiency of non-native speakers and there has been some success with new programs aimed at increasing language proficiency for Generation Alpha. For example, Kadir et al. [ 52 ] examined the effectiveness of a 3 year foreign language program of Arabic-English-Japanese in three Indonesian schools. The language program implemented smart and creative learning methodologies with audio and visual gadgets. The findings reveled that the program created engaging and enjoyable learning environment for students. Also in Indonesia, Rombot et al. [ 91 ] developed a blended learning model for foreign speakers that gave the students the opportunity to repeatedly read the text and ultimately improved Indonesian reading skills. Finally, Shamir et al. [ 101 ] explored the effectiveness of the Waterford Early Learning curriculum, a game-based curriculum designed to promote English as a foreign language through reading, writing, and typing among students in kindergarten through second grade. The results showed that students that used the curriculum had significantly higher literacy scores than students who did not use the curriculum.

In summary, as more language curriculums innovate to take advantage of technology, there will likely be an increase of research that capitalizes on Generation Alpha’s presumed digital competence.

10.3 Rethinking STEM and ICT programs

For a generation that is digitally fluent, there is a natural increased emphasis on science, technology, engineering, and math (STEM) and information and communications technology (ICT) programs in education. This increased emphasis has yielded research attempting to take advantage of Generation Alpha’s ability to learn. A quasi-experimental dissertation by LiCalsi [ 68 ] examined the effects of robotics curriculum on American elementary students’ attitude, interest, persistence, self-efficacy, and career interest in STEM. The results indicated that younger students in the treatment group had an increase in the measured variables compared to older students. Girls in the treatment group had an increase in self-efficacy and career interest in STEM compared to girls in the control group.

In another dissertation, Malallah [ 71 ] developed a computational thinking pedagogy framework with a virtual world environment for early childhood education. Using a developed STEM model designed to meet the needs of Arabic/Persian Gulf region students, the STEM program improved students’ computational thinking abilities. The study compared the implementation of the STEM program in the U.S. and in Kuwait and examined factors that influence female and male preference and performance in STEM education in Kuwait.

In a study aimed at second graders, Lucenko et al. [ 70 ] examined the effectiveness of an innovative curriculum design in a Ukrainian primary school. The design used project-research activities in the lessons and the teacher’s role was an organizer of the student project activity. The results showed that the innovative curriculum design was more effective than a traditional methodological approach.

Turkish gifted students perceived that a flipped learning model was fun, different, instructive, useful, increased learning, saved time, provided opportunities for practice, advantageous, and flexible in terms of in-class practices. The study also showed that there was not a significant difference in the emotional semantic orientations in the in-class practices between female and male students. However, there were significant differences in the out-of-class effectiveness and entertainment. Male students perceived the flipped learning model more effective than female students and female students perceived that the flipped learning model as more fun than male students did [ 80 ].

10.4 Rethinking other programs

Two studies fell outside the category of language and science programs. Akmal et al. [ 10 ] evaluated the application of a social-emotional learning model that involves collaboration with parents in early childhood education institutions in Indonesia. The results indicated that a program that aims to teach social-emotional skills in early childhood can be successfully implemented by teachers and parents. In another program aimed at teachers, Defit et al. [ 30 ] developed a Literacy and Technology-based Elementary School Teacher Development model that integrates coaching and mentoring. The aim of the program was to optimize teachers’ leadership abilities to improve the quality of Indonesian teachers in the current digital era. The feasibility of the program design was assessed by lecturers and school principals and deemed suitable for teachers.

Overall, the role of new approaches to the education of Generation Alpha has been to reimagine traditional STEM and languages areas and experiment with some non-traditional areas such as social-emotional learning. Although the cited research is included because of the link to Generation Alpha, there are likely many more relevant efforts naturally occurring with this population that do not operationally define their populations by generation.

11 The role of teaching tools

Next to the role of teachers, the availability of teaching tools (broadly construed) to teach Generation Alpha is the most important factor in understanding how and whether education differs for Generation Alpha. Tools were categorized according to whether there was some evaluation or whether they were in development. Forty-three studies examined a development, or a usage, of a specific technological teaching tool designed for use with Generation Alpha. Out of the forty-four studies, thirty-one studies were conducted in Asia (mostly in Indonesia and Malaysia), four in Europe, two in the United States, two in Middle East, one in Australia, one in Ecuador, one in collaboration between Saudi Arabia, Pakistan, Malaysia, Canada, United Kingdom, and Sweden, one in collaboration between Indonesia and Portugal, and one in a collaboration between Indonesia and Germany.

11.1 Evaluated teaching tools

Eleven studies employed either a pre-test and post-test or experimental design with a control group to evaluate the effect of the educational tool. The teaching tools that were used were the following: virtual reality glasses [ 93 ], Project Based Learning assisted by Electronic Media [ 95 ], Loose Parts learning media [ 86 ], learning media based on modules and GeoGebr [ 15 ], augmented reality pictorial storybook [ 69 ], QR codes as an Augmented reality [ 11 ], Six Facets of Serious Game Design and Ernest Adams’ Game Design [ 27 ], jazz chants approach [ 102 ], collaborative planning and teaching with virtual reality [ 72 ], multimedia learning environment Augmented Reality English Vocabulary Acquisition [ 114 ], and AsKINstagram [ 50 ].

Overall, the teaching tools were effective. Positive outcomes included improved drawing performance [ 93 ], increased motivation [ 95 ], improved science process skills [ 95 ], improved mathematics learning outcomes and performance [ 15 , 27 ], improved naturalist intelligence [ 86 ], increased anxiety in mathematics learning [ 69 ], enhanced student performance [ 11 ], improved academic performance in English as a second Language [ 102 , 114 ], improved vocabulary learning in English as a second Language [ 72 ], and improved students’ writing English as a second language [ 50 ].

11.2 Unevaluated teaching tools

Nineteen studies focused on a usage of a specific teaching tool without an evaluation of the tool’s effect. The teaching tools that were used were the following: Science Technology Engineering and Math-Project Based Learning [ 82 ], Virtual Reality technology [ 3 , 49 , 61 ], serious games [ 1 ], expected game-based learning for protracted waste problem [ 64 ], code.org [ 20 ], Minecraft [ 107 ], digital board game Master Malaysia 123 v2 [ 57 ], Instagram [ 18 ], Instagram interactive face filters [ 90 ], social media [ 116 ], YouTube [ 87 ], WhatsApp [ 105 ], interactive digital phonics show [ 42 ], voca-lens [ 117 ], virtual game using the Sphero haptic device [ 23 ], Chromebook [ 115 ], educational mobile applications (Nevřelová, 2020), and use of technology [ 98 ].

The goals of these projects were to increase cognitive engagement [ 115 ], increase phonological awareness [ 42 ], increase communication skills [ 82 ], increase engagement and entertainment [ 61 ], increase reading skills [ 107 ], increase computational thinking [ 20 ], enhance knowledge [ 57 ], increase language skills for English as a second language [ 116 , 117 ], increase motivation to speak English as a second language [ 18 , 90 ], engaged students [ 98 ], build children’s awareness of waste problems [ 3 ], increase early mathematic skills [ 87 ], increase early literacy skills [ 87 ], increase socio-emotional development [ 87 ], increase executive function [ 87 ], improve narrative writing [ 105 ], improve quality of life [ 1 ], and improve the visual-motor coordination [ 23 ].

11.3 Tools in development

Thirteen studies focused on a development of a teaching tool specifically to improve or capitalize on the digital competency of Generation Alpha. The following teaching tools were developed: argumentation-based educational digital game (Bağ &Çalık, [ 19 ]), game design activity [ 48 ], Android based educational games [ 79 , 96 ], escape room-based mobile game [ 13 ], motion comic storyboard [ 56 ], digital map application with hand gesture recognition [ 84 ], mobile-based learning application [ 17 ],Omar & Abd Muin, [ 83 ]), story digital book [ 43 ], lift the flap book digital media [ 21 ], lift-a-flap picture book with audio [ 62 ], and Edmodo-Based Science Module [ 6 ].

Those teaching tools led to improved mathematical skills [ 56 ], improved literacy [ 43 ], improved science process skills [ 6 ], improved language skills (Omar and Abd Muin, [ 83 ]), improved vocabulary learning [ 62 ], increased motivation [ 19 ], increased creativity [ 48 ], improved motivation to learn English [ 13 ], improved English language skills [ 13 ], increased interests in learning mathematics [ 96 ], improved historical learning [ 84 ], improved early reading [ 79 ], and increased interests in learning science among alpha generation [ 21 ].

In a rare study that focused on a disabled sub-population within Generation Alpha, Aziz et al. [ 17 ] developed an application to improve math skills for those with poor vision. Unfortunately, the effectiveness of the mobile application was not evaluated. Given the benefit of new educational technologies for the disabled, it is surprising that more educational technologies are not developed [ 46 ].

Only one study acknowledged disadvantages associated with the use of technology in classrooms. A study conducted by Kurniawati et al. [ 61 ] focused on the integration of virtual reality into English vocabulary teaching in Indonesia. Teachers were able to incorporate the virtual reality into classes despite some challenges with device availability, workloads, teaching media, and classroom managerial skills. The students perceived that learning English vocabulary using virtual reality was engaging and entertaining. However, the students reported headaches from prolonged exposure to the virtual reality lens. Overall, the studies reveal technology being developed to appeal to students. The state-of-the-art of research has not yet focused on potential negative effects and how to overcome them.

In summary, the development of tools represents the greatest portion of the literature reviewed and reflects the ongoing interest in discovering how best to teach Generation Alpha.

12 The role of blended/online learning

The review of blended/online learning for Generation Alpha is a subset of a far greater research literature on teaching modalities. The literature review directly related to Generation Alpha produced ten studies that examined online or blended learning: five studies were conducted in Asia, two studies in Europe, one study in the United States, and two studies in the Middle East. The findings of the articles are best synthesized and sorted into categories describing the importance of experienced teachers and parents in improving experiences with Generation Alpha and describing some successes and some challenges with adopting distance and blended learning.

12.1 Experienced adults are important

During distance learning, parent–child interaction was an important factor that influenced the success of early childhood education in Indonesia [ 88 ]. To ensure success for distance learning, teachers in Turkey recommended parental support, active participation of students, use of Web 2.0 tools, gamification, and sharing information about training for parents [ 29 ]. Another study showed that experience with technology matters. Masry-Herzallah and Stavissky [ 75 ] found that older elementary and middle school teachers and younger elementary students had more difficulties than younger teachers and older students to transition to online learning during the pandemic in Israel.

12.2 Success with online and blended learning

Although the entire world adopted online and blended learning models during the pandemic, only a few studies used the term “Generation Alpha” in defining their success. Because the overall findings in the literature review are not driven by common research paradigms or common outcome measures, the results are specific to the researchers’ interests and relevant primarily within the context of the country’s education system. Thus, there is a limitation in generalizing the findings from the following countries:

In Ukraine, when teachers incorporated videos and online learning games, students perceived the online learning more beneficial [ 106 ].

In Indonesia, secondary school teachers reported that the best way to provide learning materials was through WhatsApp, Google Classroom and for some students, directly through the school [ 7 ]. In another study, Indonesian high school teachers reported that they used synchronous video conference platforms, asynchronous learning management systems (LMSs), and various learning media to help them conduct laboratory work [ 12 ]. The implementation of the blended learning when done in collaboration between Indonesians schools, teachers, parents, and students leads to more effective and meaningful learning [ 41 ]. Duggal et al. [ 34 ] found that Indian students were accepting the online education but there was a need to keep them engaged and enticed. The implementation of new learning methodologies such as gamified online education can help to overcome the online education challenges.

In Turkey, teachers reported the use of Google Classroom, Edmodo, Classdojo, Microsoft Teams, and Twinspace during distance teaching. They used these Learning Management Systems (LMS) for course and project management, flipped education practices, personal and professional development activities, and management of extracurricular and guidance activities. They described that the LMSs allowed to quickly follow the learning process of the students, allowed students individual progress, and the lessons were more efficient [ 29 ].

In the United States, Kingsbury [ 58 ] compared U. S. students’ online learning experience between schools that were already virtual and traditional in-person schools during the pandemic. He found that the virtual schools outperformed the in-person schools and parents were more likely to report that their child learned a lot during online learning.

12.3 Teacher and school challenges

The challenges to implementing online and blended learning as related to Generation Alpha fell into two categories: teacher challenges and school challenges.

During kindergarten distance teaching in Israel, pre-service teachers came across some challenges with communications, attitudes, tools, and technological skills [ 8 ]. Legvart et al. [ 66 ] found that Slovenian elementary school teachers experienced issues with students limited digital literacy competences which impacted the communication between teachers and students and among the students. In Indonesia, secondary school teachers experienced obstacles with applications, limited internet data, learning management, assessment, and supervision [ 7 ]. Similarly for high school, Indonesian teachers experienced technical issues and reduced interaction during learning process [ 12 ]. Finally, Turkish teachers experienced the most issues with the deficiencies related to technological equipment [ 29 ].

Schools also faced challenges and some research addresses how improvements might be made. In a study of middle-schoolers, Bruggeman [ 22 ] confirmed that “the micro-school environment, with an intentional overlay of a student-centered philosophy, personalized learning, and small mixed-age classroom settings, has a positive impact on the development of three elements of student agency: motivation, choice, and competency” (p. 220). In addition to redesigning classroom settings, a study of 500 elementary school students in Indonesia show that the increased use of smartphones and social media (YouTube, Google) may necessitate the reimagining of how libraries remain relevant [ 104 ]. Given the slow rate of adaption to change, even universities should start thinking of how to meet the needs of Generation Alpha [ 118 ].

13 Conclusions

Despite frequent use of the term “Generation Alpha” in the research literature, relatively few studies report generational differences that reveal how children of this generation are characteristically different from previous generations. There is simply a strong assumption that Generation Alpha is different. A major worldwide concern is that the use of technology by Generation Alpha has decreased opportunities for social-emotional development and increased mental health problems. Where research has been conducted, the underlying goal is to discover how educational practices may benefit with parents and adults mediating technology use.

Within the reviewed literature, no reference was found to any field of studies or organization of scholars focused exclusively on Generation Alpha. Rather, the examined studies reveal research to be the work of independent researchers focused on mostly practical educational strategies. Most of the research literature assumes differences between Generation Alpha and previous generations without systematic observation. An open question is how Generation Alpha is qualitatively different from previous generations. Therefore, future research should utilize theoretical frameworks to identify and understand the unique characteristics, behaviors, and traits of the digital native Generation Alpha.

The term “Generation Alpha” frequently appears in international research literature and is not commonly used in studies the United States. Future researchers might conduct comparative studies across diverse cultures and educational settings while using international collaboration to develop a more comprehensive understanding of Generation Alpha’s characteristics and needs. Longitudinal studies could help understand how Generation Alpha’s experiences and exposure to technology shape their identities, needs, career choices, social-emotional development.

To improve education for members of Generation Alpha and all subsequent digital natives, research might also best be focused less on children’s use of technology and more on the roles and competencies of adults and teachers to create environments that facilitate both digital and social-emotional learning.

On a final note, during the pandemic, out of necessity, schools use of novel digital approaches to education accelerated and there may be many studies published in the future which are relevant to Generation Alpha. As noted, this literature review captures only a small portion of the education research directed at this population as there are many studies that target this age group but do not use the term “Generation Alpha.” A primary takeaway from the review should be that experienced adults matter in the success of Generation Alpha. To be sure, there are also many tools and digital educational tools and online strategies being developed and tested but none have emerged to be dominant. Indeed, there is not even consensus on the best approach. There is still much research needed to produce evidence-based tools that can be recommended. What is happening in the education research on Generation Alpha is an increased recognition of their presumed digital capacity without a corresponding consensus on best educational practices. Future policies and practices would benefit from more specific research on how generational cohorts differ from one another in their exposure and experience with technology.

Data availability

No datasets were generated or analysed during the current study.

Abbasi AZ, Azeem S, Farooq MU, Hussain K, Ting DH, Rehman U, Pakpour AH. Engagement in educational games and quality of life in early and middle childhood: evidence from a developing country. Curr Psychology. 2022. https://doi.org/10.1007/s12144-022-03558-1 .

Article   Google Scholar  

Aberšek MK, Kerneža M. Primary school students’ functional literacy in digital learning environments-how to teach. In: Aberšek MK, Kerneža M, editors. The 14th international scientific conference on distance learning in applied informatics. Berlin: Researchgate; 2022. p. 174–85.

Google Scholar  

Abioso WS, Imam AI, Maulana YI, Prasetyo MJ. Virtual reality utilization as a character–building of children in waste problems. IOP Conf Ser Mater Sci Engin. 2021;1158(1): 012010. https://doi.org/10.1088/1757-899X/1158/1/012010 .

Aditya BR, Ismiatun AN, Atika AR, Permadi A. Digital disruption in early childhood education: a qualitative research from teachers’ perspective. Proced Computer Sci. 2022;197:521–8. https://doi.org/10.1016/j.procs.2021.12.169 .

Adnan AHM, Karim RA, Shah DSM, Tahir MHM, Shak MY. Higher education 4.0 technologies: survey of immersive, interactive content development and materials deployment within a developing nation. J Phys Conf Ser. 2021. https://doi.org/10.1088/1742-6596/1793/1/012002 .

Ahmad NF, Iksan ZH. Edmodo-based science module development on students’ mastery of science process skills: need analysis. Creat Educ. 2021;12(11):2609–23. https://doi.org/10.4236/ce.2021.1211195 .

Ahyar J, Edyansyah T, Ikramuddin I. Online learning strategies for indonesian language teachers in improving student learning effectiveness in class VII SMP Negeri Lhokseumawe. J Sosial Teknologi. 2021;1(12):1–526. https://doi.org/10.36418/jurnalsostech.v1i12.257 .

Aizenberg M, Zilka GC. Preservice kindergarten teachers’ distance teaching practices during the COVID-19 lockdown period. J Early Child Teach Educ. 2022. https://doi.org/10.1080/10901027.2022.2075813 .

Akkaya S, Zeynep TAN, Kapidere M. Examination of primary-school teachers’ views on digital game-based teaching. J Primary Educ. 2021;11:39–55. https://doi.org/10.52105/temelegitim.11.4 .

Akmal Y, Koeswantono S, Hartati S. Character development in generation alpha through social-emotional learning with parent involvement. In: Akmal Y, Koeswantono S, Hartati S, editors. 1st international conference on early childhood care education and parenting (ICECCEP 2019). Amsterdam: Atlantis press; 2020. p. 87–93.

AlNajdi SM. The effectiveness of using augmented reality (AR) to enhance student performance: using quick response (QR) codes in student textbooks in the Saudi education system. Educ Tech Res Dev. 2022;70(3):1105–24. https://doi.org/10.1007/s11423-022-10100-4 .

Anazifa RD. The role of technology in biology teaching during and post pandemic era. In: Anazifa RD, editor. 5th international conference on current issues in education (ICCIE 2021). Amsterdam: Atlantis press; 2022. p. 46–51.

Andysa S, Wildan M, Sarasevia F, Teguh W, Limantara N. Escape room mobile game design for remote learning. In: Andysa S, Wildan M, Sarasevia F, Teguh W, Limantara N, editors. 2022 international conference on information management and technology (ICIMTech). New York: IEEE; 2022. p. 339–44.

Chapter   Google Scholar  

Apaydin Ç, Kaya F. An analysis of the preschool teacher’s views on alpha generation. Eur J Educ Stud. 2020;6(11):123–40. https://doi.org/10.5281/zenodo.3627158 .

Aspari DC, Hartono M. The effectiveness of module and geogebra based learning media to improve mathematics learning outcomes of grade IV students. In: Aspari DC, Hartono M, editors. 2021 7th international conference on education and technology (ICET). New York: IEEE; 2021. p. 315–9.

Astapenko EV, Klimova TV, Molokhina GA, Petrenko EA. Personal characteristics and environmentally responsible behavior of children of the generation Alpha with different leisure orientation. E3S Web Conf. 2021;273:10042. https://doi.org/10.1051/e3sconf/202127310042 .

Aziz N, Ahmad SZ, Rahman WRZWA, Binsaleh S. Design and development of affective 4-dimensional mobile mathematics for low vision Alpha generation. TEM J. 2021;10(4):1828. https://doi.org/10.18421/TEM104-46 .

Azlan NAB, Zakaria SB, Yunus MM. Integrative task-based learning: developing speaking skill and increase motivation via instagram. Int J Acad Res Bus Soc Sci. 2019;9(1):620–36. https://doi.org/10.6007/IJARBSS/v9-i1/5463 .

Bağ H, Çalık M. Designing an argumentation-based educational digital game to teach the subject of force. Phys Educ. 2021;56(3): 035002. https://doi.org/10.1088/1361-6552/abdae8 .

Barradas R, Lencastre JA, Soares S, Valente A. The Code.org platform in the developing of computational thinking with elementary school students. In: Lane HC, Zvacek S, Uhomoibhi J, editors. Computer supported education. CSEDU 2020. Communications in computer and information science. Cham: Springer; 2021.

Bintoro T, Lestari I, Rofiqoh F. Learning media innovation: lift the flap book digital in increasing interest in learning science for third-grade elementary school students. J Penelitian Dan Pengemb Pendidikn. 2022. https://doi.org/10.3887/jppp.v6i2.50636 .

Bruggeman AL. Examining motivation, choice, and competency in 21 st century micro-schools: a comparative mixed-methods study of middle grade students’ perceptions of student agency. Nampa: Northwest Nazarene University; 2021.

Capelo, D. C., Sánchez, M. E., Hidalgo, C. L., & Chicaiza, D. B. Development and improvement of the visomotriz coordination: virtual game of learning and using the sphero haptic device for alpha generation. In: Á Rocha, T Guarda (Eds.) Proceedings of the International Conference on Information Technology & Systems (ICITS 2018 ). Springer International Publishing: Cham. 2018. Pp.907–916.

Carter C. The complete guide to generation alpha, the children of millennials. Washington: Forbes; 2016. p. 1–3.

Carvalho RN, Monteiro CEF, Martins MNP. Challenges for university teacher education in Brazil posed by the Alpha generation. Res Educ Learn Innov Archiv. 2022;28:61–76. https://doi.org/10.7203/realia.28.21408 .

Chitra A. Impact of socioeconomic status of parents’ on the emotional intelligence of generation Alpha kids. Int J Latest Technol Engin Manag Appl Sci. 2020;9(5):46–9.

Chowanda A, Prasetio YL, Fadhlurrahman N, Fadhlurrahman NR. Designing digital games as learning tools for mathematics. ICIC Expr Lett. 2020;14(9):927–34.

Churiyah M, Basuki A, Filianti F, Sholikhan S, Akbar MF. Canva for education as a learning tool for center of excellence vocational school (SMK pusat keunggulan) program to prepare competitive graduates in the field of creativity skills in the digital age. Int J Soc Sci Res Rev. 2022;5(3):226–34. https://doi.org/10.47814/ijssrr.v5i3.228 .

Davut ATIŞ. Teachers‘ views on the use of learning management systems. Political Econ Manag Educ. 2022;3(1):20–43. https://doi.org/10.13140/RG.2.2.28778.59848 .

Defit S, Achmad N, Dewi YN, Srinovita Y. Elementary school teacher quality improvement model based on literacy and technology. Int Conf Res Dev (ICORAD). 2022;1(1):210–7. https://doi.org/10.47841/icorad.v1i1.27 .

Delgado P, Vargas C, Ackerman R, Salmeron L. A meta-analysis on the effects of reading media on reading comprehension. Educ Res Rev. 2018;25:23–5. https://doi.org/10.1016/j.edurev.2018.09.003 .

Drugaș M. Screenagers or ‘screamagers’? Current Perspectives on Generation Alpha. Psychological Thought. 2021;15(1):1–11. https://doi.org/10.37708/psyct.v15i1.732

dos Reis TA. Study on the alpha generation and the reflections of its behavior in theorganizational environment. J Res Humanit Soc Sci. 2018;6(1):9–19.

Duggal K, Singh P, Gupta LR. Intrinsic and extrinsic motivation for online teaching in COVID-19: applications, issues, and solution. In: Duggal K, Singh P, Gupta LR, editors. Emerging technologies for battling Covid-19: applications and innovations. Cham: Springer International Publishing; 2021. p. 327–49.

Fadzil NM, Abdullah MY, Salleh MAM. The level of tolerance sanctioningchildren using gadgets by parents lead to nomophobia: early age gadgets exposure. Int J Arts Sci. 2016;9(2):615.

Fakhriyah S, Masfuah FS, Hilyana NM. Analysis of technological pedagogical content knowledge ((TPACK) ability based on science literacy for pre-service primary school teachers in learning science concepts. Indones J Sci Educ. 2022. https://doi.org/10.15294/jpii.v11i3.37305 .

Fauyan M. The role and competency of millennial teachers of SD/MI in the utilization of learning resources in the time Covid-19 pandemic. Proc Intal Conf Islam Educ (ICONIE). 2021;1(1):803–27.

Fernandez TE. Educating the homo digitalis: the role of education and digcomedu to palyate the effects of algorithms, fake news, polarization and lack of critical thinking. Vivat Acad Revista De Comunicación. 2021;154:71–92. https://doi.org/10.15178/va.2021.154.e1378 .

Fernando PA, Premadasa HS. Use of gamification and game-based learning in educating generation Alpha: a systematic literature review. Educl Technol Soc. 2024;27(2):114–32. https://doi.org/10.30191/ETS.202404_27(2).RP03 .

Galindo-Domínguez H, Bezanilla MJ. Digital competence in the training of pre-service teachers: perceptions of students in the degrees of early childhood education and primary education. J Digit Learn Teach Educ. 2021;37(4):262–78. https://doi.org/10.1080/21532974.2021.1934757 .

Ginting S, Tjandra M, Wianto E. Blended learning: post pandemic solutions. Aksara J Ilmu Pendidik Nonform. 2021;7(2):425–38. https://doi.org/10.7905/aksara.7.2.425-438.2021 .

Gon F, Yunus MM. The use of interactive digital phonics show (IDPS) to enhance phonological awareness among young learners. Int J Innov Res Creat Technol. 2019;5(1):1–8.

Hamimah H, Arlis S, Arwin A, Chandra C, Anita Y, Kenedi AK, Kharisma A. Thinking the most convenient analysis of alpha generation by using social science story digital books. İlköğretim Online. 2020. https://doi.org/10.17051/ilkonline.2020.654895 .

Hashim NA, Shaari ND. Malaysian teachers’ perception and challenges towards the implementation of flipped learning approach. Asian People J (APJ). 2020;3(2):62–76. https://doi.org/10.37231/apj.2020.3.2.196 .

Harikishni N, Attree AK. Parental perception of alpha kids’ Influence in general buying decisions during the covid-19 pandemic in India. Ramanujan Int J Bus Res. 2022;7(1):1–9. https://doi.org/10.51245/rijbr.v7i1.2022.361

Heiman T, Shemesh DO. Students with LD in higher education: use and contribution of assistive technology and website courses and their correlation to students’ hope and well-being. J Learn Disabil. 2012;45(4):308–18. https://doi.org/10.1177/0022219410392047 .

Howe N, Strauss W. Generations: the history of america’s future, 1584 to 2069. New York: William Morrow & Company; 1991. https://doi.org/10.1177/15366006930140020 .

Book   Google Scholar  

Ibharim L, Yatim MM, Zain NM, Azizan U, Fabil N. Development of rubric to measure children’s creativity in game design. Int J Multimed Appl. 2021;13(1):27–34. https://doi.org/10.5121/ijma.2021.13203 .

Ignaciuk, M. The educational potential of virtual reality in polish schools. Innov Teach Method. 2022: Pp. 65–84.

Jalaludin AM, Abas NA, Yunus MM. AsKINstagram: teacher-pupil interaction. Int JAcad Res Bus Soc Sci. 2019;9(1):125–36. https://doi.org/10.6007/IJARBSS/v9-i1/5369 .

Jukić R, Škojo T. The educational needs of the Alpha Generation. In: Jukić R, Škojo T. (Eds.) 2021 44th international convention on information, communication and electronic technology (MIPRO). 2021. Pp. 564-569

Kadir PM, Risagarnwia YY, Ma’mun, T. N. Arabic english Japanese learning program in madrasah diniyah takmiliyah (MDT): a study on the role of MDT in Bandung City. Humanit Soc Sci Rev. 2020;8(3):824–35. https://doi.org/10.18510/hssr.2020.8387 .

Kaliska, L. Trait emotional intelligence development possibilities of primary school-aged children. In: Kaliska, L.(Ed.) Education and New Learning Technologies 19 Proceedings. ‎IATED: Palma. 2019. Pp. 9801-9807

Kaplan-Berkley S. Digital tools and streaming media converge to inspire social interactions of generation alpha. Int J Early Childh. 2022;54(2):185–201. https://doi.org/10.1007/s13158-021-00301-y .

Karacan CG, Polat M. Predicting pre-service English language teachers’ intentions to use augmented reality. J Digit Learnn Teach Educ. 2022;38(3):139–53. https://doi.org/10.1080/21532974.2022.2083731 .

Karlimah K, Hamdu G, Pratiwi V, Herdiansah H, Kurniawan D. The development of motion comic storyboard based on digital literacy and elementary school mathematics ability in the new normal era during covid-19 pandemic. J Phys Conf Ser. 2021;1987(1): 012026. https://doi.org/10.1088/1742-6596/1987/1/012026 .

Kassim, N. F. B., & Petani, S. Enhancing knowledge through digital game-based learning: a case study among year two and three pupils. In The 14th Kuala Lumpur international communication, education, language, social sciences conference (KLiCELS14). 2020.

Kingsbury, I. Online learning: how do brick and mortar schools stack up to virtual schools? working paper 2020-4. EdChoice. 2020. https://doi.org/10.1007/s10639-021-10450-1

Kirschner PA, De Bruyckere P. The myths of the digital native and the multitasker. Teach Teach Educ. 2017;67:135–42. https://doi.org/10.1016/j.tate.2017.06.001 .

Kumala FN, Ghufron A, Pujiastuti P. Elementary school teachers‘ TPACK profile in science teaching based on demographic factors. Int J Instr. 2022;15(4):77–100. https://doi.org/10.29333/iji.2022.1545a .

Kurniawati N, Sofarini A, Maolida EH, Jatmika RTD. The praxis of integrating virtual reality into vocabulary teaching to young learners. Engl Rev J Engl Educ. 2022;10(2):371–80. https://doi.org/10.17244/eku.1175087 .

Kusumaningtyas EA, Sihombing RM. Designing picture book about the javanese vocabulary through lift a flap for children 4–5 years old. In: Kusumaningtyas EA, Sihombing RM, editors. ICON ARCCADE 2021: The 2nd international conference on art, craft, culture and design. Amsterdam: Atlantis press; 2021. p. 493–500.

Kralovicova B. Teaching comes naturally–or does it?: Environmental education in Indian primary schools and the impediments of its application from teachers’ perspectives. Thesis, Lund University Master of Science in International Development and Management. 2020.

Kusumawati Hidayat I, Rebelo F, Noriega P. Exploring children’s behavioral intention of using the expected game-based learning for protracted waste problem. In: Soares MM, Rosenzweig E, Marcus A, editors. Design, user experience, and usability: design for emotion, well-being and health, learning, and culture HCII 2022. Lecture notes in computer science. Cham: Springer; 2022. p. 265–78.

Kwon Y, Lemieux M, McTavish J, Wathen N. Identifying and removing duplicate records from systematic review searches. J Med Libr Assoc JMLA. 2015;103(4):184. https://doi.org/10.3163/1536-5050.103.4.004 .

Legvart P, Aberšek MK, Kerneža M. Developing communication competence in digital learning environments for primary science students. J Balt Sci Educ. 2022;21(5):836–48. https://doi.org/10.3225/jbse/22.21.836 .

Lemley JB, Schumacher G, Vesey W. What learning environments best address 21st-century students’ perceived needs at the secondary level of instruction? NASSPBulletin. 2014;98(2):101–25. https://doi.org/10.1177/0192636514528748 .

LiCalsi MK. A quasi-experimental examination of the effects of integrating robotics on elementary students‘ STEM-related perceptions. Scottsdale: Northcentral University; 2021. 

Lubis AH, Dasopang MD, Ramadhini F, Dalimunthe EM. Augmented reality pictorial storybook: how does it influence on elementary school mathematics anxiety? Prem Educ. 2022;12(1):522383. https://doi.org/10.25273/pe.v12i1.12393 .

Lucenko G, Hrechanyk N, Gavrilenko T, Lutsenko O. Using the project method as a means of developing the creative potential of primary school children in Ukraine. Education. 2022;3–13:1–10. https://doi.org/10.1080/03004279.2022.2053182 .

Malallah SA. Developing computational thinking best practices for early childhood education in Kuwait and United States. Manhattan: Kansas state university; 2022.

Maolida EH, Mulyana A, Adetia E, Rizki A. Collaborative planning and teaching english vocabulary with virtual reality: a community service in SD gunung batu cianjur. AJAD J Pengabd Kpd Masy. 2022;2(1):73–81. https://doi.org/10.35870/ajad.v2i1.40 .

Mariati P, Djazilan S, Hartatik S. Before the pandemic and its impact to the future about IoT and the transformation of children,s social education. Pegem J Educ Instr. 2022;12(2):95–102. https://doi.org/10.47750/pegegog.12.02.09 .

Masril M, Jalinus N, Hendrik B. Robotic education in 21st century: teacher acceptance of lego mindstorms as powerful educational tools. Int J Adv Comp Sci Appl. 2021;12(2):119–26. https://doi.org/10.4569/IJACSA.2021.0120216 .

Masry-Herzallah A, Stavissky Y. The attitudes of elementary and middle school students and teachers towards online learning during the corona pandemic outbreak. SN Soc Sci. 2021;1:1–23. https://doi.org/10.1007/s43545-021-00083-z .

McCrindle M, Fell A. Understanding generation alpha. Sydney: McCrindle Research; 2020.

Morze N, Boiko M, Varchenko-Trotsenko L, Vember V. Formation of internet resources critical evaluation skills of future primary school teachers. CPITS-II-2021 Cybersecur Provid Inform Telecommun Syst. 2021;3187:69–78.

Mullen LD. Supporting new-hire educators through onboarding intervention. Delaware: Wilmington University; 2021.

Mustadi A, Sayekti OM, Rochmah EN, Zubaidah E, Sugiarsih S, Schulze KM. Pancalis: Android-based learning media for early-reading in new normal. J Cakrawala Pendid. 2022;41(1):71–82. https://doi.org/10.21831/cp.v41i1.45883 .

Nacaroğlu O, Bektaş O, Tüysüz M. Examining the emotional semantic orientation of gifted students towards the flipped learning model. Technol Knowl Learn. 2023;28(1):117–42. https://doi.org/10.1007/s10758-021-09581-8 .

Nagy Á, Kölcsey A. Generation alpha: marketing or science? Acta Technologica Dubnicae. 2017;7(1):107–15. https://doi.org/10.1515/atd-2017-0007 .

Nopiyanti I, Adjie N, Putri SU. STEAM-PBL in early childhood education: optimization strategies for developing communication skills. In: Nopiyanti I, Adjie N, Putri SU, editors. 1st international conference on early childhood care education and parenting (ICECCEP 2019). Amsterdam: Atlantis press; 2020. p. 81–6.

Omar AC, Aziz N, Abd Muin MA. User experience on BM year 2 mobile-based learning application for alpha generation. Int J Interact Mobil Technol. 2021;15(6):65–76. https://doi.org/10.3991/ijim.v15i06.20639 .

Padmasari AC, Hernawan AH, Rostika D, Wahyuningsih Y. Usability testing of digital map application using hand gesture recognition as a historical learning media for elementary school. J Phys Conf Ser. 2021;1987(1): 012010. https://doi.org/10.1088/1742-6596/1987/1/012010 .

Page McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, Chou R, Glanville J, Grimshaw JM, Hróbjartsson A, Lalu MM, Li T, Loder EW, Mayo-Wilson E, McDonald S, Moher D. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71–n71. https://doi.org/10.1136/bmj.n71 .

Priyanti N, Warmansyah J. The effect of loose parts media on early childhood naturalist intelligence. J Pendidik Usia Dini. 2021;15(2):239–57. https://doi.org/10.21009/JPUD.152.03 .

Puspita BB, Edvra PA. The use of youtube and apps by digital moms to support early childhood learning. Athen J Mass Media Commun. 2022;8(4):237–56. https://doi.org/10.30958/ajmmc.8-4-2 .

Putri PKD, Adeni S. Parent-child interaction in distance learning during the corona virus disease 2019 (Covid-19) pandemic. Proc Int Conf Commun Sci. 2022;2(1):131–9. https://doi.org/10.29303/iccsproceeding.v2i1.84 .

Raja MAS, Gurung DJ, Vincent TN. Market segmentation framework for generation alpha cohorts. Productivity. 2021;62(3):248–54. https://doi.org/10.32381/PROD.2021.62.03.04 .

Rohaizat R, Nie A, Yunus M. Instagram interactive face filter to motivate speaking skill among year 5 ESL learners in rural sabah: pupils perception. Int J Acad Res Bus Soc Sci. 2021;11(7):1286–96. https://doi.org/10.6007/IJARBSS/v11-i7/10401 .

Rombot O, Boeriswati E, Suparman A. The development of blended learning model for reading comprehension learning of BIPA students in grade v elementary school. Ilkogr Online. 2021;20(5):1155–64. https://doi.org/10.17051/ilkonline.2021.05.126 .

Rose A, Thomas MR. Critical factors in the selection of educational toys for generation alpha. Specialusis Ugdymas. 2022;1(43):5199–218.

Rupel N, Selan J. The significance virtual experience for drawing performance of a 7-year old child. In: Vogrinc J, Bevetak I, editors. Contemporary topics in education IV. Slovenia: University of Ljubljana; 2022.

Rusman NS, Ismail HN, Jaafar SMRS. Demand of preschool education by alpha generation on edutainment leisure in the city. Intl J Built Environ Sustain. 2019;6(1–2):121–8. https://doi.org/10.11113/ijbes.v6.n1-2.391 .

Safaruddin S, Ibrahim N, Juhaeni J, Harmilawati H, Qadrianti L. The effect of project-based learning assisted by electronic media on learning motivation and science process skills. J Innov Educ Cult Res. 2020;1(1):22–9. https://doi.org/10.46843/jiecr.v1i1.5 .

Sarifah I, Rohmaniar A, Marini A, Sagita J, Nuraini S, Safitri D, Sudrajat A. Development of android based educational games to enhance elementary school student interests in learning mathematics. Int J Interact Mobil Technol. 2022. https://doi.org/10.3991/ijim.v16i18.32949 .

Sarnou D. Questioning the significance of technologizing Algerian schools and universities: did it fail or succeed. Int J Integr Technol Educ. 2020;9(1):1–13. https://doi.org/10.5121/ijite.2020.9101 .

Scarnavack H. Implementing technology in the classrooms to increase students‘ engagement and academic achievement. Trinity Christian College: Palos Heights; 2021.

Schawbel, D. (2014). Gen Y and Gen Z global workplace expectations study. Millennial branding news release. . http://workplaceintelligence.com/geny-genz-global-workplace-expectations-study .

Selvi V, Bhuvaneswari M, Sandra S. Stories: a tool to rejuvenate the culture of generation z and generation alpha. YMER Digital. 2022;21(1):267–76. https://doi.org/10.37896/ymer21.01/25 .

Shamir H, Pocklington D, Feehan K, Yoder E. Game-based learning for young learners. Int J Learn Teach. 2019;5:206–12. https://doi.org/10.18178/ijlt.5.3.206-212 .

Singh PKP, Hashim H. Using jazz chants to increase vocabulary power among ESL young learners. Creat Educ. 2020;11(03):262. https://doi.org/10.4236/ce.2020.113020 .

Sterbenz, C. (2015). Here‘s who comes after Generation Z and they‘ll be the most transformative age group ever. Bus Insider. https://www.businessinsider.com/generation-alpha-2014-7-2

Sugihartati R. Information seeking behavior in academic assignments using smartphone among elementary school students. Libr Philos Pract. 2019;11(19):1–17.

Suhaimi ND, Mohamad M, Nie WW, Yunus MM. Writing the whatsapp way. Int J Innov Res Creat Technol. 2018;4(3):51–6.

Sysoieva SO, Mospan NV. Trends in digital adaptation of schools during the Covid-19 pandemic. Inform Technol Learn Tool. 2022;91(5):21–35. https://doi.org/10.33407/itlt.v91i5.5063 .

Taylor LE. A millennial case study of literacy in minecraft based on the four resource model for reading. Cooranbong: Avondale College of Higher Education; 2017.

Teske SS. Teacher perspectives on values, motivation, and leadership through a generational lens. Macomb: Western Illinois University; 2020.

Thomas MR, Shivani MP. Customer profiling of alpha: the next generation marketing. Ushus J Bus Manag. 2020;19(1):75–86. https://doi.org/10.2725/ujbm.50.5 .

Turnbull S. Social media and higher education: an exploratory case study of the low rate of social media integration into classroom assignments. Chandler: Ashford University; 2020.

Twenge JM. IGen: Why today’s super-connected kids are growing up less rebellious, more tolerant, less happy— and completely unprepared for adulthood—and what that means for the rest of us. New York: Simon & Schuster; 2017. https://doi.org/10.1111/fcsr.12345 .

Twenge JM, Martin GN, Campbell WK. Decreases in psychological well-being among American adolescents after 2012 and links to screen time during the rise of smartphone technology. Emotion. 2018;18(6):765–80. https://doi.org/10.1037/emo0000403 .

Valek J, Hetmankova M, Kohout O. Digital competences of teachers in vocational education in the Czech republic. Online J Res Educ. 2022. https://doi.org/10.53349/resource.2022.iS24.a1115 .

Vedadi S, Abdullah ZB, Cheok AD. The effects of multi-sensory augmented reality on students’ motivation in English language learning. In: 2019 IEEE global engineering education conference (EDUCON). New York: Ieee; 2019. p. 1079–86.

Wallace-Spurgin M. Measuring student cognitive engagement when using technology, monument. ISTES Organization: San Antonio; 2019.

Xin TC, Yunus MM. Primary pupils use of social media to learn ESL. Int J Innov Technol Explor Engin. 2019;8(12):2076–80. https://doi.org/10.35940/ijitee.L3272.1081219 .

Yunus MM, Suliman A, Huei LS, Kai TF, Kiew S. The use of voca-lens to enhance the students vocabulary repertoire. Intl Jf Engl Lang Lit Stud. 2020;9(3):172–84. https://doi.org/10.18488/journal.23.2020.93.172.184 .

Ziatdinov R, Cilliers J. Generation Alpha: understanding the next cohort of university students. Eur J Contemp Educ. 2021;10(3):783–9. https://doi.org/10.13187/ejced.2021.3.783 .

Zulkifli N, Novianti R, Garzia M. The role of preschool in using gadgets for digital natives generation. J Pendidik Usia Dini. 2021;15(2):221–38. https://doi.org/10.21009/JPUD.152.02 .

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Yoga as a treatment for chronic low back pain: A systematic review of the literature

Douglas g. chang.

1 Department of Orthopaedic Surgery, University of California, San Diego, USA

Jacquelyn A. Holt

Marisa sklar.

3 Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, USA

Erik J. Groessl

2 VA San Diego Healthcare System, San Diego, USA

Chronic low back pain (CLBP) affects millions of people worldwide, and appears to be increasing in prevalence. It is associated not only with pain, but also with increased disability, psychological symptoms, and reduced quality of life. There are various treatment options for CLBP, but no single therapy stands out as being the most effective. In the past 10 years, yoga interventions have been studied as a CLBP treatment approach. The objective of this paper is to review the current literature supporting the efficacy of yoga for CLBP.

A literature search through the beginning of 2015 was conducted in Pub Med for randomized control trials addressing treatment of CLBP with yoga.

In this review we evaluate the use of yoga as a treatment for CLBP. Specifically we evaluate how yoga impacts physical functioning and disability, pain, and associated psychological symptoms. We also evaluate possible mediators of the effect of yoga and the safety of yoga.

With few exceptions, previous studies and the recent randomized control trials (RCTs) indicate that yoga can reduce pain and disability, can be practiced safely, and is well received by participants. Some studies also indicate that yoga may improve psychological symptoms, but these effects are currently not as well established.

Introduction

About one fourth of United States adults report low back pain, lasting a whole day or more, at some point within the past 3 months [ 1 ]. It is the most common cause of limited activity in people below the age of 45, is the second most frequent reason for visits to a physician, the third most common reason for surgery, and the fifth most common cause of hospital admission in the United States [ 2 ].

The majority of individuals with back pain and sciatica recover from an acute episode in 4–8 weeks [ 3 – 5 ]. 80–90% return to work within 12 weeks post injury [ 6 ]. However 25–80% of low back pain patients experience some form of recurrent back problem in the following year [ 4 , 5 , 7 , 8 ]. Among those who suffer from an episode of low back pain, one year later as many as 33% have moderate intensity pain, and 15% may have severe pain [ 7 ].

People suffering from chronic low back pain have other associated problems such as anxiety [ 9 – 11 ], depression [ 12 , 13 ], and disability [ 2 , 14 ], with a reduced quality of life [ 15 , 16 ]. Rates of major depression are 20% for persons with chronic back pain, compared to 6% for pain-free individuals [ 13 ].

The word “yoga” literally means “yoking”, or “joining together” for a harmonious relationship between body, mind and emotions to unite individual human spirit with divine spirit or the True Self [ 17 , 18 ]. Yoga involves a process of physical and mental training towards self-realization, the practice of which has eight component limbs. The eight components guide conduct within society, personal discipline, postures/poses (“asanas”), breathing, concentration, contemplation, meditation and absorption/stillness. As classically described, yoga poses comprise just one of the eight components of a broader discipline of physical, mental, and spiritual health. Modern Hatha yoga usually combines elements of postural positioning, breathing, concentration, and meditation. A typical Hatha yoga program involves a group led by an instructor for a ~ 60–90 minute session. The instructor provides guidance for correct postures, breathing and focus. They often encourage positive self-images. Iyengar yoga has a focus on holding postures, and the use of modifications (such as blocks, belts, chairs, blankets) to accommodate individual physical abilities. Other yoga styles exist and the experience in one style or class can be very different. The intensity can range from gentle to strenuous, with some types of yoga providing a cardiovascular workout, and others focused on relaxation and calmness. Another experiential factor comes from the yoga center itself, which can provide a sense of social and spiritual community.

Yoga popularity has grown tremendously in the past several years. National Health Interview Survey data conducted by the Centers for Disease Control and Prevention (CDC) show increased usage for complementary and alternative medicine (CAM) treatments [ 19 ]. In 2007, yoga was the 7 th most commonly used CAM therapy. CAM therapies are used mostly to treat musculoskeletal conditions, in particular back pain and to a lesser degree neck pain.

CLBP pain affects millions of people. There are many treatment options, but few have strong evidence for being effective [ 20 , 21 ]. Several randomized control trials (RCT) about yoga’s effect on low back pain have been completed; however they have varying outcome measures about pain and functional disability. A few meta-analysis studies were completed with 2011 searches, generally showing a positive effect, but limited in general by a relatively small total number of eligible RCTs [ 22 – 25 ].

Holtzman et al. conducted an electronic search in 2011 to identify 8 yoga articles, with a focus on pain and functional disability [ 23 ]. Ward et al. searched through different databases, also in 2011, to identify 17 articles on functional disability, pain and depression [ 24 , 25 ]. However the relevance and quality of the articles was limited. Of the 17 articles, 12 were focussed on back pain. These 12 included two pilot studies considered of poor methodological quality, and only three of the identified CLBP studies were considered to have an acceptable adherence to the intervention. Cramer et al. also searched through 2011 articles and focused on the outcomes of pain, disability, and quality of life. They used yet another statistical method to winnow a list of yoga and low back pain papers down to 8 studies [ 22 ]. Although the Holtzman et al., Ward et al. and Cramer et al. studies used very different search strategies, they all winnowed down their findings in different, semi-objective fashions to an essentially identical, smaller list of yoga studies for further consideration.

This report is unique with updates not available in the older review articles [ 21 – 25 ]. This paper reviews randomized control trials, as well as randomized studies, comparing yoga to current exercise interventions. In addition, this paper reviews the findings in the existing literature as they relate to physical functioning and disability, pain, and psychological factors, as well as a review of findings on the biological mechanisms of yoga on back pain.

Materials and Methods

A search in PubMed was conducted in the beginning of 2015 for randomized control trials of yoga and low back pain. The initial search of “yoga and back pain” identified 128 articles. Study reports without abstracts were excluded, returning 106 articles. Titles and abstracts were then screened for relevance to yoga and back pain, resulting in 27 articles (see Figure 1 ).

Flow chart representing the search and selection of articles for review.

These articles underwent full text review. For this project, inclusion criteria included (1) yoga was actually studied as an intervention, (2) research subjects had medically diagnosed low back pain, (3) low back pain was chronic, (4) an original article, (5) a clinical trial, (6) study involved n≥20 subjects, (7) published in English. 14 study reports were determined to be eligible for review after this full text screening. These studies underwent extensive review and were rated using the Oxford Centre for Evidence Based Medicine 2011 Levels of Evidence criteria [ 26 , 27 ]. Most of the papers reviewed are level 2–4, with the majority being level 2 ( Table 1 ). Due to the variety of outcome measures reported in the articles reviewed, we divided this paper into several outcome categories including: impact of yoga on physical functioning and disability, the impact of yoga on pain, psychological impacts of yoga, and biological mechanism of yoga on back pain.

Physical functioning and disability

Yoga treatment studies of CLBP typically utilize some measure of physical functioning and disability as a primary outcome. Such outcomes can be tied to physiological performance, or validated questionnaires with specific behavioral items. Most yoga studies do demonstrate beneficial effects for adults suffering from CLBP ( Table 1 ).

A small randomized controlled trial, pilot study demonstrated trends for the yoga group in terms of improved balance and flexibility, and decreased disability and depression [ 28 ]. However, the study was weakened by the small sample size (n=22 participants) and a high dropout rate among the control group. As such, no statistical significance was observed.

The impact of Iyengar yoga therapy was assessed in a 16-week, randomized controlled trial involving subjects with non-specific CLBP compared to an educational control group [ 29 ]. The yoga subjects had less pain (Short Form-McGill Pain Questionnaire) and lower functional disability (Pain Disability Index) than the controls. Unfortunately there was a 30% drop-out rate in this study. Williams et al. conducted another 24-week study that showed significantly greater reductions in functional disability (Oswestry Disability Index), pain intensity (Visual Analog Scale) and depression (Beck Depression Inventory-Second Edition) among the subjects randomized to the yoga intervention group [ 30 ]. Both of these studies were limited by a reliance on self-report measures, a relatively healthy study population, and lack of controls for attention and physical activity between the treatment and control groups [ 29 ].

80 patients with CLBP participated in an intensive seven day long, residential yoga program. The effect of yoga on disability (Oswestry Disability Index), quality of life (World Health Organization Quality of Life-BREF) and flexibility was studied [ 31 , 32 ]. The intervention group practiced daily meditation, yoga exercise, chanting and went to lectures. The control group followed a daily routine of exercise, non-yogic breathing exercises, educational lectures and additionally filled their time watching nature programs. This control is different than the usual or no care control used in other studies. There was a significant difference in disability between groups, with the yoga group experiencing a greater improvement than the control group. The yoga group showed a greater increase in flexibility and reduction in pain (section 1 of the Oswestry Disability Index) than the control group [ 31 , 32 ].

Predictors of outcome were studied in 53 adults who were already involved either with yoga or a physical therapy intervention to treat CLBP. No significant differences in disability (Roland-Morris Disability Questionnaire) were seen at 6 weeks [ 33 ]. A major finding in both groups was that back pain self-efficacy was the most important predictor of pain, health status and disability. Self-efficacy refers to an individual’s belief in the capacity to change outcomes through their own actions, and was measured by the Back Pain Self-Efficacy Scale. A significant limitation of this study is the presence of self-selection bias because the participants were already enrolled/self-selected into the yoga or physical therapy groups prior to the study.

The effects of yoga on balance and gait were studied in an 8 week pilot study involving adult women (n=27) with musculoskeletal problems, such as osteoarthritis and low back pain [ 34 ]. The subjects’ balance and gait parameters were statistically improved compared to the pre-study values. The small sample size and lack of control group in this study make it difficult to attribute the improvements exclusively to the yoga intervention. Additionally the study failed to describe the nature of the relatively young (age 30–45 yrs) subjects’ musculoskeletal problems in any detail.

The effect of yoga on physical functioning has been described in two large randomized trials [ 35 , 36 ]. Sherman et al. studied yoga compared to stretching or a self-care book approach for patients with chronic low back pain [ 35 ]. In all the groups, function and symptoms improved over time. The yoga and stretching groups reported similarly improved results compared to the self-care group. The authors concluded that yoga benefits are due mainly to the benefits of physically stretching and strengthening the body, and not due to yoga’s mental aspect.

Tilbrook et al. studied the long-term effectiveness of a 12-week yoga program versus a back pain education booklet for low back pain patients [ 36 ]. The yoga group had significantly better back function (Roland-Morris Disability Questionnaire) than the usual care group at 3, 6, and 12 months follow-up. This study did not see any difference between interventions, in a secondary outcome, the Aberdeen Back Pain Scale for health related function and pain [ 37 , 38 ]. However this scale is noted to have significant weaknesses and is not suggested anymore for use [ 39 ].

A randomized dosing trial compared once versus twice-weekly yoga classes for CLBP in predominantly low income, racially diverse and more severely impaired populations [ 40 ]. Subjects (n=95) completed a 12-week intervention. Pain and back-related function improved in both groups, with no difference between the once and twice-weekly groups. There were several study limitations including the inability to blind participants, the use of self-reported measures, lack of a non-yoga control group, differential adherence between groups, high use of non study treatments, and no long-term follow up. The results suggest in an underserved population, weekly yoga classes do not increase benefit and present more difficult compliance issues.

A four-week, randomized control trial of a virtual reality-based Wii yoga program versus physical therapy and trunk stabilizing exercise in 30 middle-aged women with low back pain was presented [ 41 ]. Significantly improved outcomes were observed in both groups, for pain (visual analog scale), function (Oswestry low-back pain Disability Index, Roland-Morris Disability Questionnaire), and fear (fear avoidance beliefs questionnaire) scores. There were financial and time benefits provided to the middle aged women by the home, virtual reality based program. Limitations of this study included the lack of a traditional yoga control group, and the lack of frequency and dosing of exercise information in the control group. Another limitation is the specific age range and gender of the subjects, but as discussed by the authors the target group is middle aged women who have significant demands on their time and money for housekeeping and childrearing activities.

A number of studies demonstrate yoga’s effectiveness in reducing chronic low back pain. Williams et al. evaluated clinical levels of pain (using the Short Form-McGill Pain Questionnaire), pain-related fears to movement (Tampa Scale of Kinesiophobia), and pain beliefs (Survey of Pain Attitudes) [ 29 ]. The yoga intervention resulted in a two times greater reduction in pain, and reduced pain medication usage, compared to the educational control group. There was no significant difference in pain attitudes or movement fears, perhaps due to the study not having enough statistical power for these outcomes. Williams et al. further demonstrated the effectiveness of a 24 week Iyengar yoga program on improving chronic low back pain [ 30 ]. Individuals randomized to the yoga group showed greater improvements in pain intensity than in the control group.

A single group, pre-post study of military veterans who participated in a clinical yoga program at a large VA medical center showed improvement for pain between baseline and 10-weeks [ 42 ]. Pain was measured using a visual pain scale modification of the visual analog scale. Among the various indicators of the yoga “dosing” (i.e. amount of intervention), decreased pain was significantly correlated to the actual attendance. Additional analysis of this same study demonstrated that females experienced greater improvements in pain compared to the males [ 43 ]. The women had significantly greater improvements on depression, pain “on average”, energy, and Short-form 12 mental health. No gender difference was demonstrated for pain “at its worse”, total pain score, or Short-Form 12 physical health.

Saper et al. studied the effect of yoga on back pain among low income, racially diverse subjects [ 40 ]. The average low back pain intensity for the previous week (as measured by the Visual Analog Scale), was significantly reduced from 7 to 5 after the 12 week intervention, regardless of whether subjects attended once-or twice-weekly yoga classes [ 40 ].

Sherman et al. measured pain “bothersomeness” instead of pain severity because of the complex nature of pain [ 44 ]. Subjects rated their back pain during the previous week on an 11-point scale, from “not at all” to “extremely” bothersome, in response to a 12-week yoga, exercise or book education intervention. All interventions were helpful, but the yoga and exercise groups improved

Back pain “bothersomeness” was studied in individuals already involved either with yoga or a physical therapy intervention [ 33 ]. Both interventions helped, and there were no significant group differences between yoga and physical therapy after 6 weeks of treatment. However, the baseline characteristics of the yoga group were such that they demonstrated less back pain and disability to begin with.

A randomized control trial evaluated the impact of Iyengar yoga on pain intensity (Visual Analog Scale) and health related quality of life in subjects with nonspecific chronic low back pain [ 45 ]. The study compared yoga therapy to conventional exercise therapy, with 6 month follow up. Both interventions resulted in significant benefits, with the yoga intervention having the greater impact.

Psychological impact of yoga

Yoga’s effect on psychological health has not been well characterized in the scientific literature to date. Galantino et al. conducted a pilot study of depression and a Hatha yoga intervention [ 28 ]. As mentioned, this study had a small sample size and a high dropout rate. They demonstrated a non-significant trend towards decreased depression in their yoga intervention group.

Groessl et al. studied the effect of yoga on depression and quality of life (Short-Form 12 version 2) in veterans with back pain [ 42 ]. They found significant improvements in depression, and a trend towards significant improvements for the Mental Health Scale of the SF-12. The improvement in depression tended to be associated with the subjects’ self-reported amount of home practice.

The impact of Iyengar yoga on depression (Beck Depression Inventory) was studied in subjects with CLBP [ 30 ]. The subjects randomized to the yoga group showed greater improvements in depression than those in the control group. One limit of the study was that yoga group received more attention than the self-directed control group. Another limit was the lack of controls for physical activity between the groups.

Tekur et al. found their yoga group experienced significantly greater improvements in the psychological subscale of their quality of life scale (World Health Organization Quality of Life-BREF) compared with the controls [ 32 ]. However, this residential-based study involved additional elements (i.e. 8 hours a day of interactive lectures, chanting, meditation sessions) than typical Hatha or Iyengar yoga interventions. Furthermore, this was only a short-term (i.e. 1 week follow up) study.

One randomized controlled trial [ 36 ] and an affiliated pilot study [ 46 ]studied yoga versus “usual care” with the mental health ShortForm 12. The pilot study found no significant difference, but it was under-powered (n =20) [ 46 ]. Their follow-up study was adequately powered. They still found no significant difference in mental health function at the 3-, 6- and 12 month assessments (although the 3- and6-month assessments demonstrated a trend towards improvement)[ 36 ].

Biological mechanisms of yoga on back pain

A few studies have explored the mechanisms by which yoga might affect back pain. Sherman et al. and Lee et al. investigated several possible mediators, including serotonin, cortisol, dehydroepiandrosterone (DHEA), and brain derived neurotrophic factor (BDNF) [ 47 , 48 ]. Additionally Sherman et al. investigated psychological factors that may mediate the effect of yoga on back pain.

These factors included cognitive appraisal measures (fear avoidance, self-efficacy and self-awareness), affect and stress (psychological distress, perceived stress and positive states of mind), physical activity, and neuroendocrine function [ 47 ]. Neuroendocrine function was measured with cortisol and DHEA levels from saliva samples. The goal was to identify which measure had the biggest effect on back-related dysfunction (Roland-Morris Disability Questionnaire) in the yoga versus stretching versus self-care groups. Self-efficacy, and hours of back exercise were the most significant contributors to the effect of yoga. Sleep disturbance also played a small role. No effect was seen from cortisol or DHEA levels. Yoga and stretching had similar effects. One limit was the fairly healthy study population.

Lee et al. investigated the effect of yoga on pain, BDNF, and serotonin in premenopausal women with chronic low back pain [ 48 ]. The yoga group had decreased pain, increased BDNF and unchanged serotonin. The untreated control group had increased pain, decreased BDNF and decreased serotonin. This suggested that the beneficial effects of yoga are associated with elevated serum BDNF levels and maintained serotonin levels. There were several limitations including small sample size, gender bias, and a control group that could better account for group socialization effects. It’s also not clear why the control group exhibited increased pain after the intervention.

Safety of yoga

Low back pain itself is a persistent condition with a known high rate of recurrence and a high rate of incomplete resolution [ 8 , 49 ]. Therefore in studying subjects with back pain, it would not be surprising to see occasional adverse events. Overall, however, it does not appear that yoga presents a significantly increased risk for normal individuals or patients with back pain. In one study, among 30 subjects randomized to yoga, one adverse event was reported [ 29 ]. That subject had symptomatic osteoarthritis and was diagnosed with a herniated disc during the study. Medical review of the adverse event by the Institutional Review Board determined it was unrelated to the yoga postures.

No serious adverse events were reported among 101 subjects in yoga versus exercise trial [ 44 ]. One yoga participant discontinued class due to migraine headaches, one exercise participant ‘strained’ her back and sought care from a chiropractor. More recently, Sherman et al. found an equal number of mild to moderate adverse events (mostly temporarily increased back pain) among the subjects in both the yoga and a more traditional stretching intervention [ 35 ]. One of the 87 yoga class subjects experienced a serious event, a herniated disc. One in the self care control group reported increased pain. Despites these adverse events, overall the yoga and stretching groups had moderately improved outcomes.

8% of 156 yoga participants and 1% of 157 usual care participants reports adverse events in the study by Tilbrook et al. [ 36 ]. In the yoga group, 11 events were nonserious and related to temporarily increased pain. 1 event was serious, and occurred in an individual with a history of severe pain after any physical activity. In the usual care group there was actually a death, and also an injury unrelated to the intervention.

In a comprehensive review of non-pharmacological and non-invasive therapies for chronic low back pain, there were discovered only rare reports of serious adverse events [ 50 ]. However, better reporting of harms was suggested as a need.

Low back pain risk factors include previous back pain episodes, high physical demands of work, low job satisfaction, age, back weakness, and smoking [ 51 – 53 ]. Care seeking and disability due to chronic low back pain depend more on psychosocial issues than on individual clinical features or workplace physical demands [ 53 ]. Identifying and addressing these psychosocial factors helps improve outcomes and limit costs [ 20 ].

Among the treatments for CLBP, there is variable evidence to support effectiveness of non-pharmacologic [ 50 ], and medication [ 54 ]management. Yoga, in comparison to spinal manipulation, physical therapy, and acupuncture, may be more cost effective because it can be delivered in a group format and self-administered at home. However, actual cost analysis of yoga interventions is needed.

This literature review suggests that yoga is effective in reducing pain and disability, and improving both physical and mental function. The Sherman et al. study employ used a three-arm intervention, and thus, provides important “comparative effectiveness” data by comparing yoga to a conventional stretching program led by physical therapists and a self-care book from primary care providers [ 35 ]. A few key points derive from their work, which is supported also by other research [ 33 ]. Yoga was not superior in effectiveness compared to conventional stretching. Self-efficacy and hours of back exercise may be the most important factors for both conventional exercise therapy and yoga.

To this point, compared to traditional exercise programs derived physical therapy, yoga could provide superior compliance and benefit in the long term. Yoga poses, once learned, might be more easily remembered by patients because the poses and their associated names tend to have universal recognition. Yoga programs, even ‘adaptive’ or ‘senior’ classes, are accessible in most cities, at studios, local gyms, recreation centers and hotel wellness centers. In contrast, patients finishing a physical therapy program may receive a variety of suggested exercises with no standardization, and little similar to what another physical therapist might dispense. Patients can lose, forget or not even receive a home exercise program from their therapists at the conclusion of a formal physical therapy prescription. Long term outcome studies are needed to explore this hypothesis because most yoga studies to date have lasted less than 26 weeks, with the exception of the study by Tilbrook et al. [ 36 ].

Yoga, with its spiritual and psychological underpinnings, potentially might provide greater mental health benefits compared to traditional physical therapy. However, the impact of yoga on depression has been evaluated in only a small number of studies. Significant effects on depression were found in two studies [ 30 , 42 ], but only non-significant trends were found for the Mental Health Scale SF-12 [ 42 ]. Sherman et al. found that self-efficacy and also sleep were important psychological benefits of yoga on low back pain [ 47 ]. With the high rates of depression among sufferers of CLBP, further research in this area is needed [ 20 ]. To what extent yoga may impact other mental health conditions (e.g. anxiety disorders, which are not as well measured by the SF-12) is also an important research direction.

Lastly, safety data from the largest and most recent trials suggest about a 10–15% incidence of temporarily increased low back pain, and two identified cases of herniated disc. It appears that yoga participation is not without risks. However, the great majority of participants do appear to experience considerable benefits without many problems.

Overall, yoga is an intervention which appears to be well positioned, as the healthcare system shifts from caring mostly for patients with acute illness to caring mostly for patients with chronic disease, and where healthcare providers seek to design preventative strategies against the chronic conditions of modern society. More specifically, because it is a reflective activity, yoga may find particular application among military veterans who must live with the long term effects of wartime trauma [ 55 ].

Yoga appears as effective as other non-pharmacologic treatments in reducing the functional disability of back pain. It appears to be more effective in reducing pain severity or “bothersomeness” of CLBP when compared to usual care or no care. Yoga may have a positive effect on depression and other psychological co-morbidities, with maintenance of serum BDNF and serotonin levels. Yoga appears to be an effective and safe intervention for chronic low back pain.

Acknowledgments

This research was partly supported by the grant, NIH/VA RRDC RX000474

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Metabolomic biomarkers of multiple myeloma: A systematic review

Affiliations.

• 1 Department of Pharmacology, Sechenov First Moscow State Medical University (Sechenov University), Vernadskogo pr., 96, 119571 Moscow, Russia; Centre of Biopharmaceutical Analysis and Metabolomics, Institute of Translational Medicine and Biotechnology, Sechenov First Moscow State Medical University (Sechenov University), Nakhimovsky pr., 45, 117418 Moscow, Russia. Electronic address: [email protected].
• 2 Centre of Biopharmaceutical Analysis and Metabolomics, Institute of Translational Medicine and Biotechnology, Sechenov First Moscow State Medical University (Sechenov University), Nakhimovsky pr., 45, 117418 Moscow, Russia. Electronic address: [email protected].
• 3 Hospital Therapy No. 1 Department, Sechenov First Moscow State Medical University (Sechenov University), Bol'shaya Pirogovskaya st. 6/1, 119435 Moscow, Russia.
• 4 Department of Pharmacology, Sechenov First Moscow State Medical University (Sechenov University), Vernadskogo pr., 96, 119571 Moscow, Russia; Centre of Biopharmaceutical Analysis and Metabolomics, Institute of Translational Medicine and Biotechnology, Sechenov First Moscow State Medical University (Sechenov University), Nakhimovsky pr., 45, 117418 Moscow, Russia.
• PMID: 38986721
• DOI: 10.1016/j.bbcan.2024.189151

Multiple myeloma (MM) is an incurable malignancy of clonal plasma cells. Various diagnostic methods are used in parallel to accurately determine stage and severity of the disease. Identifying a biomarker or a panel of biomarkers could enhance the quality of medical care that patients receive by adopting a more personalized approach. Metabolomics utilizes high-throughput analytical platforms to examine the levels and quantities of biochemical compounds in biosamples. The aim of this review was to conduct a systematic literature search for potential metabolic biomarkers that may aid in the diagnosis and prognosis of MM. The review was conducted in accordance with PRISMA recommendations and was registered in PROSPERO. The systematic search was performed in PubMed, CINAHL, SciFinder, Scopus, The Cochrane Library and Google Scholar. Studies were limited to those involving people with clinically diagnosed MM and healthy controls as comparators. Articles had to be published in English and had no restrictions on publication date or sample type. The quality of articles was assessed according to QUADOMICS criteria. A total of 709 articles were collected during the literature search. Of these, 436 were excluded based on their abstract, with 26 more removed after a thorough review of the full text. Finally, 16 articles were deemed relevant and were subjected to further analysis of their data. A number of promising candidate biomarkers was discovered. Follow-up studies with large sample sizes are needed to determine their suitability for clinical applications.

Keywords: Amino acids; Biomarkers; Diagnosis; Lipid metabolism; Metabolomics; Multiple myeloma; Prognosis; Systematic review.

Copyright © 2024 Elsevier B.V. All rights reserved.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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