Effectiveness of biofeedback therapies in pediatric populations: An umbrella review

Effectiveness of biofeedback therapies in pediatric populations: An umbrella review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Effectiveness of biofeedback therapies in pediatric populations: An umbrella review Maanya V, Dhananjaya G, Denny John, Ramesh Debur This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8594886/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To assess the effectiveness of biofeedback therapies in children and adolescents Introduction: Biofeedback is a mind–body intervention that uses real-time physiological feedback to help individuals regulate bodily functions through behavioural modification, potentially reducing symptoms related to pain, attention, movement, and emotional control. Inclusion criteria: Systematic reviews, with or without meta-analysis, evaluating biofeedback therapies in children and adolescents were included regardless of medical condition or disability. Outcomes of interest included attention, cognitive function, functional mobility, behaviour, emotional regulation, and quality of life. Methods A comprehensive search up to July 2025 was conducted in MEDLINE (PubMed), Scopus, CINAHL, Cochrane Database of Systematic Reviews, JBI Evidence Synthesis, ProQuest Dissertations and Theses, and Epistemonikos, with supplementary searches in Google Scholar and OAIster. Study selection, data extraction, and critical appraisal were performed independently by two reviewers. Findings were summarised using tables and narrative synthesis. Evidence certainty was assessed using GRADE, and reporting followed PRIOR guidelines. Results Six systematic reviews published between 2015 and 2025, including approximately 2,600 pediatric participants, were analysed. Neurofeedback, particularly theta/beta ratio and slow cortical potential protocols, demonstrated moderate improvements in ADHD symptoms, mainly inattention and impulsivity. EMG biofeedback improved motor outcomes such as gait performance in children with cerebral palsy. HRV biofeedback showed potential benefits for emotional regulation. Study heterogeneity limited cross-review comparability. Conclusion Biofeedback therapies show promising benefits across several pediatric conditions, particularly ADHD and cerebral palsy. Nonetheless, methodological variability highlights the need for standardized protocols and further high-quality research. Pediatrics Biotechnology and Bioengineering Translational Medicine biofeedback Pediatrics effectiveness disorders Figures Figure 1 Figure 2 Introduction Managing chronic pain, anxiety, attention-deficit/hyperactivity disorder (ADHD), and psychosomatic conditions in children during medical procedures remains difficult. This has increased interest in nonpharmacological approaches, including biofeedback-assisted relaxation and virtual reality–based distraction. Biofeedback enables voluntary regulation of physiological responses and has been applied across medical conditions. Evidence supports its use in psychological and neurological disorders such as anxiety, depression, ADHD, post-traumatic stress disorder, insomnia, seizure disorders, and primary headache syndromes [1–4]. Biofeedback has also shown benefit in cardiovascular and autonomic disorders, including hypertension, Raynaud’s disease, cardiac arrhythmias, and vasovagal syncope, through autonomic regulation [1,4]. In gastrointestinal disorders, it improves symptoms of irritable bowel syndrome, constipation, and faecal incontinence via enhanced sphincter control [5,6]. Similar mechanisms support its use in musculoskeletal and neuromuscular rehabilitation, with reported benefits in urinary incontinence, pelvic floor dysfunction, post-injury recovery, and continence in children with dysfunctional voiding using pelvic floor electromyographic (EMG) biofeedback [1,4–7]. In paediatric rehabilitation, EMG biofeedback has been associated with functional improvements in juvenile rheumatoid arthritis, Guillain–Barré syndrome, and cerebral palsy [8–11]. Advances in wearable devices now provide real-time feedback and support emotional regulation and gait and balance training, improving feasibility of home-based interventions in children [11–19]. In dental and craniofacial care, occlusal biofeedback splints have reduced temporomandibular joint dysfunction pain and sleep bruxism. Biofeedback-assisted relaxation with audiovisual distraction has reduced dental anxiety in children aged 7–12 years [20,21]. Although prior umbrella reviews have examined psychological, pharmacological, and brain-stimulation interventions in youth [22,23], none focused specifically on biofeedback. Despite numerous systematic reviews evaluating paediatric biofeedback interventions [24–31], there is a lack of comprehensive umbrella review synthesising biofeedback-specific evidence in children and adolescents. This umbrella review addresses this gap by evaluating the effectiveness of key biofeedback modalities across paediatric neurodevelopmental, mental health, and chronic pain conditions. Review question What is the effectiveness of biofeedback therapies in paediatric populations based on published systematic reviews? Inclusion criteria Participants This umbrella review included systematic reviews of studies involving children and adolescents aged 4–18 years, irrespective of underlying medical conditions. Established criteria were applied to enhance consistency and comparability, and data from mixed populations were stratified for children or adolescents where appropriate. Interventions This umbrella review examined biofeedback as a therapeutic modality across a range of systemic conditions. Biofeedback enables individuals to modify physiological functions such as breathing, heart rate, muscle activity, skin temperature, and brainwave patterns through real-time feedback, supporting long-term self-regulation [1–4]. Comparators This umbrella review considered systematic reviews that included a control group, either a placebo or alternative treatments. Outcomes This umbrella review included studies with primary outcomes considered for the effectiveness of biofeedback therapies, being “Functional Mobility and Quality of Life improvement” [27], “Improvements in attention and cognitive function” [28], “Behavioural improvements and emotional regulation” [25, 28]. Any follow-up period outcomes were also included. Context All clinical settings were included in this review to enhance the generalizability of the results. No restrictions were imposed on the review's scope, and it incorporated systematic reviews of research conducted in general or public hospitals, as well as in private clinics. Also, no geographical restrictions were imposed on context. Type of studies This umbrella review included quantitative systematic reviews evaluating the effectiveness of biofeedback therapy in pediatric populations, with or without meta-analysis, across a range of experimental study designs. Reviews of mixed adult and pediatric populations were included only if separate syntheses for children or adolescents were provided. Opinion-based, narrative, qualitative, or textual reviews were excluded. Eligible reviews were required to use a well-defined, multi-database search strategy and to include critical appraisal or risk-of-bias assessment [32]. Methods The umbrella review was conducted in accordance with the JBI methodology for umbrella reviews [33]. The protocol was registered with PROSPERO (CRD42024604976). To ensure comprehensive reporting, the review followed the PRISMA guidelines [34]. Search strategy The search strategy aimed to identify both published and unpublished systematic reviews, with or without meta-analysis. An initial search was conducted in MEDLINE (PubMed), and relevant titles, abstracts, and index terms were used to develop a comprehensive search strategy for subsequent databases (Supplementary Appendix 1). Each database was searched using tailored combinations of keywords and index terms, and reference lists of included reviews were screened to identify additional relevant studies. Searches were limited to English-language publications from inception to July 2025, and withdrawn publications were excluded. Seven databases were searched: MEDLINE (Ovid), Scopus, CINAHL (EBSCOhost), the Cochrane Database of Systematic Reviews, JBI Evidence Synthesis (Ovid), ProQuest Dissertations and Theses, and Epistemonikos. Although Embase was specified in the protocol, it could not be searched due to access limitations. Grey literature sources, including Google Scholar and OAIster, were also screened. Initial MEDLINE search terms included “biofeedback,” “biofeedback therapy,” “neurofeedback,” “myofeedback,” and “pediatric,” filtered for “systematic review” or “meta-analysis.” Study selection Following the search, records were imported into Mendeley v2.64 and duplicates were removed. After a pilot test of 20 records, two reviewers independently screened titles and abstracts against the inclusion criteria. Full-text screening was conducted using Rayyan, with eligibility independently assessed by two reviewers. Reasons for exclusion were documented (Supplementary Appendix 3), and disagreements were resolved through discussion or by a third reviewer. Study selection was reported using a PRISMA flow diagram [34]. To account for overlapping primary studies across included systematic reviews, a citation matrix was constructed and the corrected coverage area (CCA) was calculated to quantify overlap [34,35]. Assessment of methodological quality Two reviewers independently assessed the methodological quality of a subset of included systematic reviews using the JBI critical appraisal instrument and AMSTAR 2 [36]. Primary studies within the reviews were not individually appraised. Disagreements were resolved by discussion or a third reviewer. All reviews were included in the data extraction and synthesis regardless of quality. Appraisal findings are presented in tabular and narrative form and were used to contextualise the evidence and interpret the robustness of the review findings. Data extraction Data were extracted independently by two reviewers using a customised JBI data extraction tool following a pilot on two systematic reviews. Extracted information included review characteristics, participant demographics, conditions studied, setting, intervention details, outcome measures, and analytical methods. For meta-analyses, effect measures, effect sizes, statistical significance, and heterogeneity were also recorded. Data summary To evaluate the effectiveness of biofeedback interventions, data from the included reviews were summarised in tables and synthesised narratively. The synthesis considered the number of studies contributing to each outcome, review time frames, and methodological quality. Overlap across reviews was identified and reported in a citation table. Interventions were described by type, participant characteristics, and level of implementation. Reported outcomes included event counts (n), total participants (N), effect estimates (odds ratios or relative risks), confidence intervals, and P values where available, as reported in the original reviews. No reanalysis of primary data was undertaken. Findings are presented as a narrative summary with discussion of effectiveness in relation to intervention type, participant characteristics, and methodological quality. Assessing confidence in the findings The certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach [37], and a Summary of Findings table was generated using GRADEpro GDT. Evidence was evaluated across five domains: risk of bias, inconsistency, indirectness, imprecision, and publication bias. Assessments were conducted independently by two reviewers at the outcome level, with disagreements resolved by consensus or a third reviewer. The Summary of Findings presents absolute and relative effect estimates and overall certainty ratings (Table 1). Where multiple meta-analyses addressed the same outcome, those with lower heterogeneity, larger sample sizes, and lower risk of bias were prioritised. Certainty ratings were upgraded or downgraded based on predefined criteria, with final classifications of high, moderate, low, or very low certainty. Review findings Gait speed (m/s) One systematic review [27] assessed electromyographic (EMG) biofeedback for improving gait performance in children with cerebral palsy (Table 1). Seven randomised controlled trials (n = 276) compared EMG-augmented gait training with conventional physiotherapy or control interventions. The pooled mean difference in gait speed was 0.12 m/s (95% CI −0.05 to 0.29), favouring EMG biofeedback but not reaching statistical significance. Heterogeneity was substantial (I² = 68%). Evidence certainty was rated very low due to imprecision and inconsistency, with additional limitations including lack of blinding and incomplete outcome data (Table 2). Overall, EMG biofeedback showed a small and uncertain effect on gait speed, with insufficient evidence to support a clinically meaningful benefit. ADHD Core Symptoms (Inattention, Hyperactivity, Impulsivity) Multiple systematic reviews [24, 26, 28, 29, 31] evaluated neurofeedback for improving parent-rated core ADHD symptoms, including inattention, hyperactivity, and impulsivity (Table 1). One review [24] pooled 13 randomised controlled trials (n = 513) and reported a small-to-moderate effect favouring neurofeedback (effect size 0.29; 95% CI 0.12–0.45), with low certainty due to unblinded outcome assessment and moderate heterogeneity (I² = 56%). Another review [29] including 14 trials (n = 874) found a similar effect (0.33; 95% CI 0.19–0.46) but with substantial heterogeneity (I² = 72%) and methodological limitations. A more recent review [31] synthesising 18 studies (n = 856) reported a pooled effect size of 0.35 (95% CI 0.14–0.56), with low-to-moderate heterogeneity (I² = 38%) and moderate certainty, suggesting more consistent effects with contemporary protocols. In contrast, one review [26] of 11 studies (n = 563) did not pool results owing to marked methodological heterogeneity and reported mixed findings with very low certainty (Table 2). The largest RCT-only review [28], including 67 trials (n = 4,980), was also unable to meta-analyse outcomes because of substantial variability in protocols and outcome measures, yielding inconsistent results and low to very low certainty. Overall, neurofeedback generally showed parent-reported symptom improvements, but confidence in these effects is limited by heterogeneity, unblinded ratings, and methodological variability. ADHD symptoms — Teacher-rated / Blinded outcomes Two systematic reviews [24,31] examined neurofeedback effects on teacher-rated or otherwise blinded ADHD outcomes, which are considered more objective measures (Table 1). One review [24] pooling 13 randomised controlled trials (n = 513) found no significant improvements in teacher-rated inattention or hyperactivity/impulsivity compared with controls. Evidence certainty was low due to limited blinding, variability in school-based measures, and moderate heterogeneity. In contrast, a more recent network meta-analysis [31] including 18 studies (n = 856) reported overall positive effects of neurofeedback on blinded outcomes. Protocol-specific analyses suggested small to moderate benefits for certain approaches, particularly slow cortical potential training (effect sizes 0.14–0.56). Heterogeneity was low to moderate (I² = 38%), and evidence certainty was rated moderate (Table 2), although limitations related to incomplete blinding and intervention fidelity persisted. Overall, earlier reviews showed no clear benefit on teacher-rated outcomes, but newer evidence suggests possible protocol-specific effects that should be interpreted cautiously. Neurofeedback versus Psychostimulants (ADHD) One review [30] compared EEG-based neurofeedback with psychostimulant medication across nine controlled studies (n = 413) (Table 1). Meta-analysis was not feasible because of heterogeneity in study design, outcomes, and treatment duration. Qualitative synthesis indicated that both interventions reduced ADHD symptoms, but psychostimulants produced faster and larger short-term effects, whereas neurofeedback showed more gradual and potentially sustained benefits at follow-up. Evidence certainty was very low due to small sample sizes, non-standardised outcomes, and methodological heterogeneity (Table 2). Overall, neurofeedback may be a complementary option, but psychostimulants remain more effective for rapid symptom reduction. Neurocognitive / cognitive performance (attention, executive function) Three systematic reviews [24,26,31] examined neurofeedback effects on neurocognitive outcomes (Table 1). One review [24] pooling 13 RCTs (n = 513) reported mixed results on objective neuropsychological tests, with low-certainty evidence due to inconsistency and methodological variation. A more recent review [31] including 18 trials (n = 856) identified protocol-specific cognitive benefits in selected domains, with low-to-moderate heterogeneity and moderate certainty of evidence (Table 2). Another review [26] of 11 studies (n = 563) found inconsistent cognitive improvements across standard and personalised protocols and rated evidence certainty as very low. Overall, neurofeedback may yield selective, task-specific gains in attention or executive function, but evidence is inconsistent and limited by methodological variability, precluding firm conclusions on neurocognitive efficacy. HRV indices & Emotional regulation / Anxiety One systematic review [25] synthesised eight controlled trials (n = 328) evaluating heart rate variability biofeedback for autonomic regulation, emotional control, and anxiety reduction (Table 1). Meta-analysis was not performed because of heterogeneity in study design and outcome measures. The review found limited and inconsistent evidence for improvements in HRV parameters or emotional regulation. Evidence certainty was rated very low due to small sample sizes, variable intervention protocols, and inconsistent HRV measurement (Table 2). Although effects generally favoured biofeedback, the lack of consistent, statistically significant findings limits interpretation, and current evidence is insufficient to support definitive clinical effectiveness. Other motor / functional outcomes (GMFM, stride length, balance, muscle strength) Secondary motor and functional outcomes, including GMFM, stride length, balance, and muscle strength, were primarily reported in one systematic review [27] (Table 1). This review synthesised 14 clinical studies involving 359 participants, most with cerebral palsy receiving EMG-enhanced rehabilitation. Owing to substantial heterogeneity in study design and outcome measures, most outcomes were not meta-analysed. Subgroup analyses suggested that treadmill-based EMG biofeedback produced favourable changes in gait parameters and muscle activation, with task-specific improvements observed in some studies. Other outcomes showed minimal or no benefit. Evidence certainty ranged from very low to low due to inconsistency, small sample sizes, and heterogeneity (Table 2). Only gait speed was pooled, showing substantial heterogeneity (I² = 68%). Overall, EMG biofeedback may support targeted motor improvements, but generalisability is limited by methodological variability. Acceptability / adverse events Across several systematic reviews [24,25,27,30,31], reporting of acceptability and adverse events for neurofeedback, HRV biofeedback, and EMG biofeedback was limited and inconsistent. Most trials did not systematically monitor or quantify adverse events, and available reports were largely qualitative, describing occasional mild discomfort, frustration, or fatigue, with no serious harms identified. Acceptability was generally reported as good, but few studies formally assessed satisfaction, adherence, or reasons for dropout. As a result of sparse and inconsistent reporting, the certainty of evidence was rated very low to low (Table 2). Although biofeedback appears broadly safe based on available data, insufficient adverse-event reporting precludes firm conclusions about its safety profile. Methodological quality Among the 11 JBI critical appraisal criteria, only one included systematic review met all requirements [24] (Supplementary Appendix 4). All eight reviews clearly stated their review questions, applied appropriate inclusion criteria, and used reasonably comprehensive search strategies across multiple databases. Most also applied suitable criteria to appraise included studies. However, several reviews [25,27–30] did not clearly report whether study appraisal and data extraction were conducted independently by at least two reviewers, increasing the risk of reviewer bias. Only a minority of reviews [24,27,31] explicitly documented independent duplicate appraisal and extraction. One review [26] reported multiple raters for methodological scoring but did not clarify independence, indicating partial compliance. Reviews that conducted meta-analyses [24,27,29,31] generally used appropriate statistical methods. In contrast, reviews relying solely on narrative synthesis [25,26,28,30] provided limited justification for their synthesis approach. Only two reviews [24,31] formally assessed publication bias; the remaining reviews did not address small-study effects. Although all reviews made practice recommendations and suggested directions for future research, the strength of these recommendations varied with methodological rigor. Using the JBI checklist, one review [24] was rated high quality, three [27,29,31] moderate quality, and four [25,26,28,30] low to very low quality. AMSTAR 2 assessment identified only one review [31] as moderate quality (Supplementary Appendix 5), supported by protocol registration, duplicate screening and extraction, appropriate risk-of-bias assessment, and evaluation of publication bias. The remaining reviews were downgraded due to critical flaws, including lack of protocol registration, incomplete reporting of excluded studies, absence of funding disclosures, and failure to assess publication bias. A common limitation across nearly all reviews was inadequate reporting of excluded studies and funding sources. GROOVE analysis showed mostly slight overlap between reviews, with moderate to high overlap limited to a small number of ADHD-focused neurofeedback reviews (Figure_3). Overall, most reviews synthesised distinct primary studies, reducing duplication bias and supporting the comprehensiveness of the umbrella review. Stoplight indicator EEG-based neurofeedback presents the most substantial and coherent evidence base, with six systematic reviews [24, 26, 28, 29, 30, 31] demonstrating improvements in core ADHD symptoms and three reviews [24, 26, 31] reporting benefits in cognitive and attentional performance, as denoted by the green cells (Figure_2). HRV biofeedback shows a smaller but emerging body of evidence, with one systematic review [25] indicating improvements in emotional regulation and HRV indices, and another [28] identifying modest gains in quality of life, represented by the yellow cells. Evidence for EMG biofeedback is limited and specific to motor outcomes, with one systematic review [27] reporting gains in gait speed in children with cerebral palsy and another noting small improvements in quality of life, depicted by the red and yellow cells. White cells signify outcome-intervention combinations for which no systematic reviews were available. Taken together, the matrix highlights that EEG neurofeedback has the broadest and most developed evidence across multiple clinical domains, while HRV and EMG biofeedback exhibit more focused and preliminary evidence profiles (Figure_2). Citation matrix The corrected coverage area analysis showed slight overlap among included systematic reviews (CCA = 0.053; 5.3%) (Table 3). Although some primary studies—particularly EEG-based neurofeedback trials for ADHD—appeared in multiple reviews, no single trial was overrepresented or disproportionately influenced the overall findings. This low overlap indicates minimal risk of duplication bias, supporting confidence in the synthesized conclusions. All contributing primary studies are listed in Table 3 [38–162]. However, the repeated inclusion of a limited set of neurofeedback trials highlights the scarcity of high-quality primary research in paediatric biofeedback. This clustering underscores a critical evidence gap and emphasizes the need for larger, independent, and methodologically rigorous trials across a wider range of biofeedback modalities and paediatric conditions to strengthen future systematic and umbrella reviews. Discussion Biofeedback therapies are increasingly recognised as promising non-pharmacological interventions for paediatric populations with neurological, psychological, behavioural, and chronic pain conditions. This umbrella review synthesised evidence across multiple biofeedback modalities, including electromyographic (EMG), heart rate variability (HRV), hemoencephalography (HEG), and EEG-based neurofeedback. Overall, the findings suggest favourable short-term effects on behavioural performance, emotional regulation, autonomic control, and motor function. However, the strength of evidence varied substantially across modalities and clinical indications, highlighting important differences in maturity and robustness of the evidence base. EMG-based biofeedback demonstrated some of the most consistent benefits in motor rehabilitation. Several primary studies and systematic reviews reported task-specific gains in gait parameters and muscle activation in children with cerebral palsy, including improvements in calf muscle recruitment, step length, and walking velocity [10,11,16,27]. Therapeutic gaming combined with EMG feedback was shown to improve movement quality and engagement in both clinic-based and home-based rehabilitation settings [17]. Benefits were not restricted to cerebral palsy; improvements in pain, muscle strength, and functional recovery were also reported in juvenile rheumatoid arthritis and Guillain–Barré syndrome [8,9]. These findings underscore the adaptability of EMG biofeedback to a range of paediatric neuromuscular conditions. Nevertheless, considerable heterogeneity in training protocols, feedback modalities, session duration, and outcome measures limited comparability across studies and reduced confidence in pooled estimates [27,163]. EMG biofeedback has also shown benefits beyond motor rehabilitation, including reductions in sleep bruxism and temporomandibular disorder–related pain [20], as well as improvements in emotional regulation in children with disruptive behaviour disorders [164]. Collectively, these findings highlight the versatility of EMG-based approaches while reinforcing the need for standardised outcome measures and longer follow-up. HRV biofeedback demonstrated emerging benefits in emotional and autonomic regulation. Evidence indicated reductions in pain intensity and improvements in school functioning among children with chronic pain conditions [165], as well as increased anxiety awareness in autistic adolescents using wearable HRV technologies [12]. Meta-analytic findings further support reductions in depressive symptoms following HRV biofeedback, and game-based HRV-CBT interventions showed improvements in anxiety and quality of life in children with chronic physical illness [18,166]. Although one systematic review reported inconsistent HRV outcomes [25], the overall direction of evidence favoured benefits in emotional control and autonomic balance. Additionally, VR-assisted HRV biofeedback emerged as a feasible perioperative intervention, suggesting that immersive formats may enhance engagement and therapeutic impact [14]. Despite these promising findings, HRV biofeedback remains supported by a relatively small number of trials with heterogeneous designs, underscoring the need for more rigorous evaluation. Neurofeedback represents the most extensively studied biofeedback modality, particularly in relation to ADHD. Multiple trials and systematic reviews reported improvements in attention, behavioural regulation, and executive functioning following theta/beta ratio and slow cortical potential training [138,149,157]. Foundational studies demonstrated clinically meaningful reductions in core ADHD symptoms, establishing the neurophysiological rationale for later clinical trials [138]. Evidence from multicentre RCTs further strengthened support for neurofeedback by demonstrating symptom reductions compared with non-specific behavioural interventions [148]. More recent work has highlighted the importance of individualisation, with personalised TBR protocols showing greater modulation of EEG activity than standardised approaches [167]. Combining neurofeedback with EMG-based relaxation or behavioural components has also been shown to enhance attentional outcomes [125]. Comparisons with stimulant medication and physical activity suggest that neurofeedback may achieve comparable improvements in selected cognitive domains, particularly over longer follow-up periods [110,112]. Home-based and mobile neurofeedback platforms have expanded accessibility and feasibility, supporting wider implementation in paediatric settings [119,168]. Importantly, large multicentre trials controlling for non-specific treatment effects demonstrated sustained improvements in ADHD symptoms following SCP neurofeedback, strengthening the overall evidence base [157]. Together, these findings support neurofeedback as a potentially effective adjunct to standard ADHD treatment, although it does not consistently outperform established pharmacological therapies. Biofeedback also demonstrated utility in specialised paediatric applications. Ultrasound visual biofeedback showed feasibility and efficacy in correcting articulation errors in children with cleft palate and childhood apraxia of speech [169,170]. In paediatric dentistry, electrodermal activity biofeedback and audiovisual-assisted relaxation significantly reduced dental anxiety during clinical procedures [21,171]. These applications highlight the adaptability of biofeedback across diverse clinical contexts. However, successful implementation depends on age-appropriate interface design, simplified feedback cues, and tailored reinforcement strategies to maintain engagement and usability in children [172]. Emerging technologies, including wearable sensors, mobile applications, home-based neurofeedback systems, and VR-assisted biofeedback, further enhance scalability and acceptability in paediatric care [14,15]. Despite these promising findings, several methodological limitations constrain the certainty of conclusions. Many included systematic reviews lacked protocol registration, duplicate screening, or transparent reporting of excluded studies, increasing the risk of selection and extraction bias. Overlap analyses revealed evidence clustering around a limited number of ADHD neurofeedback trials, reflecting a shortage of high-quality primary research in other clinical domains. This pattern supports a stratified interpretation of findings, with comparatively stronger evidence for ADHD neurofeedback, emerging evidence for HRV biofeedback, and uncertain conclusions for EMG-based motor outcomes. Inconsistent reporting of adverse events further limited assessment of safety, highlighting the need for standardised monitoring of tolerability and harms. Future trials should prioritise rigorous design, harmonised protocols, validated outcome measures, and long-term follow-up to strengthen the paediatric biofeedback evidence base. Overall, biofeedback therapies demonstrate meaningful short-term benefits across motor, cognitive, emotional, and autonomic domains in children and adolescents. However, methodological weaknesses and heterogeneity limit confidence in effect estimates. Large, well-designed multicentre trials are required to confirm efficacy, establish durability of effects, and define the optimal role of biofeedback as an adjunct within paediatric clinical care. Limitations of this umbrella review This umbrella review and the underlying evidence base have several limitations affecting the strength and interpretation of the findings. Methodological heterogeneity was substantial across studies, with wide variation in design, intervention protocols, training frequency and duration, feedback modalities (EMG, HRV, EEG), and outcome measures, limiting synthesis and comparability [24–31]. Second, many reviews included small total sample sizes, often fewer than 300 participants, reducing statistical power and increasing imprecision. Long-term follow-up was limited, restricting assessment of the durability of treatment effects, particularly for behavioural and cognitive outcomes [24–31]. Third, outcome measures were inconsistently defined and non-standardised. Motor outcomes relied on diverse gait and strength metrics [27], while cognitive outcomes ranged from objective tests to subjective ratings [24,29–31]. Selective outcome reporting was common, with limited reporting of adverse events, acceptability, adherence, funding sources, and conflicts of interest. Fourth, many systematic reviews lacked preregistered protocols and did not consistently use duplicate screening or data extraction, increasing the risk of selection and reviewer bias [24,26–30]. In addition, several analyses combined randomised and non-randomised evidence, particularly for EMG and HRV biofeedback, which may introduce confounding and limit causal inference [25,27]. Finally, inconsistent reporting of harms and acceptability limited safety assessment. Collectively, these limitations resulted in predominantly low to very low certainty of evidence, suggesting that observed effects may differ from true effects. Future studies should prioritise harmonised protocols, adequately powered trials, rigorous blinding, standardised outcomes, and longer follow-up. Recommendations for future research Future research should prioritise methodological rigour and standardisation in paediatric biofeedback studies. Large, multicentre randomised controlled trials are needed to confirm efficacy and define clinically meaningful effect sizes. Standardised intervention protocols, including session frequency, duration, and feedback modality, would improve comparability across studies. Long-term follow-up should be incorporated to assess durability of effects, and personalised approaches tailored to individual clinical and neurophysiological profiles warrant evaluation. Comprehensive reporting of adverse events, adherence, and acceptability is essential to strengthen safety assessments. Future systematic reviews should also ensure protocol registration, transparent methods, and rigorous quality appraisal to improve confidence in the synthesised evidence. Conclusion The findings of this umbrella review, reported in accordance with the PRIOR statement (Appendix 5) [173], suggest that biofeedback interventions including neurofeedback, electromyographic (EMG), and heart rate variability (HRV) biofeedback, offer potential benefits across several paediatric conditions. Evidence indicates that theta/beta ratio and slow cortical potential neurofeedback protocols reduce inattention and impulsivity in children with ADHD, while EMG biofeedback improves motor function and gait performance in children with cerebral palsy. HRV biofeedback appears promising for emotional regulation and anxiety-related symptoms. Overall, these findings support biofeedback as a non-invasive adjunctive therapy in paediatric care. However, certainty of evidence is low to moderate due to methodological heterogeneity, small sample sizes, and variable outcome measures, and results should therefore be interpreted with caution. Declarations Conflicts of interest The authors present no conflict of interest. Funding: The present review is not funded by any organisation. References Frank, D. L., Khorshid, L., Kiffer, J. F., Moravec, C. S., & McKee, M. G. (2010). Biofeedback in medicine: who, when, why and how?. Mental health in family medicine , 7 (2), 85–91. Malik, K., & Dua, A. (2025). Advancing Patient Care With Biofeedback. In StatPearls . StatPearls Publishing. Suter SE. Biofeedback: techniques and applications for children and adolescents. J Behav Med. 1999;22(5):505–20. Yucha, C., & Montgomery. (n.d.). Evidence-Based Practice in Biofeedback and Neurofeedback . 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BMJ ;378:e070849. doi:10.1136/bmj-2022-070849 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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2","display":"","copyAsset":false,"role":"figure","size":80500,"visible":true,"origin":"","legend":"\u003cp\u003eStoplight indicator with the number of systematic reviews reporting each outcome\u003c/p\u003e\n\u003cp\u003eGreen indicates an effective or beneficial intervention; amber indicates no difference compared with the comparator or unclear effect due to insufficient information; and red indicates less effective intervention compared with the comparator.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea \u003c/sup\u003eNumbers written in the coloured boxes are the number of systematic reviews reporting each outcome.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8594886/v1/d7e8e41479b07b8cb9548ba4.png"},{"id":100415843,"identity":"f4485633-37e8-4002-9ca7-f1e4167e8278","added_by":"auto","created_at":"2026-01-16 13:22:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":862347,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8594886/v1/23e310d3-57a7-494b-be65-d9f5f253706f.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eEffectiveness of biofeedback therapies in pediatric populations: An umbrella review\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eManaging chronic pain, anxiety, attention-deficit/hyperactivity disorder (ADHD), and psychosomatic conditions in children during medical procedures remains difficult. This has increased interest in nonpharmacological approaches, including biofeedback-assisted relaxation and virtual reality\u0026ndash;based distraction. Biofeedback enables voluntary regulation of physiological responses and has been applied across medical conditions. Evidence supports its use in psychological and neurological disorders such as anxiety, depression, ADHD, post-traumatic stress disorder, insomnia, seizure disorders, and primary headache syndromes [1\u0026ndash;4]. Biofeedback has also shown benefit in cardiovascular and autonomic disorders, including hypertension, Raynaud\u0026rsquo;s disease, cardiac arrhythmias, and vasovagal syncope, through autonomic regulation [1,4]. In gastrointestinal disorders, it improves symptoms of irritable bowel syndrome, constipation, and faecal incontinence via enhanced sphincter control [5,6]. Similar mechanisms support its use in musculoskeletal and neuromuscular rehabilitation, with reported benefits in urinary incontinence, pelvic floor dysfunction, post-injury recovery, and continence in children with dysfunctional voiding using pelvic floor electromyographic (EMG) biofeedback [1,4\u0026ndash;7]. In paediatric rehabilitation, EMG biofeedback has been associated with functional improvements in juvenile rheumatoid arthritis, Guillain\u0026ndash;Barr\u0026eacute; syndrome, and cerebral palsy [8\u0026ndash;11]. Advances in wearable devices now provide real-time feedback and support emotional regulation and gait and balance training, improving feasibility of home-based interventions in children [11\u0026ndash;19]. In dental and craniofacial care, occlusal biofeedback splints have reduced temporomandibular joint dysfunction pain and sleep bruxism. Biofeedback-assisted relaxation with audiovisual distraction has reduced dental anxiety in children aged 7\u0026ndash;12 years [20,21]. Although prior umbrella reviews have examined psychological, pharmacological, and brain-stimulation interventions in youth [22,23], none focused specifically on biofeedback. Despite numerous systematic reviews evaluating paediatric biofeedback interventions [24\u0026ndash;31], there is a lack of comprehensive umbrella review synthesising biofeedback-specific evidence in children and adolescents. This umbrella review addresses this gap by evaluating the effectiveness of key biofeedback modalities across paediatric neurodevelopmental, mental health, and chronic pain conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReview question\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhat is the effectiveness of biofeedback therapies in paediatric populations based on published systematic reviews? \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eParticipants\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis umbrella review included systematic reviews of studies involving children and adolescents aged 4\u0026ndash;18 years, irrespective of underlying medical conditions. Established criteria were applied to enhance consistency and comparability, and data from mixed populations were stratified for children or adolescents where appropriate.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInterventions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis umbrella review examined biofeedback as a therapeutic modality across a range of systemic conditions. Biofeedback enables individuals to modify physiological functions such as breathing, heart rate, muscle activity, skin temperature, and brainwave patterns through real-time feedback, supporting long-term self-regulation [1\u0026ndash;4].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eComparators\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis umbrella review considered systematic reviews that included a control group, either a placebo or alternative treatments.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eOutcomes\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis umbrella review included studies with primary outcomes considered for the effectiveness of biofeedback therapies, being \u0026ldquo;Functional Mobility and Quality of Life improvement\u0026rdquo; [27], \u0026ldquo;Improvements in attention and cognitive function\u0026rdquo; [28],\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u0026ldquo;Behavioural improvements and emotional regulation\u0026rdquo; [25, 28]. \u003csup\u003e\u0026nbsp;\u003c/sup\u003eAny follow-up period outcomes were also included.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eContext\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll clinical settings were included in this review to enhance the generalizability of the results. No restrictions were imposed on the review\u0026apos;s scope, and it incorporated systematic reviews of research conducted in general or public hospitals, as well as in private clinics. Also, no geographical restrictions were imposed on context.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eType of studies\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis umbrella review included quantitative systematic reviews evaluating the effectiveness of biofeedback therapy in pediatric populations, with or without meta-analysis, across a range of experimental study designs. Reviews of mixed adult and pediatric populations were included only if separate syntheses for children or adolescents were provided. Opinion-based, narrative, qualitative, or textual reviews were excluded. Eligible reviews were required to use a well-defined, multi-database search strategy and to include critical appraisal or risk-of-bias assessment [32].\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe umbrella review was conducted in accordance with the JBI methodology for umbrella reviews [33]. The protocol was registered with PROSPERO (CRD42024604976). To ensure comprehensive reporting, the review followed the PRISMA guidelines [34].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSearch strategy\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe search strategy aimed to identify both published and unpublished systematic reviews, with or without meta-analysis. An initial search was conducted in MEDLINE (PubMed), and relevant titles, abstracts, and index terms were used to develop a comprehensive search strategy for subsequent databases (Supplementary Appendix 1). Each database was searched using tailored combinations of keywords and index terms, and reference lists of included reviews were screened to identify additional relevant studies.\u003c/p\u003e\n\u003cp\u003eSearches were limited to English-language publications from inception to July 2025, and withdrawn publications were excluded. Seven databases were searched: MEDLINE (Ovid), Scopus, CINAHL (EBSCOhost), the Cochrane Database of Systematic Reviews, JBI Evidence Synthesis (Ovid), ProQuest Dissertations and Theses, and Epistemonikos. Although Embase was specified in the protocol, it could not be searched due to access limitations. Grey literature sources, including Google Scholar and OAIster, were also screened. Initial MEDLINE search terms included \u0026ldquo;biofeedback,\u0026rdquo; \u0026ldquo;biofeedback therapy,\u0026rdquo; \u0026ldquo;neurofeedback,\u0026rdquo; \u0026ldquo;myofeedback,\u0026rdquo; and \u0026ldquo;pediatric,\u0026rdquo; filtered for \u0026ldquo;systematic review\u0026rdquo; or \u0026ldquo;meta-analysis.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy selection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing the search, records were imported into Mendeley v2.64 and duplicates were removed. After a pilot test of 20 records, two reviewers independently screened titles and abstracts against the inclusion criteria. Full-text screening was conducted using Rayyan, with eligibility independently assessed by two reviewers. Reasons for exclusion were documented (Supplementary Appendix 3), and disagreements were resolved through discussion or by a third reviewer. Study selection was reported using a PRISMA flow diagram [34].\u003c/p\u003e\n\u003cp\u003eTo account for overlapping primary studies across included systematic reviews, a citation matrix was constructed and the corrected coverage area (CCA) was calculated to quantify overlap [34,35].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAssessment of methodological quality\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo reviewers independently assessed the methodological quality of a subset of included systematic reviews using the JBI critical appraisal instrument and AMSTAR 2 [36]. Primary studies within the reviews were not individually appraised. Disagreements were resolved by discussion or a third reviewer. All reviews were included in the data extraction and synthesis regardless of quality. Appraisal findings are presented in tabular and narrative form and were used to contextualise the evidence and interpret the robustness of the review findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData extraction\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were extracted independently by two reviewers using a customised JBI data extraction tool following a pilot on two systematic reviews. Extracted information included review characteristics, participant demographics, conditions studied, setting, intervention details, outcome measures, and analytical methods. For meta-analyses, effect measures, effect sizes, statistical significance, and heterogeneity were also recorded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData summary\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate the effectiveness of biofeedback interventions, data from the included reviews were summarised in tables and synthesised narratively. The synthesis considered the number of studies contributing to each outcome, review time frames, and methodological quality. Overlap across reviews was identified and reported in a citation table. Interventions were described by type, participant characteristics, and level of implementation. Reported outcomes included event counts (n), total participants (N), effect estimates (odds ratios or relative risks), confidence intervals, and P values where available, as reported in the original reviews. No reanalysis of primary data was undertaken. Findings are presented as a narrative summary with discussion of effectiveness in relation to intervention type, participant characteristics, and methodological quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAssessing confidence in the findings\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach [37], and a Summary of Findings table was generated using GRADEpro GDT. Evidence was evaluated across five domains: risk of bias, inconsistency, indirectness, imprecision, and publication bias. Assessments were conducted independently by two reviewers at the outcome level, with disagreements resolved by consensus or a third reviewer. The Summary of Findings presents absolute and relative effect estimates and overall certainty ratings (Table 1). Where multiple meta-analyses addressed the same outcome, those with lower heterogeneity, larger sample sizes, and lower risk of bias were prioritised. Certainty ratings were upgraded or downgraded based on predefined criteria, with final classifications of high, moderate, low, or very low certainty.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eReview findings\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGait speed (m/s)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne systematic review [27] assessed electromyographic (EMG) biofeedback for improving gait performance in children with cerebral palsy (Table 1). Seven randomised controlled trials (n = 276) compared EMG-augmented gait training with conventional physiotherapy or control interventions. The pooled mean difference in gait speed was 0.12 m/s (95% CI \u0026minus;0.05 to 0.29), favouring EMG biofeedback but not reaching statistical significance. Heterogeneity was substantial (I\u0026sup2; = 68%). Evidence certainty was rated very low due to imprecision and inconsistency, with additional limitations including lack of blinding and incomplete outcome data (Table 2). Overall, EMG biofeedback showed a small and uncertain effect on gait speed, with insufficient evidence to support a clinically meaningful benefit.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eADHD Core Symptoms (Inattention, Hyperactivity, Impulsivity)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultiple systematic reviews [24, 26, 28, 29, 31] evaluated neurofeedback for improving parent-rated core ADHD symptoms, including inattention, hyperactivity, and impulsivity (Table 1). One review [24] pooled 13 randomised controlled trials (n = 513) and reported a small-to-moderate effect favouring neurofeedback (effect size 0.29; 95% CI 0.12\u0026ndash;0.45), with low certainty due to unblinded outcome assessment and moderate heterogeneity (I\u0026sup2; = 56%). Another review [29] including 14 trials (n = 874) found a similar effect (0.33; 95% CI 0.19\u0026ndash;0.46) but with substantial heterogeneity (I\u0026sup2; = 72%) and methodological limitations. A more recent review [31] synthesising 18 studies (n = 856) reported a pooled effect size of 0.35 (95% CI 0.14\u0026ndash;0.56), with low-to-moderate heterogeneity (I\u0026sup2; = 38%) and moderate certainty, suggesting more consistent effects with contemporary protocols.\u003c/p\u003e\n\u003cp\u003eIn contrast, one review [26] of 11 studies (n = 563) did not pool results owing to marked methodological heterogeneity and reported mixed findings with very low certainty (Table 2). The largest RCT-only review [28], including 67 trials (n = 4,980), was also unable to meta-analyse outcomes because of substantial variability in protocols and outcome measures, yielding inconsistent results and low to very low certainty. Overall, neurofeedback generally showed parent-reported symptom improvements, but confidence in these effects is limited by heterogeneity, unblinded ratings, and methodological variability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eADHD symptoms \u0026mdash; Teacher-rated / Blinded outcomes\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo systematic reviews [24,31] examined neurofeedback effects on teacher-rated or otherwise blinded ADHD outcomes, which are considered more objective measures (Table 1). One review [24] pooling 13 randomised controlled trials (n = 513) found no significant improvements in teacher-rated inattention or hyperactivity/impulsivity compared with controls. Evidence certainty was low due to limited blinding, variability in school-based measures, and moderate heterogeneity.\u003c/p\u003e\n\u003cp\u003eIn contrast, a more recent network meta-analysis [31] including 18 studies (n = 856) reported overall positive effects of neurofeedback on blinded outcomes. Protocol-specific analyses suggested small to moderate benefits for certain approaches, particularly slow cortical potential training (effect sizes 0.14\u0026ndash;0.56). Heterogeneity was low to moderate (I\u0026sup2; = 38%), and evidence certainty was rated moderate (Table 2), although limitations related to incomplete blinding and intervention fidelity persisted. Overall, earlier reviews showed no clear benefit on teacher-rated outcomes, but newer evidence suggests possible protocol-specific effects that should be interpreted cautiously.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNeurofeedback versus Psychostimulants (ADHD)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne review [30] compared EEG-based neurofeedback with psychostimulant medication across nine controlled studies (n = 413) (Table 1). Meta-analysis was not feasible because of heterogeneity in study design, outcomes, and treatment duration. Qualitative synthesis indicated that both interventions reduced ADHD symptoms, but psychostimulants produced faster and larger short-term effects, whereas neurofeedback showed more gradual and potentially sustained benefits at follow-up. Evidence certainty was very low due to small sample sizes, non-standardised outcomes, and methodological heterogeneity (Table 2). Overall, neurofeedback may be a complementary option, but psychostimulants remain more effective for rapid symptom reduction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNeurocognitive / cognitive performance (attention, executive function)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThree systematic reviews [24,26,31] examined neurofeedback effects on neurocognitive outcomes (Table 1). One review [24] pooling 13 RCTs (n = 513) reported mixed results on objective neuropsychological tests, with low-certainty evidence due to inconsistency and methodological variation. A more recent review [31] including 18 trials (n = 856) identified protocol-specific cognitive benefits in selected domains, with low-to-moderate heterogeneity and moderate certainty of evidence (Table 2). Another review [26] of 11 studies (n = 563) found inconsistent cognitive improvements across standard and personalised protocols and rated evidence certainty as very low. Overall, neurofeedback may yield selective, task-specific gains in attention or executive function, but evidence is inconsistent and limited by methodological variability, precluding firm conclusions on neurocognitive efficacy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHRV indices \u0026amp; Emotional regulation / Anxiety\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne systematic review [25] synthesised eight controlled trials (n = 328) evaluating heart rate variability biofeedback for autonomic regulation, emotional control, and anxiety reduction (Table 1). Meta-analysis was not performed because of heterogeneity in study design and outcome measures. The review found limited and inconsistent evidence for improvements in HRV parameters or emotional regulation. Evidence certainty was rated very low due to small sample sizes, variable intervention protocols, and inconsistent HRV measurement (Table 2). Although effects generally favoured biofeedback, the lack of consistent, statistically significant findings limits interpretation, and current evidence is insufficient to support definitive clinical effectiveness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOther motor / functional outcomes (GMFM, stride length, balance, muscle strength)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSecondary motor and functional outcomes, including GMFM, stride length, balance, and muscle strength, were primarily reported in one systematic review [27] (Table 1). This review synthesised 14 clinical studies involving 359 participants, most with cerebral palsy receiving EMG-enhanced rehabilitation. Owing to substantial heterogeneity in study design and outcome measures, most outcomes were not meta-analysed. Subgroup analyses suggested that treadmill-based EMG biofeedback produced favourable changes in gait parameters and muscle activation, with task-specific improvements observed in some studies. Other outcomes showed minimal or no benefit. Evidence certainty ranged from very low to low due to inconsistency, small sample sizes, and heterogeneity (Table 2). Only gait speed was pooled, showing substantial heterogeneity (I\u0026sup2; = 68%). Overall, EMG biofeedback may support targeted motor improvements, but generalisability is limited by methodological variability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcceptability / adverse events\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcross several systematic reviews [24,25,27,30,31], reporting of acceptability and adverse events for neurofeedback, HRV biofeedback, and EMG biofeedback was limited and inconsistent. Most trials did not systematically monitor or quantify adverse events, and available reports were largely qualitative, describing occasional mild discomfort, frustration, or fatigue, with no serious harms identified. Acceptability was generally reported as good, but few studies formally assessed satisfaction, adherence, or reasons for dropout. As a result of sparse and inconsistent reporting, the certainty of evidence was rated very low to low (Table 2). Although biofeedback appears broadly safe based on available data, insufficient adverse-event reporting precludes firm conclusions about its safety profile.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMethodological quality\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 11 JBI critical appraisal criteria, only one included systematic review met all requirements [24] (Supplementary Appendix 4). All eight reviews clearly stated their review questions, applied appropriate inclusion criteria, and used reasonably comprehensive search strategies across multiple databases. Most also applied suitable criteria to appraise included studies. However, several reviews [25,27\u0026ndash;30] did not clearly report whether study appraisal and data extraction were conducted independently by at least two reviewers, increasing the risk of reviewer bias. Only a minority of reviews [24,27,31] explicitly documented independent duplicate appraisal and extraction. One review [26] reported multiple raters for methodological scoring but did not clarify independence, indicating partial compliance.\u003c/p\u003e\n\u003cp\u003eReviews that conducted meta-analyses [24,27,29,31] generally used appropriate statistical methods. In contrast, reviews relying solely on narrative synthesis [25,26,28,30] provided limited justification for their synthesis approach. Only two reviews [24,31] formally assessed publication bias; the remaining reviews did not address small-study effects. Although all reviews made practice recommendations and suggested directions for future research, the strength of these recommendations varied with methodological rigor.\u003c/p\u003e\n\u003cp\u003eUsing the JBI checklist, one review [24] was rated high quality, three [27,29,31] moderate quality, and four [25,26,28,30] low to very low quality. AMSTAR 2 assessment identified only one review [31] as moderate quality (Supplementary Appendix 5), supported by protocol registration, duplicate screening and extraction, appropriate risk-of-bias assessment, and evaluation of publication bias. The remaining reviews were downgraded due to critical flaws, including lack of protocol registration, incomplete reporting of excluded studies, absence of funding disclosures, and failure to assess publication bias.\u003c/p\u003e\n\u003cp\u003eA common limitation across nearly all reviews was inadequate reporting of excluded studies and funding sources. GROOVE analysis showed mostly slight overlap between reviews, with moderate to high overlap limited to a small number of ADHD-focused neurofeedback reviews (Figure_3). Overall, most reviews synthesised distinct primary studies, reducing duplication bias and supporting the comprehensiveness of the umbrella review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStoplight indicator\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEEG-based neurofeedback presents the most substantial and coherent evidence base, with six systematic reviews [24, 26, 28, 29, 30, 31] demonstrating improvements in core ADHD symptoms and three reviews [24, 26, 31] reporting benefits in cognitive and attentional performance, as denoted by the green cells (Figure_2). HRV biofeedback shows a smaller but emerging body of evidence, with one systematic review [25]\u003csup\u003e\u0026nbsp;\u003c/sup\u003eindicating improvements in emotional regulation and HRV indices, and another [28] identifying modest gains in quality of life, represented by the yellow cells. Evidence for EMG biofeedback is limited and specific to motor outcomes, with one systematic review [27] reporting gains in gait speed in children with cerebral palsy and another noting small improvements in quality of life, depicted by the red and yellow cells. White cells signify outcome-intervention combinations for which no systematic reviews were available. Taken together, the matrix highlights that EEG neurofeedback has the broadest and most developed evidence across multiple clinical domains, while HRV and EMG biofeedback exhibit more focused and preliminary evidence profiles (Figure_2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCitation matrix\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corrected coverage area analysis showed slight overlap among included systematic reviews (CCA = 0.053; 5.3%) (Table 3). Although some primary studies\u0026mdash;particularly EEG-based neurofeedback trials for ADHD\u0026mdash;appeared in multiple reviews, no single trial was overrepresented or disproportionately influenced the overall findings. This low overlap indicates minimal risk of duplication bias, supporting confidence in the synthesized conclusions. All contributing primary studies are listed in Table 3 [38\u0026ndash;162].\u003c/p\u003e\n\u003cp\u003eHowever, the repeated inclusion of a limited set of neurofeedback trials highlights the scarcity of high-quality primary research in paediatric biofeedback. This clustering underscores a critical evidence gap and emphasizes the need for larger, independent, and methodologically rigorous trials across a wider range of biofeedback modalities and paediatric conditions to strengthen future systematic and umbrella reviews.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBiofeedback therapies are increasingly recognised as promising non-pharmacological interventions for paediatric populations with neurological, psychological, behavioural, and chronic pain conditions. This umbrella review synthesised evidence across multiple biofeedback modalities, including electromyographic (EMG), heart rate variability (HRV), hemoencephalography (HEG), and EEG-based neurofeedback. Overall, the findings suggest favourable short-term effects on behavioural performance, emotional regulation, autonomic control, and motor function. However, the strength of evidence varied substantially across modalities and clinical indications, highlighting important differences in maturity and robustness of the evidence base.\u003c/p\u003e \u003cp\u003eEMG-based biofeedback demonstrated some of the most consistent benefits in motor rehabilitation. Several primary studies and systematic reviews reported task-specific gains in gait parameters and muscle activation in children with cerebral palsy, including improvements in calf muscle recruitment, step length, and walking velocity [10,11,16,27]. Therapeutic gaming combined with EMG feedback was shown to improve movement quality and engagement in both clinic-based and home-based rehabilitation settings [17]. Benefits were not restricted to cerebral palsy; improvements in pain, muscle strength, and functional recovery were also reported in juvenile rheumatoid arthritis and Guillain\u0026ndash;Barr\u0026eacute; syndrome [8,9]. These findings underscore the adaptability of EMG biofeedback to a range of paediatric neuromuscular conditions. Nevertheless, considerable heterogeneity in training protocols, feedback modalities, session duration, and outcome measures limited comparability across studies and reduced confidence in pooled estimates [27,163]. EMG biofeedback has also shown benefits beyond motor rehabilitation, including reductions in sleep bruxism and temporomandibular disorder\u0026ndash;related pain [20], as well as improvements in emotional regulation in children with disruptive behaviour disorders [164]. Collectively, these findings highlight the versatility of EMG-based approaches while reinforcing the need for standardised outcome measures and longer follow-up.\u003c/p\u003e \u003cp\u003eHRV biofeedback demonstrated emerging benefits in emotional and autonomic regulation. Evidence indicated reductions in pain intensity and improvements in school functioning among children with chronic pain conditions [165], as well as increased anxiety awareness in autistic adolescents using wearable HRV technologies [12]. Meta-analytic findings further support reductions in depressive symptoms following HRV biofeedback, and game-based HRV-CBT interventions showed improvements in anxiety and quality of life in children with chronic physical illness [18,166]. Although one systematic review reported inconsistent HRV outcomes [25], the overall direction of evidence favoured benefits in emotional control and autonomic balance. Additionally, VR-assisted HRV biofeedback emerged as a feasible perioperative intervention, suggesting that immersive formats may enhance engagement and therapeutic impact [14]. Despite these promising findings, HRV biofeedback remains supported by a relatively small number of trials with heterogeneous designs, underscoring the need for more rigorous evaluation.\u003c/p\u003e \u003cp\u003eNeurofeedback represents the most extensively studied biofeedback modality, particularly in relation to ADHD. Multiple trials and systematic reviews reported improvements in attention, behavioural regulation, and executive functioning following theta/beta ratio and slow cortical potential training [138,149,157]. Foundational studies demonstrated clinically meaningful reductions in core ADHD symptoms, establishing the neurophysiological rationale for later clinical trials [138]. Evidence from multicentre RCTs further strengthened support for neurofeedback by demonstrating symptom reductions compared with non-specific behavioural interventions [148]. More recent work has highlighted the importance of individualisation, with personalised TBR protocols showing greater modulation of EEG activity than standardised approaches [167]. Combining neurofeedback with EMG-based relaxation or behavioural components has also been shown to enhance attentional outcomes [125]. Comparisons with stimulant medication and physical activity suggest that neurofeedback may achieve comparable improvements in selected cognitive domains, particularly over longer follow-up periods [110,112]. Home-based and mobile neurofeedback platforms have expanded accessibility and feasibility, supporting wider implementation in paediatric settings [119,168]. Importantly, large multicentre trials controlling for non-specific treatment effects demonstrated sustained improvements in ADHD symptoms following SCP neurofeedback, strengthening the overall evidence base [157]. Together, these findings support neurofeedback as a potentially effective adjunct to standard ADHD treatment, although it does not consistently outperform established pharmacological therapies.\u003c/p\u003e \u003cp\u003eBiofeedback also demonstrated utility in specialised paediatric applications. Ultrasound visual biofeedback showed feasibility and efficacy in correcting articulation errors in children with cleft palate and childhood apraxia of speech [169,170]. In paediatric dentistry, electrodermal activity biofeedback and audiovisual-assisted relaxation significantly reduced dental anxiety during clinical procedures [21,171]. These applications highlight the adaptability of biofeedback across diverse clinical contexts. However, successful implementation depends on age-appropriate interface design, simplified feedback cues, and tailored reinforcement strategies to maintain engagement and usability in children [172]. Emerging technologies, including wearable sensors, mobile applications, home-based neurofeedback systems, and VR-assisted biofeedback, further enhance scalability and acceptability in paediatric care [14,15].\u003c/p\u003e \u003cp\u003eDespite these promising findings, several methodological limitations constrain the certainty of conclusions. Many included systematic reviews lacked protocol registration, duplicate screening, or transparent reporting of excluded studies, increasing the risk of selection and extraction bias. Overlap analyses revealed evidence clustering around a limited number of ADHD neurofeedback trials, reflecting a shortage of high-quality primary research in other clinical domains. This pattern supports a stratified interpretation of findings, with comparatively stronger evidence for ADHD neurofeedback, emerging evidence for HRV biofeedback, and uncertain conclusions for EMG-based motor outcomes. Inconsistent reporting of adverse events further limited assessment of safety, highlighting the need for standardised monitoring of tolerability and harms. Future trials should prioritise rigorous design, harmonised protocols, validated outcome measures, and long-term follow-up to strengthen the paediatric biofeedback evidence base.\u003c/p\u003e \u003cp\u003eOverall, biofeedback therapies demonstrate meaningful short-term benefits across motor, cognitive, emotional, and autonomic domains in children and adolescents. However, methodological weaknesses and heterogeneity limit confidence in effect estimates. Large, well-designed multicentre trials are required to confirm efficacy, establish durability of effects, and define the optimal role of biofeedback as an adjunct within paediatric clinical care.\u003c/p\u003e\n\u003ch3\u003eLimitations of this umbrella review\u003c/h3\u003e\n\u003cp\u003eThis umbrella review and the underlying evidence base have several limitations affecting the strength and interpretation of the findings. Methodological heterogeneity was substantial across studies, with wide variation in design, intervention protocols, training frequency and duration, feedback modalities (EMG, HRV, EEG), and outcome measures, limiting synthesis and comparability [24\u0026ndash;31].\u003c/p\u003e \u003cp\u003eSecond, many reviews included small total sample sizes, often fewer than 300 participants, reducing statistical power and increasing imprecision. Long-term follow-up was limited, restricting assessment of the durability of treatment effects, particularly for behavioural and cognitive outcomes [24\u0026ndash;31].\u003c/p\u003e \u003cp\u003eThird, outcome measures were inconsistently defined and non-standardised. Motor outcomes relied on diverse gait and strength metrics [27], while cognitive outcomes ranged from objective tests to subjective ratings [24,29\u0026ndash;31]. Selective outcome reporting was common, with limited reporting of adverse events, acceptability, adherence, funding sources, and conflicts of interest.\u003c/p\u003e \u003cp\u003eFourth, many systematic reviews lacked preregistered protocols and did not consistently use duplicate screening or data extraction, increasing the risk of selection and reviewer bias [24,26\u0026ndash;30]. In addition, several analyses combined randomised and non-randomised evidence, particularly for EMG and HRV biofeedback, which may introduce confounding and limit causal inference [25,27].\u003c/p\u003e \u003cp\u003eFinally, inconsistent reporting of harms and acceptability limited safety assessment. Collectively, these limitations resulted in predominantly low to very low certainty of evidence, suggesting that observed effects may differ from true effects. Future studies should prioritise harmonised protocols, adequately powered trials, rigorous blinding, standardised outcomes, and longer follow-up.\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eRecommendations for future research\u003c/h2\u003e \u003cp\u003eFuture research should prioritise methodological rigour and standardisation in paediatric biofeedback studies. Large, multicentre randomised controlled trials are needed to confirm efficacy and define clinically meaningful effect sizes. Standardised intervention protocols, including session frequency, duration, and feedback modality, would improve comparability across studies. Long-term follow-up should be incorporated to assess durability of effects, and personalised approaches tailored to individual clinical and neurophysiological profiles warrant evaluation. Comprehensive reporting of adverse events, adherence, and acceptability is essential to strengthen safety assessments. Future systematic reviews should also ensure protocol registration, transparent methods, and rigorous quality appraisal to improve confidence in the synthesised evidence.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of this umbrella review, reported in accordance with the PRIOR statement (Appendix 5) [173], suggest that biofeedback interventions including neurofeedback, electromyographic (EMG), and heart rate variability (HRV) biofeedback, offer potential benefits across several paediatric conditions. Evidence indicates that theta/beta ratio and slow cortical potential neurofeedback protocols reduce inattention and impulsivity in children with ADHD, while EMG biofeedback improves motor function and gait performance in children with cerebral palsy. HRV biofeedback appears promising for emotional regulation and anxiety-related symptoms. Overall, these findings support biofeedback as a non-invasive adjunctive therapy in paediatric care. However, certainty of evidence is low to moderate due to methodological heterogeneity, small sample sizes, and variable outcome measures, and results should therefore be interpreted with caution.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflicts of interest\u003c/h2\u003e \u003cp\u003eThe authors present no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThe present review is not funded by any organisation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFrank, D. L., Khorshid, L., Kiffer, J. F., Moravec, C. S., \u0026amp; McKee, M. G. (2010). Biofeedback in medicine: who, when, why and how?. \u003cem\u003eMental health in family medicine\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(2), 85\u0026ndash;91.\u003c/li\u003e\n\u003cli\u003eMalik, K., \u0026amp; Dua, A. (2025). Advancing Patient Care With Biofeedback. In \u003cem\u003eStatPearls\u003c/em\u003e. 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In-school neurofeedback training for ADHD: Sus tained improvements from a randomized control trial. Pediatrics, 133(3), 483\u0026ndash;492. https:// doi. org/ 10. 1542/ peds. 2013- 2059 \u003c/li\u003e\n\u003cli\u003eSteiner, N., Frenette, E. C., Rene, K. M., Brennan, R. T., \u0026amp; Perrin, E. C. (2014b). Neurofeedback and cognitive attention training for children with attention-deficit hyperactivity disorder in schools. Journal of Developmental and Behavioral Pediatrics, 35(1), 18. https:// doi. org/ 10. 1097/ DBP. 00000 00000 000009\u003c/li\u003e\n\u003cli\u003eVollebregt, M. A., van Dongen-Boomsma, M., Buitelaar, J. K., \u0026amp; Slaats-Willemse, D. (2014). Does EEG-neurofeedback improve neurocognitive functioning in children with attention-deficit/ hyperactivity disorder? A systematic review and a double-blind placebo-controlled study. 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Electrical stimulation of glu teus maximus in children with cerebral palsy: effects on gait characteristics and muscle strength. Dev Med Child Neurol. 2003;45:385\u0026ndash;390. \u003c/li\u003e\n\u003cli\u003evan der Linden ML, Hazlewood ME, Hill manSJ, RobbJE. Functional electrical stim ulation to the dorsiflexors and quadriceps in children with cerebral palsy. Pediatr Phys Ther. 2008;20:23\u0026ndash;29. \u003c/li\u003e\n\u003cli\u003eLofthouse, N., Arnold, L. E., Hersch, S., Hurt, E., \u0026amp; DeBeus, R. (2012). A review of neurofeedback treatment for pediatric ADHD. Journal of Attention Disorders, 16 (5), 351\u0026ndash;372. https://doi.org/10.1177/ 1087054711427530\u003c/li\u003e\n\u003cli\u003eL\u0026eacute;vesque, J., Beauregard, M., \u0026amp; Mensour, B. (2006). Effect of neuro feedback training on the neural substrates of selective attention in children with attention-deficit/hyperactivity disorder: A func tional magnetic resonance imaging study. 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International Journal of Psychophysiology, 116, 32\u0026ndash;44. https:// doi. org/ 10. 1016/j. ijpsy cho. 2017. 02. 015\u003c/li\u003e\n\u003cli\u003eD\u0026ouml;pfner, M., Hautmann, C., Dose, C., Banaschewski, T., Becker, K., Brandeis, D., Holtmann, M., Jans, T., Jenkner, C., Millenet, S., Renner, T., Romanos, M., \u0026amp; von Wirth, E. (2017). ESCA school study: Trial protocol of an adaptive treatment approach for school-age children with ADHD including two randomised trials. BMC Psychiatry, 17(1), 1\u0026ndash;14. https:// doi. org/ 10. 1186/ s12888- 017- 1433-9\u003c/li\u003e\n\u003cli\u003eMoreno-Garc\u0026iacute;a, I., Meneres-Sancho, S., Camacho-Vara de Rey, C., \u0026amp; Servera, M. (2019). A randomized controlled trial to examine the posttreatment efficacy of neurofeedback, behavior therapy and pharmacology on ADHD measures. Journal of Attention Disor ders, 23(4), 374\u0026ndash;383. https:// doi. org/ 10. 1177/ 10870 54717 693371\u003c/li\u003e\n\u003cli\u003eBioulac, S., Purper-Ouakil, D., Ros, T., Blasco-Fontecilla, H., Prats, M., Mayaud, L., \u0026amp; Brandeis, D. (2019). Personalized at-home neurofeedback compared with long-acting methylphenidate in an European noninferiority randomized trial in children with ADHD. BMC Psychiatry, 19(1), 1\u0026ndash;13. https:// doi. org/ 10. 1186/ s12888- 019- 2218-0\u003c/li\u003e\n\u003cli\u003eMacIntosh, A., Lam, E., Vigneron, V., Vignais, N. and Biddiss, E. (2018). Biofeedback interventions for individuals with cerebral palsy: a systematic review. \u003cem\u003eDisability and Rehabilitation\u003c/em\u003e, 41(20), pp.2369\u0026ndash;2391. doi: https://doi.org/10.1080/09638288.2018.1468933.\u003c/li\u003e\n\u003cli\u003ePascal-M. Aggensteiner, B\u0026ouml;ttinger, B., Baumeister, S., Hohmann, S., Heintz, S., Kaiser, A., H\u0026auml;ge, A., Werhahn, J., Hofstetter, C., Walitza, S., Franke, B., Buitelaar, J., Banaschewski, T., Brandeis, D. and Holz, N.E. (2024). Randomized controlled trial of individualized arousal-biofeedback for children and adolescents with disruptive behavior disorders (DBD). \u003cem\u003eEuropean Child \u0026amp; Adolescent Psychiatry\u003c/em\u003e. doi: https://doi.org/10.1007/s00787-023-02368-5.\u003c/li\u003e\n\u003cli\u003eYetwin, A.K., Mahrer, N.E., Bell, T.S. and Gold, J.I. (2022). Heart Rate Variability biofeedback therapy for children and adolescents with chronic pain: A pilot study. \u003cem\u003eJournal of Pediatric Nursing\u003c/em\u003e, 66, pp.151\u0026ndash;159. doi: https://doi.org/10.1016/j.pedn.2022.06.008.\u003c/li\u003e\n\u003cli\u003ePizzoli, S.F.M., Marzorati, C., Gatti, D., Monzani, D., Mazzocco, K. and Pravettoni, G. (2021). 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Adapting biofeedback for children with learning disabilities or ADHD. \u003cem\u003eBiofeedback\u003c/em\u003e, 38(2), pp.66\u0026ndash;71\u003c/li\u003e\n\u003cli\u003eGates M, Gates A, Pieper D, et al., 2022. Reporting guideline for overviews of reviews of healthcare interventions: development of the PRIOR statement. \u003cem\u003eBMJ\u003c/em\u003e;378:e070849. doi:10.1136/bmj-2022-070849\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"M S Ramaiah University of Applied Sciences","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"biofeedback, Pediatrics, effectiveness, disorders","lastPublishedDoi":"10.21203/rs.3.rs-8594886/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8594886/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo assess the effectiveness of biofeedback therapies in children and adolescents\u003c/p\u003e\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eBiofeedback is a mind\u0026ndash;body intervention that uses real-time physiological feedback to help individuals regulate bodily functions through behavioural modification, potentially reducing symptoms related to pain, attention, movement, and emotional control.\u003c/p\u003e\u003ch2\u003eInclusion criteria:\u003c/h2\u003e \u003cp\u003eSystematic reviews, with or without meta-analysis, evaluating biofeedback therapies in children and adolescents were included regardless of medical condition or disability. Outcomes of interest included attention, cognitive function, functional mobility, behaviour, emotional regulation, and quality of life.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA comprehensive search up to July 2025 was conducted in MEDLINE (PubMed), Scopus, CINAHL, Cochrane Database of Systematic Reviews, JBI Evidence Synthesis, ProQuest Dissertations and Theses, and Epistemonikos, with supplementary searches in Google Scholar and OAIster. Study selection, data extraction, and critical appraisal were performed independently by two reviewers. Findings were summarised using tables and narrative synthesis. Evidence certainty was assessed using GRADE, and reporting followed PRIOR guidelines.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSix systematic reviews published between 2015 and 2025, including approximately 2,600 pediatric participants, were analysed. Neurofeedback, particularly theta/beta ratio and slow cortical potential protocols, demonstrated moderate improvements in ADHD symptoms, mainly inattention and impulsivity. EMG biofeedback improved motor outcomes such as gait performance in children with cerebral palsy. HRV biofeedback showed potential benefits for emotional regulation. Study heterogeneity limited cross-review comparability.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBiofeedback therapies show promising benefits across several pediatric conditions, particularly ADHD and cerebral palsy. Nonetheless, methodological variability highlights the need for standardized protocols and further high-quality research.\u003c/p\u003e","manuscriptTitle":"Effectiveness of biofeedback therapies in pediatric populations: An umbrella review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 11:11:59","doi":"10.21203/rs.3.rs-8594886/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c0708249-f6f6-4df0-8f79-a6f09c96303c","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61228461,"name":"Pediatrics"},{"id":61228462,"name":"Biotechnology and Bioengineering"},{"id":61228463,"name":"Translational Medicine"}],"tags":[],"updatedAt":"2026-01-16T11:12:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 11:11:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8594886","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8594886","identity":"rs-8594886","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}