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  Digital Health Reviews

  Dec 22, 2025

  Barriers to and Facilitators of Implementation of Internet-Delivered Therapist-Guided Therapy in Child and Adolescent Mental Health Services: Systematic...

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  Authors List:

  • Annika Sannes  
  • Erling W Rognli  
  • Ketil Hanssen-Bauer  
  • Nor Christian Torp  
  • Silje Klundelien Storfossen  
  • Markus Nordheim Høstaker  
  • Marianne Aalberg  

  Abstract:

  Background: Implementation of internet-delivered therapist-guided therapy (e-therapy) can increase accessibility and resource efficiency in youth mental health services. At present, there is limited evidence to guide mental health researchers and practitioners on critical barriers and facilitators of successful e-therapy implementation in child and adolescent mental health services (CAMHS). Objective: This systematic review assesses the current state of knowledge regarding Barriers and Facilitators to the Implementation of Therapist-Guided Internet-Delivered Psychotherapy in Child and Adolescent Mental Health Services. Methods: This systematic literature review includes all peer-reviewed quantitative and qualitative studies that assess factors affecting implementation of e-therapy in the context of outpatient CAMHS (8-18 yrs). A PRISMA-compliant systematic literature search of primary research studies was performed in the PsycINFO, MEDLINE, Web of Science, CINAHL, Embase, Cochrane and OpenGrey databases. ASReview was utilized for screening. The Consolidated Framework for Implementation Research (CFIR) was applied to categorize the barriers and facilitators. We used Bayesian meta-analyses with weakly informative priors and multiple imputation of missing data to assess the implementation outcomes. Results: The database search returned 50 026 reports which were screened. 50 studies were included. We identified common barriers and facilitators related to characteristics of the intervention, organization, therapist and patient. Pooled estimates (95% credible intervals) of implementation outcomes in terms of fidelity were: 0.20 probability for dropout (0.14-0.27), and 68% of the e-therapy program modules were completed by the patients on average (60-75%); in terms of cost-effectiveness: mean therapist time per patient per week was 24 minutes (19-28 minutes); and in terms of acceptability: 24 mean CSQ-8 satisfaction level (22-27 score) and 76% mean satisfaction rate (62 -87%). Conclusions: Overall, the studies showed great heterogeneity in patient fidelity. The reporting of implementation outcomes and barriers and facilitators in the literature is inconsistent and needs a unified framework for measurement. To date, there are not enough quantitative studies on predictors or factors associated with implementation outcomes. In addition, we found a lack of studies exploring implementation processes and implementation determinants systematically and prospectively. Clinical Trial: PROSPERO 2024 CRD42024502578.

  • J Med Internet Res 2025;27(1):e83543

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  Knowledge Translation and...

  Dec 22, 2025

  Visualization of Experience Sampling Method Data in Mental Health: Qualitative Study of the Physicians’ Perspective in Germany

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  Authors List:

  • Julia C C Schulte-Strathaus  
  • Theresa Ikegwuonu  
  • Anita Schick  
  • Maria K Wolters  
  • Lena de Thurah  
  • Michal Hajdúk  
  • Adam Kurilla  
  • Inez Myin-Germeys  
  • Glenn Kiekens  
  • Jeroen D M Weermeijer  
  • Joanne R Beames  
  • Lotte Uyttebroek  
  • Rafaël Bonnier  
  • Iveta Nagyova  
  • Dagmar Breznoščáková  
  • Daniel Dančík  
  • Koraima Sotomayor Enriquez  
  • Islay Barne  
  • Jessica Gugel  
  • Ulrich Reininghaus  
  • Michel Wensing  
  • Charlotte Ullrich  

  Abstract:

  Background: Although the integration of self-monitored patient data into mental health care offers potential for advancing personalised approaches, its application in clinical practice remains largely underexplored. Capturing individuals' mental health outside the therapy room using Experience Sampling Methods (ESM) may bridge this gap by supporting shared decision-making and personalised interventions. Objective: This qualitative study investigated the perspectives of German mental health professionals regarding prototypes of ESM data visualisations designed for integration into a digital mental health tool. Methods: Semi-structured interviews were conducted with clinicians on their perceptions of such visualisations in routine care. Results: Using reflexive thematic analysis, three key findings were: (1) ESM and ESM data visualisations were seen as valuable tools for enhancing patient motivation and engagement over the course of treatment; (2) simplicity and clarity of visual formats, particularly line graphs, were preferred for usability; and (3) practical concerns, such workflow integration challenges centered on time constraints (psychotherapy session duration 50min) and need for patient psychoeducation materials, influenced perceived utility. Challenges, including the risk of cognitive overload from dense data representations (e.g., ESM mood-in-context visualisations), were raised. Conclusions: These findings underline the importance of designing digital tools that align with clinical needs while addressing potential barriers to implementation by exploring the opportunities and challenges associated with ESM visualisations.

  • J Med Internet Res 2025;27(1):e72893

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  Digital Health Reviews

  Dec 22, 2025

  Prognostic Prediction Models for Ulcerative Colitis: Systematic Review and Meta-Analysis

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  Authors List:

  • Zhijun Bu  
  • Yuan Sun  
  • Zeyang Shi  
  • Liming Hu  
  • Chuanlan Ju  
  • Yuan Liu  
  • Jing An  
  • Huiyi Sun  
  • Jianping Liu  
  • Zhaolan Liu  

  Abstract:

  Background: Ulcerative colitis (UC) is a chronic inflammatory disease with highly variable symptoms and severity. Prognostic models for UC support precision medicine by enabling personalized treatment strategies. However, the quality and clinical utility of these models remain inadequately assessed. Objective: This study aimed to systematically review and critically evaluate the development, performance, and applicability of prognostic prediction models for UC. Methods: To identify prognostic models for UC, a comprehensive search was conducted in PubMed, Embase, the Cochrane Library, Web of Science, SinoMed, China National Knowledge Infrastructure, Wanfang, and VIP Database up to November 2, 2024. Extracted data included study characteristics, model development methods, validation metrics (e.g., area under the curve [AUC], concordance index [C-index]). The risk of bias and applicability was evaluated using the Prediction Model Risk of Bias Assessment Tool (PROBAST). A meta-analysis was conducted to assess model performance. Results: A total of 30 studies involving 7,816 UC patients were included, with the largest numbers conducted in China (n=11) and Japan (n=4). Most studies were retrospective (n=22), with 67% being multi-center studies. The primary objectives of the UC prognostic models included predicting therapeutic effect and response to treatment, particularly to tumor necrosis factor-alpha inhibitors (e.g., infliximab, adalimumab), and assessing risks of surgery, disease progression, or relapse. Logistic regression was the most frequently used method for both predictor selection (n=6) and model construction (n=12). Common predictors included age, C-reactive protein, albumin, hemoglobin, disease extent, and Mayo scores. The meta-analysis yielded a pooled AUC of 0.86 (95% confidence interval [CI]: 0.80-0.92). Most studies exhibited a high risk of bias (n=29), particularly in participant selection and statistical analysis. Applicability concerns were identified in 18 studies, primarily due to subgroup-specific designs that limited the generalizability of the findings. External validation data (n=16) were limited, and only a small number of studies (n=14) included calibration curves or decision curve analysis. Conclusions: This study demonstrates that prognostic models for UC have some potential in predictive performance and clinical application. However, most models are constrained by high bias risk, insufficient external validation, and limited generalizability due to small sample sizes and subgroup-specific designs. Future research should prioritize multi-center validations, refine model development approaches, and enhance model applicability to support broader clinical implementation. Clinical Trial: PROSPERO CRD42024609424; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024609424

  • J Med Internet Res 2025;27(1):e71944

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  Digital Mental Health Interventions,...

  Dec 22, 2025

  Implementation of a Mobile Digital Tool Supporting Medication for Opioid Use Disorder Treatment Improves Retention: Stepped-Wedge Cluster Randomized...

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  Authors List:

  • Jorge E Palacios  
  • Robert Sherrick  
  • Tim Janssen  
  • Elana Deuble  
  • Sara Lorenzen  
  • Mark Schaefer  
  • Jenna Tregarthen  

  Abstract:

  Background: Despite its proven efficacy, retention in medication for opioid use disorder (MOUD) remains low, with structural and systemic barriers—such as access to care and treatment setting—alongside individual factors, including personalization and motivation, contributing to high rates of discontinuation. Digital interventions offer a promising approach to address many of these barriers; however, robust evidence for their effectiveness in improving retention and engagement with treatment remains scarce. Objective: This study aims to evaluate the impact of Recovery Connect—a white-labeled version of Recovery Path and a digital remote patient monitoring app used as part of a blended treatment model for opioid use disorder—on patient retention, treatment continuance, and medication adherence. Methods: A stepped-wedge cluster randomized trial was conducted across 9 outpatient MOUD clinics, organized into 8 clusters. Clusters were sequentially transitioned from usual care to a digitally enhanced model incorporating Recovery Connect, which provided real-time monitoring, psychoeducational and skill-based content, and messaging between patients and clinicians. The primary outcome was 30-day retention in treatment following exposure (implementation of the app in the clinic), linkage (downloading and connecting to the app), or engagement (levels of app usage). Secondary outcomes included treatment continuance—defined as receiving at least 75% of expected doses—and the number of daily doses taken within the first 3, 7, and 30 days after admission. Cluster-controlled discrete-time survival analyses were conducted, adjusting for patient- and clinic-level covariates. Results: Patients admitted to clinics that had implemented the app (n=1205) showed increased retention (922/1205, 75.5%) compared with those in clinics that had not (203/319, 63.6%, P<.001). Patients who downloaded and linked with a mental health professional on Recovery Connect had an 81.3% likelihood of retention, compared with 72.0% (P<.001) among those not linked. Linkage also significantly predicted higher treatment continuance and a greater number of daily doses taken during the first 7 and 30 days (P<.001). Low, moderate, and high engagement levels were associated with progressively higher 30-day retention compared with no engagement (P<.001). Conclusions: This study provides evidence that implementing Recovery Connect (Recovery Path) significantly enhances patient retention and treatment continuity in outpatient opioid use disorder care. Early linkage and engagement during the first week were strong predictors of positive outcomes, underscoring the value of early, proactive digital support. These findings reinforce the effectiveness of blended digital-clinical models, aligning with broader evidence that integrating remote monitoring enhances continuity of care and supports recovery. Policy implications include the need for reimbursement mechanisms, workflow integration, and ethical, privacy-preserving implementation to enable scalable and equitable adoption of digital tools in substance use treatment. Trial Registration: ClinicalTrials.gov NCT07140926; https://clinicaltrials.gov/ct2/show/NCT07140926

  • J Med Internet Res 2025;27(1):e83346

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  Digital Health Reviews

  Dec 22, 2025

  Tai Chi Chuan Auxiliary Training Systems in Health and Rehabilitation: Scoping Review

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  Authors List:

  • Hong Liu  
  • Huibiao Li  
  • Haoyu Huang  
  • Jia Huang  
  • Yanxin Zhang  
  • Lidian Chen  

  Abstract:

  Background: Tai Chi Chuan (TCC), often described as "moving meditation", is a traditional Chinese mind-body exercise suitable for individuals of all ages. Mounting evidence demonstrates that TCC can improve physical functions, promote physical activity, and positively impact health and longevity. However, systematic learning is hindered by insufficient teaching resources, difficulties in imparting expertise, and learning environment constraints. TCC auxiliary training systems, an innovative means of human-computer interaction, provide a potential solution. Objective: This scoping review evaluates the current research trends and clinical outcomes of TCC auxiliary training systems. Specifically, we compare the development tools, system design, and evaluation/validation processes used by different systems, with the aim of guiding future development in this research area. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines, electronic databases PubMed, Embase, Scopus, IEEE Xplore and ACM Digital Library were systematically searched for articles in English from 2014 to 2024. Two reviewers independently extracted the data and used an adapted version of the Santos evaluation criteria to evaluate the quality of the included studies. These studies will qualitatively summarize system design and evaluation verification. Results: Among the 2202 identified articles, 34 studies met the inclusion criteria, of which 24 were rated as medium to high quality. Desktop-based applications dominate the TCC auxiliary training system environment, comprising 38% (13/34) of the selected articles. The hardware and software components of TCC auxiliary training systems vary depending on the development objectives. Regarding system design, the majority 76% (26/34) addressed all groups, with only a minority focusing on specific populations. Interaction design in TCC auxiliary training commonly incorporates human-computer interaction technologies, such as tactile, action, visual, speech, and multimode interaction. Clinical validation is necessary to implement this system in clinical practice. Most reviewed studies were validated; six underwent acceptability validation, twenty-one underwent feasibility validation, and only two based on virtual reality underwent clinical efficacy validation, demonstrating their effectiveness in improving cognitive abilities and motor functions in older adults. Conclusions: The TCC auxiliary training system is an innovative health intervention in a rapidly advancing field. This scoping review, the first undertaken on this topic, systematically synthesizes current evidence regarding its design, applications, research trends, and clinical outcomes, thereby establishing a comprehensive foundation to guide and inform future research. However, the current evidence still faces issues such as methodological inconsistencies, insufficient sample diversity, and a lack of long-term effect validation, which limit its generalizability and effectiveness in widespread applications. Future research should place greater emphasis on standardized reporting, applicability to diverse populations, and foster ethical considerations and interdisciplinary collaboration. This will facilitate the widespread deployment of the TCC auxiliary training system and ensure its sustainable integration into the field of health intervention. Clinical Trial: PROSPERO CRD42024539375; https://www.crd.york.ac.uk/PROSPERO/view/CRD42024539375

  • J Med Internet Res 2025;27(1):e64207

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  Digital Health Reviews

  Dec 22, 2025

  Toward Inclusive Design Heuristics for Digital Health Interventions for the Aging Population: Scoping Review

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  Authors List:

  • Kerstin Denecke  
  • Lana Cvijic  
  • Carolyn Petersen  

  Abstract:

  Background: Digital health interventions (DHI) deliver health-related services in a digital manner. Meant for older adults, they must be tailored to address their needs. This may be by applying inclusive design principles. Inclusive design is an approach that aims to accommodate the needs of a broad spectrum of users, taking into account health-related factors, socioeconomic status, age, cultural background, language diversity, and other factors. Objective: This review aims to collect best practices on the inclusive design of DHIs for older adults and aggregate them into a set of design guidelines. Methods: We examined peer-reviewed papers from 3 databases that described a design and development process of a DHI specifically designed for users aged 60 years or older, and used inclusivity to design the solution. The process followed PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guideline and PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses literature search extension) checklist. Information on the DHIs and their design process, as well as facilitators and barriers for adopting DHIs by older adults, was extracted. Results: Of 1276 records, 40 papers were included and considered for data synthesis. DHIs are provided through a broad range of technical platforms (mobile apps [20/40], web-based platforms and web apps [6/40], voice and virtual assistant technology [2/40], telehealth and remote monitoring systems [4/40], and tablet-based and specialized systems [8/40]). Sometimes, their design process included older adults (2/40) but also clinicians (1/40), designers and developers (3/40), and researchers (3/40), as well as other community stakeholders (3/40). The derived design heuristics to be considered for inclusive design comprise 11 aspects covering multiple dimensions: visual design and readability, navigation, accessibility, customization and personalization, social engagement and support, learnability, multiplatforms and device compatibility, motivation, feedback and user engagement, security and privacy, inclusive language, and costs. Barriers range from age-related health issues to technical hurdles related to access or connectivity. Conclusions: The inclusive design of DHIs for older adults extends beyond usability and user interface design. This study highlights the critical role of co-designed DHIs in addressing persistent challenges of isolation, limited mobility, and access to care among older adults. Older adults must be placed at the center of development, with their needs and challenges identified and addressed in the solution. By enabling tailored, locally relevant digital experiences, co-design empowers older adults to engage meaningfully with health services despite infrastructural and socioeconomic barriers. The list of inclusive design aspects and recommendations provides a starting point for DHI developers to create functionality that supports many needs and goals of older adults. Future work must validate our results from a practical perspective. The adoption of our heuristics in practice could be fostered by developing concrete methods that implement them. Trial Registration:

  • J Med Internet Res 2025;27(1):e79449

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  Infodemiology and Infoveillance

  Dec 19, 2025

  Intersection of Big Five Personality Traits and Substance Use on Social Media Discourse: AI-Powered Observational Study

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  Authors List:

  • Julina Maharjan  
  • Ruoming Jin  
  • Jianfeng Zhu  
  • Deric Kenne  

  Abstract:

  Background: Personality traits are known predictors of substance use (SU), but their expression and association with SU in digital discourse remain largely unexamined. During theCOVID-19 pandemic, the online social engagement heightened, and led the amplification in SU rates, thereby creating a unique natural opportunity to investigate these dynamics through a large-scale digital discourse data. In our study we offer insights beyond traditional self-report methods, which is crucial for developing timely and targeted public health interventions. Objective: To evaluate whether the associations between the Big Five personality traits and SU discourse shifted during the 2019–2021 period, and to conduct a focused analysis of how these traits predict SU and relate to specific substance types, emotional expression, and demographic factors. Methods: We analyzed a corpus of several hundred million public posts from a major social media platform from 2019 to 2021. Using a pipeline of natural language processing and deep learning models, we identified SU-related posts and subsequently extracted scores for the Big Five personality traits, emotions, and user demographics. We employed trend analysis to compare annual shifts in trait-SU associations, while detailed 2020 data underwent rigorous modeling using logistic regression, correlation analysis, and topic modeling to elucidate the core relationships. Results: Our analysis revealed that Extraversion (Odd Ratio=3.22) and, most strikingly, Agreeableness (Odd Ratio=4.04) were the strongest positive predictors of being a substance user. In stark contrast to the conventional self-medication hypothesis, Neuroticism emerged as a robust protective factor against SU (Odd Ratio=0.29). This counterintuitive finding was supported by a decreased association between Neuroticism and SU posts at the pandemic's onset in 2020 (Cohen’s value, d=−0.13, 95% Confidence Interval) and a negative correlation with the expression of negative emotions online. Topic modeling further indicated that SU discourse was frequently embedded in social contexts (Social Drinking, Friendly Beverage Choices) rather than themes of solitary coping. Conclusions: Our findings challenge traditional models by demonstrating that in large-scale online discourse, SU expression is more powerfully linked to social-affiliative traits than to negative emotionality. The paradoxical protective role of Neuroticism suggests that established risk profiles may not apply uniformly to digital environments, particularly during a public health crisis. These insights are vital for refining computational methods for public health surveillance and developing interventions that recognize the potent social drivers of substance use in the digital age.

  • J Med Internet Res 2025;27(1):e79454

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  Medicine 2.0: Social Media, Open,...

  Dec 19, 2025

  Time Spent on Social Media Applications in Relation to Depressive Symptoms During Emerging Adulthood and the Mediating Role of Sleep Quality: Cross-Sectional...

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  Authors List:

  • Qi Zou  
  • Jiabi Qin  
  • Lei Zhang  
  • Wenhua Wang  
  • Xiaoxiao Yuan  
  • Tingting Wang  
  • Yuan Peng  
  • Ye Chen  
  • Linfei Dou  
  • Xinghua Yang  
  • Xirennayi Abudurexiti  
  • Mingyang Wu  

  Abstract:

  Background: The link between social media use and depressive symptoms remains bidirectional. Findings in this area are often compromised by methodological limitations related to measurement and sample size. As a result, it is challenging to assess dose-response relationships and potential causal pathways. Objective: To utilize objective measurement methods to assess the dose-response relationship and potential mechanisms between social media use and depressive symptoms. Methods: This study was conducted in six universities in 2022. Social media use duration was assessed based on the monitoring of mobile phone systems, and depressive symptoms were evaluated by the Self-Rating Depression Scale. Logistic regression and restricted cubic spline were employed to assess the relationship between social media use and depressive symptoms. Mediation analysis was used to elucidate the biological pathways of sleep quality in the above-mentioned relationship. Results: A total of 7,401 college students were included in the final analysis, with 5% of moderate to severe depressive symptoms. After adjusting for variables such as sociodemographic characteristics and health-related characteristics, there was a significant association between individuals with longer weekly social media usage time and depressive symptoms (OR>48h, 1.769; 95%CI, 1.303-2.400). Similarly, the association between instant messaging-based social media use duration and depressive symptoms was also significant (OR>24h, 1.728; 95%CI, 1.225-2.437), while no associations were observed for content-based social use (OR>24h, 1.251; 95%CI, 0.932-1.680). Restricted cubic splines regression demonstrated a J-type relationship between social media use duration and depressive symptoms. Additionally, sleep quality played a partial mediating role in the relationship between social media use duration and depressive symptoms, with the mediating effect values ranging from 24.10% to 25.25%. Conclusions: Prolonged social media use duration might be associated with an increased prevalence of depressive symptoms in emerging adulthood, and may increase the odds of depression by affecting sleep quality, suggesting that early prevention and intervention regarding social media use might help to ameliorate depressive symptoms.

  • J Med Internet Res 2025;27(1):e75337

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  Digital Health Reviews

  Dec 19, 2025

  The Impact of Patient-Generated Health Data From Mobile Health Technologies on Health Care Management and Clinical Decision-Making: Narrative Scoping Review

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  Authors List:

  • Ava Keeling  
  • John Downey  
  • Matthew Halkes  
  • Yinghui Wei  

  Abstract:

  Background: Long-term health conditions and multimorbidity are increasing globally placing an unsustainable pressure on healthcare systems. Mobile health technologies, or mHealth, enable the collection of patient-generated health data outside clinical settings, offering the potential to support personalised care and inform clinical decision-making. However, the ways in which mHealth patient data is being used in clinical practice remains unclear. Objective: To map and synthesise the existing literature on how patient-generated mHealth data is reportedly being used and influencing clinical decision-making for adults with long-term conditions in an outpatient care setting. Methods: A narrative scoping review was conducted on studies published between 2014 and 2025. Studies were eligible for inclusion if they were in English, had data on the use of patient generated mHealth data, went beyond feasibility testing, and had reference to clinician behaviour/patient interactions. Grey literature was not used to maintain a focus on peer reviewed and published evidence. Studies involving paediatric or adolescent populations were excluded. Searches were conducted across the following databases between 2014 and 2025: Embase, MEDLINE, Knowledge and Library Hub, British Nursing Indes, Proquest Health Research Premium Collection. Data were charted systematically and synthesised narratively. Key data included study characteristics, mHealth use, data types and visualisations, patient demographics, and the ways data informed clinical decision-making. Results: 16 studies met the inclusion requirements which were primarily high-income countries focusing on rheumatoid arthritis and diabetes. Studies reported on how mHealth data was integrated into workflows, influenced healthcare decisions, and shaped patient-provider interactions. mHealth patient data was found to support patient-centred care and facilitate proactive holistic care, though in some instances it was shown to reinforce medical agendas removing agency from patients. There is also a gap between the intended use of the data and its implementation in clinical practice. Reported barriers included professional scepticism, integration challenges, and concerns about data accuracy. Evidence was focused on feasibility rather than long-term outcomes, with limited evidence on the impacts of mHealth. Conclusions: PGHD has potential to enhance clinical decision-making and person-centred practices. However, integration into routine practice is hindered by technological challenges, professional hesitancy, and a lack of standardisation. Future research should prioritise supporting integration, improve data presentation, and evaluate the long-term effects on clinical workflows. Addressing these barriers and establishing clear policy frameworks will be crucial for realising the potential of mHealth in healthcare delivery.

  • J Med Internet Res 2025;27(1):e77359

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  Digital Health Reviews

  Dec 19, 2025

  Impact of Telerehabilitation on Rehabilitation Efficacy and Patient Satisfaction After Knee Surgery: Systematic Review and Meta-Analysis of Randomized...

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  Authors List:

  • Yuang Wang  
  • Xinge Liu  
  • Qingyi Wu  
  • Qiming Zhu  
  • Ming Zhang  

  Abstract:

  Background: Postoperative rehabilitation after knee surgery is crucial for functional recovery, but traditional in-person methods can impose burdens on patients, particularly those with mobility limitations or living remotely. Telerehabilitation, leveraging digital platforms, offers a potential alternative, yet its comparative efficacy and acceptability remain debated, especially across surgery types. Objective: To evaluate if telerehabilitation improves postoperative rehabilitation satisfaction and efficacy compared to traditional methods for knee joint surgery patients. Methods: Six databases (Web of Science, PubMed, MEDLINE, ScienceDirect, EMBASE, Cochrane Library) were searched from inception to September 27, 2025. Eligibility criteria included randomized controlled trials (RCTs) comparing telerehabilitation with traditional rehabilitation in adult postoperative knee surgery patients, reporting patient satisfaction and/or efficacy outcomes. Risk of bias was assessed using the Cochrane Risk of Bias 1 tool. Data were synthesized using random-effects meta-analysis with the Hartung-Knapp-Sidik-Jonkman method for confidence intervals, reporting standardized mean differences or mean differences, τ2, τ, and prediction intervals where applicable. Heterogeneity was assessed with τ2, τ and PIs. Certainty of evidence was evaluated using GRADE. Results: 19 RCTs were included. Overall, on average, patient satisfaction showed no significant difference between telerehabilitation and traditional rehabilitation (SMD = 0.15; 95% CI = -0.48 to 0.78; P = .48; τ2 = 0.30; τ = 0.55; PI = -1.17 to 1.47). Subgroup analysis revealed on average lower satisfaction with synchronous telerehabilitation (k=4; SMD = -0.52; 95% CI = -1.02 to -0.02; P = .04; τ2 = 0.17; τ = 0.41) and higher with asynchronous (k=6; SMD = 0.56; 95% CI = 0.08 to 1.03; P = .02; τ2 = 0.30; τ = 0.55). Telerehabilitation showed significant improvements on total WOMAC (k=4; SMD = -0.76; 95% CI = -1.38 to -0.14; P = .02; τ2 = 0.08; τ = 0.29; PI = -1.85 to 0.33), KOOS (k=5; SMD = 0.58; 95% CI = 0.47 to 0.70; P = .01; τ2 = 0; τ = 0; PI = 0.36 to 0.80), TUG (k=4; MD = -2.73 s; 95% CI = -4.50 to -0.96; P = .04; τ2 = 1.14; τ = 1.07; PI = -7.17 to 1.72) and knee extension range (k=3; MD=9.64°; 95% CI = 6.89 to 12.39; P=.049; τ2 = 2.45; τ = 1.56; PI = 0.60 to 18.68). Risk of bias was low to moderate; heterogeneity moderate. Conclusions: The pooled average effects suggest that telerehabilitation is noninferior to traditional care for patient satisfaction on average and may improve pain and function and some objective measures. However, bootstrapped prediction intervals and between-study variability indicate that effects vary by context; implementation should therefore be individualized with attention to modality, patient digital literacy, and technical support. Targeted trials with standardized measures are recommended to increase certainty and narrow the expected distribution of effects. Clinical Trial: PROSPERO CRD420251025461; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251025461.

  • J Med Internet Res 2025;27(1):e76844

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  Public (e)Health, Digital...

  Dec 19, 2025

  Social Media, Health Consciousness, and Cultural Influences on Sugar Reduction Behaviors in Chinese Youth: Extending the Stimulus-Organism-Response Model

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  Authors List:

  • Bing Hu  
  • Yi Zhu  
  • Ruxiang Bao  
  • Ziying Zhao  
  • Chao Liu  
  • Aomi Lin  

  Abstract:

  Background: The rising prevalence of sugar-related diseases, such as obesity and diabetes, has intensified efforts to reduce sugar intake, particularly among youth. In China, social media is playing an increasingly significant role in shaping health behaviors, including habits related to sugar consumption as sugar reduction has become a prominent youth-led movement. Objective: This study extends the Stimulus-Organism-Response (SOR) model by incorporating the distinct cultural influence of "face" to investigate the impact of social media on sugar reduction behaviors among Chinese youth, as well as the mediating role of health consciousness and conformity, and the moderating effects of face concern and eHealth literacy. Methods: We conducted a national web-based cross-sectional survey through proportionate probability sampling of 883 Chinese youth in July 2024. Descriptive statistics, Pearson correlations, Model fit indices and PLS (Partial Least Squares) SEM were employed to examine and explore the relationships among all the variables. Results: Nearly half the 883 participants were female (460/883, 52.1%) , 91.9% (812/883)of the sample ages fall within the 15-30 range. Most of the participants (602/883, 68.2%) had undergraduate education levels; the majority of participants (688/883, 77.9%) had a bachelor's degree or higher, and a normal Body Mass Index (BMI) (654/883, 74.1%). Most (575/883, 74.1%) had used social media for 3–10 years. Chinese youth reported relatively high sugar-reduction behavior scores in sugar reduction behaviors (mean score: 3.621/5, SD 0.990). Male participants achieved notably higher scores in sugar reduction behaviors.(mean score 3.725/5, SD 0.933), Participants at the age of 15–18 showed significantly lower sugar reduction behavior scores (mean score 3.508/5, SD 1.052). Structural equation modeling revealed that social media usage positively influenced conformity (β=.508, P<.001) and health consciousness (β=.353, P<.001). These factors in turn significantly predicted sugar reduction behaviors (β=.139 and β=.498, respectively; both P<.001). The influence of social media usage on sugar reduction behaviors is primarily facilitated through two mediating pathways.Health consciousness mediated the relationship between social media usage and sugar reduction behaviors (VAF=51.5%), while conformity's mediation was less pronounced (VAF=21.05%), indicating a secondary influence. Face concern (β=0.089, P=.02) and eHealth literacy (β=0.055, P=.04) moderated the respective relationships. Conclusions: This study demonstrates that social media effectively promotes sugar reduction behaviors among Chinese youth. By embedding cultural influences like face concern alongside enabling competencies like eHealth literacy an extended SOR model, we enhance our understanding of social media's influence on health behaviors. The findings highlight cultural nuances in health communication and position the enhanced SOR model as a framework for health promotion. Furthermore, The study underscores the primary mediating effect of health consciousness—surpassing that of conformity—while also delineating the moderating roles of face concern and eHealth literacy, offering actionable insights for digital-age public health strategies.

  • J Med Internet Res 2025;27(1):e68180

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  News and Perspectives

  Dec 18, 2025

  Beyond Waiting: How Patients Are Reshaping Digital Health

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  • Anshu Ankolekar

  Abstract:

  • J Med Internet Res 2025;27(1):e89205

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