Background: Multiple, independent lines of #Research on self-regulation point to executive cognitive ability (executive function/cognitive control) as a factor that underlies the capacity to successfully regulate one’s thoughts, emotion, and behavior. Critically, while leading theories point to the role of executive control in modifying ‘in-the-moment’ regulatory processes (e.g., enacting physical activity, resisting a poor dietary choice, reflecting on a stressful experience), few studies have tested the executive hypothesis at this timescale. Moreover, given normative changes in executive control across the adult lifespan, it is essential to understand how cognitive aging might impact these processes. Objective: The Physical Activity, Imaging, and Ambulatory Testing (PHIAT) project was designed to test how variation in executive control at multiple timescales (from moment-to-moment within-days to age-differences across decades) influences self-regulation across the adult lifespan. Methods: A 14-day, high-frequency, ambulatory assessment #Protocol was designed for the current #Study. The #Study was conducted in a measurement burst design and included a 14-day ecological momentary assessment (EMA) #Protocol involving 6 assessments per day. Ultra-brief ambulatory cognitive assessments of multiple domains of cognition were included in the EMA #Protocol. Throughout the measurement burst, participants also wore 3 activity monitors on the hip, thigh, and wrist to measure physical activity/exercise, sedentary behavior, and to self-monitor physical activity behavior, respectively. Results: A total of N=221 participants ranging from 18-89 years of age completed the PHIAT #Protocol over the course of 2021 to 2024 and data collection is complete. EMA data was collected from participants reflecting a wide range of psychosocial factors surrounding participation in health-promoting behaviors (motivation, intention, stress, built environment, social cognitive factors). This EMA data stream is complemented by data from high-frequency, ambulatory cognitive assessments measuring processing speed, working memory capacity, inhibitory control, and divided/sustained attention administered 5 times per day throughout the 14-day burst. In addition, health promoting behaviors, including sleep, diet, hydration, physical activity, and exercise, were assessed throughout the 14-day burst through a combination of EMA self-report and continuous activity monitoring. Conclusions: A rich, high-frequency dataset was generated by the PHIAT project that will provide a range of novel insights into the motivational, information processing, and environmental factors that surround self-regulation of health-promoting behavior.

Date Submitted: Sep 12, 2025. Open Peer Review Period: Oct 6, 2025 - Dec 1, 2025.

Background: Tele#health interventions have the potential to support preventing mother-to-child HIV transmission (PMTCT) initiatives. Nevertheless, there is a lack of reviews to explore #patient experiences and attitudes toward #digital technology interventions. Objective: The study aims of the study was to explore #patient experiences and attitudes toward #digital #health technology interventions in promoting PMTCT. Methods: The study used a systematic review and qualitative meta-aggregation adhered to the preferred reporting items for systematic review and meta-analysis (PRISMA) and Joanna Briggs Institute (JBI) Reviewer’s Manual. Electronic databases such as Scopus, PubMed, CINAHL, and Wiley were comprehensively searched. Eligibility criteria of this study are qualitative study focused on mothers living with HIV and their #healthcare providers, exploring their experiences and attitudes toward #digital #health interventions for the PMTCT of HIV. We assessed the quality of the studies using the JBI Critical Appraisal tools for qualitative #research and the Mixed Methods Appraisal Tool (MMAT) for mixed methods studies. The study used meta-aggregation to synthesis of included qualitative studies. Results: The search yielded Eight included studies were analyzed. The study revealed four synthesized finding which included (1) positive acceptability of using #health intervention for PMTCT, (2) #patients' need education, (3) concerns about confidentiality, (4) personal, interpersonal, and #healthcare barriers to adhering to care. Nine categories include good perceived-satisfaction, enhanced adherence, #patient needs education, support systems, reminders, concerns about confidentiality, lack of family support, financial, and bad attitudes of provider. Conclusions: The study demonstrates that #digital #health interventions are well-received by HIV-positive pregnant women, but attention to confidentiality, family support, financial barriers, and provider attitudes is essential. These findings suggest that nurses and other #healthcare professional can utilize #mobile #health interventions to enhance PMTCT outcomes through continuous education, support, and by addressing barriers to care.

The widespread adoption of Large Language Models (LLMs) is increasingly shaping clinical decision-making by altering how physicians engage with data and reasoning. While these tools enhance diagnostic capacity, streamline workflows, and support learning, it misuse may diminish critical, contextual, and humanized thinking, reducing physicians to passive validators of algorithmic outputs. This article explores the evolution of medical cognition and proposes strategies for integrating AI in ways that preserve cognitive autonomy, such as structuring information, reducing bias, and strengthening metacognition. We argue that AI should serve as a "cognitive stethoscope", a tool that refines reasoning without compromising its essence.

Background: Cognitive training is an effective approach to support cognitive function in older adults. Incorporating meaningful leisure activities, such as gardening, may enhance both engagement and training outcomes. While fully immersive #VirtualReality #VR (VR) offers ecologically valid and engaging environments that can further boost motivation, limited research has explored the combination of VR-based cognitive training with leisure activities for older adults. Objective: This study aims to assess the feasibility, usability, and preliminary effectiveness of leisure-based VR cognitive training for community-dwelling older adults. Methods: A fully immersive VR cognitive training system was developed using a head-mounted display, incorporating gardening-themed activities such as planting, fertilizing, watering, and harvesting. These tasks were designed to engage multiple cognitive domains, including memory, attention, executive function, processing speed, and spatial abilities. The program consisted of 16 sessions delivered over 8 weeks (twice weekly, 1 hour per session). Cognitive outcomes were assessed before and after training using the Montreal Cognitive Assessment, the Digit Symbol Substitution Test, Word List Immediate and Delayed Recall, Spatial Span, and the Stroop Color and Word Test. Feasibility, acceptance, and usability were evaluated using the System Usability Scale and a post-training questionnaire. Licensed occupational therapists from both community and institutional settings assessed the system’s usability. Results: All 41 participants (mean age = 69.8 years) completed the training with 100% adherence and no serious adverse events. Feasibility ratings—particularly for perceived usefulness, intention to use, and subjective norms—reflected strong acceptance. Usability ratings from older adults indicated high ease of use, enjoyment, and positive experience, while professionals rated the system as moderately usable (mean System Usability Scale score = 68). Statistically significant improvements were observed in general cognition (p = .004), processing speed (p = .049), immediate and delayed memory (p < .001), and executive function (p = .002). No significant changes were found in visuospatial memory (p = .29). Conclusions: This study provides preliminary evidence supporting the feasibility and usability of a gardening-based VR cognitive training program for older adults. Feasibility was demonstrated through full adherence, absence of major adverse events, and high participant acceptance. Usability feedback was favorable from both older adults and professionals across community and long-term care settings. Additionally, improvements in multiple cognitive domains—including general cognition, processing speed, memory, and executive function—suggest potential cognitive benefits. Future randomized controlled trials with more diverse samples and extended follow-up are warranted to confirm and expand upon these findings. Clinical Trial: ClinicalTrials.gov Identifier NCT05227495; https://clinicaltrials.gov/study/NCT05227495.

Background: We co-designed a novel multicomponent Care Assistant and support Program for people after Stroke or transient ischaemic attack (CAPS) to augment secondary prevention of stroke. Objective: Following completion of a feasibility study, we sought feedback from Australian clinicians and service provider representatives (the potential deliverers of CAPS) regarding their perceptions of CAPS for secondary prevention, and pathways to real-world adoption. Methods: Qualitative descriptive study of clinicians and service provider representatives involved in delivery of stroke care around Australia. A pragmatic convenience sample was obtained from previous CAPS co-design study participants, leveraging professional networks (e.g., LinkedIn), and distributing study flyers and newsletters via Primary Healthcare Networks, General Practitioner (GP) networks, and social media posts (CSIRO LinkedIn pages). Semi-structured interviews and focus groups were conducted virtually with clinicians and representatives of the Stroke Foundation (Australia). Data were thematically analysed using an integrated approach. Results: Three Stroke Foundation representatives and eighteen clinicians participated, from five Australian states, including medical specialists, GPs, nurses, and allied health professionals. We collected their perceptions of CAPS, including potential benefits of the program for secondary prevention, and considerations for facilitators and challenges to real-world program implementation. Discussion regarding the perceived benefits focussed more on the benefits to patients than to clinicians. Program implementation sub-themes included program initiation and duration, patient support considerations; and workflow alignment, which included consideration of barriers and enablers to uptake within primary care practice and Stroke Foundation outreach support programs. Conclusions: There was support from participants for the potential of CAPS to improve secondary prevention of stroke. However, addressing the challenges raised by participants including further implementation and integration considerations, such as sustainability of the model of care, are likely required for CAPS to be successfully embedded within clinical settings.

Background: The #covid19 pandemic forced many researchers, including our team, to adjust our research methods from in-person to virtual formats. This paper explores the acceptability and suitability of synchronous virtual focus groups used to explore the interplay of housing and health with Métis Nation of Ontario (MNO) citizens, one of three constitutionally recognized distinct Indigenous Peoples in Canada. Objective: The objective of this survey was to gather information on the experiences of MNO citizens participating in a synchronous virtual focus group targeting acceptability and suitability. Methods: Only participants of the “Understanding Housing and Health” project were eligible to complete the survey. A link to the survey was included in a ‘thank you’ email to participants. The survey asked respondents to rate their experience, satisfaction, preference, #feasibility, and the cultural appropriateness of the virtual focus group. An open textbox was included for respondents to share additional thoughts. Demographic and personal information (i.e., age, gender, MNO region, email) were also collected. Thirty-three of 35 eligible participants completed the survey. A content analysis was conducted to generate themes from the open-text responses and used to triangulate the results. The survey was developed collaboratively with MNO staff. Results: Most respondents identified as women and were 45-65+. All respondents had used Zoom before, with 70% having used it regularly for work or school. 85% of respondents were either strongly or somewhat confident in their ability to use Zoom. 100% of respondents strongly or somewhat agreed that they would participate in a virtual focus group in the future and 86% of respondents strongly (67%) or somewhat agreed (21%) that a virtual focus group was culturally appropriate for Métis health research. 82% of respondents strongly or somewhat agreed that a virtual focus group was more feasible. Moreover, only 58% of respondents strongly or somewhat disagreed that they would have preferred to participate in an in-person focus group, while 27% were neutral. 58% of respondents could see other participants all of the time and did not experience lag at any point while 76% could hear other participants all of the time, indicating less issues with audio. 70% of respondents felt they could connect with others all or most of the time, while 30% felt they could do this some of the time or rarely. Content analysis of the open-textbox responses generated 4 themes: Internet and technology issues, Accessibility, Structure of the group discussion, and Positive feedback. Conclusions: The use of virtual focus groups for research with MNO citizens is acceptable, however internet and technology issues can affect a participant’s ability to fully engage. Considerations around cultural appropriateness and connecting with others should be made. This information will help inform methods selection for future research work conducted in collaboration with the MNO.

Background: Rare hematologic diseases are frequently underdiagnosed or misdiagnosed due to their clinical complexity. Whether new-generation large language models (LLMs), particularly those employing chain-of-thought (CoT) reasoning, can improve diagnostic accuracy remains unclear. Objective: To evaluate the diagnostic performance of new-generation commercial LLMs in rare hematologic diseases and to determine whether LLM output enhances physicians’ diagnostic accuracy. Methods: We conducted a two-phase study. In the retrospective phase, we evaluated seven mainstream LLMs on 158 non-public real-world admission records covering nine rare hematologic diseases, assessing diagnostic performance using Top-10 accuracy and mean reciprocal rank (MRR), and evaluating ranking stability via Jaccard similarity and entropy. Spearman’s rank correlation was used to examine the association between physicians’ diagnoses and LLM-generated outputs. In the prospective phase, 28 physicians with varying levels of experience diagnosed five cases each, gaining access to LLM-generated diagnoses across three sequential steps to assess whether LLMs can improve diagnostic accuracy. Results: In the retrospective phase, ChatGPT-o1-preview demonstrated the highest Top-10 accuracy (70.3%) and MRR (0.577). DeepSeek-R1 ranked second. Diagnostic performance was low for AL amyloidosis, Castleman disease, Erdheim-Chester disease, and POEMS syndrome. Interestingly, higher accuracy often correlated with lower ranking stability across most LLMs. The physician performance showed a strong correlation with both Top-10 accuracy (ρ = 0.565) and MRR (ρ = 0.650). In the prospective phase, LLMs significantly improved the diagnostic accuracy of less-experienced physicians; no significant benefit was observed for specialists. However, when LLMs generated biased responses, physician performance often failed to improve or even declined. Conclusions: Without fine-tuning, new-generation commercial LLMs, particularly those with CoT, can identify diagnoses of rare hematologic diseases with high accuracy and significantly enhance the diagnostic performance of less-experienced physicians. Nevertheless, biased LLM outputs may mislead clinicians, highlighting the need for critical appraisal and cautious clinical integration with appropriate safeguard systems. Clinical Trial: Chinese Clinical Trial Registry Identifier: ChiCTR2400089959.

Published in the Journal of Medical Internet Research, the study reviewed 659 online posts from IBD-specific subreddits and identified common ...

A 2022 study in the Journal of Medical Internet Research found that self-care improved people's quality of life. Managing one's physical and ...

Journal of Medical Internet Research · Journal of Medical Internet Research 10484 articles · JMIR Research Protocols 5048 articles · JMIR Formative ...

Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.10.2025. Publication types. Systematic Review; Meta ...

Background: As digital technology advances, health-related data can be scientifically analyzed to predict illnesses. The analysis of international data collected during health examinations and health status monitoring, along with data collected during medical care delivery, can contribute to Precision Medicine and the public good. Understanding citizens’ attitudes and predictors of digital health data sharing is critical in promoting data-driven research. Objective: To determine the public acceptability of data sharing and the attitudes and influencing factors toward data sharing. Methods: A cross-sectional online survey was conducted in Japan from November 11–18, 2023. We analyzed 1,000 valid responses. Five factors were investigated as predictors of participants’ attitudes toward sharing digital health data for social benefit: 1) individual sociodemographic characteristics, 2) types of health data shared, 3) Motivation for Sharing Data 4) data sharing concerns, and 5) reasonable access and control over the data. The association of these factors with the respondents’ willingness to share was analyzed. We summarized demographic characteristics based on gender, age group, affiliated educational institution, and education history/degree. Continuous variables are expressed as means ± standard error (SD). Logistic regression was used to analyze the association between attitudes and acceptability of sharing digital health data and the predicting factors, such as participants’ preferences regarding data access and control, underlying concerns, motivations for data sharing, demographic characteristics, and eHealth literacy. Results: The mean age of the participants and the standard deviation was 52.8 ± 19.8 years. We identified the factors influencing respondents’ willingness to share a wide range of personal digital health data in Japan, including data in medical records, biobank samples, and digitized social communication. Approximately 70% of the participants were willing to share their digital health data . The motives associated with positive willingness to share digital health data were helping future patients (OR 2.5860 95% CI 1.8849–3.5481 P

Date Submitted: Oct 4, 2025. Open Peer Review Period: Oct 6, 2025 - Dec 1, 2025.

This is a peer review report related to "Variance estimation for assessing healthcare providers’ performance using log standardized incidence ratio: Bayesian, Bootstrap and Delta-method"

Background: In healthcare providers’ performance assessment, standardized incidence ratios (SIRs) are essential tools used to assess whether observed event rates deviate from expected values. Accurate estimation of variance in these ratios is crucial as it affects decision-making regarding providers’ performance. There is little data on how the choice of these variance estimation methods affects decision-making. Objective: In this paper, we compared three methods, namely, delta-method, bootstrapping and Bayesian approaches, to estimate the variance of the logarithm of SIR (Log-SIR). Methods: Using patient-level data from Australia and New Zealand Dialysis and Transplant Registry (ANZDATA) for 2012-2023, we used a random effects model to predict treatment at home one year after starting treatment. We compared the three approaches (with over 5000 iterations for bootstrapping and MCMC sampling) using bias, variance and mean square errors (MSE) as performance measures. Using the three methods, funnel plots were used to compare the hospitals’ performance in treating Indigenous and non-Indigenous patients close to home, as a service-level measure of equity. Results: The bias values across all methods are similar, with Bayesian narrowly having the lowest bias (0.01922), followed by the delta-method (0.01927) and Bootstrap (0.02567). In addition, the Bayesian exhibits the lowest variance (0.00005), indicating more stable and less dispersed estimates. The delta-method has a higher variance (0.00016), while Bootstrap has the highest variance (0.00027), meaning it introduces more uncertainty. Finally, the Bayesian has the lowest MSE (0.00042), indicating better overall accuracy while the Bootstrap has the highest MSE (0.00094), showing it is the least reliable method. Conclusions: We demonstrate that these methods can be used to measure equity for patient centred outcomes, both within and between service providers simultaneously. The choice of variance estimation method is critical and heavily affects the interpretation of the performance of health service providers. We favour the Bayesian MCMC method. The Bayesian MCMC method found to be better approach. Clinical Trial: actRN12623001241628

Background: Only about one in two patients with knee osteoarthritis (OA) receives a referral or recommendation for exercise. Digital health technologies could counteract this undersupply. Objective: We aimed to investigate the effectiveness of a self-directed m-Health exercise intervention (re.flex) compared to usual care in patients with knee OA. Methods: This monocentric, two-arm, randomized controlled parallel-group trial included patients with moderate to severe knee OA. Participants were mainly recruited via newspapers. Randomization was 1:1 into an intervention group (re.flex) and a control group (usual care) using computer-generated blocks (stratified by etiology, medication, laterality). Participants were unmasked to group assignment. The re.flex group conducted a 12-week self-directed app-based and sensor-assisted exercise program with three sessions per week in addition to usual care. Primary outcomes were OA-specific knee pain and physical function (using the Knee Osteoarthritis Outcome Score 0-100) at three months. Secondary outcomes included adherence and safety. The “jump to reference” method was used for the primary analysis using multiple imputation to account for missing data. Intervention effects were calculated using a baseline-adjusted ANCOVA. Bonferroni correction with an alpha level of 0.025 was applied. Results: Between Jan 25, 2023 and Aug 11, 2023, 195 participants were enrolled. 98 participants were allocated to re.flex, 97 participants to usual care. The primary analysis included 194 participants. The mean age was 61.9 years (SD 7.7) and the majority were female (68 %, 132/194). Pain reduction was significantly larger in re.flex than in usual care, with an adjusted mean difference between study groups of 4.8 points (95% CI 0.7 to 8.9, P=.02, Cohen’s d 0.35). Improvement in physical function was not statistically significant (β-Coefficient 3.9 points, 95% CI 0.0 to 7.9, P=.049). 12 adverse events were linked to re.flex, none were serious. Participants adhered to 77% (2705/3528) of all scheduled exercise sessions. Conclusions: Between Jan 25, 2023 and Aug 11, 2023, 195 participants were enrolled. 98 participants were allocated to re.flex, 97 participants to usual care. The primary analysis included 194 participants. The mean age was 61.9 years (SD 7.7) and the majority were female (68 %, 132/194). Pain reduction was significantly larger in re.flex than in usual care, with an adjusted mean difference between study groups of 4.8 points (95% CI 0.7 to 8.9, P=.02, Cohen’s d 0.35). Improvement in physical function was not statistically significant (β-Coefficient 3.9 points, 95% CI 0.0 to 7.9, P=.049). 12 adverse events were linked to re.flex, none were serious. Participants adhered to 77% (2705/3528) of all scheduled exercise sessions. Clinical Trial: German Clinical Trial Register (DRKS) DRKS00030932; https://drks.de/search/de/trial/DRKS00030932.

Date Submitted: Oct 1, 2025. Open Peer Review Period: Oct 1, 2025 - Nov 26, 2025.

Background: Hand, foot, and mouth disease (HFMD) is a global health concern requiring a risk assessment framework based on systematic factors analysis for prevention and control. Objective: This study aims to construct a comprehensive HFMD risk assessment framework by integrating multi-source data, including historical incidence information, environmental parameters and internet-based search behavior data, to improve predictive performance. Methods: We integrated multi-source data (HFMD cases, meteorology, air pollution, Baidu Index, public health measures) from Bao’an District of Shenzhen city in Southern China (2014-2023). Correlation analysis was used to assess the associations between HFMD incidence and systematic factors. The impacts of environmental factors were analyzed using the Distributed Lag Non-linear Model. Seasonal Autoregressive Integrated Moving Average (SARIMA) model and advanced machine learning methods were used to predict HFMD 1 to 4 weeks ahead. Risk levels for the 1- to 4-week-ahead forecasts were determined by comparing the predicted weekly incidence against predefined thresholds. Results: From 2014 to 2023, Bao’an District reported a total of 118,826 cases of HFMD. Environmental and search behavior factors (excluding sulfur dioxide) were significantly associated with HFMD incidence in nonlinear patterns. For 1-week-ahead prediction, SARIMA using case data alone performed best (R² = 0.95, r=0.98, MAE=53.34, RMSE=99.31). For 2- to 4-week-ahead forecasting, machine learning models incorporating internet and environmental data showed superior performance (R² = 0.83, 0.75 and 0.64; r=0.92, 0.87 and 0.80; MAE=87.84, 112.41 and 132.47; RMSE=185.08, 229.13 and 276.81). The predicted HFMD risk levels matched the observed levels with accuracies of 96%, 87%, 88%, and 83%, respectively. Conclusions: The epidemic dynamics of HFMD are influenced by multiple factors in a nonlinear manner. Integrating multi-source data, particularly internet search behavior, significantly enhances the accuracy of short- and mid-term forecasts and risk assessment. This approach offers practical insights for developing digital surveillance and early warning systems in public health.

Background: Little to no scientific literature documents the content found on social media regarding orthopaedic procedures like robotic TKA. Studies analyzing social media discussions about medical procedures are exceptionally informative as they can give insight into public opinion, the involvement of different groups to the discussion, patient/clinician perspectives, knowledge transfer, among many others. Objective: To address the current gaps in the literature, we sought to analyze the discussions regarding robotic TKA on X, as it is the social media platform that is most used for healthcare communication Methods: A comprehensive search of the Twitter database for academic research was performed from inception (March 2006) to April 1st 2023 to identify all posts relating to robotic TKA. We retrieved data regarding the posts and authors, and we used a lexicon-based natural language processing Python library (TextBlob) to assess the sentiment of the posts. We manually categorized the post’s content and accounts. A multivariable regression model was used to associate metrics with higher engagement. Results: Our results showed that 61.6% of the content analyzed had a positive sentiment. The main actors discussing robotic TKAs on X were medical centers (19.3%), news channels (16.6%) and physicians/researchers (14.6%). The most popular post category was “awareness’’ (58.6%) followed by ‘’advertising” (11.3%), and ‘’research’’ (10.4%). Post count was unimpressive from 2010 to 2019 and took off in 2020 (249 posts), with a peak in 2022 (402 posts). Posts discussing patient experience and posts discussing research increased engagement by factors of 4 and 4,1 respectively. Conclusions: The elevated proportion of posts (61.6%) with a positive sentiment reflects a positive outlook towards robotic TKA on social media. Medical centers and news channels played a bigger role in the discussions surrounding robotic TKA than they do in other social media discussions about medical procedures/pathologies, while patient/caregiver involvement was significantly lower than usual. The significant contribution of news channels, combined with the overwhelming prevalence of posts categorized as ‘’awareness’’ (58,6%), might indicate that a public interest towards technological/medical advancements is driving the social media discussions on robotic TKA more than patients, physicians or researchers. The contribution of ‘’patient experience’’ and ‘’research’’ content appears to be significantly less than in other social media discussions about medical procedures, which can impact the overall accuracy of the content. The number of posts relating to robotic TKA took off in the year 2020 and has been growing since, which indicates that robotic TKA has been gaining in popularity over recent years. It is imperative to continue analyzing social media discussions surrounding medical procedures as they can give insight into public opinion, the involvement of different groups, patient/clinician perspectives, knowledge transfer, among many others.

Background: Only 10% of Australian #Children meet the recommended daily #PhysicalActivity guidelines. Augmented reality (AR) is increasingly being used in primary education and clinical rehabilitation with high enjoyment and motivation to participate frequently reported. AR has increased #PhysicalActivity participation in adult populations, but whether AR can increase #PhysicalActivity in young #Children has not been investigated. Objective: To determine if an indoor AR enhanced playground is enjoyed by young #Children and prompts #PhysicalActivity in both low and high structured scavenger hunts. Methods: Seventeen pairs of 5–8-year-olds participated in two animal search tasks (AR and non-AR) in two activity structure levels (low structured and high structure) in a 2x2 repeated measures design in an indoor laboratory playground. #Children searched for either AR animals (custom AR app on smartphone) or toy animals, and followed a set obstacle course route (high structure) or moved wherever they wished (low structure). Questionnaires assessed #Child enjoyment, perceived #PhysicalActivity and caregiver perception of enjoyment. A thigh accelerometry (SENS) assessed postures and movements and a video camera recorded engagement time. Results: #Children rated AR conditions (low structure: 4.4 ± 1.0 /5 and high structure: 4.5 ± 0.9 /5) as more enjoyable than high structured non-AR (4.1 ± 1.0 /5, P=.03, P=.03). When asked which condition was the most enjoyable, 15 chose the low structure AR, followed by the high structure AR (n=11) and low structured non-AR (n=8). Caregiver perception of #Children’s enjoyment ratings generally aligned. Rating of perceived #PhysicalActivity level was the same in all conditions (mean: 4.3/5, P>.05). Accelerometry showed that a greater percentage of time was spent in low intensity postures and movements during AR conditions (AR: 50 ± 13% vs non-AR: 35 ± 14%, P

Date Submitted: Oct 4, 2025. Open Peer Review Period: Oct 5, 2025 - Nov 30, 2025.

Background: Generalized anxiety disorder (GAD) is common among university students due to academic pressure and financial uncertainty, among other challenges. Despite the need, the receipt of available psychological services is often low. Objective: This study investigates the feasibility of a #Digital unguided cognitive behavioral therapy (CBT)–based #Mobile #App, Cerina, and examines the likely effects of this intervention in reducing GAD symptoms compared to the waitlist control group. Methods: Eligible students (n=158) with mild to moderate GAD symptoms were self-assessed through web-based questionnaires and were randomly allocated to the intervention group (n=79) or to the waitlist control group (n=79) following their informed consent. The intervention group had direct access to Cerina and followed CBT-based interactive sessions for 6 weeks. The waitlist control group participants had access to optional on-campus well-being services, and they were given access to Cerina 6 weeks after their randomization. Participants completed assessments on anxiety, depression, worry, and usability at three time points. Additionally, upon completing the intervention, they were invited to a web-based interview to understand the implementation of the intervention in more depth. Results: On average, 13% (10/79) intervention group participants dropped out, 61% (36/69) completed the core clinical content (2 sessions), and 12% (7/69) completed the desired number of sessions (6 or 7 sessions). Analyses of the completers (2 or more sessions) revealed significant group differences in GAD (mean 8.4, SD 3.7; t42=–2.25; P=.03; d=–0.7) and worry symptoms (mean 42.3, SD 10.8; t42=–2.50; P=.02; d=–0.8), as well as functional impairment (mean 16.7, SD 2.44; t42=–2.12; P=.04; d=–0.6) in favor of the intervention group at posttest with medium to large effect sizes. The intention-to-treat analyses confirmed significant group differences in GAD (mean 8.47, SD 2.7; t156=–2.23; P=.03; d=–0.4), and there were marginally nonsignificant group differences in worry symptoms (mean 41.5, SD 8.40; t156=–1.94; P=.05; d=–0.3) in favor of the intervention group at posttest with medium effect sizes. These results suggest that the intervention had a meaningful impact on reducing GAD symptoms and a modest impact on reducing worry symptoms among participants. Conclusions: The Cerina #App showed promising results in reducing GAD symptoms among students. This result supports findings from other randomized controlled trials showing that #Digital CBT-based interventions are effective and feasible for a wide range of age groups and populations experiencing GAD symptoms. The low number of participants completing the recommended number of sessions suggests a usability issue. To address this, the intervention could be refined through an iterative design process informed by user feedback, and the long-term impact of specific engagement features in improving usability and retention could be assessed through extended evaluations. Trial Registration: ClinicalTrials.gov NCT06146530; https://clinicaltrials.gov/study/NCT06146530

Background: Intravenous ketorolac is a potent nonopioid analgesic commonly used to treat vigorous pain in children and adults. Despite its widespread use in pediatric emergency settings, ketorolac dosing in children remains “off-label,” with limited high-quality evidence to guide practice. Pharmacokinetic differences between children and adults suggest that lower ceiling doses adopted from adult practice may lead to suboptimal analgesia in pediatric populations. Inconsistent ketorolac dosing practices across centers reflect substantial clinical uncertainty. Amid efforts to reduce opioid use and provide effective nonopioid alternatives, rigorous pediatric trials evaluating ketorolac dosing are urgently needed. Objective: The primary objective is to determine whether 2 lower-dose intravenous ketorolac strategies (0.25 mg/kg-30 mg or 0.5 mg/kg-10 mg) are noninferior to the standard dosing regimen (0.5 mg/kg-30 mg) in reducing mean pain scores at 60 minutes postadministration in children aged 6-17 years presenting with vigorous pain. The secondary hypothesis is that ketorolac 0.5 mg/kg up to 10 mg will be superior to 0.25 mg/kg up to 30 mg by at least the minimally important difference of 2.0 points on the verbal Numerical Rating Scale (vNRS). Methods: The KETODOSE trial is a single-center, randomized, double-blind, double-dummy, noninferiority trial conducted at McMaster Children’s Hospital. Eligible participants aged 6 to 4) are randomized in a 1:1:1 ratio to standard dosing or one of 2 low-dose ketorolac regimens. #Study drugs are administered via intravenous push over 5 minutes. Pain scores are assessed at baseline, 30, 60, 90, and 120 minutes. The primary endpoint is the mean change in vNRS score at 60 minutes. Secondary outcomes include pain scores at other time points, time to effective analgesia, rescue analgesia requirements, opioid consumption, and adverse events. Caregiver perceptions regarding analgesic use are evaluated using a mixed-methods semistructured survey. A sample size of 180 participants (60 per group) provides 80% power to detect noninferiority within a margin of 1.0 on the vNRS, assuming an SD of 1.5. Intention-to-treat and per-#Protocol analyses will be performed. Results: Recruitment is ongoing. Final analyses will be performed once follow-up is completed for all participants. Results will be disseminated through peer-reviewed publications, conference presentations, caregiver- and clinician-facing educational tools, and national knowledge mobilization networks. Conclusions: The KETODOSE trial will provide urgently needed evidence to guide ketorolac dosing for acute pain in children. If lower-dose regimens are shown to be noninferior to standard dosing, this may promote safer prescribing practices, reduce adverse events, and support efforts to minimize pediatric opioid use, thereby improving acute pain management in pediatric emergency care. Trial Registration: ClinicalTrials.gov NCT05641363; https://clinicaltrials.gov/#Study/NCT05641363

Date Submitted: Sep 22, 2025. Open Peer Review Period: Sep 22, 2025 - Nov 17, 2025.