JMIR Research Protocols

Preoperative distress in breast cancer patients is highly prevalent and associated with adverse post-surgical outcomes. While both virtual reality (VR) distraction and mindfulness exercises have been increasingly utilized to manage this distress, the clinical impact of integrating active mindfulness meditation into the immersive experience remains under-investigated. Here, we present a pilot randomized controlled trial evaluating the feasibility, acceptability and preliminary efficacy of brief, first-time immersive nature and mindfulness interventions for patients admitted to the holding area prior to the operating room for breast cancer surgery. Sixty participants were randomized to receive an 8-minute preoperative VR experience with mindfulness instruction (VR+Meditation), a standard VR nature experience without audio guidance (VR Only), or Care-as-Usual (CAU). The intervention was feasible and well tolerated with zero patient dropout and minimal indications of cybersickness or general discomfort. Outcomes included patient-reported anxiety and fear, physiological measures, and a computational semantic analysis of post-operative patient interviews. Compared with standard care, both VR interventions significantly reduced self-reported anxiety and heart rate. Although no significant differences were observed between the two active intervention groups, the VR+Meditation group demonstrated a significant and clinically meaningful reduction in surgery-specific fear relative to standard care. Analysis of brief patient interviews provided convergent evidence supporting these findings, showing that patients receiving VR+Meditation used language more strongly aligned with relief than those receiving standard care. These findings suggest that immersive VR represents a feasible and well-tolerated first-time immersive intervention for reducing preoperative distress in patients undergoing breast cancer surgery. The addition of guided mindfulness may provide additional benefit by specifically addressing surgery-related fear, supporting the hypothesis that different digital interventions may target distinct dimensions of preoperative distress. Larger randomized studies are warranted to confirm these preliminary findings.

Background The Low Anterior Resection Syndrome (LARS) score is an internationally validated instrument for identifying bowel dysfunction following anterior resection for rectal cancer. Although widely used, it has been shown to have limited sensitivity for capturing the impact of LARS on daily-life and response to treatment. We have therefore developed a novel patient-reported outcome measure (PROM): the LARS Impact and Consequences Assessment Tool (LARS-ICAT). Methods Initial development of LARS-ICAT followed a five-stage process following established PROM development guidance. Stage one established the conceptual foundation through previously published Delphi consensus. Stage two involved item generation, followed by evaluation of content validity through patient focus groups (n=11) in stage three. Stage four comprised iterative expert review and refinement through clinical consensus with patient involvement. Stage five involved cognitive interviews with patients conducted across five rounds (n=23). Results Several items identified through the Delphi consensus were reworded as they included multiple concepts. A one-month recall period was selected, with six and four response options for symptom and consequence items respectively. Additional consequence items, including impact on sleep and transport use, were incorporated. Focus groups and clinicians emphasised the importance of capturing individual symptom burden, leading to the addition of symptom bother scales. These iterative refinements culminated in LARS-ICAT v2.6. Conclusions LARS-ICAT is a novel PROM designed to assess symptom burden and treatment response in LARS. Future studies will assess its psychometric properties. Once validated, LARS-ICAT will provide a comprehensive, patient-centred assessment of LARS, enhancing our ability to manage this challenging condition.

Objective: To identify patient- and clinician-reported barriers, facilitators, and design requirements for a centralized cascade-screening program for familial hypercholesterolemia (FH) in the United States. Methods: From June through November 2023, we conducted individual telephone interviews with 20 patients with FH and 10 clinicians recruited from UT Southwestern Medical Center, Parkland Health, the North Texas Veterans Affairs, and other clinical settings. Interview guides were informed by the Consolidated Framework for Implementation Research. Transcripts were coded in Dedoose using a piloted codebook, with discrepancies and emergent themes resolved through consensus. An advisory panel then helped translate interview findings into program design requirements and implementation strategies. Results: Five themes characterized barriers and facilitators to centralized cascade screening: (1) health-system access and fragmentation, including screening and treatment costs, transportation, and cross-system coordination; (2) privacy and trust, including concerns about genetic information and unsolicited outreach; (3) family relationships and practical burden, including competing demands, language barriers, limited contact, fear, and denial; (4) clinician capacity and workflow, including limited time, knowledge, and genetic-counseling capacity; and (5) communication and care continuity. Participants recommended proband pre-notification of relatives, culturally and linguistically responsive materials, secure data exchange, standardized scripts, flexible testing pathways, and centralized coordination. These findings informed a program model incorporating a secure pedigree platform, educational and communication resources, testing coordination, and linkage to follow-up care. Conclusions: Patients and clinicians identified multilevel determinants that a centralized FH cascade-screening program must address. The findings support specific design requirements but do not establish program feasibility or effectiveness, which require prospective evaluation.

As internet and mobile phone access increases, digital health interventions are increasingly used to support remote and low-resource populations. In many settings, the health impact of digital interventions is constrained by limited or short-lived engagement. We tested if conditional mobile data credit incentives increase digital intervention engagement within a digital intervention trial. This nested cluster randomized controlled trial was conducted with caregivers of children 3-9 months at baseline. Of 72 neighborhood clusters from the treatment arm of the parent trial (evaluating a digital early childhood development intervention), 20 were randomly assigned to treatment and 52 as controls. Eligible participants had a phone provider through which mobile data credits could be most affordably administered. Treated participants received around 250 MB mobile data credits every two weeks, conditional upon using the digital intervention at least once in the same period. Credits were digitally administered via a third-party service. Digital intervention engagement (primary outcome) was monitored continuously until endline data collection approximately 2 years after assignment. Secondary outcomes included caregivers views, behaviors, and early childhood development. We used intent-to-treat analyses to assess all outcomes. This trial was registered as NCT05202106 at clinicaltrials.gov and was completed in 2025. Participants were recruited between September 2021 and March 2023 (N Treatment = 147; N Control = 333). Conditional mobile data credits extended engagement with the digital early childhood development intervention by 6.50 weeks on average (treatment mean = 26.19 weeks, control mean = 19.69; p=0.011). No significant impacts were identified on secondary outcomes. As such, mobile data credits may be a cost-effective way for increasing caregiver engagement with digital health intervention in low resource settings.

Background: Forming an equal attachment relationship with more than one child at a time can be challenging for parents. The risks associated with multiple pregnancies for the expecting parent and fetuses can adversely affect the entire pregnancy and influence the early interaction between the woman and the baby. The purpose of this empirical study was to describe from the perspective of women which factors promote and weaken early interaction in multiple pregnancies. Methods: Data collection was conducted remotely through semistructured individual interviews, in collaboration with a regional welfare agency and multiple birth family associations. A total of 11 women expecting twins voluntarily participated in the interviews. The qualitative data were analysed via inductive content analysis. Results Factors that strengthened early maternal-fetal interaction included considering the fetus and fetuses as part of the family during pregnancy, naming the fetuses individually, and using terms other than "fetus." Strong social support and parents' understanding of fetal awareness and reciprocity also significantly promoted early interaction. Conversely, early knowledge of expecting twins, insufficient guidance from healthcare professionals for the formation of early interactions, unequal attachment to fetuses, a lack of knowledge, and fears weakened early interactions. Conclusions: Our findings suggest that early interaction and guidance should be initiated as soon as parents learn that they expect more than one child. Throughout prenatal visits, there should be a focus on supporting the resources of pregnant women and their families to enhance maternal capabilities. Keywords: early interaction, maternal-fetal attachment, multiple pregnancy, twins, qualitative study

Patient narratives can reveal aspects of health that standardized measures miss, yet collecting open-ended responses at population scale remains difficult. We evaluated whether speech-to-text (STT) could enable richer responses in online health surveys without the resource demands of interviews. Across four surveys involving people with post-COVID-19 condition, healthy adults, people who engage in sex work, and older adults, participants could answer open-ended questions by typing or using STT. We compared response length, lexical diversity, stopword proportion, and total unique content words, alongside STT uptake and participant feedback. Quantitative comparisons were made using a mixed-effects model including modality (STT vs typed) as fixed effect and a random intercept per participant. STT uptake varied markedly across populations (0.7-80.0%). Spoken responses were estimated to contain more characters than typed responses in two studies, by 245.0 and 891.8 characters on average (both p<0.001), and contained more unique content words, despite lower lexical diversity and higher stopword proportions. Participants generally valued STT for its convenience and spontaneity, but uptake was constrained by context, privacy, interface design and individual preferences. STT may enable population-scale collection of richer health narratives, provided implementation is tailored to the study population and research context.

Background Stroke remains one of the leading causes of mortality and long-term disability worldwide, with low- and middle-income countries bearing a disproportionate share of the global disease burden. In India, delays in risk identification, fragmented referral pathways, and limited continuity of preventive care present significant challenges, particularly in rural communities. As a frontline health worker Accredited Social Health Activists (ASHAs) are strategically positioned to support community-based stroke prevention; however, existing workflows are frequently constrained by multi-tasking, predominantly paper-based documentation and fragmented digital systems. Advances in mobile health, artificial intelligence along with digital health ecosystem provided by Ayushman Bharat Digital Mission (ABDM) provide an opportunity to strengthen community healthcare through integrated digital platforms. Objective This protocol describes the design, system architecture, and prospective evaluation framework of ASHA Assist India, an integrated AI-assisted mobile health platform intended to support community-based stroke prevention by connecting citizens, ASHA workers, Primary Health Centres (PHCs), and higher levels of healthcare facilities within a unified digital ecosystem. Methods ASHA Assist India has been designed as a modular, cloud-based digital health platform supporting standardized data collection, longitudinal health monitoring, referral management, and AI-assisted clinical decision support. The proposed system comprises four user-facing applications corresponding to citizens, ASHA workers, PHCs, and referral hospitals, integrated through a centralized backend providing authentication, secure data management, interoperability, analytics, and notification services. The AI framework includes three planned analytical modules: (i) population-level stroke risk stratification, (ii) longitudinal stroke risk prediction, and (iii) acute stroke symptom recognition. A prospective implementation study is planned to evaluate platform usability, feasibility, workflow integration, implementation outcomes, and operational performance within routine community healthcare settings. Future validation of the AI modules will be conducted using prospectively collected longitudinal datasets. Expected Impact The proposed platform aims to strengthen community-based stroke prevention by improving digital workflow integration, facilitating coordinated referral pathways, and supporting longitudinal monitoring through the existing healthcare providers at health and wellness centres like ASHA, Community Health Officers (CHOs), ANM, etc. Beyond stroke prevention, the modular architecture is intended to provide a scalable framework for future digital health programmes addressing multiple non-communicable diseases within primary healthcare systems. Publication of this protocol establishes a transparent implementation and evaluation framework that may guide future research, digital health innovation, and implementation science in resource-constrained settings.

Background Scientific mistrust contributes to lower participation and underrepresentation of Black Americans in genomics studies limiting understanding of how genomic variation and environmental exposures influence health disparities. Community-engaged research requires rebuilding scientific trust; however, there is a need for practical models that operationalize guidance for researchers without community-engaged research training. Therefore, we developed an educational intervention for genomics researchers initiating partnerships with Black American communities. Our intervention creates a bidirectional teaching environment that allows potential community and academic partners to discuss areas of expertise for each stakeholder, partnership perspectives and needs, while exploring modules related to genomics research and community-academic partnership. We report a novel and structured approach for prospective academic and community partners to mutually orient one another and assess partnership practicability. Methods Ten participants, recruited through established community channels, attended a four-hour workshop containing nine interactive modules about scientific mistrust, research safeguards, community-engaged research, genomics, and research for community-defined goals. We also experimented with humor to enhance engagement and trust. We used mixed-methods, single-arm research design and assessed feasibility through recruitment success and retention. Using inductive rapid thematic analyses, we assessed participant responses to eight workshop prompts. Preliminary quantitative data, used for descriptive purposes due to low sample size, were analyzed from pre- and post-Likert scale surveys assessing associations between the intervention and four domains, including scientific trust. Results All 10 enrolled participants completed the study, meeting a priori criteria of 100% for recruitment and show rate. Engagement was strongest during early workshop modules and declined in later modules. Survey data completeness was limited by missing responses. Survey instrument design limitations were identified for modification in future studies. Participants articulated expectations for partnership that aligned with community-based participatory research principles. Conclusions The intervention is feasible to deliver as a bidirectional educational experience in partnership with a community organization. The strongest implementation refinements needed were workshop duration, module prioritization, and survey instrument design, particularly the trust domain. A community advisory board is co-developing modules and refining the intervention to evaluate in a pilot version of the study with a larger sample.

IntroductionCurrent evidence suggests that patient health passports may improve care for patients with chronic illnesses. This systematic review aimed to evaluate the impact of patient health passports on health outcomes in adults with diabetes. MethodsA systematic review was conducted in February 2025 following PRISMA 2020 guidelines, using Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, Web of Science, and Scopus. The review included studies of adult diabetic patients using paper or digital patient health passport as part of their care in comparison with the standard of care. Data were analysed using meta-analysis and a thematic analysis where appropriate; otherwise, the data are presented narratively. Quality appraisal was undertaken using the Cochrane Collaboration tool for assessing risk of bias and Evidence-based librarianship checklist. The certainty of the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation. ResultsEleven studies (n=14,350) were included. Seven studies were randomised controlled trials, two were retrospective in nature, one was a qualitative and one was a pre-post study. Overall, the studies are limited in design, resulting in high or unclear risk of bias across multiple domains. Results of the meta-analysis of five studies showed a statistically significant mean difference reduction in HbA1c and total cholesterol in favour of the intervention group; however, the certainty of the evidence is low or very low. The narrative analysis of the data revealed little to no improvement in body mass index, blood pressure, blood glucose, and cholesterol levels. Patients opinions and perceptions revealed some benefits in usability, perceived value, and in enhancing collaboration. ConclusionThis review provides evidence suggesting that patient health passports may improve patient care and can inform the design of future high-quality studies. However, the low certainty of the evidence highlights the need for high-quality studies with larger sample sizes. Key PointsO_LIPatient health passports show promise in enhancing diabetes management, however current evidence is limited by high risk of bias; future high-quality studies are required to confirm efficacy. C_LIO_LINurses are pivotal in this process as they play a central role in diabetes education, self-management support and continuity of care. C_LIO_LIPatient health passports could be considered as a structured tool to facilitate ongoing monitoring, reinforce adherence, enhance communication between patient and nurses/multidisciplinary team. C_LI

Abstract Aim: To translate, culturally adapt, and psychometrically validate the Arabic version of the REAP-S among Arabic speaking young adults using Confirmatory Factor Analysis (CFA) and Rasch Measurement Theory (RMT). Design: A cross-sectional methodological psychometric validation study. Methods: The study included 500 undergraduate and postgraduate nursing students recruited from Saudi universities during the 2025-2026 academic year. The REAP-S was translated into Arabic using standardized forward backward translation procedures and cross-cultural adaptation guidelines. Participants completed the Arabic REAP-S through an online self-administered questionnaire. Construct validity was evaluated using CFA with robust estimators, assessing the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Root Mean Square Error of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR). Rasch Measurement Theory was applied to examine item fit, response category functioning, person item targeting, and person reliability. We assessed internal consistency using Cronbach's alpha and the Rasch Person Separation Index (PSI). Results: Psychometric analyses included 490 participants with a median age of 20 years (IQR = 19-22), of whom 54.1% were female. CFA supported the hypothesized one-factor structure and showed good model fit (CFI = 0.984, TLI = 0.978, RMSEA = 0.076, SRMR = 0.061). Standardized factor loadings ranged from 0.429 to 0.768, and internal consistency was good (Cronbach's = 0.863). Rasch analysis confirmed the scale's unidimensionality, with satisfactory person reliability (Expected A Posteriori [EAP] = 0.872; Weighted Likelihood Estimate [WLE] = 0.848). All items demonstrated acceptable infit and outfit mean square statistics (0.826-1.311 and 0.866-1.283, respectively), with ordered response thresholds and adequate person-item targeting. Overall, the Arabic REAP-S effectively discriminated between different levels of dietary behavior among Arabic-speaking young adults. Conclusion: The Arabic REAP-S demonstrated strong validity and reliability, supporting its unidimensional structure and appropriate psychometric performance. Evidence from both CFA and Rasch analysis confirmed acceptable model fit, good internal consistency, and adequate item functioning. The instrument provides a brief and practical tool for assessing dietary behaviors among Arabic-speaking young adults in clinical and research settings. Implications for the Profession and/or Patient Care: The Arabic REAP-S provides nurses and other healthcare professionals with a brief, standardized tool for rapidly assessing dietary behaviors and identifying individuals at nutritional risk. Its integration into routine clinical and community practice may support early dietary screening, guide nutrition education, and strengthen evidence based preventive care for diet related chronic diseases. Keywords: Arabic REAP-S; Dietary Screening; Confirmatory Factor Analysis; Rasch Measurement Theory; Construct Validity; Young Adults.

Background: Yoga may support changes in dietary intake and/or physical activity levels, supporting sustainable weight loss. However, previous research has focused on yoga postures (asanas) rather than breathing practices (pranayama). This study used the proof-of-concept stage in the ORBIT model to evaluate feasibility, acceptability, and preliminary efficacy of a breath-based yoga program integrated within a behavioral weight loss (BWL) intervention. Methods: Fifteen participants with overweight or obesity (BMI: 31.3 +/- 4.3, 80% female) were enrolled in a 16-week, single-arm, group-based BWL intervention which included four breath-based yoga sessions/week, individualized daily goals for energy intake reduction, and progressive aerobic exercise recommendations. Primary outcomes included prespecified benchmarks enrollment, retention, adherence, and acceptability. Secondary outcomes included changes in body weight and composition, metabolic health indices (e.g., blood pressure, fasting glucose, abdominal obesity), physical activity, appetite, and dietary intake. Results: Mean percent weight loss was 6.5 +/- 6.0%, exceeding the pre-defined proof-of-concept benchmark. Recruitment and adherence exceeded established benchmarks, with mean in-class attendance of 84.1 +/- 14.6% and adherence to the prescribed duration of at-home yoga sessions averaging 85.5 +/- 38.4%. However, retention was lower than the pre-specified benchmark (73% vs 80%). Positive changes were observed in waist circumference, blood pressure, and appetite traits. Self-reported satisfaction with the program and outcomes were acceptable (mean ratings >6/10). Conclusions: A BWL with a breath-based, low-intensity yoga can lead to acceptable weight loss with potential benefits in key behavioral and metabolic health indices. Recruitment, high adherence, and satisfaction demonstrated feasibility.

Background: Maternal obesity is associated with lower breastfeeding initiation, shorter breastfeeding duration and lower rates of exclusive breastfeeding. Although breastfeeding intention predicts initiation, little is known about how first-time mothers living with obesity experience the transition from antenatal intention to postpartum reality. Aim: This qualitative study explored breastfeeding expectations, intentions, attitudes and early breastfeeding challenges among first-time mothers living with obesity in Switzerland. Methods: Seven semi-structured interviews were conducted with first-time mothers living with obesity in German-speaking Switzerland. Interviews were audio-recorded, transcribed verbatim and analysed using reflexive thematic analysis according to Braun and Clarke. Results: All participants intended to breastfeed and described breastfeeding as part of motherhood. However, most experienced a postpartum reality that differed from their expectations. Three themes were developed: antenatal engagement with and expectations of breastfeeding, postpartum breastfeeding reality, and everyday breastfeeding life. Women received little antenatal breastfeeding counselling and faced challenges related to medicalised birth, delayed lactogenesis II, breast anatomy, pain, insufficient milk supply, pumping and inconsistent professional support. Several women described feelings of failure when breastfeeding did not work as hoped. Conclusion: First-time mothers living with obesity may have strong breastfeeding intentions but still experience major challenges after birth. Breastfeeding support should start during pregnancy and be realistic, respectful and weight-inclusive.

Background: Passively collected smartphone and wearable data, combined with genomic information, may enable scalable early identification of youth who are at risk for substance use disorder. However, heterogeneous data collected in naturalistic settings limit researcher control over data quality, requiring substantial preprocessing. Data cleaning and feature engineering decisions can meaningfully influence analytic outcomes yet are often minimally described or omitted in published work. Objectives: We provide rationales and recommendations for common preprocessing challenges in passive sensing research, including establishing inclusion criteria when "outliers" may reflect true behavioral variability, analyzing differences across smartphone operating systems, handling observations collected outside protocol windows, and engineering features for machine learning applications. Methods: We illustrate principled approaches to these challenges using smartphone and Fitbit data from the Adolescent Brain Cognitive Development Study (ABCD). The sample was drawn from the available half of the year-4 follow-up (data release 5.1; N = 4,754; ages 13-14). Results: Extreme outlying observations were concentrated among low-engagement participants with few observed days. Smartphone usage among Apple users appeared under-recorded relative to Android users when compared with self-report measures. Fitbit-derived behavior differed systematically between observations collected within versus outside protocol windows. We also identified potential errors in the study's default preprocessing pipeline. Conclusion: We recommend prioritizing person-level inclusion criteria that preserve meaningful behavioral variability, examining temporal distributions rather than assuming observations are exchangeable, and thoroughly investigating and reporting data quality issues. Although illustrated using the ABCD Study, these principles broadly apply to research using smartphones, wearables, and other digital data sources.

Nurse-led skin cancer screening extends specialist reach but depends on the nurse selecting which lesions to forward for diagnosis, and performance varies with experience. We evaluated whether real-time decision support using artificial intelligence (AI) improves malignancy detection in routine nurse-led teledermoscopy screening across MoleMap clinics in New Zealand and Australia (January 2024-July 2025). In this real-world study, clinics using AI decision support were compared with standard clinics. Nurses examined patients, captured dermoscopic images, and forwarded selected lesions to teledermatologists, who provided the reference diagnosis. The analytic cohort comprised 1,102,382 lesions from 98,422 patients across 577 sites. AI-assisted screening was associated with a higher malignancy detection rate than standard screening (25.5 vs 15.7 malignancies per 1,000 lesions; odds ratio adjusted for nurse experience 1.73, 95% CI 1.68-1.77), a finding consistent across all nurse-experience tiers and the three major malignant subtypes. AI assistance was also associated with a shift in recommended management: 21 additional intervention recommendations and 13 additional safety-netting recommendations (self-monitoring, short-term follow-up, or specialist referral) per 1,000 lesions, approximately balanced by 34 fewer no-action recommendations. The reference standard was teledermatologist diagnosis and allocation was not randomised; findings are therefore associational and require prospective, outcome-based confirmation.

Introduction Research demonstrates neurodevelopmental differences in children who are HIV-exposed, but uninfected (CHEU) compared to their peers born unexposed. CHEUs are at higher risk for prematurity and low birth weight, both known risk factors for developmental delays. Despite increasing evidence, HIV exposure remains underrecognised as a risk factor for poor development by policy-makers and early childhood development (ECD) programs. We trialed an ECD intervention for CHEUs based on the Nurturing Care Framework developed by WHO, UNICEF, and the World Bank to improve neurodevelopmental outcomes in this vulnerable population. Design We conducted a randomized controlled trial of an ECD intervention for mothers living with HIV and their children born HIV-exposed, aged six to 24 months, living in peri-urban Lusaka. The intervention was delivered through bi-weekly home visits over 18 months using the curriculum adapted from the Nurturing Care Framework. The curriculum addressed nutrition, maternal wellness, child health, developmental milestones, and interactive caregiving. Method The primary outcome was measured by the Malawi Developmental Assessment Tool (MDAT) at six and 18 months post enrollment, which assesses developmental scores via a context-validated, direct observation tool across four domains: gross motor, fine motor, language, and social development. Participants were also assessed at six, 12 and 18 months post enrollment using the Caregiver Reported Early Development Instrument (CREDI). MDAT assessors were blinded to the intervention and control arm. Results We enrolled 308 mother-infant pairs, randomized 1:1 into an ECD intervention (CHEU control, n = 155; CHEU intervention, n = 153). At six months post enrollment, the intervention was associated with modest improvements in two developmental domains, particularly cognitive (Adjusted 0.28, 95% CI: 0.09 to 0.46; p= 0.004) and social-emotional development (Adjusted 0.29, 95% CI: 0.08 to 0.49; p= 0.07). At 18 month post enrollment, adjusted models demonstrated a moderate positive effect with gross motor development, with participants showing a 0.24 standard deviation higher score compared with the control group (95% CI: 0.02-0.46; p=0.034). Conclusion The findings indicate that the intervention may have a moderate impact on cognitive and social-emotional outcomes after six months, as well as on gross motor functions after eighteen months of intervention.

Background: Extended-reality simulation is widely used for technical surgical training, yet immediate gains do not establish that skills persist once practice stops. Objective: To characterize delayed technical-skill outcomes after virtual, augmented, or mixed-reality training and estimate the comparative effect at the first eligible uncontaminated delayed assessment. Methods: PubMed/MEDLINE, Europe PMC, CENTRAL, ERIC, and ClinicalTrials.gov were searched from inception through May 5, 2026. Eligible studies enrolled surgical learners or practitioners, used virtual, augmented, or mixed reality for technical training, and measured objective performance at least seven days later. Pure retention was distinguished from maintenance and reacquisition. One endpoint per independent study family was selected. Standardized mean differences were expressed as Hedges' g, oriented so positive values favored extended reality. Paule-Mandel random effects with Hartung-Knapp confidence intervals were primary. Results: Thirty-four reports representing 33 studies (1,186 participants; 21 randomized trials) from 12 countries were included. Six studies (162 participants in selected arms) were pooled. The summary effect was g = 1.39 (95% CI -0.94 to 3.72; I2 = 88.0%;{tau} 2= 4.53); the 95% prediction interval was -5.04 to 7.81. Excluding the figure-derived estimate reduced the effect to g = 0.61 (95% CI -0.76 to 1.99). GRADE certainty for the primary outcome was very low. No pooled study assessed an interval of 90 days or longer. Conclusions: Delayed technical advantages after extended-reality simulation were observed in some settings, but the comparative evidence does not define a precise or generalizable retention effect. Substantial heterogeneity, sparse transfer and longer-term evidence, comparator differences, and influence from one figure-derived estimate warrant cautious interpretation. Keywords: augmented reality; extended reality; meta-analysis; mixed reality; skill retention; surgical simulation; virtual reality

Introduction: Adolescents living with HIV (ALWH) face disproportionately high rates of depression and anxiety, which can negatively affect antiretroviral adherence, viral suppression, and overall health outcomes. Despite the close relationship between mental wellness and HIV care, mental health services remain inadequately integrated into HIV programs, particularly in low- and middle-income countries. To address this gap, we developed EVA (Educaci&oacuten, Vinculaci&oacuten y Autoayuda), a mental health chatbot co-designed with ALWH to provide psychoeducation on depression and anxiety, teach self-help skills, and facilitate linkage to mental health resources. We evaluated EVA's preliminary impact on depression knowledge and its feasibility and acceptability among ALWH in Lima, Peru. Methods: During January - August 2024, ALWH in Lima, Peru completed baseline assessments, engaged independently with EVA for 20 minutes, and completed endline measures. The primary outcome was change in depression knowledge measured using the Adolescent Depression Knowledge Questionnaire (ADKQ). Secondary outcomes included acceptability, appropriateness, feasibility, intention to use and recommend the chatbot, and satisfaction with the chatbot's features and content. Paired-samples t- tests were used to evaluate pre-post changes in depression knowledge. Results: Fifty ALWH aged 11 - 19 years participated, among whom 70% reported greater-than-minimal depressive symptoms, 60% greater-than-minimal anxiety symptoms, and 92% moderate or high perceived stress. Following a single interaction with EVA, depression knowledge increased significantly, from a mean ADKQ score of 6.88 (SD=1.85) to 8.12 (SD=2.20), t(49) = -5.03, p<.001, representing a large effect size (d=1.74). The chatbot was rated highly for acceptability, appropriateness, and feasibility, and participants reported strong intentions to use and recommend it, as well as high satisfaction with its educational content, usability, and self-help resources. Conclusions: A brief interaction with a mental health chatbot developed with and for ALWH in Peru significantly increased depression knowledge and was rated highly acceptable and feasible. Mental health chatbots may offer a low-cost, scalable approach to support mental health education and linkage to care within adolescent HIV services. Future longitudinal studies should assess sustained impact on mental health outcomes and help-seeking behavior; however, the benefits of chatbots should be weighed against their potential mental health risks.

Background: Qualitative research provides insights into human behavior, perspectives, and lived experience. While existing standards like the Consolidated Criteria for Reporting Qualitative Research (COREQ) have improved transparency and rigor, the integration of large language models (LLMs) into qualitative research introduces new challenges for not covered by current guidelines. LLMs transform analytic processes and blur the line between human interpretation and algorithmic text generation, raising concerns about transparency, authorship, and epistemic trust. The here presented COREQ+LLM guideline extends COREQ to establish comprehensive reporting standards for LLM use in qualitative research. Methods: The study followed the EQUATOR Network's guideline development framework in two phases: (1) a systematic scoping review to identify best practices for reporting LLM use in qualitative research, and (2) a Delphi consensus process with international experts in qualitative research, AI, medicine, ethics, and journal editing to develop a comprehensive reporting checklist. Findings: The scoping review identified 149 studies relevant for full-text review. From this literature, 29 preliminary reporting items were extracted. In the first Delphi round, international experts (N=141) assessed the items' relevance. 20 items were accepted for inclusion in the guideline (>75% agreement); however, four required reevaluation in the second round, five underwent wording revisions, and six new items were proposed. In the second Delphi round (N=115; retention rate 82%), one was excluded, while four items still lacked consensus. Remaining items were discussed in a virtual consensus conference with nine representatives of the expert panel, resulting in the inclusion of two and the exclusion of two others. The final checklist comprises 31 items grouped into seven categories, serving as an extension of the original COREQ checklist. Interpretation: COREQ+LLM offers structured, consensus-based guidance to enhance transparency, reproducibility, and methodological rigor in qualitative research using LLMs. Its adoption will support researchers, reviewers, and editors in maintaining trust and scientific integrity.

Background: Recruitment of diverse participants remains a challenge in cardiovascular clinical trials. Little is known about how recruitment efficiency and advertising costs with web-based tools vary across US communities. We evaluated an online recruitment platform and examined the cost of acquiring both all-comers and diverse participants in relation to community-level income. Methods: The Heartbeat Study evaluated a digital recruitment strategy to identify US participants for the ongoing Phase 3 LIBREXIA-AF trial. Online advertisements directed individuals with atrial fibrillation to a pre-screening website, where demographic and health data were collected. Advertising impressions, clicks, and costs were recorded. Participant ZIP codes were linked to Core Based Statistical Areas (CBSAs) and CBSA-level income. We measured recruits from underrepresented groups (women, African Americans, Latinos) completing online registration per $100,000 in advertising expenses. Click-weighted linear regression evaluated associations between CBSA income and advertising efficiency. Results: A total of 1,406 recruits completed online registration, with 1,319 participants from 260 CBSAs included in the geographic analysis. Participants were 73 years old on average; 547 (41.5%) were women, 59 (4.5%) African American, and 44 (3.3%) Latino. A total of $163,949.13 was spent on 82,681,711 impressions and 454,750 clicks. Recruits per $100,000 in advertising spend were 334 for women, 36 for African Americans, and 27 for Latinos. CBSA-level income was modestly inversely associated with cost per impression (R2=0.058; p<0.001) and cost per click (R2=0.038; p=0.005), but not recruitment yield for African Americans (p=0.99), Latinos (p=0.37), or women (p=0.21) (R2 range, 0.000-0.13). Conclusions: In this national analysis, online advertising enabled broad engagement across diverse US communities, but income was not associated with recruitment yield among women, African American, or Latino participants. Minority representation remained limited, suggesting digital recruitment alone may be insufficient to improve trial diversity. Targeted, culturally and linguistically tailored strategies may be needed to enhance diverse recruitment.

Purpose Autistic adults have diverse communication characteristics that are not well captured by standard demographic measures. Communication affects self-determination, relationships, access to healthcare, and services. Characterizing communication differences may improve research and intervention targeting for meaningful subgroups of autistic adults. Methods The Academic Autism Spectrum Partnership in Research and Education (AASPIRE) Outcomes Project team used a community based participatory research (CBPR) approach to develop a self- or caregiver-report module to characterize communication among autistic adults. The 10-item module asks about receptive and expressive communication, literacy, speech reliability, usage of digital communication, use of alternatives to speech, and communication fluency. It can be completed directly, with or without support, or via a caregiver. We used baseline survey data from 844 autistic adults to evaluate the module and derived a five-level variable, Communication Profile, from selected module items to stratify participants. We examined completion feasibility, response consistency, and construct validity. We also assessed test-retest reliability in a 15% random subsample who completed a 2-week retest following the 6-month survey, with oversampling of caregiver-report respondents. Results The Communication Characteristics module demonstrated high completion feasibility, minimal systematic error, and strong construct validity. The Communication Profile variable stratified participants into five meaningful communication profiles and demonstrated strong construct validity and substantial test-retest reliability ({kappa} = .69). Conclusion The Communication Characteristics module and Communication Profile variable provide a valid approach for characterizing communication diversity among autistic adults for research, clinical, and service settings. The full AASPIRE Measurement Toolkit is available at https://aaspire.org/measurement. Lay Summary Autistic people communicate in many different ways, and their communication may change in different situations. We developed and tested a set of survey questions to describe an individuals communication. We also used the results to describe 5 groups of autistic people based on how they communicate, without treating these groups as different types of autism.