JMIR Research Protocols

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.

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.

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: 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.

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.

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.

Background: As required by the 21st Century Cures Act, all test results, including final radiology reports, are released to patients as soon as the results are finalized. However, radiology reports are primarily intended for communication between medical professionals and can often be difficult for patients to interpret, particularly in cancer care settings. We developed a tool that leverages a large language model (LLM; ChatGPT-5.2, OpenAI, San Francisco, CA) to draft a patient-friendly plain language version of imaging results (Patient-Friendly Scan Result Generation [PFSG] tool) that oncologists can incorporate into their communication with patients via patient portals. This article describes our mixed-methods study protocol. Objective: Our primary aims are to: 1) assess whether patients who receive patient-friendly versions of scan results report better understanding of their results than patients who do not; 2) assess whether introduction of the PFSG tool affects provider workload; and 3) explain how and under what circumstances the PFSG tool enhances communication and workflows, and affects patient and provider outcomes. Methods: We will use an embedded mixed-methods, prospective cohort design within a quality improvement (QI) initiative. The PFSG tool will be implemented using a modified three-wave staircase trial design, with providers in randomized cohorts of oncology disease groups progressively gaining access to the tool over the course of the study. Approximately 60 providers from 11 oncology disease focus groups will be randomized. Longitudinal provider outcomes will be measured through surveys at one month pre-implementation, one month post-implementation, and three months post-implementation. Patient outcomes will be measured cross-sectionally through surveys at one month pre-implementation (n=350) and at post-implementation result point-of-contact (n=350). Additionally, we will conduct interviews with patients and oncologists to inform the iterative design of the tool and its implementation. Results: This study was funded in September 2025 and data collection began in February 2026. As of September 2026, the PFSG tool has been rolled out to all oncology providers, with Cohort 3 post-implementation data collection beginning in August 2026. A total of 738 patient baseline surveys have been collected and patient post-implementation data collection is in progress. Conclusions: This is the protocol for a study of the implementation of a patient-friendly results tool in oncology provider workflows to facilitate improved communication of radiology results to oncology patients. The results of this study will lend evidence to the utility and acceptability of the study tool, and tools like it, to close an important oncology care gap. If the tool is shown to improve key oncology patient and provider outcomes, it may lead to development of a wider release for more general patient populations.

Background: System One Model is designed for structured decision-making and can provide probabilistic outputs, but their performance in domain-specific physical therapy tasks has not been established. Objective: To evaluate the performance and potential utility of Jev, a System One Model, for professional knowledge-based selection tasks in physical therapy by comparing it with GPT-4o. Methods: A total of 380 multiple-choice questions from the 2024 and 2025 Korean Physical Therapist Licensing Examinations were independently submitted to Jev and GPT-4o. The outcomes included answer accuracy, subgroup performance, output validity, API response latency, token usage, estimated API cost, and Jev's prediction uncertainty. A retrospective probability-based model-cascading simulation was also performed. Results: Jev correctly answered 282 questions (74.2%), whereas GPT-4o answered 326 (85.8%), a difference of -11.6 percentage points. Jev produced valid structured responses for all questions, whereas GPT-4o produced three invalid responses. Jev's selected-answer probabilities discriminated correct from incorrect answers (AUROC = 0.866), and accuracy reached 99.3% when probabilities were greater than or equal to 0.90. The median API response latency was 0.94 s for Jev and 1.06 s for GPT-4o, with estimated costs of US$0.008 and US$0.161, respectively. At a retrospective cascading threshold of 0.70, accuracy was 86.6% with 175 simulated GPT-4o calls. Conclusion: Jev showed lower overall accuracy than GPT-4o but provided reliable structured outputs, informative prediction probabilities, lower latency, and lower estimated cost. Its probabilistic outputs warrant further prospective evaluation for selective model escalation and decision-support workflows in physical therapy.

Background: Estimating nutrient intake from meal photographs with vision-language models (VLMs) is now practical, but patient photographs often cannot leave the institution. We developed PLANS (Personal-device Local Assessment of Nutrients System), in which a small open VLM runs entirely on a personal device. Methods: Open VLMs were compared on two image sets with reference values (NutriImage, 887 Japanese meals; SNAPMe, 1,134 US meals), and the selected model (Qwen3-VL-4B, 4-bit) was run on an iPad Air without network access. Energy (primary outcome), protein, fat, carbohydrate and salt were evaluated by median absolute percentage error (MedAPE) and Spearman rank correlation (rho). The effect of supplying the food weight, including errors in it, was examined. Results: Energy estimates on the iPad were identical to those of a desktop-computer run for 84-86% of images (other values, 75-87%). MedAPE on the iPad was 37.0% and 36.5% for energy (26-28% of images within +/-20%), 43-65% for the macronutrients and 68-101% for salt (rho 0.51-0.85). On the desktop computer, supplying the true weight reduced MedAPE of the 4B model on NutriImage from 37.0% to 32.5% for energy and from 100.0% to 66.8% for salt; energy MedAPE stayed below the base value for declared weights of 0.5-1.25 times the true weight or rounded to 50 g, but rose markedly when the container weight was included. Conclusions: An offline VLM on a tablet reproduced server-side energy accuracy and is a candidate tool for dietary counselling where photographs cannot leave the institution; given the wide limits of agreement, its usefulness in practice remains to be examined.

Introduction: Lichen sclerosus (LS) is a chronic inflammatory dermatosis predominantly affecting the anogenital region of both women and men. Sexual dysfunction remains among the most debilitating and overlooked consequences of the disease, as available patient-reported outcome measures are either restricted to one sex or capture sexual health only partially. The aim of the present work is to validate the Qualisex questionnaire (in its the Italian version) in patients with LS and to evaluate its psychometric properties, factor structure, convergent, discriminant validity, and sex symmetry. Methods: A cross-sectional study was conducted on 211 patients (167 women, 44 men; mean age 52.9 years) with a confirmed diagnosis of LS. Participants completed the Italian Qualisex, Skindex-29, DASS-21, and sexual-health-specific scales, the Female Sexual Function Index (FSFI) for women, and the International Index of Erectile Function (IIEF) for men. Construct validity was assessed via Principal Component Analysis (PCA), and reliability via Cronbach's alpha. Convergent and discriminant validities were evaluated against standard psychometric batteries. Results: Item 2 was removed due to low communality (0.167). PCA on the remaining 9 items revealed a two-factor structure accounting for 72.5% of total variance: Component 1 (Sexual Functioning and Satisfaction, 59.89%) and Component 2 (Partner Devaluation, 12.66%). Internal consistency was high (alpha= 0.911 overall; alpha= 0.841 in women; alpha= 0.899 in men). Qualisex scores correlated strongly with Skindex-29 Social Functioning (r = 0.582) and Emotions (r = 0.531) subscales, as well as FSFI (r = -0.391) and IIEF (alpha= -0.566). Discriminant validity was supported by low-to-moderate correlations with DASS-21 domains (r < 0.38). While FSFI and IIEF showed significant negative correlations with age (p = 0.002), Qualisex remained age-independent across sexes (p > 0.05). Conclusion. The 9-item Italian Qualisex is a reliable, sex-symmetrical, and age-independent patient-reported outcome measure for assessing sexual health impairment in LS, successfully isolating disease-specific distress from physiological aging and general distress.

Background HPV-vaccination prevents HPV-related cancers, but uptake remains suboptimal. In the Netherlands, a catch-up campaign invited 18-27-year-olds for an additional cost-free opportunity to initiate or complete their HPV-vaccination in 2023-2024, which led to 24% of this invited population getting vaccinated. As young adults increasingly seek health information online, understanding online questions, concerns and misinformation in response to the campaign may help improve future vaccination efforts. Supplemental to overall evaluation of the vaccination campaign, we piloted online social listening processes to generate an insight report for Public Health Service (PHS) Amsterdam. Objective This study piloted online social listening processes at the PHS Amsterdam to identify actionable insights into questions, concerns and misinformation surrounding the HPV-vaccination catch-up campaign among young adults. Methods Upon inventory of potential platforms and data sources, a retrospective online social listening analysis was conducted across the platforms Instagram, Facebook, and X, collecting data from PHS, the National Public Health Institute for Public Health and the Environment (RIVM), the Dutch public broadcasting foundation (NOS), and LINDA.meiden sources from January 1, 2023, to June 1, 2024. Publicly available posts, comments, and engagement concerning HPV-vaccination were manually collected, and inductively coded. Themes were assessed for risk, based on expected potential harm and observed reach, and used to develop recommendations. Results A total of 821 posts and 5157 comments were collected and analysed. Ten recurring themes were identified across varying levels of risk. Two themes were classified as high risk: an information gap regarding the effectiveness of HPV-vaccination and concerns about the transparency on HPV-vaccine side effects. Three themes were classified as medium risk: questioning HPV-vaccine effectiveness under certain circumstances, reduced general vaccine trust following COVID-19, and accessibility issues related to vaccination locations and service times. Two themes were classified as neutral risk: questions regarding eligibility criteria for the campaign and calls for broader HIPV-prevention measures. Finally, three low risk themes concerned questions regarding HPV-vaccine brand specifics, campaign choices, and questions about scheduling or rescheduling HPV-appointments. Comments also referred to subsequent information sources, including reliable sources (public health institutes), false narratives and misinformation. Recommendations focused on addressing questions and information gaps (i.e. improving HPV risk perception and providing more detailed HPV-vaccine information), improving communication about HPV-vaccination, and reducing practical barriers to vaccination. Conclusions Manual social listening across selected online sources provided actionable insights into the public discourse during the HPV-vaccination catch-up campaign. Results mostly reflected questions, concerns and information gaps. Although some themes were critical of HPV-vaccination, false narratives and misinformation did not dominate the discourse. Recommendations aim to reduce practical barriers and address information needs. This pilot showed that online social listening can be effectively implemented even with limited resources.

Background: People with severe mental illness (SMI) report poorer oral health outcomes than the general population, are less likely to attend regular dental check-ups, and may require additional support to visit a dentist. Our previous research showed that interventions tailored to their needs and support from the mental health care system are needed to improve oral health outcomes in people with SMI. Although there is some provision of urgent dental care for people with SMI, there are currently limited available interventions that integrate dental and mental health care and provide dental support in a mental healthcare setting. To address this gap, the aims of the SMILE project are to 1) co-develop and 2) test the feasibility and acceptability of an oral health intervention for people with SMI, delivered by mental health professionals in secondary community mental health care settings. This paper describes the protocol for the feasibility and acceptability testing of the SMILE intervention. Methods: This is a single-arm, non-randomised feasibility trial assessing the feasibility and acceptability of an intervention to support the oral health of mental healthcare service users with SMI. The intervention was co-produced with service users, carers, mental health and dental health professionals, and includes advice on maintaining good oral hygiene and lifestyle habits to maintain good oral health. The main aim of the study is to assess the feasibility and acceptability of delivering the intervention, using quantitative data collected at baseline, three and six-month follow-up, and qualitative interviews with participants and mental health staff involved in delivering the intervention. Results: The study results will determine whether the intervention can be successfully delivered in secondary community mental health care settings and inform the most appropriate primary and secondary outcomes for a future trial. Conclusion: The findings of this study will inform the feasibility of progression to the pilot stage of a randomised controlled trial to assess the clinical and cost effectiveness of delivering an oral health intervention in a mental healthcare setting.

Background: Large language models (LLMs) configured as virtual patients may expand structured practice of clinical reasoning in health professions education. Before testing effectiveness, it must be established whether students engage with them and whether the resulting scores are complete, reliable, and related to performance with real patients. Our earlier pilot randomized trial found very low engagement with a less structured LLM-based approach. Objective: This study aimed to assess the feasibility (adherence, acceptability, and data completeness) of a revised, structured LLM-based clinical reasoning laboratory (Laboratorio de Inteligencia Artificial [LIA]) in undergraduate physical therapy education and to explore its measurement properties, including its association with clinical judgment with a real patient assessed with the Lasater Clinical Judgment Rubric (LCJR). Methods: In this single-arm pilot feasibility study, 27 third-year physical therapy students at a Spanish university completed, in 2024-2025, 3 virtual patient cases (lumbar, cervical, and thoracic spine pain) simulated by ChatGPT (GPT-4) over 4 weeks, each twice. ChatGPT scored each attempt from 0 to 4 on the same 10 dimensions of the Lasater Clinical Judgment Rubric (LCJR; 0-40 points) that human assessors applied (1-4 per dimension; 10-40 points) during a real patient encounter. Feasibility outcomes were case completion, data completeness, and satisfaction (0-10). Measurement outcomes were internal consistency and convergent validity (Spearman correlations between model-generated and human LCJR scores). Variability estimates informed the sample size of a future trial. Results: All 27 students were assessed with the LCJR; 22 (81%) completed at least 1 LIA case. Both attempts of the lumbar, cervical, and thoracic cases were completed by 78%, 63%, and 74% of students, respectively. Satisfaction data were available for 15 students (56%; mean 6.0, SD 1.3), and missing secondary data clustered in the third rotation. Internal consistency was excellent for the LCJR (alpha=.96) and ranged from .43 to .90 for model-generated ratings. Model-generated LIA scores clustered near the maximum (mean 36.0, SD 1.4). Among completers, LIA scores correlated weakly with the LCJR (rho=0.25, 95% CI -0.20 to 0.61; rho=0.44, 95% CI 0.05-0.71, when noncompleted attempts were scored as 0). Grade point average correlated almost perfectly with the LCJR (rho=0.96; n=22); after adjustment for it, the LIA-LCJR association disappeared (partial rho=-0.10). A future trial would require approximately 39 students per group (80% power, conservative variance). Conclusions: Delivering the LIA within the curriculum was feasible, but clinical judgment ratings generated by ChatGPT did not reflect those of human assessors with a real patient: they clustered near the maximum and showed no convergent validity once noncompletion was separated from performance. LLM-generated ratings should not be used as outcome or assessment measures without validation against human raters. Case calibration, completion tracking, and clarification of the GPA-LCJR relationship are also needed before a definitive trial. Trial Registration: ClinicalTrials.gov NCT06809634; https://clinicaltrials.gov/study/NCT06809634

Objectives: Patients and clinicians increasingly ask large language models (LLMs) about Kampo, Japan's traditional medicine. Yet evaluations of LLMs have measured accuracy on examination questions, which ask what a model knows; a consultation asks whether it can apply that knowledge to the patient at hand. No benchmark had measured that. Materials and Methods: KampoBench comprises 74 consultation scenarios and 310 conversation-specific rubric criteria, following the design of HealthBench. Scenarios, criteria and reference answers were drafted by an LLM and revised by board-certified Kampo physicians. Ten current models from three vendors were evaluated. Because LLM graders are known to favor their own family, each response was graded by a model from each vendor. Results: The best model reached 74.8-86.3% across graders, the physician-revised reference answers 87.9-92.4%. Rankings were stable across graders (Spearman's rho 0.952-0.976), and the family-favoring deviation was 0.4 to 0.6 percentage points, below the bootstrap standard deviation of one measurement; grader leniency varied by 14.3 points. Models were most reliable on criteria about advising that care be sought (83.6%) and least reliable on those requiring a known crude-drug risk to be tied to the case (17.5%), though 79.2% of those responses named the drug. Discussion: The shortfall lay in applying knowledge to the case rather than in holding it - a distinction examination-format evaluations cannot make. Conclusion: Evaluation in traditional medicine should measure the judgments a consultation requires, not recall alone. Quoted alongside the grader that produced it, a KampoBench score is a usable measure of those judgments.

This study evaluated the feasibility and preliminary effectiveness of a 12-session group-based nurturing care intervention for adolescent mothers in the Dominican Republic. We conducted a one-group pretest-posttest feasibility study in Boca Chica, Dominican Republic. Participants were adolescent mothers under 20 years of age with a child enrolled in an early childhood development (ECD) center operated by the National Institute for Early Childhood Comprehensive Care. The intervention, based on the World Health Organization's Nurturing Care Framework, addressed ECD, affective care, positive discipline, and maternal well-being. We calculated effect sizes using Cohen's d. Of 14 adolescent mothers who started the program, 11 completed both assessments (78.6% retention). Participants had a mean age of 16.91 years (SD = 1.35), with children averaging 1.15 years (SD = 0.84). Two outcomes showed statistically significant improvements. Parental efficacy (1-4 scale) increased from M = 3.38 to M = 3.84 (d = 0.99, p = .008), with significant gains observed in three subdomains: protective (d = 1.21, p = .003), formative (d = 0.90, p = .014), and bonding competencies (d = 0.81, p = .023). Cognitive stimulation activities (0-1 scale) increased from M = 0.42 to M = 0.65 (d = 0.81, p = .036). Participant satisfaction was high (M = 4.64 on a 5-point scale). ASCENDI demonstrated feasibility and preliminary effectiveness in improving parental efficacy and cognitive stimulation among adolescent mothers. Large effect sizes and high retention and satisfaction support the potential of group-based nurturing care interventions for adolescent mothers in resource-limited settings.

Aims: To understand how users believe continuous glucose monitoring (CGM) changes their behaviour, which app features they credit, and whether endorsing more mechanisms of action (MoAs) is linked to reported diet and physical activity change. Methods: We surveyed 112 U.S. adults with type 1 or type 2 diabetes who had used a Dexcom or Abbott Libre CGM within 12 months. Participants rated 26 MoA statements mapped to the Capability, Opportunity, Motivation-Behaviour (COM-B) model, identified contributing app features, and reported CGM-attributed diet and physical activity change. Logistic regression examined MoA count and COM-B domains as predictors of behaviour change. Results: Participants (mean age 54.5 years; 60.7% female) reported dietary (82.1%) and physical activity (46.4%) change and endorsed a median of 18 MoAs, most often relating to knowledge, skills and behavioural consequences. Real-time glucose and graphs were attributed to many MoAs. Each additional MoA was associated with higher odds of dietary (OR 1.27, 95% CI 1.15-1.44) and physical activity change (OR 1.27, 95% CI 1.16-1.43). Motivation made the strongest distinct contribution among COM-B domains. Conclusions: Users perceive CGM as engaging many behavioural mechanisms; endorsing more was linked to behaviour change. Motivation may be a key target for CGM-based behavioural support.

BackgroundPatient education is critical to safe and effective postoperative bariatric surgery care. Large language models (LLMs) may improve access to personalized patient education but evidence regarding direct patient use in clinical settings remains limited. We evaluated BariBot, an LLM-powered educational application for patients undergoing bariatric surgery. MethodsWe conducted a prospective, single-arm mixed-methods feasibility study at a tertiary academic medical center from May 2024 to May 2025. Adult patients undergoing bariatric surgery used BariBot independently on postoperative day 1. The application provided conversational postoperative education and adapted language complexity to participants educational attainment. Outcomes included feasibility, usability, acceptability, perceived trustworthiness, and anticipated future use. Usability was assessed using the System Usability Scale (SUS). Immediately after BariBot use, participants completed a semi-structured qualitative interview assessing acceptability, perceived trustworthiness, and anticipated future use. Interview transcripts underwent thematic analysis. ResultsSixteen participants completed the BariBot use session, SUS assessment, and post-intervention interview. No technical failures prevented application use, and no participant requested early discontinuation. The median SUS score was 91.3 (IQR, 81.3-98.1), consistent with excellent perceived usability. Qualitative analysis showed that participants valued the applications immediacy, structured responses, conversational context, ability to address follow-up questions, judgement-free nature, and future availability between clinical encounters. Trust was strengthened by alignment with prior clinical guidance and perceived institutional association, although participants emphasized the need for transparency, clinician oversight, and use as an adjunct rather than a replacement of clinician guidance. ConclusionsBariBot was feasible to implement and was associated with high perceived usability and acceptability postoperatively after bariatric surgery. Larger, longitudinal, and comparative studies are needed to evaluate safety during unsupervised use and determine whether LLM-based educational applications improve patient understanding, engagement, and clinical outcomes.

The efficacy of current antiretroviral interventions for prevention of vertical HIV transmission is both a triumph and a challenge for future efficacy studies of novel agents, including long-acting antiretroviral agents. Given the effectiveness of current antiretroviral interventions, standard randomized controlled trials to assess novel interventions targeted towards further reducing vertical HIV transmission may be infeasible due to required sample sizes. To address this study design challenge, we propose a novel augmented clinical trial design, where a randomized trial with an active comparator is augmented with a concurrent observational cohort to supplement the standard-of-care arm. The proposed design and analysis can overcome sampling biases, and an associated diagnostic can evaluate potential biases from unmeasured covariates. The proposed trial design is illustrated with an example and studied further using a simulation study. In the illustrative example, an augmented trial with a 3:1 allocation ratio in the trial component yielded an unbiased treatment effect estimate, as compared to the trial component alone, and the standard error was reduced substantially. Although the total sample size of the augmented trial was larger than a similarly powered 1:1 standard trial, the sample size of the augmented trial's trial component was half the size of the standard trial and within the range of historically similar trials, thereby providing both feasibility and potential cost advantages. Although limitations with this design remain, many of these limitations can be mitigated by careful study planning and coordination. Augmented trials provide a potentially applicable solution to studying the efficacy of long-acting antiretrovirals for infant postnatal prophylaxis against HIV.