@Article{info:doi/10.2196/63378, author="Meyer, Eric and Sauz{\'e}on, H{\'e}l{\`e}ne and Saint-Supery, Isabeau and Mazon, Cecile", title="Evaluating a Web-Based Application to Facilitate Family-School-Health Care Collaboration for Children With Neurodevelopmental Disorders in Inclusive Settings: Protocol for a Nonrandomized Trial", journal="JMIR Res Protoc", year="2025", month="Apr", day="17", volume="14", pages="e63378", keywords="neurodevelopmental disorders", keywords="coeducation", keywords="whole-school approach", keywords="family-professional partnership", keywords="web application", keywords="inclusive education", keywords="family-school-health care", abstract="Background: An individual education plan (IEP) is a key element in the support of the schooling of children with special educational needs or disabilities. The IEP process requires effective communication and strong partnership between families, school staff, and health care practitioners. However, these stakeholders often report their collaboration as limited and difficult to maintain, leading to difficulties in implementing and monitoring the child's IEP. Objective: This paper aims to describe the study protocol used to evaluate a technological tool (CoEd application) aiming at fostering communication and collaboration between family, school, and health care in the context of inclusive education. Methods: This protocol describes a longitudinal, nonrandomized controlled trial, with baseline, 3 month, and 6-month follow-up assessments. The intervention consisted of using the web-based CoEd application for 3 months to 6 months. This application is composed of a child's file in which stakeholders of the support team can share information about the child's profile, skills, aids and adaptations, and daily events. The control group is asked to function as usual to support the child in inclusive settings. To be eligible, a support team must be composed of at least two stakeholders, including at least one of the parents. Additionally, the pupil had to be aged between 10 years and 16 years, enrolled in secondary school, be taught in mainstream settings, and have an established or ongoing diagnosis of autism spectrum disorder, attention-deficit/hyperactivity disorder, or intellectual disability (IQ<70). Primary outcome measures cover stakeholders' relationships, self-efficacy, and attitudes toward inclusive education, while secondary outcome measures are related to stakeholders' burden and quality of life, as well as children's school well-being and quality of life. We plan to analyze data using ANCOVA to investigate pre-post and group effects, with a technological skills questionnaire as the covariate. Results: After screening for eligibility, 157 participants were recruited in 37 support teams, composed of at least one parent and one professional (school, health care). In September 2023, after the baseline assessment, the remaining 127 participants were allocated to the CoEd intervention (13 teams; n=82) or control condition (11 teams; n=45). Conclusions: We expect that the CoEd application will improve the quality of interpersonal relationships in children's IEP teams (research question [RQ]1), will show benefits for the child (RQ2), and improve the well-being of the child and the stakeholders (RQ3). Thanks to the participatory design, we also expect that the CoEd application will elicit a good user experience (RQ4). The results from this study could have several implications for educational technology research, as it is the first to investigate the impacts of a technological tool on co-educational processes. International Registered Report Identifier (IRRID): DERR1-10.2196/63378 ", doi="10.2196/63378", url="https://www.researchprotocols.org/2025/1/e63378" } @Article{info:doi/10.2196/66223, author="Draugelis, Sarah and Hunnewell, Jessica and Bishop, Sam and Goswami, Reena and Smith, G. Sean and Sutherland, Philip and Hickman, Justin and Donahue, A. Donald and Yendewa, A. George and Mohareb, M. Amir", title="Leveraging Electronic Health Records in International Humanitarian Clinics for Population Health Research: Cross-Sectional Study", journal="JMIR Public Health Surveill", year="2025", month="Apr", day="17", volume="11", pages="e66223", keywords="refugee", keywords="population health", keywords="disaster medicine", keywords="humanitarian clinic", keywords="electronic health record", keywords="Fast Electronic Medical Record", keywords="fEMR", abstract="Background: As more humanitarian relief organizations are beginning to use electronic medical records in their operations, data from clinical encounters can be leveraged for public health planning. Currently, medical data from humanitarian medical workers are infrequently available in a format that can be analyzed, interpreted, and used for public health. Objectives: This study aims to develop and test a methodology by which diagnosis and procedure codes can be derived from free-text medical encounters by medical relief practitioners for the purposes of data analysis. Methods: We conducted a cross-sectional study of clinical encounters from humanitarian clinics for displaced persons in Mexico between August 3, 2021, and December 5, 2022. We developed and tested a method by which free-text encounters were reviewed by medical billing coders and assigned codes from the International Classification of Diseases, Tenth Revision (ICD-10) and the Current Procedural Terminology (CPT). Each encounter was independently reviewed in duplicate and assigned ICD-10 and CPT codes in a blinded manner. Encounters with discordant codes were reviewed and arbitrated by a more experienced medical coder, whose decision was used to determine the final ICD-10 and CPT codes. We used chi-square tests of independence to compare the ICD-10 codes for concordance across single-diagnosis and multidiagnosis encounters and across patient characteristics, such as age, sex, and country of origin. Results: We analyzed 8460 encounters representing 5623 unique patients and 2774 unique diagnosis codes. These free-text encounters had a mean of 20.5 words per encounter in the clinical documentation. There were 58.78\% (4973/8460) encounters where both coders assigned 1 diagnosis code, 18.56\% (1570/8460) encounters where both coders assigned multiple diagnosis codes, and 22.66\% (1917/8460) encounters with a mixed number of codes assigned. Of the 4973 encounters with a single code, only 11.82\% (n=588) had a unique diagnosis assigned by the arbitrator that was not assigned by either of the initial 2 coders. Of the 1570 encounters with multiple diagnosis codes, only 3.38\% (n=53) had unique diagnosis codes assigned by the arbitrator that were not initially assigned by either coder. The frequency of complete concordance across diagnosis codes was similar across sex categories and ranged from 30.43\% to 46.05\% across age groups and countries of origin. Conclusions: Free-text electronic medical records from humanitarian relief clinics can be used to develop a database of diagnosis and procedure codes. The method developed in this study, which used multiple independent reviews of clinical encounters, appears to reliably assign diagnosis codes across a diverse patient population in a resource-limited setting. ", doi="10.2196/66223", url="https://publichealth.jmir.org/2025/1/e66223" } @Article{info:doi/10.2196/63693, author="Kamberi, Ariana and Weitz, Benjamin and Flahive, Julie and Eve, Julianna and Najjar, Reem and Liaghat, Tara and Ford, Daniel and Lindenauer, Peter and Person, Sharina and Houston, K. Thomas and Gauvey-Kern, E. Megan and Lobien, Jackie and Sadasivam, S. Rajani", title="Testing a Machine Learning--Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial", journal="JMIR Res Protoc", year="2025", month="Apr", day="16", volume="14", pages="e63693", keywords="smoking cessation", keywords="mHealth", keywords="socioeconomically disadvantaged, biochemical verification", keywords="machine learning", abstract="Background: Individuals who are socioeconomically disadvantaged have high smoking rates and face barriers to participating in smoking cessation interventions. Computer-tailored health communication, which is focused on finding the most relevant messages for an individual, has been shown to promote behavior change. We developed a machine learning approach (the Adapt2Quit recommender system), and our pilot work demonstrated the potential to increase message relevance and smoking cessation effectiveness among individuals who are socioeconomically disadvantaged. Objective: This study protocol describes our randomized controlled trial to test whether the Adapt2Quit recommender system will increase smoking cessation among individuals from socioeconomically disadvantaged backgrounds who smoke. Methods: Individuals from socioeconomically disadvantaged backgrounds who smoke were identified based on insurance tied to low income or from clinical settings (eg, community health centers) that provide care for low-income patients. They received text messages from the Adapt2Quit recommender system for 6 months. Participants received daily text messages for the first 30 days and every 14 days until the end of the study. Intervention participants also received biweekly texting facilitation messages, that is, text messages asking participants to respond (yes or no) if they were interested in being referred to the quitline. Interested participants were then actively referred to the quitline by study staff. Intervention participants also received biweekly text messages assessing their current smoking status. Control participants did not receive the recommender messages but received the biweekly texting facilitation and smoking status assessment messages. Our primary outcome is the 7-day point-prevalence smoking cessation at 6 months, verified by carbon monoxide testing. We will use an inverse probability weighting approach to test our primary outcome. This involves using a logistic regression model to predict nonmissingness, calculating the inverse probability of nonmissingness, and using it as a weight in a logistic regression model to compare cessation rates between the two groups. Results: The Adapt2Quit study was funded in April 2020 and is still ongoing. We have completed the recruitment of individuals (N=757 participants). The 6-month follow-up of all participants was completed in November 2024. The sample consists of 64\% (486/757) female participants, 35\% (265/757) Black or African American individuals, 51.1\% (387/757) White individuals, and 16\% (121/757) Hispanic or Latino individuals. In total, 52.6\% (398/757) of participants reported having a high school education or being a high school graduate; 70\% (529/757) smoked their first cigarette within 30 minutes of waking, and half (379/757, 50\%) had stopped smoking for at least one day in the past year. Moreover, 16.6\% (126/757) had called the quitline before study participation. Conclusions: We have recruited a diverse sample of individuals who are socioeconomically disadvantaged and designed a rigorous protocol to evaluate the Adapt2Quit recommender system. Future papers will present our main analysis of the trial. Trial Registration: ClinicalTrials.gov NCT04720625; https://clinicaltrials.gov/study/NCT04720625 International Registered Report Identifier (IRRID): DERR1-10.2196/63693 ", doi="10.2196/63693", url="https://www.researchprotocols.org/2025/1/e63693" } @Article{info:doi/10.2196/67914, author="Liu, Darren and Hu, Xiao and Xiao, Canhua and Bai, Jinbing and Barandouzi, A. Zahra and Lee, Stephanie and Webster, Caitlin and Brock, La-Urshalar and Lee, Lindsay and Bold, Delgersuren and Lin, Yufen", title="Evaluation of Large Language Models in Tailoring Educational Content for Cancer Survivors and Their Caregivers: Quality Analysis", journal="JMIR Cancer", year="2025", month="Apr", day="7", volume="11", pages="e67914", keywords="large language models", keywords="GPT-4", keywords="cancer survivors", keywords="caregivers", keywords="education", keywords="health equity", abstract="Background: Cancer survivors and their caregivers, particularly those from disadvantaged backgrounds with limited health literacy or racial and ethnic minorities facing language barriers, are at a disproportionately higher risk of experiencing symptom burdens from cancer and its treatments. Large language models (LLMs) offer a promising avenue for generating concise, linguistically appropriate, and accessible educational materials tailored to these populations. However, there is limited research evaluating how effectively LLMs perform in creating targeted content for individuals with diverse literacy and language needs. Objective: This study aimed to evaluate the overall performance of LLMs in generating tailored educational content for cancer survivors and their caregivers with limited health literacy or language barriers, compare the performances of 3 Generative Pretrained Transformer (GPT) models (ie, GPT-3.5 Turbo, GPT-4, and GPT-4 Turbo; OpenAI), and examine how different prompting approaches influence the quality of the generated content. Methods: We selected 30 topics from national guidelines on cancer care and education. GPT-3.5 Turbo, GPT-4, and GPT-4 Turbo were used to generate tailored content of up to 250 words at a 6th-grade reading level, with translations into Spanish and Chinese for each topic. Two distinct prompting approaches (textual and bulleted) were applied and evaluated. Nine oncology experts evaluated 360 generated responses based on predetermined criteria: word limit, reading level, and quality assessment (ie, clarity, accuracy, relevance, completeness, and comprehensibility). ANOVA (analysis of variance) or chi-square analyses were used to compare differences among the various GPT models and prompts. Results: Overall, LLMs showed excellent performance in tailoring educational content, with 74.2\% (267/360) adhering to the specified word limit and achieving an average quality assessment score of 8.933 out of 10. However, LLMs showed moderate performance in reading level, with 41.1\% (148/360) of content failing to meet the sixth-grade reading level. LLMs demonstrated strong translation capabilities, achieving an accuracy of 96.7\% (87/90) for Spanish and 81.1\% (73/90) for Chinese translations. Common errors included imprecise scopes, inaccuracies in definitions, and content that lacked actionable recommendations. The more advanced GPT-4 family models showed better overall performance compared to GPT-3.5 Turbo. Prompting GPTs to produce bulleted-format content was likely to result in better educational content compared with textual-format content. Conclusions: All 3 LLMs demonstrated high potential for delivering multilingual, concise, and low health literacy educational content for cancer survivors and caregivers who face limited literacy or language barriers. GPT-4 family models were notably more robust. While further refinement is required to ensure simpler reading levels and fully comprehensive information, these findings highlight LLMs as an emerging tool for bridging gaps in cancer education and advancing health equity. Future research should integrate expert feedback, additional prompt engineering strategies, and specialized training data to optimize content accuracy and accessibility. International Registered Report Identifier (IRRID): RR2-10.2196/48499 ", doi="10.2196/67914", url="https://cancer.jmir.org/2025/1/e67914" } @Article{info:doi/10.2196/60587, author="Hall, A. Deborah and Shulman, M. Josh and Singleton, Andrew and Bandres Ciga, Sara and S Tosin, Hyczy Michelle and Ouyang, Bichun and Shulman, Lisa", title="Racial Disparities in Parkinson Disease Clinical Phenotype, Management, and Genetics: Protocol for a Prospective Observational Study", journal="JMIR Res Protoc", year="2025", month="Apr", day="7", volume="14", pages="e60587", keywords="Parkinson disease", keywords="racial disparities", keywords="clinical protocol", keywords="health disparities", keywords="genetic risk factors", keywords="quality of life", keywords="quality of care", abstract="Background: Parkinson disease (PD) has been described and studied extensively in White populations, with little known about how the disease manifests and progresses in patients from the Black community. Studies investigating disease features in Black populations are uncommon, with some suggesting that the Black population with PD is more disabled and has greater disease severity and different clinical features compared with the White population with PD. These health disparities are likely to influence the quality of care for Black patients with PD. Objective: This study aimed to investigate the motor and nonmotor symptoms and quality of life in Black and White participants with PD in a case-case design. Methods: This is an observational, prospective, multicenter, case-case design study. Other aims will investigate the management of PD in Black individuals and the presence of shared or unique genetic risk factors among the Black PD population. A total of 400 Black and 200 White participants with PD will be recruited. Data will be collected at 7 US sites and entered into a Research Electronic Data Capture database. Linear multivariate regression analysis will be used, except for comparing PD management, which will be analyzed using the chi-square test or Fisher exact test. Bonferroni correction will be applied. This protocol also describes plans for educational programming for clinicians and patients at the end of the study in partnership with national PD organizations. Results: The Rush Institutional Review Board approved the project as the single-site institutional review board in February 2022, and it was funded by the National Institute of Neurological Disorders and Stroke in April 2022. Recruitment began in July 2022. At the time of submission of this manuscript, 131 participants had been recruited. Conclusions: To our knowledge, this is the largest study of PD phenotype and management in Black patients in the United States. The planned collaboration with the Global Parkinson's Genetics Program and PD GENEration will enhance our understanding of genetic risk factors for PD in this understudied population. International Registered Report Identifier (IRRID): DERR1-10.2196/60587 ", doi="10.2196/60587", url="https://www.researchprotocols.org/2025/1/e60587" } @Article{info:doi/10.2196/69048, author="Oliveira, Fonseca Juliane and Vasconcelos, O. Adriano and Alencar, L. Andr{\^e}za and Cunha, L. Maria C{\'e}lia S. and Marcilio, Izabel and Barral-Netto, Manoel and P Ramos, Ivan Pablo", title="Balancing Human Mobility and Health Care Coverage in Sentinel Surveillance of Brazilian Indigenous Areas: Mathematical Optimization Approach", journal="JMIR Public Health Surveill", year="2025", month="Apr", day="1", volume="11", pages="e69048", keywords="representative sentinel surveillance", keywords="early pathogen detection", keywords="indigenous health", keywords="human mobility", keywords="surveillance network optimization", keywords="infectious disease surveillance", keywords="public health strategy", keywords="Brazil", abstract="Background: Optimizing sentinel surveillance site allocation for early pathogen detection remains a challenge, particularly in ensuring coverage of vulnerable and underserved populations. Objective: This study evaluates the current respiratory pathogen surveillance network in Brazil and proposes an optimized sentinel site distribution that balances Indigenous population coverage and national human mobility patterns. Methods: We compiled Indigenous Special Health District (Portuguese: Distrito Sanit{\'a}rio Especial Ind{\'i}gena [DSEI]) locations from the Brazilian Ministry of Health and estimated national mobility routes by using the Ford-Fulkerson algorithm, incorporating air, road, and water transportation data. To optimize sentinel site selection, we implemented a linear optimization algorithm that maximizes (1) Indigenous region representation and (2) human mobility coverage. We validated our approach by comparing results with Brazil's current influenza sentinel network and analyzing the health attraction index from the Brazilian Institute of Geography and Statistics to assess the feasibility and potential benefits of our optimized surveillance network. Results: The current Brazilian network includes 199 municipalities, representing 3.6\% (199/5570) of the country's cities. The optimized sentinel site design, while keeping the same number of municipalities, ensures 100\% coverage of all 34 DSEI regions while rearranging 108 (54.3\%) of the 199 cities from the existing flu sentinel system. This would result in a more representative sentinel network, addressing gaps in 9 of 34 previously uncovered DSEI regions, which span 750,515 km{\texttwosuperior} and have a population of 1.11 million. Mobility coverage would improve by 16.8 percentage points, from 52.4\% (4,598,416 paths out of 8,780,046 total paths) to 69.2\% (6,078,747 paths out of 8,780,046 total paths). Additionally, all newly selected cities serve as hubs for medium- or high-complexity health care, ensuring feasibility for pathogen surveillance. Conclusions: The proposed framework optimizes sentinel site allocation to enhance disease surveillance and early detection. By maximizing DSEI coverage and integrating human mobility patterns, this approach provides a more effective and equitable surveillance network, which would particularly benefit underserved Indigenous regions. ", doi="10.2196/69048", url="https://publichealth.jmir.org/2025/1/e69048" } @Article{info:doi/10.2196/55931, author="Roberts, T. Sarah and Minnis, M. Alexandra and Napierala, Sue and Montgomery, T. Elizabeth and Digolo, Lina and Cottrell, L. Mackenzie and Browne, N. Erica and Ndirangu, Jacqueline and Boke, Joyce and Agot, Kawango", title="Evaluation of the Tu'Washindi Na PrEP Intervention to Reduce Gender-Based Violence and Increase Preexposure Prophylaxis Uptake and Adherence Among Kenyan Adolescent Girls and Young Women: Protocol for a Cluster Randomized Controlled Trial", journal="JMIR Res Protoc", year="2025", month="Apr", day="1", volume="14", pages="e55931", keywords="adolescent girls and young women", keywords="HIV prevention", keywords="preexposure prophylaxis", keywords="PrEP", keywords="adherence", keywords="Kenya", keywords="intimate partner violence", abstract="Background: Adolescent girls and young women constitute a priority population disproportionately affected by HIV, accounting for 25\% of annual HIV incidence among people older than 15 years in Kenya. Although oral preexposure prophylaxis (PrEP) is effective in reducing HIV acquisition, its protective benefit has been limited among adolescent girls and young women in sub-Saharan Africa because of low uptake, adherence, and persistence. Intimate partner violence (IPV) and relationship power inequities are widespread among adolescent girls and young women and contribute to higher HIV incidence and lower PrEP use. Interventions are needed to support sustained PrEP use among adolescent girls and young women by addressing IPV and relationship dynamics. Objective: This study aims to test the effectiveness of Tu'Washindi na PrEP (``We are Winners with PrEP''), a multilevel community-based intervention, to increase uptake and adherence to PrEP and reduce IPV among adolescent girls and young women in Siaya County, Kenya. Methods: The Tu'Washindi na PrEP intervention was co-designed by our team and adolescent girls and young women using participatory methods and includes 3 components delivered over 6 months: an 8-session, empowerment-based support club for adolescent girls and young women, community sensitization targeted toward male partners, and PrEP education events for couples. The intervention will be evaluated using a cluster randomized controlled trial across 22 administrative wards in Siaya County, Kenya, enrolling 72 adolescent girls and young women per ward (total N=1584). The primary objectives are to test the effectiveness of the intervention on PrEP uptake and adherence immediately after delivery (month 6 after enrollment) and 6 months later (month 12). As secondary objectives, we will test the intervention effect on IPV. A rigorous process evaluation will explore mechanisms of change, contextual factors, and implementation considerations to inform future refinement and scale-up, using programmatic data, participant questionnaires, and qualitative interviews with participants and intervention providers. Results: Data collection started in September 2022. As of December 2024, enrollment has been completed in 16 of the 22 study wards, with 72.6\% (1150/1584) of participants enrolled. We anticipate that data collection will be completed in May 2026 and results will be available by mid-2027. Conclusions: The study builds directly on our promising formative and pilot research to develop the evidence base for this youth-designed, multilevel HIV prevention intervention. If effective, Tu'Washindi will be ideally positioned for sustainable integration into existing youth-focused programming to expand and support PrEP use in this priority population. Trial Registration: ClinicalTrials.gov NCT05599581; https://www.clinicaltrials.gov/study/NCT05599581 International Registered Report Identifier (IRRID): DERR1-10.2196/55931 ", doi="10.2196/55931", url="https://www.researchprotocols.org/2025/1/e55931" } @Article{info:doi/10.2196/70404, author="Mackwood, Matthew and Fisher, Elliott and Schmidt, O. Rachel and O'Malley, James A. and Rodriguez, P. Hector and Shortell, Stephen and Akr{\'e}, Ellesse-Roselee and Berube, Alena and Schifferdecker, E. Karen", title="Primary Care Practice Factors Associated With Telehealth Adoption in the United States: Cross-Sectional Survey Analysis", journal="J Med Internet Res", year="2025", month="Mar", day="28", volume="27", pages="e70404", keywords="telehealth", keywords="telemedicine", keywords="remote consultation", keywords="primary health care", keywords="general practice", keywords="internet access", keywords="health policy", keywords="health care economics and organizations", keywords="access to primary care", keywords="digital divide", keywords="vulnerable populations", keywords="medically underserved area", doi="10.2196/70404", url="https://www.jmir.org/2025/1/e70404" } @Article{info:doi/10.2196/67487, author="Li, Mingyan and Sun, Changxuan and Ji, Chai and Gao, Meiying and Wang, Xia and Yao, Dan and Guo, Junxia and Sun, Lidan and Rafay, Abdul and George, Shereen Antonita and Muhandiramge, Samararathna Sanduni Hasara Samararathna and Bai, Guannan", title="Vaccine Hesitancy and Associated Factors Among Caregivers of Children With Special Health Care Needs in the COVID-19 Era in China: Cross-Sectional Study", journal="JMIR Public Health Surveill", year="2025", month="Mar", day="26", volume="11", pages="e67487", keywords="COVID-19", keywords="caregivers", keywords="children with special health care needs", keywords="vaccination hesitancy", keywords="decision-making", abstract="Background: Immunization is a cost-effective way to prevent infectious diseases in children, but parental hesitancy leads to low vaccination rates, leaving children at risk. Caregivers of children with special health care needs are more hesitant about vaccines than those of healthy children. Objective: The aim of the study is to investigate the changes in caregivers' vaccination hesitation of children with special health care needs before, during, and after the COVID-19 pandemic in China and to identify associated factors for caregivers' attitudes toward National Immunization Program (NIP) and non-NIP vaccines. Methods: We included 7770 caregivers of children with special health care needs (median age 7.0, IQR 2.4-24.1 months) who visited the Vaccination Consultation Clinic at Children's Hospital, Zhejiang University School of Medicine (Hangzhou, China) from May 2017 to May 2023. General and clinical information was extracted from the immunization evaluation system for children with special health care needs and medical records. We compared the differences in caregivers' willingness and hesitation for vaccinating their children across the 3 stages of the COVID-19 pandemic using chi-square tests. Multinomial logistic regression models were used to identify independent variables that were associated with caregivers' willingness and hesitation toward NIP and non-NIP vaccines. Results: There is a statistically significant difference in caregivers' vaccine hesitancy before, during, and after the COVID-19 pandemic (P<.05). During the COVID-19 pandemic, the percentages of choosing NIP, alternative non-NIP, and non-NIP vaccines are highest (n=1428, 26\%, n=3148, 57.4\%, and n=3442, 62.7\%, respectively) than those at other 2 stages. In comparison, caregivers' hesitation toward NIP and non-NIP vaccines is lowest (n=911, 16.6\% and n=2045, 37.3\%, respectively). Despite the stages of the COVID-19 pandemic, multiple factors, including children's age and sex, parents' educational level, comorbidities, and history of allergy, were significantly associated with caregivers' attitude toward NIP and non-NIP vaccines (P<.05). The profiles of risk factors for hesitancy toward NIP and non-NIP vaccines are different, as indicated by the results from the logistic regression models. Conclusions: This study demonstrated that caregivers' willingness to vaccinate their children with special health care needs with NIP and non-NIP vaccines was highest during the COVID-19 pandemic in China, and their hesitancy was lowest. Additionally, we have identified multiple factors associated with caregivers' willingness and hesitancy to vaccinate their children. These findings provide evidence-based support for developing personalized health education strategies. ", doi="10.2196/67487", url="https://publichealth.jmir.org/2025/1/e67487" } @Article{info:doi/10.2196/70983, author="Schmit, D. Cason and O'Connell, Curry Meghan and Shewbrooks, Sarah and Abourezk, Charles and Cochlin, J. Fallon and Doerr, Megan and Kum, Hye-Chung", title="Dying in Darkness: Deviations From Data Sharing Ethics in the US Public Health System and the Data Genocide of American Indian and Alaska Native Communities", journal="J Med Internet Res", year="2025", month="Mar", day="26", volume="27", pages="e70983", keywords="ethics", keywords="information dissemination", keywords="indigenous peoples", keywords="public health surveillance", keywords="privacy", keywords="data sharing", keywords="deidentification", keywords="data anonymization", keywords="public health ethics", keywords="data governance", doi="10.2196/70983", url="https://www.jmir.org/2025/1/e70983" } @Article{info:doi/10.2196/64745, author="MacIsaac, Angela and Neufeld, Teagan and Malik, Ishaq and Toombs, Elaine and Olthuis, V. Janine and Schmidt, Fred and Dunning, Crystal and Stasiuk, Kristine and Bobinski, Tina and Ohinmaa, Arto and Stewart, H. Sherry and Newton, S. Amanda and Mushquash, R. Aislin", title="Increasing Access to Mental Health Supports for 18- to 25-Year-Old Indigenous Youth With the JoyPop Mobile Mental Health App: Study Protocol for a Randomized Controlled Trial", journal="JMIR Res Protoc", year="2025", month="Jan", day="30", volume="14", pages="e64745", keywords="mental health", keywords="youth", keywords="Indigenous", keywords="First Nations", keywords="eHealth", keywords="mHealth", keywords="JoyPop", keywords="protocol", keywords="mobile mental health app", keywords="mobile app", keywords="Canada", keywords="mobile health", keywords="emotion regulation", abstract="Background: Transitional-aged youth have a high burden of mental health difficulties in Canada, with Indigenous youth, in particular, experiencing additional circumstances that challenge their well-being. Mobile health (mHealth) approaches hold promise for supporting individuals in areas with less access to services such as Northern Ontario. Objective: The primary objective of this study is to evaluate the effectiveness of the JoyPop app in increasing emotion regulation skills for Indigenous transitional-aged youth (aged 18-25 years) on a waitlist for mental health services when compared with usual practice (UP). The secondary objectives are to (1) evaluate the impact of the app on general mental health symptoms and treatment readiness and (2) evaluate whether using the app is associated with a reduction in the use (and therefore cost) of other services while one is waiting for mental health services. Methods: The study is a pragmatic, parallel-arm randomized controlled superiority trial design spanning a 4-week period. All participants will receive UP, which involves waitlist monitoring practices at the study site, which includes regular check-in phone calls to obtain any updates regarding functioning. Participants will be allocated to the intervention (JoyPop+UP) or control (UP) condition in a 1:1 ratio using stratified block randomization. Participants will complete self-report measures of emotion regulation (primary outcome), mental health, treatment readiness, and service use during 3 assessments (baseline, second [after 2 weeks], and third [after 4 weeks]). Descriptive statistics pertaining to baseline variables and app usage will be reported. Linear mixed modeling will be used to analyze change in outcomes over time as a function of condition assignment, while a cost-consequence analysis will be used to evaluate the association between app use and service use. Results: Recruitment began September 1, 2023, and is ongoing. In total, 2 participants have completed the study. Conclusions: This study will assess whether the JoyPop app is effective for Indigenous transitional-aged youth on a waitlist for mental health services. Positive findings may support the integration of the app into mental health services as a waitlist management tool. Trial Registration: ClinicalTrials.gov NCT05991154; https://clinicaltrials.gov/study/NCT05991154 International Registered Report Identifier (IRRID): DERR1-10.2196/64745 ", doi="10.2196/64745", url="https://www.researchprotocols.org/2025/1/e64745" } @Article{info:doi/10.2196/60829, author="Karasek, Deborah and Williams, C. Jazzmin and Taylor, A. Michaela and De La Cruz, M. Monica and Arteaga, Stephanie and Bell, Sabra and Castillo, Esperanza and Chand, A. Maile and Coats, Anjeanette and Hubbard, M. Erin and Love-Goodlett, Latriece and Powell, Breezy and Spellen, Solaire and Malawa, Zea and Gomez, Manchikanti Anu", title="Designing the First Pregnancy Guaranteed Income Program in the United States: Qualitative Needs Assessment and Human-Centered Design to Develop the Abundant Birth Project", journal="JMIR Form Res", year="2025", month="Jan", day="27", volume="9", pages="e60829", keywords="maternal and child health", keywords="economics", keywords="public health", keywords="qualitative research methods", keywords="programs (evaluation and funding)", keywords="community-centered", keywords="pregnancy", keywords="first pregnancy", keywords="behavioral interventions", keywords="racial health", keywords="financial stress", keywords="Abundant Birth Project", keywords="infant health", keywords="infant", keywords="Black", abstract="Background: Racial inequities in pregnancy outcomes persist despite investments in clinical, educational, and behavioral interventions, indicating that a new approach is needed to address the root causes of health disparities. Guaranteed income during pregnancy has the potential to narrow racial health inequities for birthing people and infants by alleviating financial stress. Objective: We describe community-driven formative research to design the first pregnancy-guaranteed income program in the United States---the Abundant Birth Project (ABP). Informed by birth equity and social determinants of health perspectives, ABP targets upstream structural factors to improve racial disparities in maternal and infant health. Methods: The research team included community researchers, community members with lived experience as Black or Pacific Islander pregnant, and parenting people in the San Francisco Bay Area. The team conducted needs assessment interviews and facilitated focus groups with participants using human-centered design methods. Needs assessment participants later served as co-designers of the ABP program and research, sharing their experiences with financial hardships and government benefits programs and providing recommendations on key program elements, including fund disbursement, eligibility, and amount. Results: Housing affordability and the high cost of living in San Francisco emerged as significant sources of stress in pregnancy. Participants reported prohibitively low income eligibility thresholds and burdensome enrollment processes as challenges or barriers to existing social services. These insights guided the design of prototypes of ABP's program components, which were used in a design sprint to determine the final components. Based on this design process, the ABP program offered US \$1000/month for 12 months to pregnant Black and Pacific Islander people, selected through a lottery called an abundance drawing. Conclusions: The formative design process maximized community input and shared decision-making to co-design a guaranteed income program for Black and Pacific Islander women and people. Our upstream approach and community research model can inform the development of public health and social service programs. ", doi="10.2196/60829", url="https://formative.jmir.org/2025/1/e60829" } @Article{info:doi/10.2196/66496, author="Amsalem, Doron and Greuel, Merlin and Liu, Shuyan and Martin, Andr{\'e}s and Adam, Maya", title="Effect of a Short, Animated Storytelling Video on Transphobia Among US Parents: Randomized Controlled Trial", journal="JMIR Public Health Surveill", year="2025", month="Jan", day="20", volume="11", pages="e66496", keywords="public health communication", keywords="vulnerable population", keywords="stigma reduction", keywords="stigma", keywords="transphobia", keywords="transgender", keywords="gender diverse", keywords="LGBTQ", keywords="parent", keywords="mental health", keywords="mental illness", keywords="transgender children", keywords="children", keywords="youth", keywords="adolescent", keywords="storytelling", keywords="animation", abstract="Background: Parents play a pivotal role in supporting transgender and gender diverse (TGD) youth. Yet only 35\% of TGD youth describe their home as a gender-affirming place. Lack of parental support contributes to recent findings that TGD youth are approximately three times more likely to attempt suicide than their cisgender peers. In contrast, parents' affirmation of their children's gender identity significantly improves their mental health outcomes, by reducing anxiety, depression, and suicidality. Objective: Addressing the urgent need for effective, scalable interventions, this study evaluates a novel digital approach: short, animated storytelling videos. We hypothesized that our 2.5-minute video intervention would reduce antitransgender stigma, or transphobia, and improve attitudes toward gender diverse children among US parents. Methods: We recruited 1267 US parents, through the Prolific Academic (Prolific) online research platform, and randomized them into video intervention or control groups. We measured transphobia using the Transgender Stigma Scale, and attitudes toward transgender children using the gender thermometer, before and after watching the video. We compared outcomes between the two groups using 2 {\texttimes} 3 ANOVA. Both groups were invited to return 30 days later for follow-up assessment, before being offered posttrial access to the intervention video, which portrayed an authentic conversation between a mother and her transgender child. Results: Single exposure to a short, animated story video significantly reduced transphobia and improved attitudes toward transgender children among US parents, immediately post intervention. We observed a significant group-by-time interaction in mean Transgender Stigma Scale scores (F2,1=3.7, P=.02) and significant between-group changes when comparing the video and control groups from baseline to post intervention (F1=27.4, P<.001). Effect sizes (Cohen d) indicated small to moderate immediate changes in response to the 2.5-minute video, though the effect was no longer observed at the 30-day follow-up. Gender thermometer scores revealed significant immediate improvements in the attitudes of participants in the video intervention arm, and this improvement was sustained at the 30-day time point. Conclusions: Short, animated storytelling is a novel digital approach with the potential to boost support and affirmation of transgender children, by offering authentic insights into the lived experiences of TGD youth. Repeated exposures to such interventions may be necessary to sustain improvements over time. Future studies could test a series of short, animated storytelling videos featuring the lived experiences of several TGD youth. Evaluating the effect of such a series could contribute to the fields of digital health communication and transgender health. Digital approaches, such as short, animated storytelling videos, that support empathy and acceptance of TGD youth could foster a more inclusive society in which every child can thrive. Trial Registration: AsPredicted.org 159248; https://aspredicted.org/ptmd-3kfs.pdf ", doi="10.2196/66496", url="https://publichealth.jmir.org/2025/1/e66496" } @Article{info:doi/10.2196/58546, author="Buetti, David and Larche, Cynthia and Fitzgerald, Michael and Bourgeois, Isabelle and Cameron, Erin and Carr, Kady and Aubry, Tim and Persaud, Sydney and Kendall, E. Claire", title="Evaluating the Impacts of Community-Campus Engagement on Population Health in Ottawa and Thunder Bay, Canada: Protocol for a Mixed Methods Contribution Analysis", journal="JMIR Res Protoc", year="2025", month="Jan", day="17", volume="14", pages="e58546", keywords="community-campus engagement", keywords="population health", keywords="contribution analysis", keywords="mixed methods", keywords="health determinants", keywords="community health", keywords="CityStudio", keywords="theory of change", keywords="impact evaluation", abstract="Background: Municipalities play a crucial role in population health due to their community connections and influence on health determinants. Community-campus engagement (CCE), that is, collaboration between academic institutions and communities, is a promising approach to addressing community health priorities. However, evidence of CCE's impact on population health remains limited. Measuring the impacts of CCE is inherently complex due to factors such as diverse stakeholders, context-specific variables, and dynamic interactions within a community. Objective: This study aims to develop robust evidence on the impacts of CCE on population health outcomes in Ottawa and Thunder Bay, Ontario, Canada, focusing on 5 shared health priorities: housing, discrimination, poverty, violence, and mental health. Methods: We will use a proven CCE model called CityStudio, which has been implemented in both cities. We will use Mayne's mixed methods contribution analysis in three stages: (1) formulating a theory of change that outlines the expected contributions of CCE to population health outcomes; (2) gathering qualitative and quantitative data in line with the established Theory of Change; the data will be collected from various sources, including case studies of existing CityStudio projects, a web-based CCE stakeholder survey, a literature review, and population and community health data; and (3) reviewing the gathered evidence to determine the extent of CCE impacts on population health. Results: Ethical approval for this project was granted in May 2023. We have since initiated stage 1 by reviewing the literature to inform the development of the theory of change. We expect to complete this study by May 2026. Conclusions: This study will address two critical gaps about how improving health outcomes depends on CCE: (1) how academic institutions can best engage with their communities to improve population health outcomes, and (2) how municipalities can engage with academic institutions to address their community health priorities. Conducting our work in differing contexts will allow us to consider a broader range of other influences on outcomes, thus making our work applicable to various settings and outcomes. International Registered Report Identifier (IRRID): PRR1-10.2196/58546 ", doi="10.2196/58546", url="https://www.researchprotocols.org/2025/1/e58546" } @Article{info:doi/10.2196/60189, author="Klein, Dave and Montgomery, Aisha and Begale, Mark and Sutherland, Scott and Sawyer, Sherilyn and McCauley, L. Jacob and Husbands, Letheshia and Joshi, Deepti and Ashbeck, Alan and Palmer, Marcy and Jain, Praduman", title="Building a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the All of Us Research Program: Design and Implementation Study", journal="J Med Internet Res", year="2025", month="Jan", day="15", volume="27", pages="e60189", keywords="longitudinal studies", keywords="cohort studies", keywords="health disparities", keywords="minority populations", keywords="vulnerable populations", keywords="precision medicine", keywords="biomedical research", keywords="decentralization", keywords="digital health technology", keywords="database management system", abstract="Background: Longitudinal cohort studies have traditionally relied on clinic-based recruitment models, which limit cohort diversity and the generalizability of research outcomes. Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of digitally enabled studies rely heavily on the design, implementation, and management of the digital platform being used. Objective: We sought to design and build a secure, privacy-preserving, validated, participant-centric digital health research platform (DHRP) to recruit and enroll participants, collect multimodal data, and engage participants from diverse backgrounds in the National Institutes of Health's (NIH) All of Us Research Program (AOU). AOU is an ongoing national, multiyear study aimed to build a research cohort of 1 million participants that reflects the diversity of the United States, including minority, health-disparate, and other populations underrepresented in biomedical research (UBR). Methods: We collaborated with community members, health care provider organizations (HPOs), and NIH leadership to design, build, and validate a secure, feature-rich digital platform to facilitate multisite, hybrid, and remote study participation and multimodal data collection in AOU. Participants were recruited by in-person, print, and online digital campaigns. Participants securely accessed the DHRP via web and mobile apps, either independently or with research staff support. The participant-facing tool facilitated electronic informed consent (eConsent), multisource data collection (eg, surveys, genomic results, wearables, and electronic health records [EHRs]), and ongoing participant engagement. We also built tools for research staff to conduct remote participant support, study workflow management, participant tracking, data analytics, data harmonization, and data management. Results: We built a secure, participant-centric DHRP with engaging functionality used to recruit, engage, and collect data from 705,719 diverse participants throughout the United States. As of April 2024, 87\% (n=613,976) of the participants enrolled via the platform were from UBR groups, including racial and ethnic minorities (n=282,429, 46\%), rural dwelling individuals (n=49,118, 8\%), those over the age of 65 years (n=190,333, 31\%), and individuals with low socioeconomic status (n=122,795, 20\%). Conclusions: We built a participant-centric digital platform with tools to enable engagement with individuals from different racial, ethnic, and socioeconomic backgrounds and other UBR groups. This DHRP demonstrated successful use among diverse participants. These findings could be used as best practices for the effective use of digital platforms to build and sustain cohorts of various study designs and increase engagement with diverse populations in health research. ", doi="10.2196/60189", url="https://www.jmir.org/2025/1/e60189" } @Article{info:doi/10.2196/58460, author="Leung, May May and Mateo, F. Katrina and Dublin, Marlo and Harrison, Laura and Verdaguer, Sandra and Wyka, Katarzyna", title="Testing a Web-Based Interactive Comic Tool to Decrease Obesity Risk Among Racial and Ethnic Minority Preadolescents: Randomized Controlled Trial", journal="JMIR Form Res", year="2025", month="Jan", day="15", volume="9", pages="e58460", keywords="childhood obesity", keywords="preadolescents", keywords="racial and ethnic minority populations", keywords="dietary behaviors", keywords="BMI", keywords="digital health", abstract="Background: Childhood obesity prevalence remains high, especially in racial and ethnic minority populations with low incomes. This epidemic is attributed to various dietary behaviors, including increased consumption of energy-dense foods and sugary beverages and decreased intake of fruits and vegetables. Interactive, technology-based approaches are emerging as promising tools to support health behavior changes. Objective: This study aimed to assess the feasibility and acceptability of Intervention INC (Interactive Nutrition Comics for Urban, Minority Preadolescents), a 6-chapter web-based interactive nutrition comic tool. Its preliminary effectiveness on diet-related psychosocial variables and behaviors was also explored. Methods: A total of 89 Black or African American and Hispanic preadolescents with a mean age of 10.4 (SD 1.0) years from New York City participated in a pilot 2-group randomized study, comprising a 6-week intervention and a 3-month follow-up (T4) period. Of the 89 participants, 61\% were female, 62\% were Black, 42\% were Hispanic, 53\% were overweight or obese, and 34\% had an annual household income of