JMIR Research Protocols

Background: Documentation burden significantly impacts nursing workload and well-being, with nurses spending an estimated 20-40% of their time on documentation. Ambient AI technologies offer potential to reduce documentation time by mapping real-time nurse-patient conversations to structured EHR data entries with human-in-the-loop verification. Methods: This protocol describes a pragmatic, EHR-embedded randomized controlled trial evaluating the effectiveness of an Ambient AI tool in reducing nursing documentation time across three inpatient medical/surgical units. The study employs a closed-cohort, stepped-wedge, unit-randomized design, integrating the intervention into routine clinical workflows. The primary outcome is documentation time per shift hour, derived from EHR audit logs. Secondary outcomes include documentation burden, professional well-being, and perceived usability. Results: The trial is being implemented within a shared governance model that integrates executive oversight, operational feasibility, and research rigor. Multidisciplinary workgroups coordinate technical integration, user experience, and analytics, ensuring alignment between operational priorities and pragmatic trial objectives. Early implementation has highlighted the importance of adapting training and analytic strategies to address differential intervention exposure, as well as the need for rapid operational responses to late-emerging technical issues. Discussion: This protocol demonstrates the feasibility of embedding a randomized pragmatic trial within a health system-led operational deployment of Ambient AI for inpatient nursing documentation. The approach highlights the necessity of adapting existing outpatient provider-focused AI implementation strategies for inpatient nursing, emphasizing the unique nature of different nursing care environments. Recruitment challenges and the integration of research with operational workflows are discussed as key considerations for future pragmatic AI trials in nursing. Keywords: Artificial Intelligence; Ambient AI; Nursing Documentation; Documentation Burden; Large Language Models; Speech Recognition Software; Stepped-Wedge Design ClinicalTrials.gov Identifier NCT07456241V4: 2026-05-27 https://clinicaltrials.gov/study/NCT07456241

In Brazil, autistic children and their families face significant challenges in accessing evidence-based interventions, especially via the national public health service. Here, we report the protocol for a hybrid effectiveness-implementation trial, which will investigate the large-scale implementation of Paediatric Autism Communication Therapy (PACT) as well as its real-world effectiveness in Brazilian public health services for autistic children. Eligible professionals from public health services across the five regions of Brazil will be trained in PACT. They will deliver the intervention, which consists of 14 sessions delivered over 6 months, to dyads of autistic children and their caregivers in their regular clinical practice for the trial period of 18 months. We will use elements of three implementation science frameworks to systematically study factors that influence the implementation of PACT in this setting. To study effectiveness dyads will be randomised to receive PACT immediately or following a 6-month waitlist, stratified by healthcare service. Effectiveness outcomes (parent-child interaction, child adaptive social communication skills, caregiver well-being) will be collected pre- and post-PACT/waitlist and compared between groups. This trial will provide the first evidence on the effectiveness of PACT implemented in a public health system and the barriers and facilitators to such large-scale implementation.

Aims To develop the Bowel Irrigation Questionnaire (BIQ), a patient-reported experience measure (PREM) designed to assess the user experience of transanal irrigation (TAI). Methods Statements were generated through literature review and qualitative interviews with healthcare professionals (HCPs) and product users. Statements were rated on a 6-point content validity index scale through an international three-round online Delphi survey by 20 expert panel members. Consensus attainment was defined based on percentage agreement, statements which did not meet consensus were discussed at a final international online consensus meeting. The content validity of the PREM was evaluated through cognitive interviews and the Questionnaire on Questionnaires (QQ-10). Reliability was assessed using a test-retest design, where users completed the BIQ on two occasions one week apart. Results 215 statements were generated from 9 multi-disciplinary qualitative interviews and literature review. Statements were refined to reduce repetition and ensure clarity. 73 statements grouped into 11 domains were reviewed through the Delphi survey. Following the Delphi survey and clinical consensus meeting, the preliminary BIQ consisted of 15 items. Six cognitive interviews were conducted, resulting in a finalised BIQ of 16 items. 32 product users completed both the QQ-10 and test-retest study, the results of which demonstrated good content validity and temporal stability respectively. Conclusions The Bowel Irrigation Questionnaire is a novel PREM designed to assess the user experience of TAI in both clinical and research settings. The instrument demonstrates good validity, acceptability and temporal stability, supporting its use as a reliable measure of patient experience.

Objective: To describe and critically appraise the participatory design process underpinning a multimedia patient education platform for thyroid surgery in light of subsequent evaluation findings, in order to derive human?factors and methodological lessons for future co?creation. Methods: Using a multi-phase participatory design approach anchored in the Technology Acceptance Model and Mayer's Cognitive Theory of Multimedia Learning, including dual?channel processing and cognitive load principles, a multidisciplinary team including a patient representative co?created Medtronic's Butterfly platform for preoperative thyroid patients. Two Nominal Group Technique-based workshops mapped a six-stage surgical pathway, identified stage-specific information needs, and specified formats and sequencing for educational content. An external communication agency developed storyboards as precursors to webpages, animated videos, and leaflets, which underwent iterative advisory board review and content validity indexing before external mixed-methods evaluation in a cohort of thyroidectomy candidates. Results: The co-creation process yielded a modular platform comprising five informational webpages, five short animated videos, and three downloadable leaflets, each mapped to specific pathway stages, learning objectives, and information needs. The platform achieved high scores on validated measures of information quality, credibility, understandability, and actionability, and patients reported enhanced preparedness and decision-making support. However, formal readability assessments of webpages and video scripts showed that most materials exceeded recommended grade levels, usability issues in digital user experience (e.g., mobile responsiveness, navigation, subtitles) emerged only after implementation, and group-level stress, anxiety, and depression scores did not substantially improve despite perceived informational and emotional support. Conclusions: Participatory design facilitated the creation of a clinically credible, pathway-aligned educational platform that addresses key informational gaps in thyroid surgery care but also exposed boundaries of information-focused co-creation. Future projects should treat readability as a non-negotiable design constraint, extend co-creation to systematic usability testing of digital interfaces, and explicitly distinguish educational from psychosocial aims while co-designing complementary distress screening and referral pathways. The Butterfly platform offers a transferable model for co-creating high-quality digital patient education while highlighting the need to more fully center equity, accessibility, and broader patient support in participatory design.

BACKGROUND: Older adults with cancer often struggle to achieve recommended levels of physical activity and dietary intake. Ecological momentary assessment combined with accelerometry can provide insights into the temporal dynamics of psychological and behavioral processes at the individual level, such as motivation towards health behaviors. OBJECTIVE: This N-of-1 study aims to improve physical activity and nutritional behaviors among older patients with cancer using an mHealth behavioral intervention. METHODS: A single-subject ABA' design will be employed among older patients with cancer ([≥] 70 years). A 2-week baseline phase (A) will be followed by an 8-week intervention phase (B) and a two-week withdrawal phase (A'). Throughout all these phases, participants will complete a daily data collection protocol combining ecological momentary assessment questionnaires and an ActiGraph wGT3X-BT accelerometer worn on the waist to measure physical activity. Ecological momentary assessment questionnaires will be delivered via a digital application to collect information on nutritional behavior, fatigue, and motivational constructs based on the Theory of Planned Behavior. The intervention (B) will consist of an mHealth intervention based on behavior change techniques, delivered via weekly calls, personalized messages, and a digital application. Data will be analyzed using piecewise and segmented regression models. In addition, a semi-structured interview will be conducted to assess patient experience. These qualitative data will help identify contextual factors, such as treatment-related side effects or variations in health status, that may have influenced behavior change and participation in data collection. CONCLUSION: This N-of-1 study explores intra-individual behavioral dynamics using intensive longitudinal data rather than testing a strictly reversible intervention effect. The mHealth intervention is based on behavior change techniques and tailored to each patient, with adjustments made based on repeated daily assessments in a real-world setting using a wGT3X-BT accelerometer and ecological momentary assessment questionnaires. The results will contribute to the evidence base for mHealth interventions designed to promote sustained physical activity and dietary intake among older adults with cancer.

Background: Children and young people (CYP) are particularly affected by mental health problems. Mobile apps provide a scalable and accessible approach to adolescent mental health support, and schools are well-positioned to address multiple risk factors and deliver large-scale interventions. By combining active (self-reported) and passive (sensor-derived) data, mobile apps can model mental states and deliver context-aware support. Artificial Intelligence (AI) enables adaptive, context-aware recommendations tailored to each user. However, there is limited research on AI-based mental health interventions in community CYP. MindCraft is a mobile app designed to monitor adolescents mental health using active and passive data and provide AI-informed recommendations ("nudges"). This study aims to investigate the effectiveness of personalised AI nudges delivered through MindCraft on improving mental health outcomes among adolescents in schools in the United Kingdom. Methods: The study is a three-arm RCT using a prospective cohort of secondary school students aged 14-19. Following informed consent, participants complete a baseline online assessment at school and download MindCraft. The primary outcome is the Strengths and Difficulties Questionnaire global and subscale scores. Secondary outcomes include the Eating Disorders Diagnostic Scale, the Sleep Condition Indicator Questionnaire, the Self-Injurious Thoughts and Behaviours Interview, the Self-Efficacy Questionnaire for Children and the World Health Organisation-Five Well-Being Index. Participants are randomised to: (1) an AI-informed intervention group receiving personalised nudges, (2) an active control receiving non-personalised nudges, or (3) a control group with self-monitoring only. Participants use the app for four weeks, with follow-up at one month. Repeated-measures analyses will assess changes across time points. Discussion: We hypothesise that AI nudges will have a greater positive effect on mental health outcomes at one month than general nudges and self-monitoring. Our findings will provide key evidence on the effectiveness of personalised mobile AI recommendations for adolescents mental health and inform school-based mental health prevention and early intervention. This study will contribute evidence on the ethical, acceptable, and scalable integration of AI-enabled digital mental health tools within public health and educational systems, with implications for the design of future digital public health interventions and policies supporting their safe integration in schools.

Background: Obesity is globally recognized as a complex, multifactorial chronic disease, with biological, psychological, environmental and behavioural factors involved in both disease pathogenesis and maintenance. Although previous group-based studies demonstrated involvement of each of these factors, there is large inter-individual variability in the factors contributing to disease development as well as intervention outcomes, causing limited translatability to the individual level. This heterogeneity in treatment effectiveness might be due to differential causal and maintenance factors of obesity. To enable the transition from a one-size-fits-all approach to a more personalized approach for individuals with overweight or obesity, this study aims to investigate if and how the degree of weight loss and changes in daily life behaviour after a combined lifestyle intervention depend on individual baseline profiles comprising of person characteristics, biological, psychological, environmental and behavioural factors. Methods: This study will include 600 individuals varying in BMI, 200 participants with a healthy BMI (18.5-24.9kg/m2), 200 with overweight (BMI 25.0-29.9kg/m2), and 200 with obesity (BMI [≥]30.0kg/m2). For all participants, a comprehensive individual baseline profile is created, including person characteristics, biological, psychological, environmental and behavioural factors. A clustering method is applied to identify clusters of participants with similar characteristics. Next, we examine if and how these clusters are linked to bodyweight indicators measured at baseline, and how they relate to daily lifestyle behaviour, as measured by ecological momentary assessment (EMA) using a smartphone app and sensor technology (3-week measurements). Individuals with overweight or obesity will be randomized to the intensive lifestyle intervention or a lifestyle information condition, to determine if treatment response can be predicted based on cluster characteristics, how daily lifestyle behaviour changes after an intervention, and how changes in daily lifestyle behaviour relate to treatment response. Discussion: The End of Average study aims to characterize a large set of individuals varying in body weight to predict intervention effectiveness measured as changes in body weight indicators and in daily lifestyle behaviours. If reliable predictors of treatment success can be identified, these can be applied in personalized lifestyle interventions to improve lifestyle behaviour, body weight management and overall health.

Background Clinical decision support systems configured as electronic medical records alerts can support clinical trial recruitment by identifying eligible participants. While they are typically used to evaluate a single patient record, their application for a linked maternal infant chart has not been extensively explored. Objective This project aimed to design and implement a clinical trial alert using linked maternal infant records and to evaluate researchers perceived usability. Materials and Methods We conducted a two phase quality assurance project: (1) design and implementation of an alert aligned with the anticipated recruitment workflow, and (2) evaluation of usability using the System Usability Scale. Basic content analysis described the alert design and implementation processes, while quantitative scoring assessed perceived usability. Results Over a 12 month period, only one alert was triggered due to changes in the recruitment workflow. Two silent alerts assessed maternal eligibility in outpatient and infant eligibility in inpatient settings. Three of four researchers completed the survey, yielding a score of 92.5, indicating excellent usability. Conclusion Although the alert was technically functional and perceived to have excellent usability, its performance was limited by deviations from the intended recruitment workflow. Researcher engagement and recruitment workflow alignment emerged as critical factors influencing alert utility. Clinical trial alerts for linked maternal infant records can be designed and implemented with excellent usability; however, consistent adherence to the recruitment workflow is essential. Broader application in additional study settings is recommended.

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

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

Background: Despite ample evidence of the benefits of cardiac rehabilitation (CR), few transcatheter aortic valve replacement (TAVR) patients participate. Commercially available mobile health offers an opportunity to deliver activity-promotion content to populations that are challenged to participate in CR. This study aims to test the efficacy of clinically controlled, commercially available fitness programming for improving physical activity and cardiovascular health outcomes designed to be initiated while patients are on waitlists for traditional CR. Methods: The Cardio Heart Connect study is a hybrid type I effectiveness-implementation trial aiming to enroll N=200 patients who have been placed on a cardiac rehab waitlist following a TAVR procedure from the University of Colorado Hospital Heart and Vascular Center. Participants will be randomized 1:1 to the Cardio Heart Connect intervention with commercially available fitness or attention control, designed to control for technology access. At baseline, post-intervention (8 weeks), and follow-up (12 months), we will assess the primary outcome of participants? daily steps as measured by smartwatch accelerometer and secondary outcomes of interest including functional capacity (Duke Activity Status Index; VO2max), quality of life (Kansas City Cardiomyopathy Questionnaire), and cardiovascular health status (Life Essential 8). In addition, we will use mixed methodologies to evaluate the implementation of intervention using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) Framework. Conclusions: Commercially available fitness programs have the potential to provide more accessible opportunities for patients recovering from TAVR to engage in physical activity and may be preferred due to their customizability, convenience, and ease of scheduling. Overall, this study will provide insight into the use of commercial mHealth to promote activity following TAVR.

Background A drug-repurposing-specific phenome-wide association study (PheWAS) demonstrated that patients with a single nucleotide variant that decreases expression of platelet-derived growth factor receptor beta (PDGFR{beta}) have a higher prevalence of fistulas, suggesting that PDGFR{beta} signaling is important for tissue repair. Recombinant human platelet derived growth factor B (rhPDGF) is an FDA-approved protein-based therapeutic that signals through PDGFR{beta} to heal and regenerate cutaneous skin wounds, periodontal tissue, and orthopedic bone with a strong safety profile. We hypothesize that rhPDGF will benefit other conditions identified by PheWAS with a similar physiological mechanism as the existing indications, such as complex perianal fistulas that are ineligible for a fistulotomy. Methods and analysis This prospective, blinded, single-site study aims to enroll 12 participants, randomized at a ratio of 2:1, comparing implantation of rhPDGF-enhanced collagen to routine care procedures, and stratified by fistula etiology, idiopathic versus Crohns disease (CD)-related. The primary outcome of this study will evaluate the technical performance of the rhPDGF-enhanced collagen implant for treatment of complex perianal fistulas as measured by the proportion of participants with successful implantation of the intervention without any intervention-related serious adverse events. The secondary outcomes will assess the preliminary safety and efficacy of the intervention based on all intervention-related adverse events, total fistulas healed, rate of fistula recurrence, and change in patient-reported symptoms. Complex perianal fistulas, idiopathic or CD-related, remain a major clinical challenge in need of new multimodal treatments aimed at tissue repair and regeneration. Pharmaceutical rhPDGF stimulation of PDGFR{beta} signaling promotes healing of skin, bone, and soft tissue. PheWAS revealed fistulas as a novel indication for repurposing rhPDGF. This protocol aims to evaluate the technical performance, preliminary safety and efficacy, and feasibility of rhPDGF-enhanced collagen for healing and remission of complex perianal fistulas. Ethics and dissemination This trial was approved by the Vanderbilt University Medical Center institutional review board (IRB#240585). Results will be submitted for publication in a peer-reviewed journal.

Background Promoting at-home tests (e.g., for COVID-19) using chatbots may be a novel and scalable way to improve uptake across underserved populations. Objective The objective of this study was to assess the navigational patterns (i.e., sequence of interactions) of underserved populations when using a chatbot designed to provide education on COVID-19 testing and free order access for at-home COVID-19 test kits. Methods The study was a descriptive analysis of the original data of the chatbot intervention of the SCALE-UP II trial, which compared different digital health modalities (i.e., chatbots versus simple text messages) to deliver free at-home COVID-19 test kits to minority populations in Utah. SCALE-UP II (registration numbers NCT05533918; NCT05533359) was a multisite, pragmatic clinical trial with patients randomized in a 2x2x2 factorial design (smartphone study) to receive (1) chatbot or text messaging, (2) the option to request patient navigation, and (3) intervention frequency every 10 or 30 days. All other participants were randomized in a 2x2 factorial design (nonsmartphone study) to receive the option to request patient navigation and intervention frequency every 10 or 30 days. Eligible patients (1) had an appointment at one of the participating community health centers (CHC) in the last 3 years, (2) were 18 years and older, and (3) had a valid cellphone number recorded in the CHC electronic health record (EHR). The trial enrolled 2117 in the smartphone study and 31,439 in the nonsmartphone study. In the smartphone study, the proportion of participants who requested test kits in the Chatbot arm was lower than in SMS text messaging. In the nonsmartphone study, test kits was higher if they were messaged every 10 days. Sources of funding included the National Institute on Minority Health and Health Disparities (NIMHD) of the US National Institutes of Health (NIH) grant number 5U01MD017421 and by awards from the National Cancer Institute of the NIH (P30CA042014) and the Huntsman Cancer Foundation. Results: Of 1,051 patients randomized to the chatbot intervention, 309 (29%) launched the chatbot, 196 (63%) interacted with it, and 186 (60%) started the COVID-19 test kit ordering process. Among those who launched the chatbot, 170 (55%) completed a test kit order. One patient (0.3%) accessed the chatbot educational content. The median age was 51, with 66% female, 54% Latino/a, 55% uninsured, and 86% located in an urban area. Conclusion: Ordering of COVID-19 test kits among underserved patients who interacted with the chatbot was high. Thus, chatbots may represent a viable approach to reach underserved populations as a part of public health response in a pandemic. All patients except one placed orders without reviewing educational content. Chatbot design should identify and minimize the number of steps for patients to achieve a specific goal.

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

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

There is increasing interest in parent-child technoference: the interference with personal interactions caused by technology devices. This study examined the reliability and construct validity of the Technology Device Interference Scale (TDIS) to measure technoference in a sample of Canadian parents and children. Parents (n=883) and children (n=376) were recruited from clinical and community settings and completed the TDIS for their own and family member technoference over three timepoints (T1=2023, T2=2024, T3=2025). TDIS internal consistency, test-retest reliability, and construct validity were assessed using Cronbachs alpha, intraclass correlation coefficient, and confirmatory factor analysis, respectively. The TDIS showed good internal consistency and adequate to good construct validity when used by children to report on their own technoference (all >.70; CFI>.95, TLI>.95, RMSEA<.07) or their parents technoference (all >.70; CFI>.95, TLI>.90, RMSEA[&le;].11). The TDIS had low to acceptable internal consistency and poor model fit for parent report of their own technoference ( range: .63 - .66; CFI<.95, TLI[&le;].80, RMSEA[&ge;].14) or their childs technoference ( range: .56 - .63; CFI<.95, TLI[&le;].85, RMSEA[&ge;].11), factor loadings for the items "phone" and "tablet" were low (phone<.50, tablet<.50). Test-retest reliability was moderate for all reports. The TDIS demonstrated good reliability and construct validity of child-reported technoference. Parent-reported technoference demonstrated lower reliability and construct validity, with "phone" and "tablet" weakly associated with the other technological devices. Future studies should distinguish between handheld vs. non-handheld devices when investigating parent-reported technoference.

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

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

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

Background Gestational diabetes mellitus (GDM) affects 1-in-7 pregnancies globally and is associated with significant short- and long-term health consequences. Although health behaviour change interventions can effectively reduce these risks, a significant implementation gap exists in translating this evidence into routine practice. Bump2Baby and Me (B2B&Me) was a mobile health (mHealth) coaching intervention provided to women at-risk of GDM from early pregnancy through to 1-year postpartum. B2B&Me Plus (B2B&Me+) aims to refine, implement and evaluate the implementation of this personalised intervention across 4 countries (Ireland, Spain, Poland and Norway) with differing health systems and population profiles. Methods This study employs a hybrid type 3 implementation-effectiveness design using a non-randomised ABA block approach within a longitudinal cohort. Participants will be screened using the Monash machine learning GDM screening tool (MMLGDST). During the intervention (Block B), women at risk of developing GDM will be offered access to a smartphone-based coaching application featuring 1:1 synchronous sessions, asynchronous text and video messaging along with a Bluetooth-enabled weighing scale for self-monitoring. Support continues from early pregnancy through to nine months postpartum. The studys primary objective is to evaluate reach, adoption, implementation and maintenance of the B2B&Me+ intervention programme when delivered within routine maternity care. Implementation success will be assessed using the RE-AIM framework, while secondary outcomes will assess intervention effectiveness. The study will examine population-level uptake at each site, evaluate the benefits and costs of implementation across varying contexts, and analyse how four different referral methods, randomised at the site level, affect uptake. In addition, a European implementation toolkit will be developed to provide health services with scalable strategies to bridge the evidence-to-practice gap. Discussion This study will contribute to a growing literature on the implementation of a successfully trialled mHealth intervention in a real-world context. Understanding variation in both intervention and implementation success within a routine maternity care context across diverse settings will inform the development of an implementation toolkit to support health services in reducing the incidence of GDM and improving maternal and child health outcomes.