JMIR Formative Research最新文献

{"title":"Future Me, a Prospection-Based Chatbot to Promote Mental Well-Being in Youth: Two Exploratory User Experience Studies.","authors":"Martin Dechant, Eva Lash, Sarah Shokr, Ciarán O'Driscoll","doi":"10.2196/74411","DOIUrl":"https://doi.org/10.2196/74411","url":null,"abstract":"<p><strong>Background: </strong>Digital interventions have been proposed as a solution to meet the growing demand for mental health support. Large language models (LLMs) have emerged as a promising technology for creating more personalized and adaptive mental health chatbots. While LLMs generate responses based on statistical patterns in training data rather than through conscious reasoning, they can be designed to support important psychological processes. Prospection-the ability to envision and plan for future outcomes-represents a transdiagnostic process altered across various mental health conditions that could be effectively targeted through such interventions. We designed \"Future Me,\" an LLM-powered chatbot designed to facilitate future-oriented thinking and promote goal pursuit using evidence-based interventions including visualization, implementation intentions, and values clarification.</p><p><strong>Objective: </strong>This study aims to understand how users engage with Future Me, evaluate its effectiveness in supporting future-oriented thinking, and assess its acceptability across different populations, with particular attention to postgraduate students' stress management needs. We also seek to identify design improvements that could enhance the chatbot's ability to support users' mental well-being.</p><p><strong>Methods: </strong>In total, 2 complementary studies were conducted. Study 1 (n=20) examined how postgraduate students used Future Me during a single guided session, followed by semistructured interviews. Study 2 (n=14) investigated how postgraduate students interacted with Future Me over a 1-week period, with interviews before and after usage. Both studies analyzed conversation transcripts and interview data using thematic analysis to understand usage patterns, perceived benefits, and limitations.</p><p><strong>Results: </strong>Across both studies, participants primarily engaged with Future Me to discuss career or education goals, personal obstacles, and relationship concerns. Users valued Future Me's ability to provide clarity around goal-setting (85% of participants), its nonjudgmental nature, and its 24/7 accessibility (58%). Future Me effectively facilitated self-reflection (80%) and offered new perspectives (70%), particularly for broader future-oriented concerns. However, both studies revealed limitations in the chatbot's ability to provide personalized emotional support during high-stress situations, with participants noting that responses sometimes felt formulaic (50%) or lacked emotional depth. Postgraduate students specifically emphasized the need for greater context awareness during periods of academic stress (58%). Overall, 57% of requests occurred outside office hours, dropping from 40 on day 1 to 12 by day 7.</p><p><strong>Conclusions: </strong>Future Me demonstrates promise as an accessible tool for promoting prospection skills and supporting mental well-being through future-oriented thinking. However, effectiv","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e74411"},"PeriodicalIF":2.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote Patient Monitoring for Global Emergencies: Case Study in Patients With COVID-19.","authors":"Ramin Ramezani, Wenhao Zhang, Minh Cao, Alex Bui, Antonia Petruse, Amelia Weldon, Arash Naeim","doi":"10.2196/66773","DOIUrl":"https://doi.org/10.2196/66773","url":null,"abstract":"<p><strong>Background: </strong>The COVID-19 pandemic has highlighted the critical need for telehealth and remote patient monitoring in health care delivery. Despite the growing use of on-body wearable sensors for continuous monitoring and predicting adverse events, their widespread adoption remains a significant challenge. While the pandemic has accelerated the acceptance of these technologies, achieving widespread integration requires their sustained incorporation into routine health care practices beyond emergencies. In this study, we extend the application of our previously developed remote patient monitoring system to patients with COVID-19.</p><p><strong>Objective: </strong>Our objective is to assess whether the metrics obtained from our previously developed system can provide additional insights into the recovery trajectory of individuals affected by COVID-19. This case study aims to demonstrate that remote patient monitoring systems can be adapted to diverse patient cohorts during emergencies. We aim to illustrate the ease of deployment, particularly when these systems are already integrated into the existing health care ecosystem.</p><p><strong>Methods: </strong>From November 2020 to July 2021, a total of 73 patients were recruited through the University of California, Los Angeles, Center for Smart Health, after having consented to participate in this study for 2 weeks. The research concentrated on an exploratory analysis, focusing on the detailed examination of characteristics and behaviors of patients with COVID-19 as captured by the remote patient monitoring system. We collected day-to-day changes in the following sensor measurements: daily activity, daily energy expenditure, indoor localization, SpO2, respiratory rate, heart rate, and temperature.</p><p><strong>Results: </strong>Out of the 73 patients satisfying the inclusion criteria, 41 successfully adhered to using the monitoring technology, with only 22 providing substantial watch data (>4 h). Among the participants, 39 used the pulse oximeter, 37 used the thermometer, and 36 used respiratory monitoring at night. This study demonstrated an overall increase in patients' activity levels toward the end of this study, with many beginning to leave their homes after 2 weeks. Additionally, respiratory rates shifted toward healthier lower levels, and oxygen saturation improved. Fatigue and headache were identified as the most prevalent symptoms, followed by cough and loss of smell.</p><p><strong>Conclusions: </strong>The conclusion highlights the critical importance of monitoring patients outside of hospital settings, especially during pandemics, when patients travel to hospitals or receive home visits by health care professionals, which could increase the risk of disease transmission. Studies demonstrating the benefits and efficacy of remote monitoring in home settings can better prepare health care professionals for future pandemic events. Continuous monitoring of a wide range of patie","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e66773"},"PeriodicalIF":2.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing the Ethical, Legal, and Social Issues of Healthtech in Education: Insights From Japan.","authors":"Motofumi Sumiya, Tomoko Nishimura, Kyoko Aizaki, Ikue Hirata, Nobuaki Tsukui, Yuko Osuka, Manabu Wakuta, Atsushi Senju","doi":"10.2196/72781","DOIUrl":"https://doi.org/10.2196/72781","url":null,"abstract":"<p><p>The increasing application of health technology (healthtech) in educational settings, particularly for monitoring students' mental health, has garnered significant attention. These technologies, which range from wearable devices to digital mental health screenings, offer new opportunities for enhancing student well-being and strengthening support systems. Numerous studies have explored the ethical, legal, and social issues (ELSIs) of healthtech in the field of psychiatry, highlighting its potential benefits while also acknowledging the inherent complexities and risks that demand careful consideration. However, the ELSIs related to the use of healthtech in educational settings remain largely overlooked and insufficiently addressed. This study provides an overview of items that should be considered by researchers, teachers, and education boards or committees to promote healthtech in the educational context. By adapting existing ELSI frameworks from educational technology and digital health, this study systematically reviews ethical concerns surrounding healthtech in schools. Expert consultations were conducted through a project consisting of members with expertise related to healthtech, including developers, a teacher, a school counselor, and university researchers, leading to the identification of 52 ELSI concerns categorized into 8 domains: consent, rights and privacy, algorithms, information management, evaluation, use, role of public institutions, and relationships with private companies. Using Japan as a case study, we examine regulatory and cultural factors affecting healthtech adoption in schools. The findings reveal critical challenges, such as ensuring informed consent for minors, protecting student privacy, preventing biased algorithmic decision-making, and maintaining transparency in data management. In addition, institutional factors, including the role of public education policies and private-sector involvement, shape the ethical landscape of healthtech implementation. This study highlights the need for multistakeholder collaboration to establish guidelines that balance innovation with ethical responsibility. The study underscores the need for a multifaceted approach to mitigate risks such as data misuse, inequitable access, and algorithmic bias, ensuring the ethical and effective use of healthtech in education. The fundamental ELSI framework for healthtech, including privacy, consent, and algorithms, can be applied to educational systems worldwide, while aspects related to public education policies should be considered in accordance with the specific context of each country and culture. Incorporating healthtech into the educational system helps address the barriers associated with traditional approaches, including limited resources, cost constraints, and logistical challenges. Researchers from universities and healthtech companies, along with educators and other stakeholders, should ensure that healthtech projects consider diver","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e72781"},"PeriodicalIF":2.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144663846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breath-Focused Mindfulness and Compassion Training in Parent-Child Dyads: Pilot Intervention Study.","authors":"Satish Jaiswal, Jason Nan, Seth Dizon, Jessica O Young, Suzanna R Purpura, James K Manchanda, Dhakshin Ramanathan, Dennis J Kuo, Jyoti Mishra","doi":"10.2196/69607","DOIUrl":"https://doi.org/10.2196/69607","url":null,"abstract":"<p><strong>Background: </strong>Depression in children is a concerning societal issue and can be associated with poor academic performance, school dropout, and poor overall quality of life. Additionally, child depression is often associated with parallel stress and depression in parents.</p><p><strong>Objective: </strong>This scenario highlights the urgent need for the development and implementation of accessible and scalable solutions that may cobenefit child and parent mental well-being.</p><p><strong>Methods: </strong>This pilot study introduced \"Cooperative Compassion\" (CoCo), a parent-child cotraining digital application aimed at promoting mindfulness and compassion through brief, performance-adaptive sessions. A community sample of 24 parent-child dyads (children's mean age 9.5, SD 3.27 years; female: n=14, male: n=10; Asian: n=5, White: n=11, mixed race: n=7, other race: n=1; and parents' mean age 44.5, SD 6.5 years; 20 female: n=20, male: n=4; Asian: n=8, White: n=14, mixed race: n=2) of high average affluence socioeconomic scores participated in the study. These parent-child dyads completed 30 sessions of CoCo training over 3 months with baseline and postintervention assessments occurring within 2 weeks of training initiation or completion, respectively.</p><p><strong>Unlabelled: </strong>The program was feasible, with 80% (n=19) of families completing over 90% (n=22) of sessions and providing positive feedback. Mental health assessments showed a nonsignificant effect in the expected direction in children's depression scores (Cohen d=-0.19; 95% CI -8.89 to 1.74; P=.07) and significant reductions in parental stress (d=-0.41; 95% CI -2.63 to -0.16; P=.02), anxiety (d=-0.47; 95% CI -2.67 to -0.20; P=.02), and depression (d=-0.50; 95% CI -3.25 to -0.08; P=.03), with sustained benefits at the 3-month follow-up. Parental mindfulness improvements were correlated with stress reduction (ρ=-0.45; P=.03). On an emotion bias task used as an objective assessment of cognition, children demonstrated improved processing speed after the intervention (d=0.54; 95% CI 0.012-0.083; P=.005), and a marginal improvement was also observed in parents (d=0.19; 95% CI -0.004 to 0.030; P=.05). Cortical source imaging of electroencephalographic recordings was acquired simultaneous to an attention-to-breathing assessment that showed significant reduction in task-related default mode network activity (d=-0.62; 95% CI -0.0096 to -0.0002; P=.01).</p><p><strong>Conclusions: </strong>Post-CoCo intervention decrease in default mode network activity on the attention-to-breath task in parent-child dyads may be indicative of cortical plasticity reflecting reduced mind-wandering and thereby, enhanced focus after training. The current promising behavioral and cognitive results suggest the need for a larger sample size and a randomized controlled study design. Overall, these findings highlight the potential for brief, digital mindfulness and compassion cotraining to improve famil","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e69607"},"PeriodicalIF":2.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting Conversation Topics in Recruitment Calls of African American Participants to the All of Us Research Program Using Machine Learning: Model Development and Validation Study.","authors":"Priscilla Pemu, Michael Prude, Atuarra McCaslin, Elizabeth Ojemakinde, Christopher Awad, Kelechi Igwe, Anny Rodriguez, Jasmine Foriest, Muhammed Idris","doi":"10.2196/65320","DOIUrl":"https://doi.org/10.2196/65320","url":null,"abstract":"<p><strong>Background: </strong>Advancements in science and technology can exacerbate health disparities, particularly when there is a lack of diversity in clinical research, which limits the benefits of innovations for underrepresented communities. Programs like the All of Us Research Program (AoURP) are actively working to address this issue by ensuring that underrepresented populations are represented in biomedical research, promoting equitable participation, and advancing health outcomes for all. African American communities have been particularly underrepresented in clinical research, often due to historical instances of research misconduct, such as the Tuskegee Syphilis Study, which have deeply impacted trust and willingness to participate in research studies. With the US population becoming increasingly diverse, it is crucial that clinical research studies reflect this diversity to improve health outcomes. However, limited data and small sample sizes in qualitative studies on the inclusion of underrepresented groups hinder progress in this area.</p><p><strong>Objective: </strong>The goal of this paper is to analyze recruitment conversations between research assistants (RAs) and potential participants in the AoURP to identify key topics that influence enrollment. By examining these interactions, we aim to provide insights that can improve engagement strategies and recruitment practices for underrepresented groups in biomedical research.</p><p><strong>Methods: </strong>Our study design was an observational, retrospective approach using machine learning for content analysis. Specifically, we used structural topic modeling to identify and compare latent topics of conversation in recruitment calls by Morehouse School of Medicine RAs between February 2021 and April 2022 by estimating expected topic proportions in the corpus as a function of enrollment and participation in AoURP.</p><p><strong>Results: </strong>In total, our model estimated 45 topics of which 12 coherent topics were identified. Notable topics, that were more likely to occur in conversations between RAs and participants that enrolled and participated, include closing or following up to schedule an appointment, COVID-19 protocols for in-person visits, explaining precision medicine and the need for representation, and working through objections, including concerns about costs, insurance, care changes, and health fears. Topics among potential participants who did not enroll include technical challenges and describing physical measurement visits (eg, collection of basic physical data, such as height, weight, and blood pressure).</p><p><strong>Conclusions: </strong>Using an approach that leverages machine learning to identify topical structure and themes with limited human subjectivity is a promising strategy to identify gaps in, and opportunities to improve, the recruitment of underserved communities into clinical trials.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e65320"},"PeriodicalIF":2.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of a Retinal Imaging Camera With On-Device Intelligence for Primary Care: Retrospective Study.","authors":"Matthew Silvestrini, Clarissa Lui, Anil Patwardhan, Ying Chen, Tayyeba Ali, Elie Glik, Honglei Wu, Brian Levinstein, Adrianna Wenz, Nathan Shemonski, Lin Yang, Ian Atkinson, Sam Kavusi","doi":"10.2196/70331","DOIUrl":"https://doi.org/10.2196/70331","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Access to screening continues to be a barrier for the early detection of diabetic retinopathy (DR). Primary care-based diabetic retinopathy screening could improve access, but operational challenges, such as cost and workflow management, hamper the widespread adoption of retinal camera systems in primary care clinics in the United States.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to develop and evaluate a retinal screening system suitable for integration into a primary care workflow.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We developed a nonmydriatic, 45° field imaging retinal camera system, the Verily Numetric Retinal Camera (VNRC; Verily Life Sciences LLC), able to generate high-fidelity retinal images enabled by on-device intelligent features. The VNRC output flows into cloud-based software that accepts and routes digitized images for grading. We evaluated the performance and usability of the VNRC in 2 studies. A retrospective performance study compared the performance of VNRC against a reference camera (Crystalvue NFC-700 [Crystalvue Medical]) as well as the correlation between VNRC capture status and gradability (as determined by ophthalmologist graders). The usability study simulated a primary care setting for a combined cohort of trained and untrained users (corresponding to patients in the simulation) and operators (corresponding to health care personnel in the simulation), where respondents completed a questionnaire about their user experience after attempting to capture images with the VNRC.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In the comparative performance study (N=108, K=206 images), a total of 98.5% (203/206) of images captured by the VNRC were graded as sufficient for clinical interpretation compared to 97.1% (200/206) of Crystalvue NFC-700 images (difference in proportion was 0.015, 95% CI -0.007 to 0.033). In the quality control algorithm evaluation (N=172, K=343 images), we found a positive association (φ=0.58, 95% CI 0.45-0.69) between gradability status (gradable or nongradable) as determined by ophthalmologists and the capture status (recapture not-needed or needed) as determined by the VNRC quality control algorithm. In the usability study (n=15 users and n=30 operators), all participating users (15/15) indicated that they were able to have both eyes screened easily. Most users and operators indicated agreement (from somewhat agree to strongly agree) with statements describing the imaging process as intuitive (15/15, 100% and 29/30, 97%), comfortable (15/15, 100% and 30/30, 100%), and allowing for a positive experience (15/15, 100% and 30/30, 100%), of users and operators, respectively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our findings about the performance and usability of this retinal camera system support its deployment as an integrated end-to-end retinal service for primary care. These results warrant additional studies to fully characterize real-world usability across a wider and diverse set o","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e70331"},"PeriodicalIF":2.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-Disclosure and Social Support in a Web-Based Opioid Recovery Community: Machine Learning Analysis.","authors":"Yu Chi, Huai-Yu Chen, Khushboo Thaker","doi":"10.2196/71207","DOIUrl":"https://doi.org/10.2196/71207","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The opioid crisis remains a critical public health challenge, with opioid use disorder (OUD) imposing significant societal and health care burdens. Web-based communities, such as the Reddit community r/OpiatesRecovery, provide an anonymous and accessible platform for individuals in recovery. Despite the increasing use of Reddit for substance use research, limited studies have explored the content and interactions of self-disclosure and social support within these communities.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to address the following research questions: (1) What content do users disclose in the community?; (2) What types of social support do users receive?; and (3) How does the content disclosed relate to the type and extent of social support received?&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We analyzed 32,810 posts and 324,224 comments from r/OpiatesRecovery spanning 8 years (2014-2022) using a mixed method approach. Posts were coded for recovery stages, self-disclosure, and goals, while comments were categorized into informational and emotional support types. A machine learning-based classifier was used to scale the analysis. Regression analyses were conducted to examine the relationship between post content and received support.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The majority of posts were made by individuals using opioids (7225/32,810, 22.0%) or in initial recovery stages (less than 1 mo of abstinence; 27.7%). However, posts by individuals in stable recovery (abstinence for more than 5 years) accounted for only 1.8%. Informational self-disclosure appeared in 88.3% (n=28,977) of posts, while emotional self-disclosure was present in 75.6% (n=24,816). Posts seeking informational support (19,153/32,810, 58.4%) were far more common than those seeking emotional support (779/32,810, 2.4%). On average, each post received 9.88 (SD 11.36) comments. The most frequent types of support were fact and situational appraisal (mean 5.62, SD 6.82) and personal experience (mean 4.88, SD 5.98), while referral was the least common (mean 0.61, SD 0.50). Regression analyses revealed significant relationships between self-disclosure and received support. Posts containing informational self-disclosure were more likely to receive advice (β=0.17, P&lt;.001), facts (β=0.30, P&lt;.001), and opinions (β=0.11, P&lt;.001). Emotional self-disclosure predicted higher levels of emotional support (β=0.17, P&lt;.001) and personal experiences (β=0.07, P&lt;.001). Posts from individuals in the addiction stage received more advice (β=-0.06, P&lt;.001) but less emotional support (β=-0.05, P&lt;.001) compared with posts from individuals in later recovery stages.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study highlights the role of self-disclosure in fostering social support within web-based OUD recovery communities. Findings suggest a need for increasing engagement from individuals in stable recovery stages and improving the diversity and quality of social support. By ","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e71207"},"PeriodicalIF":2.0,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144659288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Usability and Usefulness of SMS-Based Artificial Intelligence Intervention (Mwana) on Breastfeeding Outcomes in Lagos, Nigeria: Pilot App Development Study.","authors":"Anisha Musti","doi":"10.2196/65157","DOIUrl":"10.2196/65157","url":null,"abstract":"<p><strong>Background: </strong>Nigeria has one of the highest child mortality rates globally, with 111 deaths per 1000 live births. Exclusive breastfeeding (EBF) improves infant survival by providing essential nutrients and antibodies that protect against infections and diseases. Despite its benefits, EBF rates in Nigeria remain low at 29%, largely due to limited health care support and breastfeeding guidance. With the proliferation of mobile phones in Nigeria, mobile health (mHealth) interventions are being explored as scalable solutions. SMS text messaging interventions have demonstrated success in delivering behavioral interventions; yet, few use artificial intelligence (AI) for personalized breastfeeding support.</p><p><strong>Objective: </strong>This study evaluates the effectiveness of Mwana, an AI-powered SMS-based app, in improving breastfeeding outcomes for postpartum mothers in Lagos, Nigeria.</p><p><strong>Methods: </strong>Mwana was developed using TextIt for SMS integration and Meta's Wit.ai for natural language processing (NLP). The chatbot provides breastfeeding support via SMS, offering personalized tips, addressing common challenges, and connecting users to human agents when necessary. The intervention was piloted with 216 postpartum mothers recruited through local health care networks, focusing on usability, usefulness, and engagement. The study used a mixed methods approach, using structured surveys and observation to assess participant experiences at multiple intervals over a 6-month period. Primary outcomes measured were app usability, usefulness, and breastfeeding adherence.</p><p><strong>Results: </strong>The intervention was well-received, with high scores for both usefulness (mean 4.01, SD 1.41) and usability (mean 3.92, SD 1.35) on a 5-point scale. The majority of respondents, 57% (118/206), rated the chatbot's usefulness at the highest score of 5. Qualitative feedback statements identified areas for improvement, including enhancing AI comprehension, response times, and human-like interaction.</p><p><strong>Conclusions: </strong>The study highlights the potential of Mwana to improve breastfeeding outcomes in resource-limited settings, contributing to the growing body of evidence supporting mHealth interventions in maternal and child health. By leveraging personalized messaging, SMS-based delivery, and language localization, Mwana offers a scalable, accessible solution. However, challenges remain regarding AI comprehension, and further research is necessary to evaluate Mwana's effectiveness among populations not actively engaged with health care services. Future iterations will expand AI training datasets, refine NLP capabilities, and scale to broader populations.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e65157"},"PeriodicalIF":2.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acceptability of Guided Symptom Entry and Asynchronous Clinical Communication Software Among Primary Care Staff: Qualitative Study.","authors":"Riina Raudne, Taavi Tillmann","doi":"10.2196/59620","DOIUrl":"https://doi.org/10.2196/59620","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Patients often communicate with primary care centers remotely (eg, by telephone or email) before seeking in-person care. A comparatively novel addition might be patient-facing symptom entry websites, where subsequent questions are automatically guided by previous responses. However, the acceptability of such systems to health care staff remains unclear, particularly in terms of what features staff perceive as useful.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to investigate a patient-facing algorithm-guided symptom-entry software (developed by Certific OÜ, Estonia), which also supports subsequent asynchronous communication, for its acceptability and perceived utility to primary health care providers.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In-depth and open-ended interviews were conducted in 8 primary care centers in Estonia, including 8 nurses and 6 doctors, 3-6 months after the implementation of a novel patient-facing website. Transcripts were coded inductively, using grounded theory and phenomenological approaches to uncover themes most salient to providers. Two family doctors provided feedback on the final analysis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Staff perceived unstructured communication (via email and phone calls) as a burden that increased their cognitive load. Sometimes, this arises out of the perceived mismatch between needing to identify and document critical symptom information and being unable to standardize the supply of such information, due to a heterogeneous and unpredictable communication processes whose duration, quality, and risk of miscommunication are hard to predict and control. All interviewees expressed the desire that more patients initiate their remote query via the algorithm-guided symptom-entry software. The software was reported to satisfy perceived feature needs for patient verification, privacy and data security, editable plain-language symptom summaries of symptoms, and integration with prewritten response templates (particularly for staff who were nonnative speakers). Safety of the new software was perceived as high, on account of integration alongside traditional telephone requests. Staff reported the challenge that great effort was needed to persuade patients to use the website. Among perceived challenges, some providers reported difficulty in onboarding patients, digital literacy gaps, and limited time savings. While previous research has criticized poorly designed multiple-choice systems, our findings suggest that an appropriately designed and personalized multiple-choice system can be preferable to health care staff, as they may lower cognitive demands and enhance well-being.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Interviewed primary health care staff felt that this symptom entry software was acceptable and desirable. They valued a perceived reduction in cognitive demands. This holds promise for increasing staff well-being and increasing efficiency, which needs to be quantified i","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e59620"},"PeriodicalIF":2.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144649502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reducing Methamphetamine Use in Aboriginal and Torres Strait Islander Communities With the \"We Can Do This\" Web App: Qualitative Evaluation of Acceptability and Feasibility.","authors":"Leda Sivak, Rachel Reilly, Shani Crumpen, Carla Treloar, Rebecca McKetin, Julia Butt, Yvette Roe, Nadine Ezard, Brendan Quinn, Jack Nagle, Wade Longbottom, Clifford Warrior, James Ward","doi":"10.2196/58369","DOIUrl":"10.2196/58369","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Preventing and treating methamphetamine-related harm in Aboriginal and Torres Strait Islander populations is a significant challenge for health care services. Digital health care may offer opportunities to support individuals and families in ways that complement existing methamphetamine treatment options. This study responds to a community-identified priority as Aboriginal Community Controlled Health Services identified methamphetamine use as a key concern and sought support to respond to the needs of people who use methamphetamine and their families.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This paper reports on a process evaluation of the web application's acceptability and feasibility when used by clients and clinicians in residential rehabilitation services and primary care. This study is part of a larger project entitled \"Novel Interventions to address Methamphetamine use in Aboriginal and Torres Strait Islander Communities\" (NIMAC), which seeks to develop culturally appropriate and strengths-based prevention and treatment interventions to reduce methamphetamine related harm. \"We Can Do This\" was a web application developed for Aboriginal and Torres Strait Islander people who are seeking to reduce or stop methamphetamine use.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Clinicians and clients who had used the web application were recruited through Aboriginal Community Controlled Health Services and Aboriginal residential rehabilitation services in urban and regional Victoria and South Australia. Unidentified usage data was collected from all participants. After using the web application, those who indicated a willingness to be interviewed were contacted and interviewed by phone or in person and asked about the feasibility and acceptability of the web application. The framework method of analysis was used to structure and summarise the resulting qualitative data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Interviews with 24 clients and 11 clinicians explored the acceptability and feasibility of the web application. Acceptability incorporated the following domains: affective attitude, burden, ethicality, cultural appropriateness, coherence, opportunity cost, perceived effectiveness, and self-efficacy. The evaluation of feasibility assessed barriers and facilitators to the implementation of the program, with a focus on demand, practicality, fidelity, and integration. Results indicated that both clients and clinicians found the web application content coherent, relatable, empowering, and culturally safe. Barriers to using the web application for clients included a lack of internet connectivity and personal issues such as scheduling.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Process evaluation is often under-valued. However, as \"We Can Do This\" was new, innovative and targeted a hard-to-reach population, understanding its feasibility and acceptability as a clinical tool was essential to understanding its potential. \"We Can Do This\" is unique as the on","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e58369"},"PeriodicalIF":2.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144642615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}