JMIR Formative Research最新文献

{"title":"Patient-Health Care Professional Communication via a Secure Web-Based Portal in Severe Mental Health Conditions: Qualitative Analysis of Secure Messages.","authors":"Eva Meier-Diedrich, Carolyn Turvey, Jonas Maximilian Wördemann, Justin Speck, Mareike Weibezahl, Julian Schwarz","doi":"10.2196/63713","DOIUrl":"10.2196/63713","url":null,"abstract":"<p><strong>Background: </strong>Patients' web-based access to their medical records and secure messaging (SM) via patient portals is becoming increasingly prevalent worldwide. SM offers several potential benefits, including improved health outcomes and increased patient engagement. However, SM also raises concerns about effects on the therapeutic relationship and may be constrained by factors such as limited digital literacy and access to digital devices. Evidence on the use of SM in mental health is limited, and results are inconclusive.</p><p><strong>Objective: </strong>This study aimed to examine (1) the purposes for which health care professionals (HCPs) and patients with psychiatric disorders use SM to communicate and (2) the specific use patterns associated with both patients and HCPs.</p><p><strong>Methods: </strong>The secure messages (n=274) of 38 patients with psychiatric disorders and 4 HCPs (psychiatrists) from 3 psychiatric outpatient clinics in Brandenburg, Germany, was analyzed using thematic analysis. The data selected for this study represent a subsample from a larger study comprising a total of 116 patients. The subsample consists of the patients and HCPs who used SM.</p><p><strong>Results: </strong>A total of 274 messages were analyzed: 22.3% (61/274) were initial notes from HCPs, 44.5% (122/274) were patient responses, and 33.2% (91/274) were HCP replies. Patients sent between 1 and 15 messages (mean 4.16, SD 3.42) and logged in 1 to 42 times (mean 10.78, SD 9.38). Most messages were sent during the day, although some were also sent at night and in the early morning. Regarding the purposes of SM, 4 core functions of SM were identified: reporting and feedback, interpersonal uses, intrapersonal uses, and organizational uses. Both patients and HCPs used SM to share treatment-relevant information and elicited feedback on treatment and medication. Furthermore, secure messages included expressions of gratitude by the patients, in addition to well-wishes and emotional support from the HCPs. SM allowed patients to reflect on their treatment and provide self-encouragement. Finally, secure messages were used to address organizational aspects such as scheduling, appointments, and administrative tasks.</p><p><strong>Conclusions: </strong>SM in outpatient mental health care is multifaceted and holds the potential to enhance therapeutic contact and improve access to care by enabling quick, low-threshold communication between patients and HCPs, allowing treatment-related concerns to be addressed promptly and effectively. However, the asynchronous nature of SM also poses new challenges, particularly in managing acute mental health crises and in setting boundaries to prevent HCPs from being perceived as constantly available. Therefore, specific training for HCPs-both during medical education and in clinical practice-is essential, along with clear guidelines on handling crises and managing sensitive information.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e63713"},"PeriodicalIF":2.0,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12254702/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144511982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Public Perception of the Brain-Computer Interface Based on a Decade of Data on X: Mixed Methods Study.","authors":"Mohammed A Almanna, Lior M Elkaim, Mohammed A Alvi, Jordan J Levett, Ben Li, Muhammad Mamdani, Mohammed Al-Omran, Naif M Alotaibi","doi":"10.2196/60859","DOIUrl":"10.2196/60859","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Given the recent evolution and achievements in brain-computer interface (BCI) technologies, understanding public perception and sentiments toward such novel technologies is important for guiding their communication strategies in marketing and education.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to explore the public perception of BCI technology by examining posts on X (formerly known as Twitter) using natural language processing (NLP) methods.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A mixed methods study was conducted on BCI-related posts from January 2010 to December 2021. The dataset included 65,340 posts from 38,962 unique users. This dataset was subject to a detailed NLP analysis including VADER, TextBlob, and NRCLex libraries, focusing on quantifying the sentiment (positive, neutral, and negative), the degree of subjectivity, and the range of emotions expressed in the posts. The temporal dynamics of sentiments were examined using the Mann-Kendall trend test to identify significant trends or shifts in public interest over time, based on monthly incidence. We used the Sentiment.ai tool to infer users' demographics by matching predefined attributes in users' profile biographies to certain demographic groups. We used the BERTopic tool for semantic understanding of discussions related to BCI.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The analysis showed a significant rise in BCI discussions in 2017, coinciding with Elon Musk's announcement of Neuralink. Sentiment analysis revealed that 59.38% (38,804/65,340) of posts were neutral, 32.75% (21,404/65,340) were positive, and 7.85% (5132/65,340) were negative. The average polarity score demonstrated a generally positive trend over the course of the study (Mann-Kendall Statistic=0.266; τ=0.266; P&lt;.001). Most posts were objective (50,847/65,340, 77.81%), with a smaller proportion being subjective (14,393/65,340, 22.02%). Biographic analysis showed that the \"broadcasting\" group contributed the most to BCI discussions (17,803/58,030, 30.67%), while the \"scientific\" group, contributing 27.58% (n=16,005), had the highest overall engagement metrics. The emotional analysis identified anticipation (score = 10,802/52,618, 20.52%), trust (score=9244/52,618, 17.56%), and fear (score=7344/52,618, 13.95%) as the most prominent emotions in BCI discussions. Key topics included Neuralink and Elon Musk, practical applications of BCIs, and the potential for gamification.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This NLP-assisted study provides a decade-long analysis of public perception of BCI technology based on data from X. Overall, sentiments were neutral yet cautiously apprehensive, with anticipation, trust, and fear as the dominant emotions. The presence of fear underscores the need to address ethical concerns, particularly around data privacy, safety, and transparency. Transparent communication and ethical considerations are essential for building public trust and reducing apprehension. Influenti","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e60859"},"PeriodicalIF":2.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12242710/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144496736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of a Novel Electronic Medical Record-Integrated Electronic Form (Provider Asthma Assessment Form) and Severe Asthma Algorithm in Primary Care: Single-Center, Pre- and Postobservational Study.","authors":"Matheson L McFarlane, Alison Morra, Delanya Podgers, David Barber, M Diane Lougheed","doi":"10.2196/74043","DOIUrl":"10.2196/74043","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Despite national asthma care guidelines, care gaps persist between best-practice and clinical practice, contributing to poor health outcomes. The Provider Asthma Assessment Form (PAAF) is an electronic asthma management and Knowledge Translation tool with an embedded decision support algorithm for severe and/or uncontrolled asthma, designed to support evidence-based asthma management.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;In this study, we aimed to document baseline asthma practice patterns and determine whether the broader intervention of PAAF integration into a primary care electronic medical record (EMR) improves evidence-based asthma diagnosis and management.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We performed a single-center pre- and postobservational study at an academic Family Health Team in Kingston, Ontario, Canada. Retrospective baseline data were collected for 2 years prior to PAAF implementation from January 2018 to December 2019. Prospective postintervention data were collected from October 2022 to July 2024. A validated adult asthma EMR case definition was applied to EMR data to identify suspected or objectively confirmed asthma cases for both datasets, on which detailed manual chart abstractions were performed. A data extraction was performed for completed PAAFs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;There were 230 patients in the retrospective baseline and 143 patients in the postimplementation cohort. Overall, 31.3% (n=72) of patients at baseline versus 23.8% (n=34) at postimplementation had confirmed asthma. There were significantly more pulmonary function tests requested after the implementation of the PAAF (postimplementation: n=70, 49%; baseline: n=71, 30.9%; P&lt;.001). A significantly higher percent of postimplementation patients were on single inhaler controller and reliever therapy (postimplementation: n=31, 21.7%; baseline: n=2, 0.9%; P&lt;.001), inhaled corticosteroid/long-acting β-2 agonist therapy (postimplementation: n=36, 25.2%; baseline: n=34, 14.8%; P=.01), and inhaled corticosteroid if their asthma was uncontrolled (postimplementation: n=69, 62.2%; baseline: n=100, 43.5%; P=.002). Barriers were significantly more commonly addressed after implementation (postimplementation: n=24, 16.8%; baseline: n=11, 4.8%; P&lt;.001). A significantly higher average number of asthma control parameters was documented when the PAAF was used (PAAF: mean 5.4, SD 1.9; manual chart abstraction: mean 2.3, SD 1.2; P&lt;.001). Care as assessed by key Primary Care-Asthma Performance Indicators showed improvement in the postimplementation cohort, which did not reach statistical significance.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The multifaceted intervention of implementing the PAAF in this primary care practice was associated with improved documentation of diagnosis status and asthma control parameters and improved adherence with evidence-based recommendations for care, such as the use of pulmonary function tests and addressing barriers t","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e74043"},"PeriodicalIF":2.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12242708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144496735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research Dissemination Strategies in Pediatric Emergency Care Using a Professional Twitter (X) Account: A Mixed Methods Developmental Study of a Logic Model Framework.","authors":"Gwendolyn C Hooley, Julia N Magana, Jason M Woods, Shyam Sivasankar, Lauren VonHoltz, Anita R Schmidt, Todd P Chang, Michelle Lin","doi":"10.2196/59481","DOIUrl":"10.2196/59481","url":null,"abstract":"<p><strong>Background: </strong>Research dissemination is a vital step in bridging the gap between the publication of cutting-edge research and its adoption into clinical practice. Social media platforms like Twitter (rebranded as X) offer promising channels for dissemination, yet research organizations lack clear guidance on establishing a professional social media presence. We present a structured framework based on our research network's multiyear experience developing a Twitter account for research dissemination.</p><p><strong>Objective: </strong>This study aimed to provide a roadmap for organizations aiming to create a professional Twitter account for research dissemination.</p><p><strong>Methods: </strong>This was a mixed methods study analyzing the Pediatric Emergency Care Applied Research Network (PECARN) Twitter team's 4-year experience (2020-2023) with building a social media account. Using the nominal group technique qualitative approach, we recorded insights from the 6 team members' experiences in a round-robin fashion until response saturation. In addition, we analyzed internal Slack (Slack Technologies) communications to identify key developmental events. Together, these were then prioritized by consensus to elucidate key developmental events that enhanced both social media and scientific engagement. This process was informed by quantitative data from Twitter performance metrics and Altmetric Attention Scores for journal publications collected over a 39-month period. Together, these elements informed the design of a logic model framework.</p><p><strong>Results: </strong>The nominal group technique generated 63 thematic statements which included issues such as organizational structure, content strategy, technologies, analytics, organizational priorities, and challenges. These statements coalesced into the 7 domains (priorities, assumptions, inputs, outputs, outcomes, and external factors) that comprise the logic model. Inputs included organizational support (eg, executive-level champion and funding), specialized personnel (eg, content writer and analytics manager), and operational technologies (eg, communications and data analytics tools). Outputs encompassed targeted activities, such as engaging with other Twitter accounts, publishing high-quality tweets highlighting scholarly work, and developing a dynamic operations manual for the Twitter team. Outcomes were measured through tweet metrics, account analytics, and article-level impact scores.</p><p><strong>Conclusions: </strong>Our logic model roadmap, based on our practical multiyear experience and data-driven strategies, can serve as a guide for research organizations or medical institutions aiming to incorporate Twitter or other social media platforms for research dissemination.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e59481"},"PeriodicalIF":2.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12238784/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Video- Versus Text-Based Psychoeducation in Web-Based E-Mental Health Programs: Randomized Controlled Trial.","authors":"Swantje Borsutzky, Josefine Gehlenborg, Lara Rolvien, Steffen Moritz","doi":"10.2196/65478","DOIUrl":"10.2196/65478","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Mental health disorders affect 1 in 8 people worldwide, yet many face barriers to accessing care. E-mental health interventions, including self-guided internet-based programs, offer promising solutions. However, the mechanisms driving knowledge gain in such programs remain poorly understood. The role of medium, topic, sequence, and confidence and their interaction in learning outcomes need further investigation. Additionally, the influence of knowledge gaps on the outcome of psychoeducational intervention is not well understood (eg, whether psychoeducation requires an existing knowledge gap to be effective).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This randomized controlled trial investigated the role of medium, topic, sequence, and participants' initial knowledge levels on knowledge gain and confidence in fully automated self-guided e-mental health psychoeducation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A total of 158 adults (mean age 34, SD 12.4 years; n=118, 74.7% female) were randomized to 8 experimental conditions (receiving video, texts, or both containing psychoeducational content on sleep or social competence; n=142) or a control group (neutral video; n=16). The fully automated interventions (videos) were developed for use in web-based e-mental health interventions. They address transdiagnostic symptoms and hence are relevant across various disorders. To assess the added value of video production for knowledge gain, text-based scripts corresponding to the video content were created and compared. All interventions and outcome assessments were delivered on the web via Qualtrics without face-to-face components. Pre- and postintervention knowledge was assessed using a validated 30-item knowledge test (true/false). Confidence in responses was rated on a 0% to 100% scale. Statistical analyses included 3-way ANOVA and multivariate ANOVA.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Knowledge significantly increased across experimental groups (F&lt;sub&gt;1,156&lt;/sub&gt;=17.272; P&lt;.001; η&lt;sub&gt;p&lt;/sub&gt;&lt;sup&gt;2&lt;/sup&gt;=0.10). Participants with social competence deficits had significantly lower baseline knowledge (P=.04; d=0.41). For sleep deficits, a nonsignificant trend emerged (P=.09; d=0.28). Participants with social competence deficits demonstrated greater knowledge improvement (t&lt;sub&gt;141&lt;/sub&gt;=7.12; P&lt;.001; d=0.60). Participants with sleep deficits showed smaller but significant gains (t&lt;sub&gt;141&lt;/sub&gt;=2.43; P=.02; d=0.20). No significant differences in knowledge gain were found between video and text formats. Confidence in correct answers increased significantly in the experimental group (mean 42.82, 95% CI 41.15-44.50 to mean 51.67, 95% CI 49.28-54.04), with larger gains for social competence than sleep. Confidence in the control group remained unchanged.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Both video and text formats effectively facilitated knowledge gain in e-mental health interventions, with no clear advantage of one medium over the other. Particip","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e65478"},"PeriodicalIF":2.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12238786/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Misrepresentation of Overall and By-Gender Mortality Causes in Film Using Online, Crowd-Sourced Data: Quantitative Analysis.","authors":"Calla Glavin Beauregard, Christopher M Danforth, Peter Sheridan Dodds","doi":"10.2196/70853","DOIUrl":"10.2196/70853","url":null,"abstract":"<p><strong>Background: </strong>The common phrase \"representation matters\" asserts that media has a measurable and important impact on civic society's perception of self and others. The representation of health in media, in particular, may reflect and perpetuate a society's disease burden.</p><p><strong>Objective: </strong>In this study, for the top 10 major causes of death in the United States, we aimed to examine how cinematic representation overall and by-gender mortality diverges from reality.</p><p><strong>Methods: </strong>Using crowd-sourced data on over 68,000 film deaths from Cinemorgue Wiki, we employ natural language processing techniques to analyze shifts in representation of deaths in movies versus the 2021 National Vital Statistics Survey top 10 mortality causes. We parsed, stemmed, and classified each film death database entry, and then categorized film deaths by gender using a specifically trained gender text classifier.</p><p><strong>Results: </strong>Overall, movies strongly overrepresent suicide and, to a lesser degree, accidents. In terms of gender, movies overrepresent men and underrepresent women for nearly every major mortality cause, including heart disease and cerebrovascular disease (chi-square test, P<.001); 73.6% (477/648) of film deaths from heart disease were men (vs 384,866/695,547, 55.4% in real life) and 69.4% (50/72) of film deaths from cerebrovascular disease were men (vs 70,852/162,890, 43.5% in real life). The 2 exceptions for which women were overrepresented are suicide and accidents (chi-square test, P<.001), with 39.7% (945/2382) deaths from suicide in film being women (vs 9825/48,183, 20.4% in real life) and 38.8% (485/1250) deaths from accidents in film being women (vs 75,333/225,935, 33.5% in real life).</p><p><strong>Conclusions: </strong>We discuss the implications of under- and overrepresenting causes of death overall and by gender, as well as areas of future research.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e70853"},"PeriodicalIF":2.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12212890/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction of Personalized Predictive Models for Missed Medication Doses Using Wearable Device Data: Prospective Observational Study.","authors":"Haru Iino, Hayato Kizaki, Shungo Imai, Satoko Hori","doi":"10.2196/72113","DOIUrl":"10.2196/72113","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Declining medication adherence remains a critical health care issue, often assessed through unreliable self-reporting methods. Wearable devices (WDs) may offer an objective means to improve adherence monitoring by continuously recording physiological and activity data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to develop and internally validate personalized predictive models, utilizing objective physiological and activity data from WDs, for identifying missed medication doses.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A 30-day prospective observational study was conducted with 8 participants who wore Apple Watches and used a dedicated iOS app. The app collected demographics, medication details, psychological factors, mealtimes, and daily missed dose events. WDs recorded time-series data (ie, activity, heart rate, sleep) at 3-minute intervals. Data were aggregated into 1-hour segments, and lag (6 and 12 h) as well as rolling (24 h) features were generated. Light Gradient Boosting Machine models were constructed for each individual's dosing regimen if the missed dose rate exceeded 20%. Two modeling approaches were compared: a group cross-validation (CV) model that grouped data by day to avoid data leakage from rolling features, and a nonrolling feature model that excluded rolling features and used leave-one-out CV. F1-score, accuracy, recall, and precision were assessed between the 2 models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of the 15 enrolled participants, 8 completed the study; 4 had a missed dose rate above 20%. In these 4 individuals, the group CV model achieved F1-scores of 0.435 to 0.902, with accuracy ranging from 0.711 to 0.911, recall from 0.278 to 0.822, and a precision of 1.000 for the most robust regimens. The nonrolling feature model yielded F1-scores of 0.667 to 0.910, with accuracy ranging from 0.800 to 0.906, recall from 0.500 to 0.835, and a precision of 1.000. Morning dosing regimens generally showed higher predictive performance than evening or afternoon. Time-series features, particularly those reflecting 6-, 12-, and 24-hour patterns, emerged as key predictors, indicating that physiological and lifestyle variations prior to dosing strongly influenced missed dose events.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Personalized predictive models using WD-derived data demonstrated high precision for detecting missed medication doses, especially in morning and evening regimens. These findings underscore the feasibility of employing continuous, objective physiological and activity data from WDs to forecast nonadherence events. Although the sample size was limited, restricting the generalizability of the results, this study demonstrates the potential of WD-based personalized prediction of medication adherence. Future work should involve larger populations for external validation, strategies to improve recall, especially for clinically critical medications, and careful consideration of real-world implementation ch","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e72113"},"PeriodicalIF":2.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12212888/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Internet Health Information-Seeking Trend of Urinary Incontinence in Mainland China: Infodemiology Study.","authors":"Shuangquan Lin, Lingxing Duan, Xiongbing Lu, Haichao Chao, Xi Wen, Shanzun Wei","doi":"10.2196/55670","DOIUrl":"10.2196/55670","url":null,"abstract":"<p><strong>Background: </strong>Urinary incontinence (UI) is a series of clinical episodes featuring involuntary urine leakage. UI affects people in terms of their physical, emotional, and cognitive functioning, and the negative perceptions and impact on patients are not fully understood. In addition, the true demand for the treatment of UI and related issues is yet to be revealed.</p><p><strong>Objective: </strong>The aim of this study is to examine the online search trend, user demand, and encyclopedia content quality related to UI on a national and regional scale on Baidu search, the major search engine in Mainland China.</p><p><strong>Methods: </strong>The Baidu Index was queried using UI-related terms for the period from January 2011 to August 2023. The search volume for each term was recorded to analyze the search trend and demographic distributions. For user interest, the demand graph data and trend data were collected and analyzed.</p><p><strong>Results: </strong>Three search topics were identified with the 18 available UI search keywords. The total Baidu search index for all UI topics was 11,472,745. The annual percent changes (APCs) for the topic Complaint were 1.7% (P<.05) from 2011-2021 and -7.9% (P<.05) from 2021-2023, and the average annual percent change (AAPC) was 0.1% (P<.05). For the topic Inquiry, the APCs were 16% (P<.05) from 2011 to 2016, -27.00% from 2016 to 2019, and 21.2% (P<.05) from 2019 to 2023, with an AAPC of 4.8%. Regarding the topic of Treatment, the APC was 20.3% from 2011-2018 (P<.05), -36.9% from 2018-2021 (P>.05), and 2.2% from 2021-2023, with a -0.4% overall AAPC. The age distribution of the population of each UI search topic inquiry shows that the search inquiries for each topic were mainly made by the population aged 30 to 39 years. People from the eastern part of China made up around 30% of each search query.</p><p><strong>Conclusions: </strong>Web-based searching for UI topics has been continuous and traceable since January 2011. Different categorized themes within the UI topic highlight specific demands from various populations, necessitating tailored responses. Although online platforms can offer answers, medical professionals' involvement is crucial to avoid misdiagnosis and delayed treatment.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e55670"},"PeriodicalIF":2.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12208350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144475296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating Awareness and Acceptance of Digital Phenotyping in Dhaka's Korail Slum: Qualitative Study.","authors":"Nadia Alam, Domenico Giacco, Bulbul Siddiqi, Swaran P Singh, Sagar Jilka","doi":"10.2196/65530","DOIUrl":"10.2196/65530","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Digital phenotyping (DP), the process of using data from digital devices, such as smartphones and wearable technology to understand and monitor people's behavior, health, and daily activities, has shown significant promise in mental health care within high-income countries. However, its application in low- and middle-income countries (LMICs) is limited, particularly among impoverished populations such as slum residents.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objectives: &lt;/strong&gt;This study investigates the awareness, knowledge, acceptance, and implementation of DP, including willingness to share data, and concerns regarding privacy and data security, among residents of Dhaka's Korail slum, one of Bangladesh's largest and most densely populated informal settlements. Understanding awareness, acceptance, and privacy concerns surrounding DP in these settings is critical for its effective implementation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted 8 focus group discussions with 79% (30/38) of female participants (mean age 37, SD 13.7 years). Participants included 20 individuals diagnosed with serious mental disorders and 18 caregivers. The focus group discussions also included a section explaining what DP is.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Smartphone ownership was reported by 45% (17/38) of the participants, while 92% (35/38) of the participants had access to a smartphone through family members. There was a general lack of awareness about DP among the participants. Initially, 92% (35/38) of participants had no prior knowledge of DP, but after receiving an explanation, they acknowledged its potential applications and benefits. Participants recognized the use of DP for health monitoring, particularly in managing mental health conditions. Participants expressed willingness to share certain types of data, particularly phone usage and location data, provided that content-level information remained private. Despite these perceived benefits, significant concerns about privacy and data security emerged. Participants expressed fears about the potential misuse of their personal information, with some feeling resigned to the idea of already being constantly monitored. Trust in DP tools emerged as a critical factor for adoption, highlighting the need for transparent data protection policies and user control over data sharing. Additionally, participants emphasized the importance of adapting DP tools to local contexts, including cultural considerations and technological literacy.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;While DP presents a promising avenue for mental health support in underserved urban populations, its adoption in LMIC slum settings requires targeted educational initiatives, robust privacy safeguards, and community involvement to ensure trust and usability. DP tools should be adapted to fit the cultural context of the target population, possibly involving modifications to the types of data collected or the way data are interpreted. While DP hol","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e65530"},"PeriodicalIF":2.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12207998/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144475297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of a Novel eHealth Tool for Pulmonary Rehabilitation in People With Chronic Obstructive Pulmonary Disease: Randomized Controlled Pilot and Feasibility Trial.","authors":"Åsa Karlsson, Pernilla Sönnerfors, Sara Lundell, Annika Toots, Karin Wadell","doi":"10.2196/68195","DOIUrl":"10.2196/68195","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;There is a growing interest in eHealth solutions to enhance access to and use of pulmonary rehabilitation for people with chronic obstructive pulmonary disease (COPD).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to evaluate the feasibility of a novel eHealth tool (Me&COPD) to support pulmonary rehabilitation concerning usability, exercise adherence, intensity, progression, and adverse events. Moreover, this study aims to evaluate clinical outcome measures to prepare for a future larger trial.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A multicenter, parallel-group randomized controlled pilot and feasibility trial was conducted in 6 primary health care centers. People with mild to severe COPD were recruited by physiotherapists at the included health care centers and randomized either to the intervention group with access to Me&COPD for 3 months or to the control group receiving usual care. The Me&COPD tool comprised audio-visual and written self-management strategies, including an individually tailored home-based exercise program and interaction with a physiotherapist. The exercise program was prescribed in a face-to-face meeting with a physiotherapist, and thereafter it was regularly reviewed and adjusted through the eHealth tool. The primary outcome, usability, was self-assessed at intervention completion in the intervention group and among participating physiotherapists (n=7) using the Swedish version of the Mobile Health App Usability Questionnaire (S-MAUQ). In addition, use data on exercise adherence, intensity, and progression and adverse events were exported from the eHealth tool. Clinical outcomes, assessed by blinded assessors at baseline and 3 months in the intervention and control groups, included exercise capacity, balance, physical activity level, COPD-related symptoms, and health-related quality of life. Descriptive statistics were used for analysis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In total, 22 participants (women: n=12, 55%), aged 72.3 (SD 8.4) years on average, were included in the intervention (n=15) and control (n=7) groups. The mean overall S-MAUQ scores out of 7 (highest possible usability) were 4.4 (SD 1.5) for participants and 4.5 (SD 1.2) for physiotherapists. Among the subscales, the highest score was assigned to usefulness among participants (S-MAUQ: mean 4.9, SD 1.3) and physiotherapists (S-MAUQ: mean 5.1, SD 1.7). No severe adverse events were registered, although exercise adherence, intensity, and progression evaluation were limited by incomplete exercise session registration. The test procedures and the clinical outcome measures used were found to be feasible for the participants and the assessors.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The novel eHealth tool, Me&COPD, seemed feasible in terms of safety and had acceptable usability among people with COPD and participating physiotherapists. Usability may be improved by better organization of the information and simplification of the exercise diar","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e68195"},"PeriodicalIF":2.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12235207/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144475349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}