JMIR Formative Research最新文献

{"title":"Probing the Relationship Between Perioperative Complications in Patients With Valvular Heart Disease: Network Analysis Based on Bayesian Network.","authors":"Wenyuan Lu, Kun Zhu, Zhiliang Gao, Yuanming Li, Hanwei Tang, Cheng Sun, Jianfeng Hou","doi":"10.2196/68710","DOIUrl":"10.2196/68710","url":null,"abstract":"<p><strong>Background: </strong>Heart valve surgery is associated with a high risk of perioperative complications. However, current approaches for predicting perioperative complications are all based on preoperative or intraoperative factors, without taking into account the fact that perioperative complications are multifactorial, dynamic, heterogeneous, and interdependent.</p><p><strong>Objective: </strong>We aimed to construct and quantify the association network among multiple perioperative complications to elucidate the possible evolution trajectories.</p><p><strong>Methods: </strong>This study used the data from China Cardiac Surgery Registry (CCSR), in which 37,285 patients were included in the analysis. A Bayesian network was used to analyze the associations among 12 complications. Score-based hill-climbing algorithms were used to build the structure and the association between them was quantified using conditional probabilities.</p><p><strong>Results: </strong>We obtained the network of valve surgery complications. A total of 13 nodes represented complications or death, and 34 arcs with arrows represented the directly dependent relationship between them. We identified clusters of complications that were logically related and not related and quantified the associations. The correlation coefficient between complications increases with the severity of the complications, ranging from 0.01 to 0.41. Meanwhile, the probability of death when multiple complications occurred was calculated. Even mild complications, when progressing to multiple organ dysfunction syndrome, result in a mortality rate of over 90%.</p><p><strong>Conclusions: </strong>Our network facilitates the identification of associations among specific complications, which help to develop targeted measures to halt the cascade of complications in patients undergoing the valve surgery.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e68710"},"PeriodicalIF":2.0,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12503447/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244472","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":"Use of a Preliminary Artificial Intelligence-Based Laryngeal Cancer Screening Framework for Low-Resource Settings: Development and Validation Study.","authors":"Shao Wei Sean Lam, Min Hun Lee, Michael Dorosan, Samuel Altonji, Hiang Khoon Tan, Walter T Lee","doi":"10.2196/66110","DOIUrl":"10.2196/66110","url":null,"abstract":"<p><strong>Background: </strong>Early-stage diagnosis of laryngeal cancer significantly improves patient survival and quality of life. However, the scarcity of specialists in low-resource settings hinders the timely review of flexible nasopharyngoscopy (FNS) videos, which are essential for accurate triage of at-risk patients.</p><p><strong>Objective: </strong>We introduce a preliminary AI-based screening framework to address this challenge for the triaging of at-risk patients in low-resource settings. This formative research addresses multiple challenges common in high-dimensional FNS videos: (1) selecting clear, informative images; (2) deriving regions within frames that show an anatomical landmark of interest; and (3) classifying patients into referral grades based on the FNS video frames.</p><p><strong>Methods: </strong>The system includes an image quality model (IQM) to identify high-quality endoscopic images, which are then fed into a disease classification model (DCM) trained on efficient convolutional neural network (CNN) modules. To validate our approach, we curated a real-world dataset comprising 132 patients from an academic tertiary care center in the United States.</p><p><strong>Results: </strong>Based on this dataset, we demonstrated that the IQM quality frame selection achieved an area under the receiver operating characteristic curve (AUROC) of 0.895 and an area under the precision-recall curve (AUPRC) of 0.878. When using all the image frames selected by the IQM, the DCM improved its performance by 38% considering the AUROC (from 0.60 to 0.83) and 8% considering the AUPRC (from 0.84 to 0.91). Through an ablation study, it was demonstrated that a minimum of 50 good-quality image frames was required to achieve the improvements. Additionally, an efficient CNN model can achieve 2.5-times-faster inference time than ResNet50.</p><p><strong>Conclusions: </strong>This study demonstrated the feasibility of an AI-based screening framework designed for low-resource settings, showing its capability to triage patients for higher-level care efficiently. This approach promises substantial benefits for health care accessibility and patient outcomes in regions with limited specialist care in outpatient settings. This research provides necessary evidence to continue the development of a fully validated screening system for low-resource settings.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e66110"},"PeriodicalIF":2.0,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12503431/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244532","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":"Collaborative Development of a Self-Tracking Assisted Psychotherapy Treatment Concept for Refugees With Complex Posttraumatic Stress Disorder: Participatory Action Research.","authors":"Lisa Groenberg Riisager, Jakob Eg Larsen, Lotte Huniche, Thomas Blomseth Christiansen, Stine Bjerrum Moeller","doi":"10.2196/66663","DOIUrl":"https://doi.org/10.2196/66663","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Refugees are at high risk of severe mental health challenges due to exposure to war, torture, genocide, and childhood abuse. These experiences may lead to complex posttraumatic stress disorder (CPTSD), a condition that traditional treatments such as cognitive behavioral therapy and eye movement desensitization and reprocessing often struggle to treat adequately. Cultural complexity, limited relevance of standard interventions, and low adherence to therapeutic homework pose additional challenges. Self-tracking technologies offer a promising path for personalized mental health support in patients' everyday lives, but their integration into psychotherapy remains underexplored.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to collaboratively develop a psychotherapeutic treatment concept for refugees with CPTSD by integrating a personalized, wearable self-tracking instrument, the One Button Tracker (OBT), into psychotherapy. The OBT allows patients to track subjective experiences in the moment they occur, offering a way to bridge therapy sessions and everyday life.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study was conducted at a Danish trauma clinic specializing in treatment for refugees and veterans with posttraumatic stress disorder and CPTSD. A Participatory Action Research approach situated within the qualitative paradigm guided the process from November 2022 to April 2024. The codevelopment of the treatment concept involved therapists, patients, clinical psychology researchers, and human-computer interaction researchers (n=21). Qualitative data were gathered through patient interviews, therapist logbooks, and peer supervision sessions, and supplemented by self-tracking data from the OBT.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Across 17 months, the team conducted 40 peer supervision sessions, 2 collaborative workshops, and 25 interviews with 9 patients who participated in therapy for 8 to 24 sessions. Self-tracking durations ranged from 22 to 366 days, covering 1 to 14 target phenomena per patient. The OBT was found to enhance patient engagement by supporting active symptom monitoring and reinforcing therapeutic interventions outside sessions. Therapists reported that the self-tracking data provided valuable insights into patients' lived experiences, supporting more personalized and context-sensitive interventions. The flexible use of the OBT also allowed patients to shift their focus from distressing symptoms to alternative coping strategies. Furthermore, the integration of self-tracking data strengthened the therapeutic alliance by improving communication and collaboration between patients and therapists. Some technical limitations affected data collection but did not substantially hinder the therapeutic process.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This is the first study to use a Participatory Action Research approach to codevelop a psychotherapeutic treatment concept integrating self-tracking technology for refugees ","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e66663"},"PeriodicalIF":2.0,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244514","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":"Assessing a Community Health Worker-Facilitated, Digitally Delivered, Family-Centered Diabetes Management Program: Single-Arm Quasi-Experimental Study.","authors":"Zenong Yin, Vanessa L Errisuriz, Heather Cuevas, Bertha E Flores, Laura Delfausse, Christina Galvan, Jing Wang, Chengdong Li, Renata Morfin, Shiyu Li, Maysa Sapargeldiyeva, Giliane Yza Muyna, Minyu Zhang, Vanessa Sweet, Deborah Parra-Medina","doi":"10.2196/79032","DOIUrl":"https://doi.org/10.2196/79032","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The high prevalence of type 2 diabetes (T2D) and associated complications disproportionately affect low-income Latino populations, who also experience disparities in diabetes self-management (DSM), including poor medication adherence, physical activity, diet, and glycemic control.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study examined, through an academic-community partnership, the effectiveness of ¡Salud, Salud! (an evidence-based, family-centered diabetes self-management education and support [DSMES] program) on primary (glycemic control and quality of life) and secondary (social, psychological, and behavioral factors related to T2D management) outcomes among low-income Latino adults with T2D or prediabetes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In total, 81 adults (mean age 48.90 years, SD 12.57; n=57, 70.4%, female; n=66, 81.5%, Latino) with T2D or prediabetes were enrolled in a 12-week, single-arm quasi-experimental study conducted in two Central Texas Young Men's Christian Association (YMCA) locations. ¡Salud, Salud! incorporated individual coaching by community health workers (CHWs), online family-centered DSMES training lessons, and a YMCA family membership. The delivery of ¡Salud, Salud! was supported and facilitated by digital technologies, including a dashboard to deliver intervention content and monitor participants' engagement in intervention activities. Outcomes measured at baseline and 12 weeks (ie, postintervention) included hemoglobin A1c (HbA1c); quality of life; anthropometrics; self-reported physical activity and diet; mindfulness; perceived stress; and diabetes-related knowledge, self-efficacy, and support. Participant engagement in program activities was assessed via four index variables that underlay multiple dimensions of influences on ¡Salud, Salud! uptake: family engagement and support, participation in self-management education, program support and facilitation, and participation in self-monitoring. Paired t-tests and McNemar chi-square tests were used to examine the change in outcomes from baseline to 12 weeks. The number of program activities participants completed for each engagement index variable was converted to percentages to estimate the mean proportion of activities completed.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In total, 48 (59.3%) participants completed the 12-week posttest. At the end of the program, participants demonstrated a marginally significant reduction in HbA1c (-0.30%, P≤.09) and a significant increase in participants reporting good-to-excellent health from baseline (n=19, 39.6%) to posttest (n=28, 58.3%; P≤.003). There were significant reductions in body weight (-1.30 kg, P=.02), body fat percentage (-1.26%, P=.01), perceived stress (-0.28, P=.02), added sugar intake (-2.15 teaspoons/day, P=.001), and time spent sedentary per week (-70.27 minutes, P=.003) from baseline to posttest. Mindfulness increased significantly (2.21, P=.01). Participant engagement in ¡Salud, Salud! varie","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e79032"},"PeriodicalIF":2.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145238628","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":"Clinical System for Mood Disorder Care in Córdoba, Colombia: Participatory Design and Scenario-Based Usability Evaluation Study.","authors":"Ever Augusto Torres-Silva, Juan José Gaviria-Jiménez, Eider Pereira-Montiel, David Andrés Montoya-Arenas, José Fernando Flórez-Arango","doi":"10.2196/58909","DOIUrl":"10.2196/58909","url":null,"abstract":"<p><strong>Background: </strong>Mood disorders are among the leading causes of disability worldwide and present a growing public health concern. In Córdoba, Colombia, suicide rates have risen significantly in recent years, exposing structural gaps in mental health care delivery. Digital health solutions and telehealth interventions can expand access to early detection, referral, and monitoring of patients in underserved regions. However, their effectiveness depends on rigorous and diverse evaluations to ensure adoption and sustainability.</p><p><strong>Objective: </strong>This study evaluated the usability of a clinical telehealth system for mood disorder care developed through participatory design, with emphasis on user-centered functionality and workload analysis.</p><p><strong>Methods: </strong>The system was designed through 2 iterative development cycles, followed by a scenario-based usability evaluation. A functional Domain Ontology was constructed to prioritize 8 core functionalities, including telecounseling, a georeferenced institutional directory, hotline services, patient self-report tools, educational content, forums, and a population dashboard. Thirty participants representing patients, caregivers, clinical staff, and administrative personnel were recruited through convenience sampling. Usability was assessed through cognitive walk-throughs, the NASA (National Aeronautics and Space Administration) Task Load Index, and the Post-Study System Usability Questionnaire.</p><p><strong>Results: </strong>A total of 34 usability sessions and 223 task-level workload assessments were conducted across 2 evaluation cycles. The system demonstrated high usability, with overall Post-Study System Usability Questionnaire scores of 2.2 in cycle 1 and 2.3 in cycle 2. Interfaces prioritized for patients and clinical staff achieved better evaluations (average 1.9-2.0) than administrative interfaces (average 3.0). Workload analysis indicated improvements between cycles, particularly for patient-centered tasks, with mental workload as the most significant source of cognitive demand. Twenty-three critical issues (9 system errors and 14 design flaws) were identified and corrected between cycles, leading to measurable usability gains.</p><p><strong>Conclusions: </strong>The participatory and scenario-based approach facilitated early identification of usability challenges and supported iterative refinement of the system. Results suggest that the system is usable, acceptable, and effective in reducing workload for key user groups, particularly patients and clinicians. The findings reinforce the value of participatory methodologies in digital mental health and highlight the need to prioritize patient-facing interfaces. Future research should extend evaluations to mobile platforms and larger populations to support scalability and integration into regional mental health services.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e58909"},"PeriodicalIF":2.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145232880","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":"Designing Digital Mental Health Tools to Support the Needs of Black Adults in the United States: Qualitative Analysis.","authors":"Sarah Alexandra Popowski, Jonah Meyerhoff, Olivia Marin Allen, Theresa Nguyen, Terika McCall, Aderonke Bamgbose Pederson, Madhu Reddy, David Mohr, Rachel Kornfield","doi":"10.2196/73279","DOIUrl":"10.2196/73279","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Depression and anxiety are associated with excess morbidity and mortality, constituting a major health care challenge. The prevalence of these conditions is increasing. In the United States, the health-related burden of depression and anxiety may disproportionately affect Black adults, who face unique stressors impacting their mental health and barriers to accessing treatment, including but not limited to systemic racism, discrimination, underdiagnosis of common mental health concerns (ie, depression, anxiety), limited access to culturally sensitive care, and mental health stigma within and outside Black communities.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to explore the mental health experiences of nontreatment-seeking Black adults, and how these experiences relate to their needs and preferences for the design of digital mental health (DMH) tools through user-centered design methods.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study included 25 nontreatment-seeking Black adults (aged 18-61 years) with experiences of depression or anxiety to share their perspectives on how DMH tools can meet their needs. Participants were recruited either through social media advertisements or depression and anxiety questionnaires. All participants engaged in an asynchronous online discussion group in which they discussed their past and current mental health experiences, distinct challenges faced by Black Americans, and perceptions of DMH tools, as well as how such tools can be tailored to meet their mental health needs. Participants also completed a technology probe in which they used an automated mental health self-management text messaging tool (Small Steps SMS; Audacious Software) for 18 days. They shared their perceptions of the tool and ideas for specific design improvements in the discussion group. A subset (n=6) completed follow-up interviews to elaborate on their online discussion group posts.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;All participants reported significant mental health concerns and difficulty managing related symptoms. A majority of participants (22/25, 88%) expressed that racism and mental health stigma severely impacted their mental health and limited opportunities to discuss their experiences within and outside Black communities. They were interested in the use of DMH tools for mental health self-management and nearly all participants (23/25, 92%) endorsed text messaging as a convenient way to introduce techniques for coping with symptoms of depression and anxiety; however, some participants strongly advocated for additional design features that they believed would improve the program, including the integration of content that centers the experiences of Black individuals, creating nonjudgmental spaces for discussing mental health experiences, and linking formal mental health treatment resources for those who want them.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;These findings suggest that our participants hold gener","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e73279"},"PeriodicalIF":2.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12500225/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145238666","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":"Misinformation About Medical Cannabis in YouTube Videos: Systematic Review.","authors":"Shivank Khare, Simon Erridge, Swathikan Chidambaram, Mikael Hans Sodergren","doi":"10.2196/76723","DOIUrl":"10.2196/76723","url":null,"abstract":"<p><strong>Background: </strong>YouTube has become a major source of health information, with 2.5 billion monthly users. Despite efforts taken to promote reliable sources, misinformation remains prevalent, particularly regarding medical cannabis.</p><p><strong>Objective: </strong>This study aims to evaluate the quality and reliability of medical cannabis information on YouTube and to examine the relationship between video popularity and content quality.</p><p><strong>Methods: </strong>A systematic review of YouTube videos on medical cannabis was conducted. Search terms were selected based on Google Trends, and 800 videos were retrieved on July 8, 2024. After applying exclusion criteria, 516 videos were analyzed. Videos were categorized by content creators: (1) nonmedical educational channels, (2) medical education channels, and (3) independent users. Two independent reviewers (SK and SE) assessed content quality using the DISCERN grade and the Health on the Net (HON) code. Statistical analysis included one-way ANOVA and Pearson correlation coefficient.</p><p><strong>Results: </strong>Of the 516 videos analyzed, 48.5% (n=251) were from the United States, and 17.2% (n=89) from the United Kingdom. Only 12.2% (n=63) were produced by medical education channels, while 84.3% (n=435) were by independent users. The total views reached 119 million, with nonmedical educational channels having the highest median views with 274,957 (IQR 2161-546,887) and medical education channels having the lowest median views at 5721 (IQR 2263-20,792.50). The mean DISCERN and HON code scores for all videos were 34.63 (SD 9.49) and 3.93 (SD 1.20), respectively. Nonmedical educational creators had the highest DISCERN score (mean 47.78, SD 10.40) and independent users had the lowest score (mean 33.5, SD 8.50; P<.001). Similarly, nonmedical educational creators had the highest HON code score (mean 5.33, SD 1.22), while independent users had the lowest (mean 3.78, SD 1.10; P=.007). Weak positive correlations were found between video views and DISCERN scores (r=0.34, P<.001) and likes and DISCERN scores (r=0.30, P<.001).</p><p><strong>Conclusions: </strong>YouTube is a key source of information on medical cannabis, but the credibility of videos varies widely. Independent users attract the highest viewers but have reduced reliability according to the DISCERN and HON scores. Educational channels, despite increased reliability received the least engagement. The weak correlation between views and content quality emphasizes the need for content moderation to ensure that the most reliable and accurate information on health issues is widely disseminated. Future research should identify strategies to promote verified sources of information and limit misinformation.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e76723"},"PeriodicalIF":2.0,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12500220/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145238705","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":"Motives for Cannabis Use and Readiness to Change Among Users of the \"Stop-Cannabis\" Mobile App: Cluster Analysis.","authors":"Milena Wegener, Stéphane Rothen, Elise Dan-Glauser, Tania Lecomte, Stéphane Potvin, Lucien Rochat, Marissa Sjöblom, Germano Vera Cruz, Jean-François Etter, Yasser Khazaal","doi":"10.2196/70849","DOIUrl":"10.2196/70849","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Cannabis use is widespread and driven by diverse motives, ranging from recreational purposes to coping with psychological distress. Understanding the underlying reasons for cannabis use, their distribution across different subgroups of people who use cannabis, and how they relate to possible behavior change is essential for developing effective prevention and intervention strategies such as smartphone apps designed to support change.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The primary objective of the study was to determine whether analyzing profiles on the \"Stop-cannabis\" app (Institute of Global Health, University of Geneva, Switzerland) could reveal subgroups based on motives for cannabis use and readiness to change. A secondary objective was to explore differences among these subgroups in terms of problematic use and other indicators of change readiness.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study analyzed data from 2578 individuals using the \"Stop-cannabis app\", a mobile app developed in Switzerland to support those seeking to manage their cannabis use. Participants completed validated questionnaires assessing motives for use (Marijuana Motives Measure [MMM]), readiness to change (Stages of Change Readiness and Treatment Eagerness Scale [SOCRATES]), and risk of problematic use (Alcohol, Smoking, and Substance Involvement Screening Test [ASSIST]). They also self-rated their \"readiness for action,\" the \"importance of change,\" and their \"confidence in their ability to change.\" These assessments were part of the app's intervention model, with personalized feedback delivered based on participants' responses; no external incentives were offered. Cluster analysis was conducted to identify subgroups based on MMM and SOCRATES scores.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In total, 3 distinct profiles emerged: the \"individually coping users\" (ICU), the \"social and coping users\" (SCU), and the \"enhancement-seeking users\" (ESU). ICU and SCU scored higher on coping motives compared with ESU, along with greater ambivalence and stronger recognition of problematic use, as measured by SOCRATES. They also scored higher on the ASSIST (indicating greater risk of problematic cannabis use), placed more importance on making behavioral changes, yet reported lower confidence in their ability to enact those changes. By contrast, ESU primarily used cannabis for recreational reasons and had low recognition of problematic use, despite being at moderate risk.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This research highlights that while motives for cannabis use are varied and individually nuanced, distinct subgroups can be identified, each with specific challenges. The findings align with previous research emphasizing the importance of coping motives in behavior change. Tailoring app content to reflect the unique profiles and needs of each subgroup may improve intervention outcomes. For instance, SCU and ICU may benefit from strategies targeting emotion regul","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e70849"},"PeriodicalIF":2.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12494107/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225369","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":"Identification of Syndrome Types in Patients With Pancreatic Cancer From Free Text in Electronic Medical Records: Model Development and Validation.","authors":"He Ba, Haojie Du, Chienshan Cheng, Yuan Zhang, Linjie Ruan, Zhen Chen","doi":"10.2196/70602","DOIUrl":"https://doi.org/10.2196/70602","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Syndrome differentiation is crucial in traditional Chinese medicine (TCM) diagnosis and treatment, but it heavily relies on expert experience, limiting systematic standardization.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study developed and validated a BERT (bidirectional encoder representations from transformers)-based model, the traditional Chinese medicine pancreatic cancer syndrome differentiation bidirectional encoder representations from transformers (TCMPCSD-BERT), using in-house pancreatic cancer medical records, to digitalize expert knowledge and support standardized syndrome differentiation in TCM.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A retrospective dataset of pancreatic cancer cases (2011-2024) from Fudan University Shanghai Cancer Center was annotated into 4 TCM syndrome types by 2 experts (Cohen κ=0.913). The proposed TCMPCSD-BERT model was compared with conventional models (long short-term memory and text convolutional neural network) embedded in TCM diagnostic tools and with large language models (LLMs; ChatGPT-4o, Kimi, Ernie Bot 4.0 Turbo, and Zhipu Qingyan) under a prompt engineering framework. Performance evaluation on in-house data was supplemented with attention visualizations and integrated gradients analyses for interpretability. The McNemar test assessed classification accuracy differences, while bootstrap 95% CIs quantified statistical uncertainty and stability. The Welch t test (2-tailed) was used to evaluate mean differences between TCMPCSD-BERT and the comparator models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among 6830 records, case counts were damp-heat syndrome (n=1694), spleen-deficiency syndrome (n=1185), damp-heat with spleen-deficiency syndrome (n=1178), and others (n=2773). On the test set, McNemar test showed significantly higher accuracy for TCMPCSD-BERT than the 3 baseline models and generally better performance than LLMs. In all comparisons, TCMPCSD-BERT achieved higher mean macroprecision, macrorecall, macro-F&lt;sub&gt;1&lt;/sub&gt;-score, and accuracy, with nonoverlapping 95% bootstrap CIs and significant Welch t test results (P&lt;.01). The model achieved a macroprecision of 0.935 (95% CI 0.918-0.951), macrorecall of 0.921 (95% CI 0.900-0.942), macro-F&lt;sub&gt;1&lt;/sub&gt;-score of 0.927 (95% CI 0.908-0.945), and accuracy of 0.919 (95% CI 0.899-0.939). Attention visualizations suggested the model could capture less common TCM term associations, while integrated gradients highlighted high-attribution diagnostic features (eg, \"gray-white stool\" 0.933 in damp-heat syndrome; \"indigestion\" 1.204 in spleen-deficiency syndrome). Misclassification analyses indicated challenges in handling overlapping or atypical symptom presentations. Compared with LLMs, web-based platforms, and diagnostic instruments, TCMPCSD-BERT appeared to provide relatively higher accuracy, interpretability, and efficiency in processing long unstructured texts for syndrome differentiation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The TCMPCSD-BERT mo","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e70602"},"PeriodicalIF":2.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225386","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":"Low Risk Perception of Harm From Substance Use and Sexual Behaviors Among Online Help-Seeking Sexual and Gender Minoritized People in San Francisco, California: Cross-Sectional Survey.","authors":"Jarett Maycott, Sean Arayasirikul","doi":"10.2196/81753","DOIUrl":"https://doi.org/10.2196/81753","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Substance use and HIV epidemics have disproportionately affected sexual and gender minoritized (SGM) communities, with heightened risks among men who have sex with men (MSM) and transgender women of color due to intersecting challenges like poverty, mental health issues, and discrimination. Despite overall declines in substance use and sexual risk behaviors in the general population, these issues persist within SGM communities, exacerbated by stigma and systemic barriers to care. Digital health interventions have emerged as promising tools to address these disparities, offering accessible and stigma-reducing alternatives to traditional care, particularly effective among younger individuals and in underserved areas.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study seeks to examine the social correlates of substance use and sexual risk perception among an online sample of help-seeking MSM and transgender women in San Francisco, California.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We recruited 409 help-seeking MSM and transgender women by using social media advertisements on Facebook, Instagram, and Grindr in 2022-2024. Participants provided informed consent and completed a baseline assessment.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Utilization of testing resources for HIV and hepatitis was high among the participants (401/409, 98.04% and 360/409, 88.02%, respectively). Knowledge of HIV or other sexually transmitted infection health services was also high (379/409, 92.67%). Fewer participants (264/409, 64.55%) were knowledgeable about substance use-related services. Although many participants reported that using substances posed a high risk of harm, some perceived engaging in condomless sex, using prescription opioid drugs without a prescription, and using substances during sex as low risk (122/409, 29.83%, 41/409, 10.02%, and 60/409, 14.67%, respectively). Participants who reported experiencing unstable housing were more likely to report perceiving sharing needles (adjusted odds ratio [aOR] 7.20, 95% CI 1.99-27.80) and nonprescription opioid use (aOR 4.02, 95% CI 1.08-14.90) as low risk. Participants who reported an income below the federal poverty level were more likely to report perceiving sharing needles (aOR 6.35, 95% CI 1.84-23.40), prescription opioid use (aOR 2.89, 95% CI 1.32-6.18), and substance use during sex (aOR 2.29, 95% CI 1.14-4.48) as low risk. Participants who have not been tested for hepatitis in the past have 3.31 times the odds of perceiving prescription opioid use as low risk compared to counterparts who have been tested for hepatitis before (95% CI 1.36-7.68).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study underscores the importance of social determinants in shaping low risk perception of the harm associated with substance use behaviors among online help-seeking SGM people in San Francisco. These systemic inequities structure participants' perceptions, access, and utilization of preventive and public health service","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e81753"},"PeriodicalIF":2.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145225449","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}