JMIR Human Factors最新文献

{"title":"Evaluating the Usability, Technical Performance, and Accuracy of Artificial Intelligence Scribes for Primary Care: Competitive Analysis.","authors":"Emily Ha, Isabelle Choon-Kon-Yune, LaShawn Murray, Siying Luan, Enid Montague, Onil Bhattacharyya, Payal Agarwal","doi":"10.2196/71434","DOIUrl":"https://doi.org/10.2196/71434","url":null,"abstract":"<p><strong>Background: </strong>Primary care providers (PCPs) face significant burnout due to increasing administrative and documentation demands, contributing to job dissatisfaction and impacting care quality. Artificial intelligence (AI) scribes have emerged as potential solutions to reduce administrative burden by automating clinical documentation of patient encounters. Although AI scribes are gaining popularity in primary care, there is limited information on their usability, effectiveness, and accuracy.</p><p><strong>Objective: </strong>This study aimed to develop and apply an evaluation framework to systematically assess the usability, technical performance, and accuracy of various AI scribes used in primary care settings across Canada and the United States.</p><p><strong>Methods: </strong>We conducted a systematic comparison of a suite of AI scribes using competitive analysis methods. An evaluation framework was developed using expert usability approaches and human factors engineering principles and comprises 3 domains: usability, effectiveness and technical performance, and accuracy and quality. Audio files from 4 standardized patient encounters were used to generate transcripts and SOAP (Subjective, Objective, Assessment, and Plan)-format medical notes from each AI scribe. A verbatim transcript, detailed case notes, and physician-written medical notes for each audio file served as a benchmark for comparison against the AI-generated outputs. Applicable items were rated on a 3-point Likert scale (1=poor, 2=good, 3=excellent). Additional insights were gathered from clinical experts, vendor questionnaires, and public resources to support usability, effectiveness, and quality findings.</p><p><strong>Results: </strong>In total, 6 AI scribes were evaluated, with notable performance differences. Most AI scribes could be accessed via various platforms (n=4) and launched within common electronic medical records, though data exchange capabilities were limited. Nearly all AI scribes generated SOAP-format notes in approximately 1 minute for a 15-minute standardized encounter (n=5), though documentation time increased with encounter length and topic complexity. While all AI scribes produced good to excellent quality medical notes, none were consistently error-free. Common errors included deletion, omission, and SOAP structure errors. Factors such as extraneous conversations and multiple speakers impacted the accuracy of both the transcript and medical note, with some AI scribes producing excellent notes despite minor transcript issues and vice versa. Limitations in usability, technical performance, and accuracy suggest areas for improvement to fully realize AI scribes' potential in reducing administrative burden for PCPs.</p><p><strong>Conclusions: </strong>This study offers one of the first systematic evaluations of the usability, effectiveness, and accuracy of a suite of AI scribes currently used in primary care, providing benchmark data for further","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e71434"},"PeriodicalIF":2.6,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144699788","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":"A Comprehensive Profiling System Integrating Myers-Briggs Type Indicator (MBTI) and Dominance, Influence, Steadiness, and Conscientiousness (DISC) for Personalized Health Training: Correlational Analysis and Usability Evaluation.","authors":"Donghyun Kim, Dong Hun Lee, Mi Kyung Hwang","doi":"10.2196/73397","DOIUrl":"https://doi.org/10.2196/73397","url":null,"abstract":"<p><strong>Background: </strong>This study proposes an integrated approach to developing personalized health behavior change programs by combining personality traits and behavior types. Existing tools, such as Myers-Briggs Type Indicator (MBTI) and Dominance, Influence, Steadiness, and Conscientiousness (DISC), have limitations: MBTI reflects internal tendencies but lacks behavioral insights, while DISC highlights behavior but overlooks deeper personality aspects. To address these gaps, the study integrates MBTI and DISC to create a comprehensive profiling system.</p><p><strong>Objective: </strong>The goal of this research is to design a novel profiling system that merges MBTI and DISC for personalized health management. This system aims to link personality traits with behavior patterns to enhance the effectiveness of tailored health behavior change programs.</p><p><strong>Methods: </strong>The study involved 3 phases: administering MBTI and DISC tests to 130 participants to analyze correlations, developing an integrated survey for health behavior analysis, and testing its usability with 20 experts for validation.</p><p><strong>Results: </strong>Significant correlations were observed between MBTI and DISC indicators, including a notable negative correlation between Thinking-Feeling (T/F) and Dominance (D), suggesting an inverse relationship between decision-making preferences and assertiveness. Usability testing results indicated high participant satisfaction, with an average SUS (System Usability Scale) score of 86.0. The SUS is a widely used questionnaire for measuring subjective assessments of usability. This score exceeded industry benchmarks for system usability. Expert evaluations further reinforced the system's practical applicability, highlighting its potential to enhance user engagement through personalized behavioral insights.</p><p><strong>Conclusions: </strong>This study presents a combined MBTI and DISC profiling system, offering both theoretical insights and practical tools for health behavior change programs. Future research should validate its effectiveness with larger samples and explore broader applications in various health domains.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e73397"},"PeriodicalIF":2.6,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676040","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":"Factors Influencing Health Workers' Acceptance of Guideline-Based Clinical Decision Support Systems for Preventive Services in Thailand: Questionnaire-Based Study.","authors":"Tullaya Sitasuwan, Prapat Suriyaphol, Saranath Lawpoolsri, Ngamphol Soonthornworasiri, Wirichada Pan-Ngum","doi":"10.2196/57314","DOIUrl":"10.2196/57314","url":null,"abstract":"<p><strong>Background: </strong>A guideline-based clinical decision support system (CDSS) is a knowledge-based system designed to collect crucial data from electronic medical records to generate decision-making based on system data requirements and inputs from standard guidelines. Despite the potential to enhance health care delivery, the adoption rate of CDSSs in clinical practice remains suboptimal.</p><p><strong>Objective: </strong>This study aimed to evaluate the determinants influencing the intention to use a new CDSS in preventive care within clinical practice.</p><p><strong>Methods: </strong>A single-center, questionnaire-based, cross-sectional study was conducted among physicians and medical students responsible for providing comprehensive preventive services at the Continuity of Care Clinic, Siriraj Hospital, Thailand.</p><p><strong>Results: </strong>In total, 89 participants were enrolled. Relationships between factors impacting the adoption of CDSSs were analyzed using correlation and regression analysis. We found that physicians' intentions to adopt the CDSS for preventive care were high, with 79% (70/89) of participants expressing their intention to use the system. According to the study's conceptual framework, modified from the original unified theory of acceptance and use of technology model, physicians' positive attitudes toward CDSS use in preventive services and a high level of effort expectancy emerged as crucial factors influencing the intention to use the new CDSS. The odds ratios for these factors were 5.44 (95% CI 1.62-18.34, P=.006) and 7.60 (95% CI 1.55-31.37, P=.01), respectively. Similar results were observed for medical students and for physicians who had graduated. The most prevalent barriers to CDSS implementation were related to physicians' attitudes, followed by issues such as the accuracy and burden of data input, time constraints for clinicians, and the risk of workflow disruption.</p><p><strong>Conclusions: </strong>There was a high intention to adopt the CDSS in preventive care. Positive physician attitudes toward CDSS use in preventive services and effort expectancy were found to be critical factors influencing the intention to use the new CDSS.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e57314"},"PeriodicalIF":2.6,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12286562/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144650808","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":"Identifying Design Requirements for an Interactive Physiotherapy Dashboard With Decision Support for Clinical Movement Analysis of Musicians With Musculoskeletal Problems: Qualitative User Research Study.","authors":"Eduard Wolf, Karsten Morisse, Sven Meister","doi":"10.2196/65029","DOIUrl":"https://doi.org/10.2196/65029","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Performance-related musculoskeletal disorders are common among musicians, requiring precise diagnostic and therapeutic approaches. Physiotherapists face unique challenges due to the complex relationship between musculoskeletal health and the demands of musical performance. Traditional methods often lack the necessary precision for this specialized field. Integrating clinical movement analysis (CMA) with clinical decision support (CDS) could improve diagnostic accuracy and therapeutic outcomes by offering detailed biomechanical insights and facilitating data-driven decision-making.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to identify design requirements for an interactive dashboard that aids clinical decision-making by incorporating CMA to assist physiotherapists in managing musculoskeletal disorders in musicians.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A qualitative user research study was conducted, using human factors engineering methods from problem-driven research, user-centered design, and decision-centered design. Data collection included a domain-specific literature review, workflow observations, and focus group discussions with domain experts, including 4 physiotherapist experts and an expert for clinical reasoning and applied biomechanics. This qualitative data was triangulated to characterize the domain, identify the CMA workflow, user needs, key cognitive tasks, and decision requirements. These insights were translated into concrete design requirements.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A workflow for integrating musician-specific CMA into physiotherapy was established. In total, 21 user requirements, 7 key cognitive tasks, and 5 key decision requirements were defined, along with 49 design seeds. Key features identified include (1) efficient integration of musician-specific biomechanical findings into therapy, (2) combining heterogeneous data types for holistic assessment, (3) providing an adaptive overview of patient-related information, (4) using adequate visual representations and interaction techniques, (5) facilitating efficient visual-interactive analysis of findings and treatment results, and (6) enabling preparation and export of therapy findings and analysis results. Additionally, 14 CDS recommendations and 11 technical prerequisites were identified. These requirements guide the design of an interactive tool featuring advanced visualization, interactive data exploration capabilities, and contextual integration of clinical and biomechanical data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;An interactive physiotherapy dashboard with CDS incorporating CMA data holds significant potential to enhance decision-making in physiotherapy for musicians with performance-related musculoskeletal disorders. By addressing cognitive demands and integrating advanced visualization techniques, the tool can support physiotherapists in making more accurate assessments, potentially improving patient outcomes, reducing injury","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e65029"},"PeriodicalIF":2.6,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144650809","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":"Evaluating the Usability of an HIV Prevention Artificial Intelligence Chatbot in Malaysia: National Observational Study.","authors":"Zhao Ni, Sunyoung Oh, Rumana Saifi, Iskandar Azwa, Frederick L Altice","doi":"10.2196/70034","DOIUrl":"https://doi.org/10.2196/70034","url":null,"abstract":"<p><strong>Background: </strong>Malaysia, an upper middle-income country in the Asia-Pacific region, has an HIV epidemic that has transitioned from needle sharing to sexual transmission, mainly in men who have sex with men (MSM). MSM are the most vulnerable population for HIV in Malaysia. In 2022, our team developed a web-based artificial intelligence (AI) chatbot and tested its feasibility and acceptability among MSM in Malaysia to promote HIV testing. To enhance the usability of the AI chatbot, we made it accessible to the public through the website called MYHIV365 and tested it in an observational study.</p><p><strong>Objective: </strong>This study aimed to test the usability of an AI chatbot in promoting HIV testing among MSM living in Malaysia.</p><p><strong>Methods: </strong>This observational study was conducted from August 2023 to March 2024 among 334 MSM. Participants were recruited through community outreach and social-networking apps using flyers. The interactions between participants and the AI chatbot were documented and retrieved from the chatbot developer's platform. Data were analyzed following a predefined metrics using R software (Posit Software, PBC).</p><p><strong>Results: </strong>The AI chatbot interacted with 334 participants, assisting them in receiving free HIV self-testing kits, offering information on HIV, pre-exposure prophylaxis (PrEP), and mental health, and providing details of 220 MSM-friendly clinics, including their addresses, phone numbers, and operating hours. After the study, 393 human-chatbot interactions were documented on the chatbot developer's platform. Most participants (304/334, 91.0%) interacted with the AI chatbot once, 30 (9.0%) engaged 2 or more times at different intervals. Participants' interaction time with the chatbot varied, ranging from 1 to 31 minutes. The AI chatbot properly addressed most participants' questions (362/393, 92.1%) about HIV and PrEP. However, in 31 interactions, participants posed additional questions to the chatbot that were not programmed into the chatbot algorithms, resulting in unanswered interactions.</p><p><strong>Conclusions: </strong>The web-based AI chatbot demonstrated high usability in delivering HIV self-testing kits and providing clinical information on HIV testing, PrEP, and mental health services. To enhance its usability in community and clinical settings, the chatbot must offer personalized health information and precise interaction, powered by sophisticated machine learning algorithms. In addition, establishing an effective connection between the AI chatbot and health care systems to eliminate stigma and discrimination toward MSM is crucial for the future implementation of AI chatbots.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e70034"},"PeriodicalIF":2.6,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144643722","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":"A Mobile App Designed to Promote Shared Decision-Making in the Treatment of Psychotic Disorders: Feasibility and Acceptability Study.","authors":"Mari Skoge, Sofie Ragnhild Aminoff, Elizabeth Ann Barrett, Gina Engen Bryhni, Kristine Kling, Kari Jorunn Kværner, Ingrid Melle, Erlend Mork, Carmen Simonsen, Linn Nathalie Støme, Josina Vink, Tor Gunnar Værnes, Kristin Lie Romm","doi":"10.2196/68813","DOIUrl":"10.2196/68813","url":null,"abstract":"<p><strong>Background: </strong>Strengthening shared decision-making in mental health care may improve the quality of services and treatment outcomes, but its implementation in services for severe mental disorders is currently lacking.</p><p><strong>Objective: </strong>This study aims to explore the feasibility and acceptability of iTandem (University of Oslo), a mobile app designed to promote shared decision-making in the treatment of psychotic disorders. In addition, the study aims to investigate mechanisms that potentially contribute to the intended effect of the app. iTandem is a therapy supplement that facilitates patient involvement in decisions regarding treatment goals and focus areas. It is designed for personalized use and contains 8 optional modules: sleep, medication, recovery, mood, psychosis, activity, substance use, and feedback concerning therapy.</p><p><strong>Methods: </strong>Patients undergoing assessment or treatment for psychotic disorders and their clinicians were recruited for the study. Patients and clinicians jointly used iTandem as part of standard treatment in a 6-week trial. We used a mixed-methods study design with a clear emphasis on qualitative methods. Feasibility and acceptability were assessed through descriptive statistics based on preintervention and postintervention questionnaires and app usage data, in addition to text responses to open-ended items. We conducted a reflexive thematic analysis of postintervention interviews to elaborate these measures and to explore mechanisms potentially contributing to achieving shared decision-making when using iTandem.</p><p><strong>Results: </strong>A total of 9 patients and 8 clinicians completed the trial. The participants evaluated iTandem as a user-friendly and acceptable tool, but there were considerable variations in how the app was integrated into treatment and in perceptions of its clinical value. The thematic analysis suggests that iTandem has the potential to facilitate shared decision-making through supporting cognition and shifting the patient's role. We also identified scaffolding structures, an analogy of personalized support, as a precondition for these mechanisms and for the overall feasibility and acceptability of iTandem.</p><p><strong>Conclusions: </strong>iTandem was generally perceived as a feasible and acceptable tool in the treatment of patients with psychotic disorders. Our findings suggest that nonclinical aspects, such as support structures, are important to the feasibility and acceptability of such digital interventions and patients' aptness for digitalized treatment in general. Future research should explore related nonclinical aspects further instead of defining potential target groups based on diagnoses and symptom severity alone.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e68813"},"PeriodicalIF":2.6,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12274015/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612393","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":"Assessing Postoperative Pain in Patients Who Underwent Total Knee Arthroplasty Using an Automated Self-Logging Patient-Reported Outcome Measure Collection Device: Retrospective Cohort Study.","authors":"Prabjit Ajrawat, Blaine Price, Daniel Gooch, Rudolf Serban, Ruqaiya Al-Habsi, Oliver Pearce","doi":"10.2196/65271","DOIUrl":"10.2196/65271","url":null,"abstract":"<p><strong>Background: </strong>Patient-reported outcome measures (PROMs) are tools for assessing symptoms and the quality of care. Despite their growing use, conventional data collection methods limit widespread PROM implementation. In orthopedics, pain is a frequent patient complaint and a common PROM, especially following total knee arthroplasty (TKA). Although TKA is generally successful, some patients still report postoperative pain, potentially due to tourniquet use. Using an improved PROM data-gathering technique may help to address tourniquet use during a TKA procedure and its impact on postoperative pain. The PainPad, an automated self-logging device, was developed to capture patient pain levels accurately.</p><p><strong>Objective: </strong>The aim of the study is to assess the feasibility and effectiveness of the PainPad device in quantifying in-hospital postoperative pain following TKA with or without tourniquet use.</p><p><strong>Methods: </strong>A retrospective study with 234 patients who underwent TKA from 2018 to 2021 at Milton Keynes University Hospital was conducted. Patients were categorized as receiving TKA with an intraoperative tourniquet (tourniquet group) or TKA without a tourniquet (nontourniquet group). Postoperative pain during the first 24 hours was self-reported every 2 hours using the PainPad device. From both groups, data on hospital length of stay, total tourniquet time, and the presence of postoperative deep vein thrombosis were also collected.</p><p><strong>Results: </strong>There were 115 TKAs with tourniquets (72/115, 62.6% female patients; mean age 69.26, SD 9.93 years) and 119 TKAs without tourniquets (91/119, 76.4% female patients; mean age 70.97, SD 9.01 years). When assessing 24-hour mean postoperative pain scores, the PainPad device data indicated no significant difference (P=.53; 95% CI -0.76 to 0.39) between the tourniquet (mean pain score 3.31, SD 2.34) and nontourniquet groups (mean pain score 3.12, SD 2.15). There was no correlation between tourniquet times and the pain scores retrieved from the PainPad device. A subgroup analysis comparing longer (>90 minutes) versus shorter (<90 minutes) tourniquet times showed no significant difference in terms of pain and length of stay.</p><p><strong>Conclusions: </strong>The PainPad device is a feasible and effective method for collecting and evaluating in-hospital postoperative pain following TKA, allowing for the quantification of individual pain levels. This study aligns with the current health care trend toward leveraging innovative technologies and personalized data to enhance patient-centered care.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e65271"},"PeriodicalIF":2.6,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12270187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144609771","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":"Exploring Clinicians' and Patients' Acceptance and Utilization of a Digital Solution to Support Individualized Care in Diabetes Specialist Outpatient Care (DigiDiaS): Qualitative Study.","authors":"Maria Aadland Mollestad, Annesofie Lunde Jensen, Heidi Holmen, Tone Singstad, Eirik Årsand, Jacob Andreas Winther, Astrid Torbjørnsen","doi":"10.2196/70301","DOIUrl":"10.2196/70301","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;With the increasing prevalence of type 1 diabetes alongside limited health care resources, the need for more sustainable health care services is apparent. Central to ensuring the standard of diabetes care while simultaneously optimizing resource utilization is improved patient-clinician communication and the provision of individualized care. Digital outpatient solutions incorporating patient-reported outcome measures (PROMs) have been introduced in diabetes outpatient care over recent years; however, features and delivery methods differ, and existing studies on their use and perceived clinical value are limited. Furthermore, clinicians' acceptance has been suggested as a key factor in the sustainability of digital solutions. Thus, to support the implementation of digital outpatient solutions perceived as valuable by clinicians and patients, we need more knowledge about how they are accepted and utilized in clinical practice.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study investigates how clinicians and patients with type 1 diabetes accept and utilize a digital outpatient solution to support individualized care in the context of full-scale implementation at a diabetes specialist outpatient clinic. Furthermore, we aim to explore the synchronous interaction between patients and clinicians when they are allowed to prepare through the filling and reviewing of asynchronous PROMs before consultations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This qualitative study uses interpretive description as a methodological approach. The digital outpatient solution features various components, including PROM questionnaires, asynchronous chat, remote consultations, e-learning, and information distribution. Data were collected through semistructured interviews with 10 clinicians and 20 patients with type 1 diabetes and observations of consultations. The data from the patient and clinician interviews (267 A4 pages) were analyzed separately before being jointly analyzed in the context of the findings from the observations (40 A4 pages).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Our analysis resulted in the following three main themes that describe the interplay between clinicians' and patients' acceptance, utilization, and perceived clinical value of a digital outpatient solution: (1) clinicians' acceptance of the digital outpatient solution influences patients' acceptance, (2) variations in the use of different features influence the extent of individualized care, and (3) clinicians' and patients' utilization influences perceived care efficiency and quality. Those who demonstrated higher acceptance and more extensive utilization reported that the solution was more valuable in enhancing individualized care efficiency and quality.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study highlights the interplay between clinicians' and patients' acceptance, utilization, and perceived clinical value of a digital outpatient solution in diabetes specialist outpatient care","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e70301"},"PeriodicalIF":2.6,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12262153/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144592509","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":"Usability and Quality of the JoyPop App: Prospective Evaluation Study.","authors":"Ishaq Malik, Teagan Neufeld, Aislin Mushquash","doi":"10.2196/65472","DOIUrl":"10.2196/65472","url":null,"abstract":"<p><strong>Background: </strong>Mental health difficulties are increasing among Canadian postsecondary students, and many face barriers to accessing mental health care. Mobile health smartphone apps for mental health reduce common barriers to care and improve student mental health outcomes. However, students' engagement and use of mental health apps is low. Evaluating the usability and quality of mental health apps is essential not only for user engagement but also for safety and overall utility. Few mental health apps have undergone usability and quality evaluations, especially with measures explicitly designed for these apps. The JoyPop app is a resilience-building mental health app with evidence supporting its effectiveness for student mental health. It has yet to be evaluated using standardized measures of mental health app usability and quality, and the influence of usability and quality on use is unknown.</p><p><strong>Objective: </strong>We evaluated the usability and quality of the JoyPop app and the predictive importance of usability and quality, compared to other relevant user characteristics, in predicting intentions to use the app in the future (usage intentions).</p><p><strong>Methods: </strong>Participants (N=183) completed preapp measures assessing demographics and personality traits, then used the app for 1 week, and then completed postapp measures assessing the usability, quality, and use of the JoyPop app. Usability (overall; and subscales: ease of use, interface and satisfaction, and usefulness) and quality (objective, subjective, and perceived impact) were assessed with descriptive statistics. Multiple regression analyses tested the predictive importance of usability and quality on usage intentions after controlling for other user characteristics.</p><p><strong>Results: </strong>Participants rated the JoyPop app's overall usability as \"very good\" (mean 5.63, SD 0.85). Participants rated the JoyPop app's overall objective quality as \"excellent\" (mean 4.06, SD 0.54). Subjective quality ratings were good, with many participants (135/183, 73.8%) indicating they would recommend the app to others. Participants rated the app as having a moderate and helpful impact on their mental health and coping skills (mean 3.48, SD 0.88). In each regression model, usability (β=.56, P<.001) and quality (β=.52, P<.001) were the strongest predictors and predicted usage intentions over and above other user characteristics.</p><p><strong>Conclusions: </strong>Results align with prior research evaluating the JoyPop app and maintain that it is an engaging and high-quality mental health app that can support students. Findings provide important insight into the optimal design of mental health apps for students and inform adaptations to future iterations of the JoyPop app.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e65472"},"PeriodicalIF":2.6,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12248135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144561411","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":"Growth Mindset Intervention's Impact on Positive Response to eHealth for Older Adults With Chronic Disease: Randomized Controlled Trial.","authors":"Meijuan Cao, Xiaojuan Xu, Yaling Zeng, Binyu Zhao, Chunqi Xie, Hailu Wu, Jianlin Lou","doi":"10.2196/65519","DOIUrl":"10.2196/65519","url":null,"abstract":"<p><strong>Background: </strong>Although eHealth has shown promise in managing chronic diseases, there remains a substantial digital divide among older adults. The concept of a growth mindset, based on psychological theory, offers a new direction and potential breakthrough for addressing this dilemma.</p><p><strong>Objective: </strong>This study aims to develop and explore the feasibility and efficacy of a growth mindset intervention for older adults with chronic diseases and their positive response to eHealth.</p><p><strong>Methods: </strong>A randomized controlled trial was conducted at the internal medicine departments of a hospital in Hangzhou, Zhejiang Province, China, from September 2021 to October 2022. A total of 77 older patients with chronic disease initially participated in the study. The mean age of the participants was 67.16 (SD 7.04) years, with 42.86% (33/77) being women and 57.14% (44/77) being men. The experimental group received an eHealth program intervention plus a growth mindset intervention over 12 weeks, with weekly sessions for the first 6 weeks and biweekly follow-up phone calls for the next 6 weeks. Each session lasted at least 25-45 minutes. Data were collected using a personal information form, the Implicit Theories of Intelligence Scale-6 (ITIS-6), and a questionnaire on knowledge, willingness, confidence, and practice of smart medicine (KWCP-SM). Measurements were taken at the beginning of the study (T0), immediately after the 6 weeks of training provided to the experimental group (T1), and after the 12 weeks of training for the intervention (T2). Data were analyzed using repeated-measures analysis of variance and analysis of covariance.</p><p><strong>Results: </strong>The final sample comprised 74 participants, of which 36 were in the experimental group and 38 in the control group. After 12 weeks of intervention, the level of growth mindset was significantly higher in the intervention group (P<.05) and significant group × time interaction was observed (Wald=11.57; P<.05) between the two groups. KWCP-SM scores increased in both groups (P<.05), with more significant changes in the intervention group.</p><p><strong>Conclusions: </strong>This study demonstrated the effectiveness of the intervention program in improving the growth mindset level of older adults with chronic diseases and bridging the \"digital divide\" among them. Future studies should refine this intervention, considering the characteristics and needs of this population, to create fault-tolerant and lifelong growth environments that enhance growth mindset in older adults.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"12 ","pages":"e65519"},"PeriodicalIF":2.6,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12244278/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144609772","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}