JMIR Human Factors最新文献

{"title":"Continuous Glucose Monitoring for Personalized Nutrition in Real-World Vively App Users: Retrospective Observational Study.","authors":"Michelle R Jospe, Kelli M Richardson, Susan M Schembre","doi":"10.2196/80734","DOIUrl":"https://doi.org/10.2196/80734","url":null,"abstract":"<p><strong>Background: </strong>The rising popularity of apps that sync with continuous glucose monitors (CGMs) reflects growing interest in on-demand, personalized care. These platforms combine real-time glucose biofeedback with self-monitored behaviors to optimize metabolic health among individuals with and without diabetes. However, little is known about user characteristics, engagement patterns, or factors associated with sustained use of CGM-integrated digital health apps in real-world settings.</p><p><strong>Objective: </strong>This study aimed to describe user demographics, CGM usage patterns, and food logging behaviors among Vively app users and to identify characteristics of sustained engagement with CGM wear and food tracking.</p><p><strong>Methods: </strong>We conducted a retrospective observational study of Vively app users between August 2021 and February 2025. Vively is a commercial digital health app that integrates with Abbott FreeStyle Libre CGMs to deliver personalized nutrition guidance. Users with at least 1 day of CGM wear were included. Primary outcomes were CGM wear duration (total days) and food logging engagement. Factors associated with engagement were identified using negative binomial regression for CGM wear and hurdle negative binomial models for food logging, adjusting for age, sex, BMI, baseline glucose, and device connectivity; the food logging model additionally adjusted for CGM wear category.</p><p><strong>Results: </strong>The analytical sample included 7647 users (4782/6905, 69.3% female, mean age 44.4, SD 10.9 years, mean BMI 27.8, SD 6.1 kg/m²). Users wore CGMs for a median of 15 (IQR 14-30) days, with 42.7% (3263/7647) completing one full wear period (13-15 days) and 30.3% (2315/7647) completing 2 or more wear periods (≥28 days). Most users (7013/7647, 91.7%) logged food at least once, with a median of 47 (IQR 18-91) food entries over 12 days. Food logging declined progressively during CGM wear (mean 63.2%, SD 8) and dropped sharply after sensor removal (mean 2.4%, SD 1.1). In multivariate models, higher baseline glucose was associated with longer CGM wear (incidence rate ratio [IRR] 1.15, 95% CI 1.13-1.17) but fewer food logging days (IRR 0.96, 95% CI 0.94-0.98). Connected device syncing showed the strongest association for both CGM wear (IRR 1.32, 95% CI 1.28-1.37) and food logging (IRR 1.45, 95% CI 1.39-1.51). Older age and female sex were associated with higher engagement in both behaviors.</p><p><strong>Conclusions: </strong>This large-scale analysis reveals distinct engagement patterns with CGM-integrated digital health applications. Food logging was largely concurrent with active CGM wear, dropping dramatically in CGM-free periods. The divergent associations of baseline glucose levels, with longer CGM wear but reduced food logging, may reflect different motivational drivers for passive monitoring versus active behavior tracking. These findings have important implications for designing sustainable digi","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e80734"},"PeriodicalIF":3.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783851","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":"Development and Usability of a Dashboard for Quality Monitoring and Resident-Centered Care in Australian Residential Long-Term Care: Mixed-Methods Study.","authors":"Ronald Dendere, Gillian Stockwell-Smith, Michelle Lang, Murray Hargrave, Sara Mayfield, Leonard Charles Gray","doi":"10.2196/80478","DOIUrl":"10.2196/80478","url":null,"abstract":"<p><strong>Background: </strong>The Australian National Aged Care Mandatory Quality Indicator Program (QI Program) requires government-subsidized residential aged care service providers to report quarterly data on a set of quality indicators. These indicators measure provider performance across specific domains of care and are intended to support continuous quality improvement. Health care dashboards can enhance the use of indicators by presenting data in interactive and intuitive formats that enable actionable insights.</p><p><strong>Objective: </strong>This mixed methods study aimed to develop an electronic dashboard to assist service providers' use of QI Program data to measure, track, and improve the quality of resident care.</p><p><strong>Methods: </strong>A participatory design methodology was used to co-design and co-develop the dashboard. Initially, stakeholder participants for the co-design were identified. A combination of workshops, meetings, and email communications with co-design participants was then used to iteratively define and refine user requirements and to develop and improve the dashboard prototype. A 3-month pilot of the dashboard was conducted with a convenience sample of 30 end-users across 12 nursing homes and a post-pilot survey based on the System Usability Scale (SUS) was used to assess end-users' perceptions of the dashboard usability.</p><p><strong>Results: </strong>The dashboard supports multiple user roles by enabling comparisons across homes and detailed views of all indicators for individual homes. A key feature is the ability to progressively view data at various levels of detail: groups of homes, individual homes, resident groups, and individual residents. The resident-level view enables more targeted, personalized care by helping staff identify and prioritize the specific indicators triggered by each resident. The average SUS score was 75.2 (SD 16.3), indicating good usability for the dashboard. Most survey respondents (12/14, 85.7%) were likely or extremely likely to recommend the dashboard to a colleague and agreed the dashboard would support the delivery of personalized care for residents. Almost all respondents (13/14) agreed or strongly agreed that the dashboard would assist with quality monitoring and improvement activities, and some pilot participants also made suggestions for incorporating the dashboard into those activities.</p><p><strong>Conclusions: </strong>This study demonstrates the potential value of a co-designed dashboard to support the use of quality indicator data in residential aged care. Limitations of the current prototype include short pilot duration, convenience sampling, and reliance on manual quarterly data uploads, which constrain generalizability and scalability. Future work should explore long-term integration of the dashboard into routine quality improvement processes and evaluate its impact on resident outcomes and care quality over time.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e80478"},"PeriodicalIF":3.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13128054/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783847","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":"Technology Acceptance of 2 mHealth Apps During an Observational Technology Evaluation Study: Qualitative Results of a Mixed Methods Study.","authors":"Johanna Graeber, Elke Warmerdam, Svenja Aufenberg, Christopher Bull, Kristen Davies, Juliane Döhring, Kirsten Emmert, Claire Judd, Corina Maetzler, Nikolay V Manyakov, Ralf Reilmann, Wan-Fai Ng, Victoria Macrae, Walter Maetzler, Hanna Kaduszkiewicz","doi":"10.2196/70873","DOIUrl":"https://doi.org/10.2196/70873","url":null,"abstract":"<p><strong>Background: </strong>Mobile health (mHealth) apps are useful tools for research and disease management. However, implementation of mHealth apps is lacking in many areas. While mHealth apps offer various advantages to researchers and patients, their effectiveness depends on their actual use. Barriers to using mHealth apps are often due to human factors such as usability or technology acceptance. Although prior studies have examined the acceptance of mHealth apps in patient treatment, the key factors driving or hindering the use of mHealth apps in research remain unclear.</p><p><strong>Objective: </strong>This study explores user perceptions of 2 mHealth apps in the setting of an observational technology evaluation study using the unified theory of acceptance and use of technology. We aim to evaluate the technology acceptance of these specific apps and to investigate challenges in choosing suitable mHealth apps in research. The apps were intended for data collection; no effect on health was expected.</p><p><strong>Methods: </strong>Patients with chronic diseases as well as healthy participants used a symptom tracking app and a cognitive test app over the course of 4 weeks within the feasibility study of the project \"Identifying Digital Endpoints to Assess Fatigue, Sleep and Activities of Daily Living in Neurodegenerative Disorders and Immune-Mediated Inflammatory Diseases.\" Thereafter, 61 qualitative interviews were conducted, recorded, and transcribed. A qualitative content analysis using the unified theory of acceptance and use of technology was performed.</p><p><strong>Results: </strong>An important aspect of motivation for participants was feedback on their health data and performance in the cognitive tests. Effort played a significant role in app use. Patients rated the apps as easy to use and quick. Using the app multiple times per day at fixed times was perceived as disruptive. Participants preferred using their own phone. Social influence as well as facilitating conditions played a lesser role in intention to use the apps. Data security was no concern for most participants. They stressed the importance of good relations with the study team.</p><p><strong>Conclusions: </strong>In choosing suitable apps, one size will certainly not fit all. For medical research, pretesting of all materials with the potential users is of utmost importance. If the positive effects of the app on users' health are not immediately apparent, other factors may motivate use, for example, feedback, gamification, adjustable functions, applicability on all smartphone operating systems, and good relations to the study team.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e70873"},"PeriodicalIF":3.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147821534","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":"On the Design of a Sign Language Corpus of Medical Terms for Automatic Translation Systems: Mixed Methods Approach.","authors":"Milena Soriano Marcolino, Luiza Marinho Motta Santa Rosa, Elidea Lucia Almeida Bernardino, Mario Fernando Montenegro Campos","doi":"10.2196/72789","DOIUrl":"10.2196/72789","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Hearing loss is a global health issue affecting millions and creating significant communication barriers, particularly in accessing health care services. These barriers can lead to complications and iatrogenic events, emphasizing the need for assistive technologies that enhance communication efficiency.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to develop a corpus of medical terms for the \"Captar-Libras\" project, designed to improve communication between health care professionals and deaf patients through a bidirectional sign language system.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study used the Delphi method to obtain consensus on key terms for a sign language translation system in health care emergency consultations. Initially, a questionnaire with common emergency questions was developed and distributed to health care professionals. The collected data were analyzed by a team of experts and adapted to Brazilian Sign Language (Língua Brasileira de Sinais [Libras]). Simulated clinical scenarios were then created to validate the system and ensure the accuracy of the vocabulary in the medical context.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Among the 16 participants, most were physicians (n=14, 87.5%) with experience in emergency care, and half had previously treated patients with hearing loss in emergency settings. The questions evaluated received high average importance scores, particularly those related to initial symptoms and pain intensity. Some suggestions for adjustments were made, with two wording modifications significantly improving clarity regarding smoking and alcohol use. Additional suggestions to enhance the medical interview were also proposed. This study aimed to identify essential questions for emergency consultations with deaf patients, focusing on developing a corpus for Libras recognition system. The findings emphasize the importance of effective communication and highlight the challenges of translating medical terms into Libras. To address these complexities, a multidisciplinary team used the Delphi method to ensure linguistic and cultural accuracy. Additionally, the study reinforces the need for clear, structured medical queries to improve accessibility in emergency care. As a next step, system validation through simulated scenarios will be conducted. Despite certain limitations, this research lays a solid foundation for advancing sign language recognition in medical settings.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This study represents a significant methodological step toward improving communication between health care professionals and deaf individuals in emergency medical settings. Rather than proposing a universal solution, the study presents a structured and participatory approach for developing a corpus of medical terms in Libras, with interdisciplinary validation. The process included the involvement of deaf sign language experts during the translation and linguistic adaptation phase, ensurin","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e72789"},"PeriodicalIF":3.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13127854/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783717","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":"Adaptation and Acceptability of a Low-Intensity Cognitive Behavioral Therapy App to Support Low Mood and Worry Management in Female Forces Veterans: Mixed Methods Study.","authors":"Paul Farrand, Andy Bacon, Melika Janbakhsh, Natalie Flay, Elizabeth Turnbull, Jonathan Baker","doi":"10.2196/84365","DOIUrl":"10.2196/84365","url":null,"abstract":"<p><strong>Background: </strong>Mental health help-seeking barriers experienced by female forces veterans result in them being underserved and underrepresented. Efforts are therefore required to adapt interventions for female veterans to enhance acceptability and maximize engagement. Given a smaller number and wider geographical distribution of female veterans, targeting adaptation efforts at a digital mobile phone app based on cognitive behavioral therapy (CBT) has potential for greatest impact to improve access to a scalable evidence-based psychological therapy.</p><p><strong>Objective: </strong>This study aimed to examine the adaptation of a low-intensity CBT app to support low mood and worry management in female forces veterans and examine acceptability and usability.</p><p><strong>Methods: </strong>Using a mixed methods methodology, this study comprises a focus group of female forces veterans to inform adaptation with extracted themes used as the basis of an adaptation framework. Following adaptation, a wider sample of female veterans was recruited to use the app and complete the mHealth App Usability Questionnaire to determine acceptability, usability, and usefulness.</p><p><strong>Results: </strong>Two main areas were identified as requiring adaptation to maximize acceptability and usability. While using imagery and quotes to reflect the armed forces was initially found helpful to initiate engagement, it was considered that continued reference to the armed forces should be dropped when progressing through the app. Most app features were found acceptable; however, adaptations were requested to the content and structure of signposting information, navigation, and the way progress was monitored. No adaptations were required, however, regarding the CBT techniques used, with specific app features motivating engagement. Following the adaptation, there were good levels of acceptability, usability, and usefulness.</p><p><strong>Conclusions: </strong>Involving female forces veterans as part of an intervention adaptation process has promise to improve acceptability and engagement with a digital CBT mobile phone intervention. Ensuring that the intervention represented the transition from serving to female forces veteran is of particular significance in enhancing acceptability.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e84365"},"PeriodicalIF":3.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13128060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783798","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 Combined Educational Methods on Motivational Interviewing for Final-Year Medical Students: Mixed Methods Study.","authors":"Isaraporn Thepwongsa, Radhakrishnan Muthukumar, Pat Nonjui","doi":"10.2196/89126","DOIUrl":"10.2196/89126","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Motivational interviewing (MI) is a patient-centered communication approach that supports health behavior change; yet, its integration into undergraduate medical curricula remains inconsistent. Combined learning models that comprise face-to-face instruction with structured web-based components may strengthen MI training, but evidence supporting their effectiveness among medical students, particularly in Asian contexts, is limited.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study evaluated the impact of a combined MI educational model on final-year medical students' MI knowledge, confidence, and application in real patient encounters during clinical rotations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study used a sequential explanatory mixed methods design. The quantitative component used a before-and-after study to evaluate changes in MI knowledge and confidence among final-year medical students enrolled in an Ambulatory Care course in 2024. All 130 students participated in a 2-hour interactive MI workshop, and 120 completed pre- and postintervention questionnaires assessing MI knowledge and self-reported confidence. Students were also provided access to a 3-hour web-based MI learning module, and learning-management system analytics were used to track engagement. The qualitative component consisted of semistructured interviews with 12 purposively selected students, conducted to explore their experiences applying MI during clinical encounters. Quantitative data were analyzed using paired-samples t tests, and qualitative data were analyzed using inductive conventional content analysis. Findings from both components were integrated during interpretation to provide a comprehensive understanding of the educational intervention.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Students demonstrated a significant improvement in MI knowledge following the educational intervention (pretest mean 8.87, SD 2.69; posttest mean 15.04, SD 2.99; t₁₁₉=-18.45; P&lt;.001; η²=0.74). After the workshop, 96.9% (126/130) of students reported applying MI with patients, and 92.3% (n=120) agreed that the combined learning approach was adequate for supporting clinical use. Learning analytics data showed that 76.9% (n=100) of students enrolled in the web-based MI module, and 51% (n=51) completed all lessons. Students most frequently applied MI when counseling patients with diabetes, hypertension, and dyslipidemia, especially related to diet, physical activity, and medication adherence. Interview findings indicated that students mainly used brief MI, were most comfortable with engaging and focusing, and developed greater empathy, confidence, and patient-centered communication skills. Challenges included limited time during consultations, clinical workload, and difficulty applying all MI processes to complex cases.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;A combined MI learning approach integrating a short workshop with a web-based course was associated with higher MI knowledg","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e89126"},"PeriodicalIF":3.0,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13128157/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147782942","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":"Evaluating a Shared Decision Support Tool for Pediatric Cardiopulmonary Arrest: Mixed Methods Usability Study.","authors":"Ana Rajic, Sharleen Kayne Olanka, Marco Generelli, Jennifer Davidson, Yiqun Lin, Ryan Kang, Kangsoo Kim, Pierre-Louis Rebours, Marc Ibrahim, Donovan Duncan, Sergio Manzano, Adam Cheng, Alexandre De Masi, Johan N Siebert, Frederic Ehrler","doi":"10.2196/78736","DOIUrl":"https://doi.org/10.2196/78736","url":null,"abstract":"<p><strong>Background: </strong>Effective team communication is critical in pediatric cardiopulmonary arrest management, where delays or miscommunication can jeopardize survival. TeamScreen, a web-based interface displayed on a large screen, was developed to enhance cardiopulmonary resuscitation (CPR) by providing real-time visualization of clinical data and resuscitation steps aligned with the American Heart Association pediatric advanced life support algorithms.</p><p><strong>Objective: </strong>This study evaluated the usability of the TeamScreen Figma prototype, evaluating how efficiently and accurately experienced emergency physicians and nurses retrieved critical information during a simulated pediatric in-hospital cardiac arrest scenario. Although no strict time constraints were imposed, participants were instructed to perform the tasks as spontaneously and as quickly as possible.</p><p><strong>Methods: </strong>Usability testing involved 20 pediatric emergency physicians and nurses with varied CPR experience. Participants performed 21 information retrieval tasks within a simulated pediatric cardiac arrest scenario (shockable rhythm). The data collected included audio-video recordings via the think-aloud method and participant responses to the Post-Study System Usability Questionnaire (PSSUQ) version 3 and a posttest survey. Effectiveness, efficiency, and satisfaction were measured by task completion rates, time-on-task metrics, and PSSUQ scores, respectively. Think-aloud data were analyzed for usability issues using Nielsen Norman Group's rating scale and Bastien and Scapin's ergonomic criteria.</p><p><strong>Results: </strong>Five physicians and 15 nurses achieved a mean task success rate of 81.19% (SD 16.87%), with a mean completion time of 8.13 (SD 7.07) seconds, calculated across all 21 tasks and all participants. PSSUQ scores reflected high satisfaction (mean 2.40 [SD 1.24] of 7.00; the lower the better), notably for information clarity and system utility. Qualitative analyses identified 16 usability issues, of which 5 were deemed major, primarily involving information visibility, navigation, and density, highlighting areas for interface and workflow enhancement.</p><p><strong>Conclusions: </strong>The usability evaluation confirmed TeamScreen's potential to improve real-time information access during pediatric CPR, with high task success and satisfaction scores supporting its role in aiding decision-making. Challenges with visibility, navigation, and information density require further refinement. These findings will guide improvements and inform the design of multicenter trials to assess TeamScreen's efficacy in simulation-based resuscitation settings.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e78736"},"PeriodicalIF":3.0,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13123637/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783770","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 Biomarkers Using a Portable, Home-Based Eye-Tracking System to Predict Short-Term Visual Fatigue Deterioration: Prospective Observational Feasibility Study.","authors":"Fan Song, Guangyu Li, Jian Zhang, Zhen Tian, Mingge Li, Mengying Lai, Mingguang He, Yanxian Chen","doi":"10.2196/84479","DOIUrl":"https://doi.org/10.2196/84479","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The escalating prevalence of screen-related eye fatigue has become a health burden in the digital era worldwide, yet routine monitoring relies largely on subjective reports. This underscores the urgent need for clinically applicable, objective diagnostic solutions. Ocular metrics provide an objective method to assess computer vision syndrome, or asthenopia.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to develop and evaluate an integrated at-home system for predicting short-term deteriorated asthenopia using objective ocular metrics. This system classifies the short-term risk level for practical monitoring and automatically generates a session report that summarizes metrics to complement symptom-based evaluation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We developed EyeFatigue Tracker, an integrated at-home system delivered via a desktop app, comprising a head-mounted device to record binocular infrared eye videos, a deep learning (DL) model to extract ocular metrics, and a machine learning (ML) classifier to estimate asthenopia risk. The DL model, trained on an in-house dataset, segments the palpebral fissure, pupil, and iris from recorded videos to derive ocular metrics. To build the prediction model, participants were recruited to complete a 1-hour computer gameplay session. Changes in the Computer Vision Syndrome Questionnaire (CVS-Q) scores served as the primary outcome measure to classify participants into deteriorated and nondeteriorated asthenopia groups. Metrics showing significant between-group differences were used as inputs for four ML models, including support vector machine (SVM), decision tree, extreme gradient boosting (XGBoost), and random forest, to identify deteriorated asthenopia. Model performance was evaluated with fivefold cross-validation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;This study enrolled 38 participants aged 19-31 (mean 24.8, SD 3.11) years. Following visual tasks, participants' CVS-Q scores were higher compared to baseline values (mean 9.21, SD 4.57, vs mean 6.76, SD 3.76; P&lt;.001). Alongside the critical flicker fusion frequency (CFF), nine key features were selected as predictive indicators, with the top five reflecting fissure length variability (variance, coefficient of variation, and SD), average blink duration, and pupil size variability (coefficient of variation). Most ML models exhibited high discriminative ability, with the random forest achieving the best overall performance (mean accuracy 0.720, SD 0.035; mean area under the receiver operating characteristic curve 0.850, 95% CI 0.830-0.860).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The findings highlight the potential of objective indicators in identifying individuals at risk for asthenopia following computer gameplay. The ML models using ocular biomarkers identified in this study achieved plausible discriminative ability in detecting deteriorated asthenopia. EyeFatigue Tracker functions as an integrated, at-home system that produces a","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e84479"},"PeriodicalIF":3.0,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147782921","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":"Enhancing Understanding and Acceptance of Equipment Localization: Mixed Methods Study With Clinic Staff and Potential Patients.","authors":"Angela Fiedler, Sabine Patzl, Melissa Schütz, Astrid Schütz","doi":"10.2196/79583","DOIUrl":"https://doi.org/10.2196/79583","url":null,"abstract":"<p><strong>Background: </strong>Digital technologies, such as equipment localization systems, can help clinics use mobile devices more efficiently. Their successful implementation, however, depends not only on technical feasibility but also on how staff and patients perceive and understand these systems.</p><p><strong>Objective: </strong>This research used 2 complementary studies to (1) obtain an initial picture of clinic staff attitudes toward the localization of vacuum-assisted closure (VAC) pumps and related concerns and (2) examine whether a simple layout change in a privacy policy (using guiding questions vs standard text) is associated with greater subjective understanding and acceptance among potential patients.</p><p><strong>Methods: </strong>In study 1, 38 employees of a German clinic completed a short survey assessing their comfort with and perceived usefulness of VAC pump localization and answered an open-ended question about reservations or concerns. Quantitative responses were analyzed descriptively, and free-text answers were coded using qualitative content analysis. In study 2, 498 participants from an online sample took part in a preregistered experiment. They were randomly assigned to read either a standard privacy policy information sheet or an otherwise identical version supplemented with guiding questions. Subjective understanding of the information and acceptance of the policy were then assessed and analyzed using rank-based regression models controlling for sociodemographic covariates.</p><p><strong>Results: </strong>Clinic staff in study 1 generally reported high levels of comfort (mean 7.34, SD 2.75) and perceived usefulness (mean 7.29, SD 2.69) regarding localization on 0-10 scales. Concerns centered mainly on implementation feasibility, technical reliability, costs, and possible additional workload, rather than on privacy. In study 2, subjective understanding was slightly higher in the guiding-question layout condition than in the standard layout condition (mean 3.37, SD 0.63 [n=248] vs mean 3.24, SD 0.68 [n=250]); this difference was also significant in the rank-based regression model (b=0.13, SE=0.05, t=2.57; P=.01), and better understanding was associated with higher acceptance of the policy, explaining about 13.8% of the variance in acceptance scores.</p><p><strong>Conclusions: </strong>The exploratory findings suggest that, in the context of VAC pump localization, clinic staff generally view equipment tracking positively while still raising practical concerns that should be addressed during implementation. For potential patients, relatively small changes in the layout of privacy information-such as adding guiding questions-may support subjective understanding and willingness to accept data collection.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e79583"},"PeriodicalIF":3.0,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13117219/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783815","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":"Grip Strength Estimation Using Input Data From a Commodity Smartphone: Model Development and Validation Study.","authors":"Komei Tajima, Kaori Ikematsu, Toshiya Isomoto, Kunihiro Kato, Yuta Sugiura","doi":"10.2196/90316","DOIUrl":"10.2196/90316","url":null,"abstract":"<p><strong>Background: </strong>Grip strength is a crucial indicator of muscle deterioration, recovery, sarcopenia, and neurological disorders. However, conventional measurement requires a dedicated dynamometer, which limits accessibility and requires specific movements.</p><p><strong>Objective: </strong>This study aimed to propose and validate a method for estimating grip strength using standard smartphone operations, thereby eliminating the need for specialized equipment.</p><p><strong>Methods: </strong>Data were collected from 21 young adults in the main experiment, who performed standard smartphone tasks (tapping, flicking, and dragging) after measuring their grip strength with a dynamometer. A predictive regression model was developed using touch and inertial sensor data. The model was first evaluated using a random split of the entire dataset (random split evaluation). To further assess practical feasibility and generalizability, we conducted leave-one-user-out validation and a few-day calibration validation; the latter simulated a calibration scenario by incorporating 1 to 4 days of user-specific data into the training set.</p><p><strong>Results: </strong>The regression analysis using a random split of the dataset demonstrated high accuracy, with a mean absolute error of 2.62 (SD 0.18) kg, a mean absolute percentage error (MAPE) of 8.91% (SD 0.57%), and a coefficient of determination of 0.802 (SD 0.036). In the validation of practical scenarios, the leave-one-user-out validation resulted in a MAPE of 15.08% (SD 5.40%). However, the personalized few-day calibration model showed significant improvements as calibration days increased, with the MAPE decreasing to 13.96% (SD 5.57%) after 1 day and reaching 11.64% (SD 5.80%) after 4 days. Furthermore, the National Aeronautics and Space Administration Task Load Index assessment indicated a low overall subjective workload (mean 3.04, SD 2.23 on a scale of 10), confirming the method's suitability for daily use without a significant burden on users.</p><p><strong>Conclusions: </strong>The proposed method demonstrates that smartphones can serve as a viable, pervasive tool for daily grip strength monitoring, offering a convenient alternative to traditional dynamometers.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e90316"},"PeriodicalIF":3.0,"publicationDate":"2026-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13153751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147821459","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}