JMIR Formative Research最新文献

{"title":"Usability and Usefulness of a Symptom Management Coaching System for Patients With Cancer Treated With Immune Checkpoint Inhibitors: Comparative Mixed Methods Study.","authors":"Savannah Lucia Caterina Glaser, Itske Fraterman, Noah van Brummelen, Valentina Tibollo, Laura Maria Del Campo, Henk Mallo, Sofie Wilgenhof, Szymon Wilk, Vitali Gisko, Vadzim Khadakou, Ronald Cornet, Manuel Ottaviano, Stephanie Medlock","doi":"10.2196/57659","DOIUrl":"https://doi.org/10.2196/57659","url":null,"abstract":"<p><strong>Background: </strong>The prognosis for patients with several types of cancer has substantially improved following the introduction of immune checkpoint inhibitors, a novel type of immunotherapy. However, patients may experience symptoms both from the cancer itself and from the medication. A prototype of the eHealth tool Cancer Patients Better Life Experience (CAPABLE) was developed to facilitate symptom management, aimed at patients with melanoma and renal cell carcinoma treated with immunotherapy. Better usability of such eHealth tools can lead to improved user well-being and reduced risk of harm. It is unknown for usability evaluations whether certain usability problems would only be evident to patients whose condition closely resembles the target population, or if a broader group of patients would lead to the identification of a broader range of potential usability issues.</p><p><strong>Objective: </strong>This study aims to evaluate the CAPABLE prototype by conducting tests to assess usability, user experience, and perceived acceptability among end users, and to assess any agreements or differences in the results of our wide range of participants.</p><p><strong>Methods: </strong>This usability study was executed by interviewing participants with a melanoma or renal cell carcinoma diagnosis who have received immunotherapy and participants without direct experience with the targeted cancer types who have not received immunotherapy. Participants were asked to review the concept of the tool, perform think-aloud tasks, and complete the System Usability Scale and a Perceived Usefulness questionnaire. Usability problems were extracted from the interview data by independent coding and mapped to an eHealth Usability Problem Framework.</p><p><strong>Results: </strong>We included 21 participants in the study, aged 29 to 73 years; 13 participants who had received immunotherapy and 8 participants who had not received immunotherapy. In total, 76 usability problems were identified. A total of 22 usability problems were in the task-technology fit category of the usability framework, mostly regarding the coaching and symptom functionality of the prototype. Critical problems regarding the symptom monitoring functionality were mainly found by participants who had received immunotherapy. For 8 out of 10 statements in the Perceived Usefulness questionnaire, more than 75% of participants agreed or strongly agreed. The overall mean System Usability Scale score was 80 out of 100 (SD 11.3).</p><p><strong>Conclusions: </strong>Despite identified usability issues, participants responded positively to the Perceived Usefulness questionnaire regarding the evaluated tool. Further analysis of the usability problems indicates that it was essential to include participants who matched the target end users. Participants treated with immunotherapy, specifically with previous experience in immune-related adverse events, encountered critical problems with symptom report","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e57659"},"PeriodicalIF":2.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143028720","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":"Use of Go-Beyond as a Self-Directed Internet-Based Program Supporting Veterans' Transition to Civilian Life: Preliminary Usability Study.","authors":"Karolina Katarzyna Alichniewicz, Sarah Hampton, Madeline Romaniuk, Darcy Bennett, Camila Guindalini","doi":"10.2196/60868","DOIUrl":"10.2196/60868","url":null,"abstract":"<p><strong>Background: </strong>The transition from military service to civilian life presents a variety of challenges for veterans, influenced by individual factors such as premilitary life, length of service, and deployment history. Mental health issues, physical injuries, difficulties in relationships, and identity loss compound the reintegration process. To address these challenges, various face-to-face and internet-based programs are available yet underused. This paper presents the preliminary evaluation of \"Go-Beyond, Navigating Life Beyond Service,\" an internet-based psychoeducational program for veterans.</p><p><strong>Objective: </strong>The study aims to identify the reach, adoption, and engagement with the program and to generate future recommendations to enhance its overall impact.</p><p><strong>Methods: </strong>This study exclusively used data that were automatically and routinely collected from the start of the Go-Beyond program's launch on May 24, 2021, until May 7, 2023. When accessing the Go-Beyond website, veterans were asked to complete the Military-Civilian Adjustment and Reintegration Measure (M-CARM) questionnaire, which produces a unique M-CARM profile of results specifying potential areas of need on the 5 domains of the measure. Users were then automatically allocated to Go-Beyond modules that aligned with their M-CARM profile. Additionally, quantitative and qualitative data were collected from a survey on aesthetics, interactivity, user journey, and user experience, which was optional for users to complete at the end of each module.</p><p><strong>Results: </strong>Results show a conversion rate of 28.5% (273/959) from the M-CARM survey to the Go-Beyond program. This rate is notably higher compared with similar internet-based self-help programs, such as VetChange (1033/22,087, 4.7%) and resources for gambling behavior (5652/8083, 14%), but lower than the MoodGYM program (82,159/194,840, 42.2%). However, these comparisons should be interpreted with caution due to the limited availability of published conversion rates and varying definitions of uptake and adoption across studies. Additionally, individuals were 1.64 (95% CI 1.17-2.28) more likely to enroll when they express a need in Purpose and Connection, and they were 1.50 (95% CI 1.06-2.18) times more likely to enroll when they express the need Beliefs About Civilians, compared with those without these needs. The overall completion rate for the program was 31% (85/273) and modules' individual completion rates varied from 8.4% (17/203) to 20% (41/206). Feedback survey revealed high overall user satisfaction with Go-Beyond, emphasizing its engaging content and user-friendly modules. Notably, 94% (88/94) of survey respondents indicated they would recommend the program to other veterans, family, or friends.</p><p><strong>Conclusions: </strong>The Go-Beyond program may offer promising support for veterans transitioning to civilian life through digital technology. Our study re","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e60868"},"PeriodicalIF":2.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143023351","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":"Improving Mental Health and Well-Being Through the Paradym App: Quantitative Study of Real-World Data.","authors":"Athina Marina Metaxa, Shaun Liverpool, Mia Eisenstadt, John Pollard, Courtney Carlsson","doi":"10.2196/68031","DOIUrl":"https://doi.org/10.2196/68031","url":null,"abstract":"<p><strong>Background: </strong>With growing evidence suggesting that levels of emotional well-being have been decreasing globally over the past few years, demand for easily accessible, convenient, and affordable well-being and mental health support has increased. Although mental health apps designed to tackle this demand by targeting diagnosed conditions have been shown to be beneficial, less research has focused on apps aiming to improve emotional well-being. There is also a dearth of research on well-being apps structured around users' lived experiences and emotional patterns and a lack of integration of real-world evidence of app usage. Thus, the potential benefits of these apps need to be evaluated using robust real-world data.</p><p><strong>Objective: </strong>This study aimed to explore usage patterns and preliminary outcomes related to mental health and well-being among users of an app (Paradym; Paradym Ltd) designed to promote emotional well-being and positive mental health.</p><p><strong>Methods: </strong>This is a pre-post, single-arm evaluation of real-world data provided by users of the Paradym app. Data were provided as part of optional built-in self-assessments that users completed to test their levels of depression (Patient Health Questionnaire-9), anxiety (Generalized Anxiety Disorder Questionnaire-7), life satisfaction (Satisfaction With Life Scale), and overall well-being (World Health Organization-5 Well-Being Index) when they first started using the app and at regular intervals following initial usage. Usage patterns, including the number of assessments completed and the length of time between assessments, were recorded. Data were analyzed using within-subjects t tests, and Cohen d estimates were used to measure effect sizes.</p><p><strong>Results: </strong>A total of 3237 app users completed at least 1 self-assessment, and 787 users completed a follow-up assessment. The sample was diverse, with 2000 users (61.8%) being located outside of the United States. At baseline, many users reported experiencing strong feelings of burnout (677/1627, 41.6%), strong insecurities (73/211, 34.6%), and low levels of thriving (140/260, 53.8%). Users also experienced symptoms of depression (mean 9.85, SD 5.55) and anxiety (mean 14.27, SD 6.77) and reported low levels of life satisfaction (mean 12.14, SD 7.42) and general well-being (mean 9.88, SD 5.51). On average, users had been using the app for 74 days when they completed a follow-up assessment. Following app usage, small but significant improvements were reported across all outcomes of interest, with anxiety and depression scores improving by 1.20 and 1.26 points on average, respectively, and life satisfaction and well-being scores improving by 0.71 and 0.97 points, respectively.</p><p><strong>Conclusions: </strong>This real-world data analysis and evaluation provided positive preliminary evidence for the Paradym app's effectiveness in improving mental health and well-being, supporting it","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e68031"},"PeriodicalIF":2.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143028715","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":"Characterizing Telehealth Barriers and Preferences to Promote Acceptable Implementation Strategies in Central Uganda: Multilevel Formative Evaluation.","authors":"Michael Kizito, Erina Nabunjo Mugabi, Sabrina Ford, Bree Holtz, Kelly Hirko","doi":"10.2196/60843","DOIUrl":"https://doi.org/10.2196/60843","url":null,"abstract":"<p><strong>Background: </strong>Telehealth approaches can address health care access barriers and improve care delivery in resource-limited settings around the globe. Yet, telehealth adoption in Africa has been limited, due in part to an insufficient understanding of effective strategies for implementation.</p><p><strong>Objective: </strong>This study aimed to conduct a multi-level formative evaluation identifying barriers and facilitators for implementing telehealth among health service providers and patients in Central Uganda.</p><p><strong>Methods: </strong>We collected surveys characterizing telehealth perceptions, barriers, and preferences from health care providers and patients seeking primary care in the Central Region of Uganda from January 2022 to July 2022. Survey development was informed by the technology acceptance model and evaluated predictors of technology acceptance (ie, perceived usefulness, ease of use, and attitudes). We used descriptive statistics to characterize telehealth perceptions and examined differences according to provider and patient characteristics using Student t tests.</p><p><strong>Results: </strong>Nearly 79% (n=48) of 61 providers surveyed had used telehealth, and perceptions were generally favorable. While 93.4% (n=57) reported that telehealth adds value to clinical practice, less than half (n=30, 49.2%) felt telehealth was more efficient than in-person visits. Provider-reported barriers to telehealth included technology challenges for the patient (34/132, 26%), low patient engagement (25/132, 19%), and lack of implementation support (24/132, 18%). Telehealth use was lower among the 91 surveyed patients, with only 19.8% (n=18) having used telehealth. Although 89% (n=81) of patients reported saving time with telehealth approaches, 33.3% (n=30) of patients reported that telehealth made them feel uncomfortable, and 43.8% (n=39) reported concerns about confidentiality. Over 72% (n=66) of patients who had used telehealth previously reported satisfaction with the telehealth services they received. Several differences in perceptions of telehealth according to patient's self-reported health status were observed.</p><p><strong>Conclusions: </strong>Perceptions of telehealth were generally favorable, although higher among providers than patients. Barriers impeding telehealth use include technology challenges and the lack of infrastructure and implementation support. Findings from this study can inform the implementation of acceptable telehealth approaches to address disparities propagated by health care access barriers in Sub-Saharan Africa.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e60843"},"PeriodicalIF":2.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046835","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":"The Association of Psychological Factors With Willingness to Share Health-Related Data From Technological Devices: Cross-Sectional Questionnaire Study.","authors":"Marijn Eversdijk, Emma Rixt Douma, Mirela Habibovic, Willem Johan Kop","doi":"10.2196/64244","DOIUrl":"https://doi.org/10.2196/64244","url":null,"abstract":"<p><strong>Background: </strong>Health-related data from technological devices are increasingly obtained through smartphone apps and wearable devices. These data could enable physicians and other care providers to monitor patients outside the clinic or assist individuals in improving lifestyle factors. However, the use of health technology data might be hampered by the reluctance of patients to share personal health technology data because of the privacy sensitivity of this information.</p><p><strong>Objective: </strong>This study investigates to what extent psychological factors play a role in people's willingness to share personal health technology data.</p><p><strong>Methods: </strong>Data for this cross-sectional study were obtained by quota sampling based on age and sex in a community-based sample (N=1013; mean age 48.6, SD 16.6 years; 522/1013, 51.5% women). Willingness to share personal health technology data and related privacy concerns were assessed using an 8-item questionnaire with good psychometric properties (Cronbach's α=0.82). Psychological variables were assessed using validated questionnaires for optimism (Life Orientation Test-Revised), psychological flexibility (Psychological Flexibility Questionnaire), negative affectivity (Type D Scale-14-Negative Affectivity), social inhibition (Type D Scale-14-Social Inhibition), generalized anxiety (Generalized Anxiety Disorder-7), and depressive symptoms (Patient Health Questionnaire-9). Data were analyzed using multiple linear regression analyses, and network analysis was used to visualize the associations between the item scores.</p><p><strong>Results: </strong>Higher levels of optimism (β=.093; P=.004) and psychological flexibility (β=.127; P<.001) and lower levels of social inhibition (β=-.096; P=.002) were significantly associated with higher levels of willingness to share health technology data when adjusting for age, sex, and education level in separate regression models. Other associations with psychological variables were not statistically significant. Network analysis revealed that psychological flexibility clustered more with items that focused on the benefits of sharing data, while optimism was negatively associated with privacy concerns.</p><p><strong>Conclusions: </strong>The current results suggest that people with higher levels of optimism and psychological flexibility and those with lower social inhibition levels are more likely to share health technology data. The magnitude of the effect sizes was low, and future studies with additional psychological measures are needed to establish which factors identify people who are reluctant to share their data such that optimal use of devices in health care can be facilitated.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e64244"},"PeriodicalIF":2.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046946","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 of the Big Ten Academic Alliance Collaborative for Women in Medicine and Biomedical Science: \"We Built the Airplane While Flying It\".","authors":"Maya S Iyer, Aubrey Moe, Susan Massick, Jessica Davis, Megan Ballinger, Kristy Townsend","doi":"10.2196/65561","DOIUrl":"https://doi.org/10.2196/65561","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Unlabelled: &lt;/strong&gt;Women-identifying and women+ gender faculty (hereto described as women+ faculty) face numerous barriers to career advancement in medicine and biomedical sciences. Despite accumulating evidence that career development programming for women+ is critical for professional advancement and well-being, accessibility of these programs is generally limited to small cohorts, only offered to specific disciplines, or otherwise entirely unavailable. Opportunities for additional, targeted career development activities are imperative in developing and retaining women+ faculty. Our goal was the development of a new collaborative of Big Ten Academic Alliance (BTAA) institutions to support gender equity for women+ faculty in medicine and biomedical sciences, with two initial aims: (1) hosting an inaugural conference and establishing a foundation for rotation of conference hosts across BTAA schools, and (2) creating an infrastructure to develop programming, share resources, conduct environmental scans, and promote networking. In 2022, leaders from The Ohio State University College of Medicine Women in Medicine and Science envisioned, developed, and implemented a collaborative named CommUNITYten: The Big Ten Academic Alliance for Women in Medicine and Biomedical Science. Conference program development occurred through an iterative and collaborative process across external and internal task forces alongside industry partners. We developed a fiscal model to guide registration fees, budget tracking, and solicitation of conference funding from academic and industry sponsors. Attendees completed postconference surveys assessing speaker or workshop effectiveness and suggestions for future events. Finally, we developed an environmental scan survey to assess gender equity needs and existing programming across BTAA institutions. In June 2024, The Ohio State University hosted the inaugural CommUNITYten conference in Columbus, Ohio, featuring 5 keynote presentations, 9 breakout sessions, and networking opportunities across one and a half days of curated programming. Nearly 180 people attended, with representation from 9 BTAA institutions, 6 industry companies, staff, and trainees. Postconference surveys showed 50% (n=27) of respondents were likely to attend another in-person conference and suggested future conference topics. The environmental scan survey launched in October 2024. We successfully established the CommUNITYten collaborative and hosted the inaugural conference. Establishing key stakeholders from each BTAA institution, obtaining sponsorship, and detailed conference planning and partnerships were critical in ensuring realization of this collaborative. The conference brought together leaders, faculty, staff, trainees, and industry partners from across the country and met the initial goal of networking, sharing resources, and building community for women+ faculty. These efforts lay a robust foundation for the BTAA CommUNITYten collabora","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e65561"},"PeriodicalIF":2.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046759","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":"Identifying the Minimal Clinically Important Difference in Emotion Regulation Among Youth Using the JoyPop App: Survey Study.","authors":"Jaidyn Charlton, Ishaq Malik, Angela M Ashley, Amanda Newton, Elaine Toombs, Fred Schmidt, Janine V Olthuis, Kristine Stasiuk, Tina Bobinski, Aislin Mushquash","doi":"10.2196/64483","DOIUrl":"10.2196/64483","url":null,"abstract":"<p><strong>Background: </strong>The minimal clinically important difference (MCID) is an important threshold to consider when evaluating the meaningfulness of improvement following an intervention. The JoyPop app is an evidence-based smartphone app designed to improve resilience and emotion regulation. Information is needed regarding the JoyPop app's MCID among culturally diverse youth.</p><p><strong>Objective: </strong>This study aims to calculate the MCID for youth using the JoyPop app and to explore how the MCID may differ for a subset of Indigenous youth.</p><p><strong>Methods: </strong>Youth (N=36; aged 12-18 years) were recruited to use the JoyPop app for up to 4 weeks as part of a larger pilot evaluation. Results were based on measures completed after 2 weeks of app use. The MCID was calculated using emotion regulation change scores (Difficulties in Emotion Regulation-Short Form [DERS-SF]) and subjective ratings on the Global Rating of Change Scale (GRCS). This MCID calculation was completed for youth overall and separately for Indigenous youth only.</p><p><strong>Results: </strong>A significant correlation between GRCS scores and change scores on the DERS-SF supported face validity (r=-0.37; P=.04). The MCID in emotion regulation following the use of the JoyPop app for youth overall was 2.80 on the DERS-SF. The MCID for Indigenous youth was 4.29 on the DERS-SF. In addition, most youth reported improved emotion regulation after using the JoyPop app.</p><p><strong>Conclusions: </strong>These MCID findings provide a meaningful threshold for improvement in emotion regulation for the JoyPop app. They provide potential effect sizes and can aid in sample size estimations for future research with the JoyPop app or e-mental health technologies in general. The difference between overall youth and Indigenous youth MCID values also highlights the importance of patient-oriented ratings of symptom improvement as well as cultural considerations when conducting intervention research and monitoring new interventions in clinical practice.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e64483"},"PeriodicalIF":2.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143023600","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":"Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study.","authors":"Stanford Martinez, Carolina Ramirez-Tamayo, Syed Hasib Akhter Faruqui, Kal Clark, Adel Alaeddini, Nicholas Czarnek, Aarushi Aggarwal, Sahra Emamzadeh, Jeffrey R Mock, Edward J Golob","doi":"10.2196/53928","DOIUrl":"https://doi.org/10.2196/53928","url":null,"abstract":"<p><strong>Background: </strong>Perception-related errors comprise most diagnostic mistakes in radiology. To mitigate this problem, radiologists use personalized and high-dimensional visual search strategies, otherwise known as search patterns. Qualitative descriptions of these search patterns, which involve the physician verbalizing or annotating the order he or she analyzes the image, can be unreliable due to discrepancies in what is reported versus the actual visual patterns. This discrepancy can interfere with quality improvement interventions and negatively impact patient care.</p><p><strong>Objective: </strong>The objective of this study is to provide an alternative method for distinguishing between radiologists by means of captured eye-tracking data such that the raw gaze (or processed fixation data) can be used to discriminate users based on subconscious behavior in visual inspection.</p><p><strong>Methods: </strong>We present a novel discretized feature encoding based on spatiotemporal binning of fixation data for efficient geometric alignment and temporal ordering of eye movement when reading chest x-rays. The encoded features of the eye-fixation data are used by machine learning classifiers to discriminate between faculty and trainee radiologists. A clinical trial case study was conducted using metrics such as the area under the curve, accuracy, F₁-score, sensitivity, and specificity to evaluate the discriminability between the 2 groups regarding their level of experience. The classification performance was then compared with state-of-the-art methodologies. In addition, a repeatability experiment using a separate dataset, experimental protocol, and eye tracker was performed with 8 participants to evaluate the robustness of the proposed approach.</p><p><strong>Results: </strong>The numerical results from both experiments demonstrate that classifiers using the proposed feature encoding methods outperform the current state-of-the-art in differentiating between radiologists in terms of experience level. An average performance gain of 6.9% is observed compared with traditional features while classifying experience levels of radiologists. This gain in accuracy is also substantial across different eye tracker-collected datasets, with improvements of 6.41% using the Tobii eye tracker and 7.29% using the EyeLink eye tracker. These results signify the potential impact of the proposed method for identifying radiologists' level of expertise and those who would benefit from additional training.</p><p><strong>Conclusions: </strong>The effectiveness of the proposed spatiotemporal discretization approach, validated across diverse datasets and various classification metrics, underscores its potential for objective evaluation, informing targeted interventions and training strategies in radiology. This research advances reliable assessment tools, addressing challenges in perception-related errors to enhance patient care outcomes.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e53928"},"PeriodicalIF":2.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143023596","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":"Attitudes of German General Practitioners Toward eHealth Apps for Dementia Risk Reduction: Qualitative Interview Study.","authors":"Adrian Schultz, Melanie Luppa, Markus Bleckwenn, Steffi G Riedel-Heller, Andrea Zuelke","doi":"10.2196/56310","DOIUrl":"https://doi.org/10.2196/56310","url":null,"abstract":"<p><strong>Background: </strong>eHealth interventions constitute a promising approach to disease prevention, particularly because of their ability to facilitate lifestyle changes. Although a rather recent development, eHealth interventions might be able to promote brain health and reduce dementia risk in older adults.</p><p><strong>Objective: </strong>This study aimed to explore the perspective of general practitioners (GPs) on the potentials and barriers of eHealth interventions for brain health. Understanding the perspective of GPs allows us to identify chances and challenges for implementing eHealth apps for dementia risk reduction.</p><p><strong>Methods: </strong>We conducted semistructured expert interviews with 9 GPs working in an outpatient setting in and near Leipzig, Germany. Data were fully transcribed and analyzed using a process model of qualitative content analysis with codes and categories being constructed inductively and deductively.</p><p><strong>Results: </strong>We found generally favorable but balanced views of eHealth apps for brain health. Eight themes were identified and elaborated on in the data as follows: \"addressing dementia,\" \"knowledge about dementia,\" \"need for information,\" \"potential for prevention,\" \"chances for apps for prevention,\" \"development of apps for prevention,\" and \"barriers of apps for prevention.\" GPs talked mostly about how and when to address dementia and the requirements for their use of eHealth apps for dementia prevention. GPs stated that they only addressed dementia once abnormalities were already present or less frequently when a patient or relative expressed a direct wish, while individual dementia risk or standardized diagnostic during routine check-ups were mentioned much less frequently. According to GPs, knowledge about dementia in patients was low; therefore, patients expressed little need for information on dementia risk factors and prevention in GP practices. Most patients wished for quick information regarding diagnostics, treatment options, and progression of the disease. GPs mentioned a lack of overview of the available eHealth apps and their content. They also expressed a fear of inducing health anxiety when talking to patients about risk factors and prevention.</p><p><strong>Conclusions: </strong>GPs want patients to receive relevant and individualized information. Prerequisites for the use of eHealth apps for dementia prevention were app characteristics related to design and content. GPs need to address dementia more routinely, assess relevant risk factors, and aid patients in a preventive role. Concerns were expressed over limited effectiveness, overwhelming patients, limited use in clinical practice, and only targeting patients with an already low risk of dementia.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e56310"},"PeriodicalIF":2.0,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143023555","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":"AI Machine Learning-Based Diabetes Prediction in Older Adults in South Korea: Cross-Sectional Analysis.","authors":"Hocheol Lee, Myung-Bae Park, Young-Joo Won","doi":"10.2196/57874","DOIUrl":"https://doi.org/10.2196/57874","url":null,"abstract":"<p><strong>Background: </strong>Diabetes is prevalent in older adults, and machine learning algorithms could help predict diabetes in this population.</p><p><strong>Objective: </strong>This study determined diabetes risk factors among older adults aged ≥60 years using machine learning algorithms and selected an optimized prediction model.</p><p><strong>Methods: </strong>This cross-sectional study was conducted on 3084 older adults aged ≥60 years in Seoul from January to November 2023. Data were collected using a mobile app (Gosufit) that measured depression, stress, anxiety, basal metabolic rate, oxygen saturation, heart rate, and average daily step count. Health coordinators recorded data on diabetes, hypertension, hyperlipidemia, chronic obstructive pulmonary disease, percent body fat, and percent muscle. The presence of diabetes was the target variable, with various health indicators as predictors. Machine learning algorithms, including random forest, gradient boosting model, light gradient boosting model, extreme gradient boosting model, and k-nearest neighbors, were employed for analysis. The dataset was split into 70% training and 30% testing sets. Model performance was evaluated using accuracy, precision, recall, F1 score, and area under the curve (AUC). Shapley additive explanations (SHAPs) were used for model interpretability.</p><p><strong>Results: </strong>Significant predictors of diabetes included hypertension (χ²1=197.294; P<.001), hyperlipidemia (χ²1=47.671; P<.001), age (mean: diabetes group 72.66 years vs nondiabetes group 71.81 years), stress (mean: diabetes group 42.68 vs nondiabetes group 41.47; t3082=-2.858; P=.004), and heart rate (mean: diabetes group 75.05 beats/min vs nondiabetes group 73.14 beats/min; t3082=-7.948; P<.001). The extreme gradient boosting model (XGBM) demonstrated the best performance, with an accuracy of 84.88%, precision of 77.92%, recall of 66.91%, F1 score of 72.00, and AUC of 0.7957. The SHAP analysis of the top-performing XGBM revealed key predictors for diabetes: hypertension, age, percent body fat, heart rate, hyperlipidemia, basal metabolic rate, stress, and oxygen saturation. Hypertension strongly increased diabetes risk, while advanced age and elevated stress levels also showed significant associations. Hyperlipidemia and higher heart rates further heightened diabetes probability. These results highlight the importance and directional impact of specific features in predicting diabetes, providing valuable insights for risk stratification and targeted interventions.</p><p><strong>Conclusions: </strong>This study focused on modifiable risk factors, providing crucial data for establishing a system for the automated collection of health information and lifelog data from older adults using digital devices at service facilities.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e57874"},"PeriodicalIF":2.0,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143005703","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}