JMIR Formative Research最新文献

{"title":"Economic Deterioration and Social Factors Affecting Mental Health During the COVID-19 Pandemic in Japan: Web-Based Cross-Sectional Survey.","authors":"Kentaro Hori, Yosuke Yamada, Hideyuki Namba, Misaka Kimura, Hiroyuki Fujita, Heiwa Date","doi":"10.2196/65204","DOIUrl":"10.2196/65204","url":null,"abstract":"<p><strong>Background: </strong>The socioeconomic impact of the COVID-19 pandemic has severely affected individuals' mental health. However, the factors that mitigate or exacerbate the mental health effects of economic deterioration remain underexplored.</p><p><strong>Objective: </strong>This paper analyzes survey data from the second wave of the COVID-19 pandemic in Japan, a period during which women workers were reported to be economically and psychologically vulnerable. The analysis examined factors that mitigate or amplify the impact of COVID-19-induced economic deterioration on mental health, testing 3 hypotheses based on the conservation of resources theory and the stress buffering model: the negative impact of economic deterioration on mental health is greater for individuals with less social support compared to those with more social support (hypothesis 1); the negative impact of economic deterioration on mental health is greater for individuals experiencing more negative interactions compared to those experiencing fewer (hypothesis 2); and the buffering effect of social support is stronger in women than in men, with women receiving less social support experiencing greater mental health impacts from economic deterioration (hypothesis 3).</p><p><strong>Methods: </strong>A web-based survey was conducted by an internet research company in Japan from June to July 2020. A balanced sample of 250 men and 250 women was recruited from each of the following age groups: 20-29, 30-39, 40-49, 50-59, 60-69, and 70-79 years. The analysis focused on working men and women aged 20-50 years (n=1238). Psychological distress was measured using the K6 scale. Economic deterioration was defined as a decrease in income compared to the prepandemic levels, and scales for social support and negative interactions were included. Logistic regression analysis was performed, using K6≥9 as the dependent variable, with interaction terms for each hypothesis sequentially incorporated.</p><p><strong>Results: </strong>In the best-fitting model determined by the Bayesian Information Criterion, a significant association was observed between the interaction of COVID-19-induced economic deterioration and social support with K6 scores (odds ratio [OR] 0.90, 95% CI 0.81-0.99). However, in other models, the interaction between economic deterioration and negative interactions (OR 1.01, 95% CI 0.90-1.13) as well as the 3-way interaction involving economic deterioration, social support, and gender (OR 1.13, 95%CI 0.92-1.39) were not significant. The average marginal effect of economic deterioration was statistically significant for social support scores ranging from 4 to 10. The average marginal effect was 0.11 when social support was 4 (95% CI 0.03-1.20; P=.009) and 0.028 when social support was 10 (95% CI 0.00-0.06; P=.047).</p><p><strong>Conclusions: </strong>The adverse impact of economic deterioration on mental health was more pronounced among individuals with lower levels of socia","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e65204"},"PeriodicalIF":2.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12173149/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144266289","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":"Caregivers' Perceptions of Clinical Symptoms, Disease Management, and Quality of Life Impact in Cases of Cyclin-Dependent Kinase-Like 5 Deficiency Disorder: Cross-Sectional Online Survey.","authors":"Sam Amin, Carol-Anne Partridge, Helen Leonard, Jenny Downs, Helen Allvin, Valentine Ficara, Emilie Pain, Minna A Korolainen","doi":"10.2196/72489","DOIUrl":"10.2196/72489","url":null,"abstract":"<p><strong>Background: </strong>Cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD) is an ultrarare genetic condition causing developmental epileptic encephalopathy characterized by seizures and motor and intellectual disabilities. No disease-modifying therapies are available, and treatments focus mainly on symptom management to improve quality of life.</p><p><strong>Objective: </strong>The aim of this study was to better understand the burden of CDD based on family caregivers' perceptions.</p><p><strong>Methods: </strong>The study was a cross-sectional, web-based survey comprising 40 questions for caregivers of patients with CDD and focusing on sociodemographic and medical characteristics, disease burden, unmet needs, treatments, and support. An adapted version of the EQ-5D-5L instrument was included to measure patients' health-related quality of life as perceived by their caregivers.</p><p><strong>Results: </strong>A total of 132 caregivers, mostly from western parts of Europe, responded. The median patient age was 7.6 (IQR 2.9-12.2) years. Seizure onset occurred early, with the median onset at 2.0 (IQR 1.0-3.0) months of age. The median age at diagnosis was 1.2 (IQR 0.6-4.0) years. Epilepsy (123/132, 93.2%) and limited communication skills (111/132, 84.1%) were the most commonly reported symptoms. The highest number of different types of symptoms was reported for patients aged 5-9 years, with a median of 9.0 (IQR 7.5-10.0) symptoms. Most patients with epilepsy experienced daily seizures (81/123, 65.9%), and nearly all (119/123, 96.7%) were on antiseizure medications. A minority was on a ketogenic diet (21/123, 17.1%) or underwent vagus nerve stimulation (14/123, 11.4%). The care received was multidisciplinary. Compared to younger patients, adults had fewer medical appointments and a smaller variety of health care professionals in their care team. The EQ-5D-5L, adapted for caregivers, indicated low health-related quality of life for patients, with a median global index value of 0.18 (IQR 0.11-0.32). The most severe consequences of CDD on patients' daily lives were reported for mobility (88/132, 66.7%), self-care (120/132, 90.9%), and everyday activities (103/132, 78.0%). Caregiver burden was also substantial, with all life aspects reportedly impacted by CDD, including professional life and financial resources (median impact ratings of 9.0/10 and 7.0/10, respectively). Access to support and care varied depending on location. Caregivers outside Europe reported a longer time between the first seizure and diagnosis (26.5, IQR 3.2-47.0 months) compared to European caregivers (11.0, IQR 5.0-45.0 months). They also reported a higher impact of CDD on their financial resources (rating of 10/10) compared to European caregivers (rating of 6/10) and greater challenges in covering costs.</p><p><strong>Conclusions: </strong>The study findings provide valuable insights on symptoms and disease burden related to CDD. This burden was quantitatively ","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e72489"},"PeriodicalIF":2.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12188142/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144258097","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":"Community Health Worker Diabetes Prevention Awareness Training in an Immersive Virtual World Environment: Mixed Methods Pilot Study.","authors":"Laurie Ruggiero, Lauretta Quinn, Amparo Castillo, Colleen Monahan, Leticia Boughton Price, Wandy Hernandez","doi":"10.2196/64051","DOIUrl":"10.2196/64051","url":null,"abstract":"<p><strong>Background: </strong>The burden of diabetes and obesity are greater for some racial-ethnic minority groups in the United States, including non-Hispanic blacks, underscoring the importance of raising community awareness of diabetes prevention. Community health workers (CHWs) play a critical role in extending our reach into communities to raise awareness of diabetes prevention. Systematic training and support are central to their work. Remote approaches have been helpful in delivering training to overcome common participation barriers. One remote approach, immersive 3D virtual worlds (VW) offer a unique approach to providing remote training incorporating engaging interactive contextual learning opportunities.</p><p><strong>Objective: </strong>This study aimed to implement and evaluate an internet-based 3D VW model to remotely deliver an adapted CHW training program on diabetes prevention awareness for racial-ethnic minority communities.</p><p><strong>Methods: </strong>A sequential mixed methods design, including a pre-post pilot and explanatory phase, examined the feasibility, acceptability, and impact of the VW training. Female CHWs who self-identified as African American or Black or African Ancestry, between 21-65 years of age, fluent in English, and with risk factors for diabetes were recruited. CHW input was gathered to adapt a Centers for Disease Control and Prevention's CHW diabetes prevention awareness training and the VW environment for this study. The final adapted training was standardized for delivery over 10 weeks. Quantitative and qualitative data were collected to examine acceptability, feasibility, and impact of the training model. Primary quantitative pre-post outcomes included training content knowledge and confidence; and secondary behavioral outcomes included motivation for lifestyle change and eating habits. Focus group feedback was collected on acceptability and feasibility during the explanatory phase. Quantitative descriptive and qualitative thematic analysis approaches were used to examine the acceptability, feasibility, and impact of the VW training model.</p><p><strong>Results: </strong>A total of 26 CHWs initiated the study and 22 completed the postassessment. The majority of participants reported that their expectations were met across all sessions and content topics. Participants generally reported satisfaction with the information provided (20/22, 91% rated very good-excellent) and high levels of interactivity in the training (17/22, 77% rated very good-excellent). Results of the posttraining acceptability and feasibility quantitative survey and qualitative feedback were generally positive. Mean pre-post values improved across all quantitative outcomes for the VW training group (eg, 92% [11/12] improved in knowledge; 62% [8/13]-77% [10/13] improved across eating habits measures). Explanatory focus group findings were generally positive, highlighting satisfaction with the overall training, its interactivity, ","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e64051"},"PeriodicalIF":2.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12172805/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144266288","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 Generative Pre-Trained Transformer-4-Vision for Nystagmus Classification: Development and Validation of a Pupil-Tracking Process.","authors":"Masao Noda, Ryota Koshu, Reiko Tsunoda, Hirofumi Ogihara, Tomohiko Kamo, Makoto Ito, Hiroaki Fushiki","doi":"10.2196/70070","DOIUrl":"10.2196/70070","url":null,"abstract":"<p><strong>Background: </strong>Conventional nystagmus classification methods often rely on subjective observation by specialists, which is time-consuming and variable among clinicians. Recently, deep learning techniques have been used to automate nystagmus classification using convolutional and recurrent neural networks. These networks can accurately classify nystagmus patterns using video data. However, associated challenges including the need for large datasets when creating models, limited applicability to address specific image conditions, and the complexity associated with using these models.</p><p><strong>Objective: </strong>This study aimed to evaluate a novel approach for nystagmus classification that used the Generative Pre-trained Transformer 4 Vision (GPT-4V) model, which is a state-of-the-art large-scale language model with powerful image recognition capabilities.</p><p><strong>Methods: </strong>We developed a pupil-tracking process using a nystagmus-recording video and verified the optimization model's accuracy using GPT-4V classification and nystagmus recording. We tested whether the created optimization model could be evaluated in six categories of nystagmus: right horizontal, left horizontal, upward, downward, right torsional, and left torsional. The traced trajectory was input as two-dimensional coordinate data or an image, and multiple in-context learning methods were evaluated.</p><p><strong>Results: </strong>The developed model showed an overall classification accuracy of 37% when using pupil-traced images and a maximum accuracy of 24.6% when pupil coordinates were used as input. Regarding orientation, we achieved a maximum accuracy of 69% for the classification of horizontal nystagmus patterns but a lower accuracy for the vertical and torsional components.</p><p><strong>Conclusions: </strong>We demonstrated the potential of versatile vertigo management in a generative artificial intelligence model that improves the accuracy and efficiency of nystagmus classification. We also highlighted areas for further improvement, such as expanding the dataset size and enhancing input modalities, to improve classification performance across all nystagmus types. The GPT-4V model validated only for recognizing still images can be linked to video classification and proposed as a novel method.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e70070"},"PeriodicalIF":2.0,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12164947/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144247972","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":"Remote Photoplethysmography Technology for Blood Pressure and Hemoglobin Level Assessment in the Preoperative Assessment Setting: Algorithm Development Study.","authors":"Selene Y L Tan, Jia Xin Chai, Minwoo Choi, Umair Javaid, Brenda Pei Yi Tan, Belinda Si Ying Chow, Hairil Rizal Abdullah","doi":"10.2196/60455","DOIUrl":"10.2196/60455","url":null,"abstract":"<p><strong>Background: </strong>Blood pressure (BP) and hemoglobin concentration measurements are essential components of preoperative anesthetic evaluation. Remote photoplethysmography (rPPG) is an emerging technology that may be used to measure BP and hemoglobin concentration noninvasively with just a consumer-grade smartphone, replacing traditional in-person measurements. However, there is limited data regarding the use of this technology in patients with diverse skin tones and medical comorbidities. Hence, widespread applicability is yet to be achieved. The potential benefits of achieving this would be immense, allowing for greater convenience, accessibility, and reduction in labor and resources.</p><p><strong>Objective: </strong>Our study aims to be the first to develop an algorithm for noninvasive rPPG-based BP and hemoglobin concentration measurement that can be used for preoperative evaluation of patients in real-world clinical practice settings.</p><p><strong>Methods: </strong>We conducted the study at Singapore General Hospital from March 1, 2023, to June 28, 2024. A total of 200 patients were recruited. Our primary analysis compared the accuracy of rPPG-based systolic and diastolic BP measurements against measurements taken with automated BP measuring devices. Our secondary analysis compared the accuracy of rPPG-based hemoglobin concentration measurement against traditional blood sampling.</p><p><strong>Results: </strong>Our model performed best with diastolic BP predictions, with a mean absolute percentage error of 7.52% and a mean difference of 0.16 mm Hg (SD 3.22 mm Hg) between reference and measured readings. The 95% CI for the mean difference between predicted and measured diastolic BP was ±0.57 (-0.41 to 0.73) mm Hg. Systolic BP predictions yielded a mean absolute percentage error of 9.52% and a mean difference of 2.69 mm Hg (SD 7.86 mm Hg). The 95% CI for the mean difference between predicted and measured systolic BP was ±1.14 (-1.54 to -3.83) mm Hg. Hemoglobin concentration predictions had a mean absolute percentage error of 8.52%, with a mean difference of 0.23 g/dL (SD 0.67 g/dL). The 95% CI for the mean difference between predicted and reference measured hemoglobin concentration was ±0.10 (95% CI 0.13-0.33) g/dL.</p><p><strong>Conclusions: </strong>Noninvasive rPPG-based measurement of BP and hemoglobin concentration at the preoperative evaluation setting has great potential for improving convenience, improving efficiency, and conserving resources for patients and health care providers. Our model was able to accurately predict diastolic BP in patients with diverse skin tones and medical comorbidities. The findings of this study serve as a basis for further studies to develop and validate the model for noninvasive rPPG-based BP and hemoglobin concentration measurement.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e60455"},"PeriodicalIF":2.0,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12165443/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144247973","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":"Personalized Support in Hereditary Breast and Ovarian Cancer After Genetic Counseling by the Chatbot-Based GENIE Mobile App: Proof-of-Concept Wizard of Oz Study.","authors":"Dominik Wolff, Thomas Kupka, Chiara Reichert, Nils Ammon, Steffen Oeltze-Jafra, Beate Vajen","doi":"10.2196/69115","DOIUrl":"10.2196/69115","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The primary aim of genetic counseling at a human genetics center is to empower individuals at risk for hereditary diseases to make informed decisions regarding their health. In Germany, genetic counseling sessions typically last approximately 1 hour and provide highly personalized information by a specialist in human genetics. Despite this, many counselees report a need for additional support following the counseling session.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study introduces GENIE, a chatbot-based mobile app designed to assist individuals in the postcounseling phase, with a focus on hereditary breast and ovarian cancer. GENIE delivers expert-curated, personalized information tailored to the user's health and family circumstances. The content is presented through predefined dialogs between the user and the mobile assistant, aiming to extend the benefits of genetic counseling beyond the initial session.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A Wizard of Oz study was conducted to evaluate a functional prototype of GENIE. A total of 6 patients with breast cancer, at least 2 years postdiagnosis, participated in the study. Participants were given access to the app for a minimum of 1 week. The evaluation was based on their interaction with GENIE, which was personalized using the details of a fictitious patient. Data collection included semistructured interviews and a 45-item questionnaire to assess usability and content quality.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The analysis of the interview and questionnaire data indicated high usability for GENIE, with a mean System Usability Score of 75.33 (SD 4.13). In total, 5 of the 6 participants used the app daily; 3 participants were willing to pay between US $5 and US $45 as a single purchase, while the other 3 participants agreed that the app should be free for the user and the costs should be directly covered by health insurance. Still, opinions on the app's appeal were divided. The layout was seen as moderately professional, a bit crowded, and slightly uninspiring. Nevertheless, participants highlighted the credibility and relevance of the content, noting its alignment with the fictitious patient's scenario. However, areas for improvement were identified, particularly concerning the app's design. All participants would recommend the app to other affected persons.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The findings suggest that a mobile app like GENIE can provide valuable support to individuals in the postcounseling phase of genetic services. GENIE offers distinct advantages over large language models, as the information it provides is carefully curated by human experts, minimizing the risk of inaccuracies or hallucinations and significantly enhancing the system's credibility. This study highlights the need to involve the user group as early as possible in the development of a digital health app. Future work will focus on the implementation of a comprehensive personalization engine,","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e69115"},"PeriodicalIF":2.0,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12161161/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144234155","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":"Usage of a Multipurpose mHealth App Among Adults With Sickle Cell Disease: Randomized Controlled Trial.","authors":"Robert M Cronin, Nives Quaye, Xin Liu, Kristina Landes, Lori E Crosby, Adetola A Kassim, Michael R DeBaun, Patrick M Schnell","doi":"10.2196/67906","DOIUrl":"10.2196/67906","url":null,"abstract":"<p><strong>Background: </strong>While mobile health (mHealth) apps have been made for various diseases, including sickle cell disease (SCD), most focus on a single purpose. SCD is a chronic disease that requires knowledge of the disease, self-management, and adherence to treatment plans. While mHealth apps have been made with single features for SCD, there is limited understanding of using an mHealth app with a more comprehensive set of features that could engage adults with SCD, depending on what features they prefer and need to engage and empower them in living with their disease.</p><p><strong>Objective: </strong>We evaluated the usage of an mHealth app with various features, including pain tracking, quizzes for patient-facing guidelines, pain and asthma action plans, and goal setting.</p><p><strong>Methods: </strong>Adults with SCD were enrolled at 2 sickle cell centers between 2018 and 2022 as part of a 6-month feasibility randomized controlled trial with participants completing surveys at baseline and 6 months. Participants were randomized into receiving either an mHealth app and booklet with patient-facing guidelines or a booklet with the guidelines alone. The mHealth app comprised web pages with patient-facing guideline material and a Research Electronic Data Capture (REDCap) project. The REDCap project included a personal profile, a pain tracker, goal setting, quizzes about the guidelines, and pain or asthma action plans. The REDCap project also included the ability to send daily text messages at a time they chose, which contained a message they could create and a link to their profile. Outcomes included SCD-specific knowledge and acute health care utilization (emergency room visits and hospitalizations). We evaluated the usage of these different features and relationships with baseline variables, each other, and study outcomes.</p><p><strong>Results: </strong>Approximately 75% (50/67) of the enrolled and randomized participants completed all the study components, and 100% (26/26) of the participants who were randomized to the mHealth app arm and completed the study used the mHealth app. Further, 15/30 (50%) participants used multiple features. Baseline sickle cell knowledge and female gender were associated with more usage of pain diary (P=.04) and mission (P=.046) features, respectively. While not significant, mission completion was associated with lower hospitalizations (P=.06).</p><p><strong>Conclusions: </strong>Adults with SCD engaged differently with an mHealth app with multiple features. As this study was not focused on one part of our app, engagement with features in this app was entirely patient-driven, which may demonstrate the expected real-world use of an mHealth app in this population. A multipurpose app can help engage participants in self-management strategies through different features and potentially improve outcomes.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e67906"},"PeriodicalIF":2.0,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12161614/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144234156","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":"Developing and Testing a Framework for Learning Online Collaborative Creativity in Medical Education: Cross-Sectional Study.","authors":"Shairah Radzi, Joo Seng Tan, Preman Rajalingam, Jennifer Cleland, Sreenivasulu Reddy Mogali","doi":"10.2196/50912","DOIUrl":"10.2196/50912","url":null,"abstract":"<p><strong>Background: </strong>Collaborative creativity (CC) is a social process of generating creative and innovative solutions to real-world problems through collective effort and interaction. By engaging in this process, medical students can develop abilities and mindset for creative thinking, teamwork, interdisciplinary learning, complex problem-solving, and enhanced patient care. However, medical students have demonstrated limited creativity, constrained by existing pedagogical approaches that predominantly emphasize knowledge outcomes. The increasing complexity of health care challenges necessitates a pedagogical framework for medical students to foster CC in a rapidly evolving professional environment.</p><p><strong>Objective: </strong>This study aimed to develop, test, and evaluate a new Framework for Learning Online Collaborative Creativity (FLOCC).</p><p><strong>Methods: </strong>FLOCC builds on established pedagogical approaches such as design thinking and integrates sociocultural learning methods (team-based learning [TBL] and problem-based learning [PBL]). It includes 4 individual asynchronous activities (empathy map, frame your challenge, turning insights into how might we questions, and individual brainstorming) and 5 collaborative synchronous activities (bundle ideas, list constraints, final idea, prototyping, and blind testing). In this cross-sectional study, 85 undergraduate medical students participated in 2 separate studies (study 1, n=44; study 2, n=41) involving health care and engineering sustainability problems. Learner acceptability was measured using a 31-item survey (using 7-point Likert scale) consisting of 4 factors (distributed creativity, synergistic social collaboration, time regulation and achievement, and self and emotions) and 3 free text questions. Free-text comments were subjected to the inductive thematic analysis.</p><p><strong>Results: </strong>Most students were positive about FLOCC, with distributed creativity and synergistic social collaboration factors receiving the highest mean percentages of \"'Agree\" (78/85, 92% and 75/85, 88%, respectively). These were followed by time regulation and achievement factor (68/85, 80%) and the self and emotions factor (59/85, 70%). Only time regulation and achievement was statistically significant (P=.001) between means of studies 1 and 2. Thematic analysis revealed 4 themes such as learning experiences, collaborative responsibilities, perceived skill development, and technical challenges.</p><p><strong>Conclusions: </strong>With effective time management, FLOCC shows potential as a framework for nurturing CC in medical students. Medical schools could provide the opportunity and environment that supports creative thinking; therefore, creativity-focused approaches could be integrated into the curriculum to encourage a culture of creativity for breakthrough solutions by future doctors.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e50912"},"PeriodicalIF":2.0,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12161162/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144234154","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":"Integrating Nurse Preferences Into AI-Based Scheduling Systems: Qualitative Study.","authors":"Fabienne Josefine Renggli, Maisa Gerlach, Jannic Stefan Bieri, Christoph Golz, Murat Sariyar","doi":"10.2196/67747","DOIUrl":"10.2196/67747","url":null,"abstract":"<p><strong>Background: </strong>Nurse scheduling is a complex challenge in health care, impacting both patient care quality and nurse well-being. Traditional scheduling methods often fail to consider individual preferences, leading to dissatisfaction, burnout, and high turnover. Inadequate scheduling practices, including restricted autonomy and lack of transparency, can further reduce nurse morale and negatively affect patient outcomes. Research suggests that participative scheduling approaches incorporating nurse preferences can improve job satisfaction. Artificial intelligence (AI) and mathematical optimization methods, such as mixed-integer programming (MIP), constraint programming (CP), genetic programming (GP), and reinforcement learning (RL), offer potential solutions to optimize scheduling and address these challenges.</p><p><strong>Objective: </strong>This study aims to develop a framework for integrating nurses' preferences into AI-supported scheduling methods by gathering qualitative insights from nurses and supervisors and mapping these to mathematical and AI-based scheduling techniques.</p><p><strong>Methods: </strong>Focus group interviews were conducted with 21 participants (nurses, supervisors, and temporary staff) from Swiss health care institutions to understand experiences and preferences related to staff scheduling. Qualitative data were analyzed using open and axial coding to extract key themes. These themes were then mapped to AI methodologies, including MIP, CP, GP, and RL, based on their suitability to address identified scheduling challenges.</p><p><strong>Results: </strong>The study revealed key priorities in nurse scheduling. Fairness and participation were highlighted by 85% (18/21) of interview participants, emphasizing the need for transparent and inclusive scheduling. Flexibility and autonomy were preferred by 76% (16/21), favoring shift swaps and self-scheduling. AI expectations were mixed: 62% (13/21) saw potential for improved efficiency and fairness, while 38% (8/21) expressed concerns over reliability and loss of human oversight. Mapping to AI methods showed MIP as effective for fair shift allocation, CP for complex rule-based conditions, GP for handling unforeseen absences, and RL for dynamic schedule adaptation in hospital environments. A preliminary AI implementation of MIP in a training hospital unit (35 staff members) showed how to design a system from a mathematical perspective.</p><p><strong>Conclusions: </strong>AI-supported scheduling systems can significantly enhance fairness, transparency, and efficiency in nurse scheduling. However, concerns regarding AI reliability, adaptability to individual needs, and human oversight must be addressed. A hybrid approach integrating AI recommendations with human decision-making may be optimal. Future research should explore the broader implementation of AI-driven scheduling models and assess their impact on nurse satisfaction and patient outcomes over time.</p>","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e67747"},"PeriodicalIF":2.0,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157959/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144225555","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":"Determining the Requirements of Vulnerable Groups for Health Counseling and Optimizing the Evaluation of Health Consultations: Mixed Methods Study With the Use of AI.","authors":"Annina Boehm-Fischer, Luzi M Beyer","doi":"10.2196/68888","DOIUrl":"10.2196/68888","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Evaluating health counseling services is crucial for ensuring their quality and effectiveness. However, this process is hampered by challenges such as language barriers and limited awareness of their needs and concerns.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The studies aimed to enhance and digitize an existing paper-and-pencil evaluation form for a health counseling service while gaining insights into client needs and barriers. This effort intends to adapt a health care facility's offerings to better meet client demands and implement a multilingual format for greater accessibility.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The research team designed and conducted an in-depth interview study with clients of a health counseling service to gather new information. The insights regarding client demands, wishes, and social needs were used to revise and supplement the existing 1-page questionnaire (originally in German) for evaluating counseling sessions. Using artificial intelligence, the team transformed the new 3-page questionnaire into easy language with a Kunin smiley scale, translated it into 7 other languages, and created audio recordings for all questions in each language. The questionnaire was then programmed into an web-based tool, allowing data collection both on-site with tablets and through integration into the counseling service's website. This digital format is now continuously used to adapt the counseling service to clients' needs.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 18 clients participated in the in-depth interviews, which were conducted in their native languages whenever possible and lasted between 8 and 30 minutes. The results indicated that many clients attending the counseling center are burdened by physical and mental health issues, with a significant portion of the assistance provided focused on helping clients complete various forms required by health insurance providers and medical professionals. Despite these challenges, clients expressed a high level of satisfaction with the health counseling services they received. The revised and supplemented web-based questionnaire has been completed by 41 clients. Evaluation results revealed that only 21 respondents (51%) filled out the questionnaire in the national language (German), while English and Arabic were the next most common choices, each used by 6 clients (15%). Findings regarding health burdens and the need for assistance were reaffirmed, highlighting that clients' self-perception regarding their ability for self-help is notably low.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Contrary to previous assumptions, it was found that client interests predominantly lie in receiving help with the excessive demands imposed by institutional forms and requirements rather than solely addressing health issues. Clients showed strong satisfaction with the advice received and emphasized the necessity for multilingual health counseling services and evaluations. There is a disti","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"9 ","pages":"e68888"},"PeriodicalIF":2.0,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157954/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144225554","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}