JMIR Human Factors最新文献

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Exploring Response Patterns to Motivational Messages Supporting Physical Activity: Latent Class Analysis. 探索对支持体育活动的动机信息的反应模式:潜在类分析。
IF 3.9
JMIR Human Factors Pub Date : 2026-08-19 DOI: 10.2196/91917
Chihiro Moriishi, Takeyuki Oba, Keisuke Takano, Kentaro Katahira, Kenta Kimura
{"title":"Exploring Response Patterns to Motivational Messages Supporting Physical Activity: Latent Class Analysis.","authors":"Chihiro Moriishi, Takeyuki Oba, Keisuke Takano, Kentaro Katahira, Kenta Kimura","doi":"10.2196/91917","DOIUrl":"10.2196/91917","url":null,"abstract":"<p><strong>Background: </strong>In mobile health care, text messages play an important role in improving physical activity. Recent studies have developed message banks based on theories, including the behavior change technique (BCT) taxonomy. However, little evidence is available for individual differences (ie, who responds to which BCTs presented in messages), which is crucial for optimizing message delivery.</p><p><strong>Objective: </strong>We investigated how individuals perceive messages supporting physical activity and what clusters of individuals are identified by their responses.</p><p><strong>Methods: </strong>Japanese-speaking adults (n=2859; mean age 54.5, SD 17.5 years; 1486 women) were presented with messages conveying different BCTs and rated how motivational each message was. The motivation ratings were subjected to latent class analysis to identify clusters of individuals per motivation rating.</p><p><strong>Results: </strong>A total of 7 clusters were identified. Two clusters gave consistently high ratings across BCT types; one showed a general receptivity to all messages, while the other showed a clearer preference for information-based BCTs. Two clusters showed moderate ratings, both preferring information about consequences but differing in their additional preferences for goal setting vs rewards. Two clusters gave overall low ratings and typically included less active individuals in the preaction stages, both showing a preference for information-based BCTs. The remaining cluster showed the greatest variability in BCT preferences, with the strongest preference for salience of consequences.</p><p><strong>Conclusions: </strong>These results highlight individual differences in perceived motivations across BCTs, informing what BCTs should be prioritized in delivery. The practical implications for message tailoring are also discussed.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e91917"},"PeriodicalIF":3.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13539174/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148798980","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}
引用次数: 0
Correction: Acceptability of a Digital Care App in Patients Undergoing Hip and Knee Arthroplasty: Prospective Cohort Study. 更正:数字护理应用程序在髋关节和膝关节置换术患者中的可接受性:前瞻性队列研究。
IF 3.9
JMIR Human Factors Pub Date : 2026-08-14 DOI: 10.2196/101097
Yacine Louni, Matthew Laroche, Abdulrhman Alnasser, Mohammad Abuhaneya, Eric Belzile, Sandhya Baskaran, Jennifer Mutch, Anthony Albers
{"title":"Correction: Acceptability of a Digital Care App in Patients Undergoing Hip and Knee Arthroplasty: Prospective Cohort Study.","authors":"Yacine Louni, Matthew Laroche, Abdulrhman Alnasser, Mohammad Abuhaneya, Eric Belzile, Sandhya Baskaran, Jennifer Mutch, Anthony Albers","doi":"10.2196/101097","DOIUrl":"https://doi.org/10.2196/101097","url":null,"abstract":"","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e101097"},"PeriodicalIF":3.9,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13475920/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148765375","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}
引用次数: 0
Correction: Quality of Informed Consent and Interface Usability in Primary Care e-Consultation: Cross-Sectional Study. 更正:初级保健电子咨询中知情同意的质量和界面可用性:横断面研究。
IF 3.9
JMIR Human Factors Pub Date : 2026-08-12 DOI: 10.2196/103250
Caitlin Parfitt-Ford, Lisa Ballard, Adriane Chapman
{"title":"Correction: Quality of Informed Consent and Interface Usability in Primary Care e-Consultation: Cross-Sectional Study.","authors":"Caitlin Parfitt-Ford, Lisa Ballard, Adriane Chapman","doi":"10.2196/103250","DOIUrl":"10.2196/103250","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.2196/78483.].</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e103250"},"PeriodicalIF":3.9,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13519505/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148721409","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}
引用次数: 0
Optimizing Usability of Digital Health Interventions for Nondigitally Native Adults: A Framework-Based Approach to Develop Just-in-Time Adaptive Interventions (JITAIs) and Other Adaptations. 优化非数字化原生成人的数字健康干预的可用性:一种基于框架的方法来开发即时适应性干预(JITAIs)和其他适应性。
IF 3.9
JMIR Human Factors Pub Date : 2026-08-11 DOI: 10.2196/87365
Abby L Cheng, Christine Y Gou, Adriana Martin, Sarah M Hartz, Joanna Abraham
{"title":"Optimizing Usability of Digital Health Interventions for Nondigitally Native Adults: A Framework-Based Approach to Develop Just-in-Time Adaptive Interventions (JITAIs) and Other Adaptations.","authors":"Abby L Cheng, Christine Y Gou, Adriana Martin, Sarah M Hartz, Joanna Abraham","doi":"10.2196/87365","DOIUrl":"10.2196/87365","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Health-related technology use among nondigitally native adults is becoming widespread. Nevertheless, digital health interventions are typically not designed with the unique usability needs and preferences of this population in mind. Furthermore, most of these middle-aged and older adults are managing multiple medical conditions, which can also impact their preferences related to digital health interventions. A prime opportunity to address multimorbidity in nondigital natives using a digital health intervention is the intersection between mental health and chronic pain.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;The goal of this study was to use established frameworks and end-user feedback to identify actionable, usability-related features that can be incorporated into existing digital health interventions and that are preferred among nondigitally native adults. We aimed to identify general usability adaptations, as well as just-in-time adaptive interventions (JITAIs).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a qualitative usability study of a convenience sample using a hybrid inductive-deductive content analysis to evaluate an existing mental health app (Wysa for Chronic Pain). Participants were 45 years or older; reported at least moderate symptoms of depression or anxiety (Patient Health Questionnaire -9 ≥10 or Generalized Anxiety Disorder -7 score ≥10); and endorsed having pain at least most days in the past 3 months. The Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies was used to identify potential usability-related adaptations for the target population. Development of usability-related JITAIs was guided by Nahum-Shani's pragmatic framework for JITAI development and the Behavioral Integration Technology model.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Forty-two participants completed usability testing (mean age 57, SD 8 years; women n=32, 76%). Participants identified numerous opportunities to optimize their user experience, primarily by ensuring the app clearly describes how all its features are intended to be used and by minimizing navigation burden. Specifically, participants requested clear, step-by-step orientation and navigation instructions, rather than a brief onboarding experience that relies on user-led exploration and familiarity with conventional app symbols. Participants also recommended a customized experience based on their unique usage patterns. The most common JITAI opportunity identified was to strategically reduce user notifications in order to reduce the risk of notification fatigue and subsequent complete disengagement with the app.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Identifying actionable opportunities to improve usability and prompt engagement with \"the right tool at the right time for the right person\" holds promise to improve the effectiveness of digital health interventions across the age span. The usability-related refinement opportunities identifie","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e87365"},"PeriodicalIF":3.9,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13460799/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148713717","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}
引用次数: 0
Designing a Trauma-Informed Safety by Design Framework for Nonconsensual Intimate Image Removal Platforms: A 2-Phase Sequential Exploratory Study. 通过非自愿亲密图像移除平台的设计框架设计创伤知情安全性:一项两阶段顺序探索性研究。
IF 3.9
JMIR Human Factors Pub Date : 2026-08-10 DOI: 10.2196/94438
Ji-Yeon Lee, Yejun Koh
{"title":"Designing a Trauma-Informed Safety by Design Framework for Nonconsensual Intimate Image Removal Platforms: A 2-Phase Sequential Exploratory Study.","authors":"Ji-Yeon Lee, Yejun Koh","doi":"10.2196/94438","DOIUrl":"10.2196/94438","url":null,"abstract":"<p><strong>Background: </strong>Removal platforms for nonconsensual intimate images (NCIIs) are essential, as they have become the recourse for victims of such abuse; yet their interfaces are not designed around the cognitive and emotional realities of trauma. Safety by Design directs platforms to protect vulnerable users but not how; trauma-informed care defines what that protection requires, while usability heuristics keep interfaces usable but are not themselves trauma-sensitive. However, no framework integrates them into design guidance that is both usable and protective for NCII removal platforms.</p><p><strong>Objective: </strong>This study develops trauma-informed design, a cohesive framework that integrates trauma-informed care with established usability heuristics under Safety by Design, so that NCII removal platforms protect trauma-affected users while remaining realistically usable; a preliminary, domain-informed evaluation provides initial supporting evidence.</p><p><strong>Methods: </strong>We used a 2-phase sequential exploratory design, drawing on a globally accessible NCII removal platform as an illustrative case. Phase 1 developed trauma-differentiated personas and mapped each persona's user journey to surface pain points that varied by level of trauma. Phase 2 analyzed a focus group of 8 female Counseling-UX (User Experience) Psychology students who had completed coursework in user psychological safety with consensual qualitative research methodology. Participants assessed the plausibility of the personas and the proposed framework with respect to perceived emotional safety and perceived usability.</p><p><strong>Results: </strong>Mapping each persona's journey surfaced pain points that differed by level of trauma, which were synthesized into a 6-guideline trauma-informed design framework: emotional scaffolding, process transparency, self-pacing mechanisms, institutional trust signals, context-aware support, and grounding tools. In phase 2, domain-informed evaluators judged the personas plausible, and the framework directions emotionally safer, and potentially more usable.</p><p><strong>Conclusions: </strong>Integrating trauma principles into user experience evaluation can help identify and address psychological barriers in NCII removal platforms. The framework provides the preliminary, domain-informed foundation that trauma-sensitive design of such platforms requires. Because the framework was not tested with NCII victim-survivors or users actively seeking image-removal support, findings represent preliminary plausibility and acceptability evidence rather than ecological validation or real-world effectiveness.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e94438"},"PeriodicalIF":3.9,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13455849/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148707772","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}
引用次数: 0
Human-AI Interaction With AI-Assisted Tumor Overlays in Pediatric Whole-Body Magnetic Resonance Imaging: Exploratory Reader Study. 儿童全身磁共振成像中人工智能与人工智能辅助肿瘤覆盖的交互:探索性阅读器研究。
IF 3.9
JMIR Human Factors Pub Date : 2026-08-07 DOI: 10.2196/81066
Abhishek Moturu, Olurotimi Komolafe, Sayali Joshi, Andrea S Doria, Anna Goldenberg
{"title":"Human-AI Interaction With AI-Assisted Tumor Overlays in Pediatric Whole-Body Magnetic Resonance Imaging: Exploratory Reader Study.","authors":"Abhishek Moturu, Olurotimi Komolafe, Sayali Joshi, Andrea S Doria, Anna Goldenberg","doi":"10.2196/81066","DOIUrl":"10.2196/81066","url":null,"abstract":"<p><strong>Background: </strong>AI tools have the potential to enhance personalized clinical care, particularly in radiology. However, their integration into clinical workflows remains complex, especially in pediatric oncology, where early cancer detection is critical. Children with Li-Fraumeni syndrome (LFS), a rare cancer predisposition disorder, undergo regular surveillance whole-body magnetic resonance imaging (wbMRI), which presents an opportunity for AI-assisted tumor detection.</p><p><strong>Objective: </strong>We evaluated the feasibility of an AI-assisted overlay for highlighting tumor-like regions in pediatric surveillance wbMRI and explored how access to the overlay influenced radiologist workflow, candidate-lesion marking behavior, follow-up recommendations, and perceived workload.</p><p><strong>Methods: </strong>We developed a patch-based AI segmentation model trained on augmented 2D slices from 675 surveillance wbMRI volumes of pediatric patients with LFS. The model was designed to highlight regions with high tumor probability. A reader study was conducted with 2 radiologists who independently reviewed wbMRI cases both with and without AI assistance. We measured evaluation time, number and location of reader-marked candidate lesions, type of follow-up recommendation, and subjective feedback using structured questionnaires.</p><p><strong>Results: </strong>AI assistance altered interpretation workflows for both radiologists, with mixed effects. On average, the time required to evaluate each case increased when using the AI tool for both radiologists. However, one radiologist had an increase in the number of candidate lesion locations selected with the tool, and one had a decrease in the number of candidate lesion locations selected with the tool. Subjective feedback indicated that one of the radiologists reported lower mental demand with the AI tool, while both radiologists reported lower stress with the AI tool. Interrater variability was evident, underscoring the need for personalized calibration of AI tools.</p><p><strong>Conclusions: </strong>AI-assisted wbMRI interpretation can improve tumor detection in pediatric cancer surveillance by reducing false negatives. However, its influence on workflow efficiency and interradiologist variability highlights the importance of careful implementation. Successful integration requires addressing challenges such as improving the predictive precision of AI models, offering intuitive end-user designs and instructions, and building trust in AI outputs. AI outputs can influence workflow and behavior in reader-specific ways. Clinical translation will require larger, randomized, multireader studies and model refinement to reduce false positives and quantify lesion-level reader performance. This can help ensure better patient outcomes in addition to reduced clinician burnout.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e81066"},"PeriodicalIF":3.9,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13451057/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148689965","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}
引用次数: 0
An Online Epilepsy Self-Management Tool for Patients With Epilepsy: A Formative Usability Study. 癫痫患者的在线癫痫自我管理工具:形成性可用性研究。
IF 3.9
JMIR Human Factors Pub Date : 2026-08-05 DOI: 10.2196/79540
Katarzyna Czerniak, Ross Shegog, Refugio Sepulveda, Robert Addy, Youngran Kim, Sahiti Myneni, Alejandra Garcia-Quintana, Kimberly Martin, David M Labiner
{"title":"An Online Epilepsy Self-Management Tool for Patients With Epilepsy: A Formative Usability Study.","authors":"Katarzyna Czerniak, Ross Shegog, Refugio Sepulveda, Robert Addy, Youngran Kim, Sahiti Myneni, Alejandra Garcia-Quintana, Kimberly Martin, David M Labiner","doi":"10.2196/79540","DOIUrl":"10.2196/79540","url":null,"abstract":"<p><strong>Background: </strong>Epilepsy is a serious chronic neurological condition with no permanent cure. Continual self-management is important to mitigate seizure frequency and optimize quality of life in people with epilepsy who have greater disparities in accessing epilepsy care. The Management Information & Decision Support Epilepsy Tool (MINDSET [UTHealth, University of Arizona, and Radiant Digital]) was developed to enhance accessibility to epilepsy self-management (ESM) assessment and treatment. The purpose of this formative usability pilot study was to assess the user experience and functionality of MINDSET 2.0, an enhanced cross-platform online version of MINDSET, among a sample of patients with epilepsy prior to feasibility testing within neurology clinic settings.</p><p><strong>Methods: </strong>MINDSET 2.0 comprised an updated cross-platform architecture for easier accessibility and added quality of life, cognitive function, and social determinants assessments. User experience and functionality were assessed in January 2022. Six patients with epilepsy in Texas (n=4) and Arizona (n=2) participated in individual online usability sessions, completing a sociodemographic survey, accessing all components of MINDSET, and then completing usability rating scales and an exit interview. Logical inconsistencies in embedded algorithms were examined for the usability sample and in user case challenges to ensure functional fidelity.</p><p><strong>Results: </strong>Patients reported low adherence to ESM behaviors in each of the management domains. More than 80% of patients agreed that MINDSET 2.0 was acceptable, easy to use, likable, credible, of appropriate duration, and motivationally appealing. Patients agreed that the program helped them think about and manage their epilepsy more carefully, and that it improved decision-making between them and their health care providers (100%). Patients provided lower ratings (≤50%) and reported the greatest number of difficulties with their understanding of how to select goals and strategies, and develop an action plan due to constraints of item response options leading to user confusion. An inconsistency in algorithm branched logic was identified that related to translating depression scores into recommendations for depression self-management programming.</p><p><strong>Conclusions: </strong>The results replicated usability findings from earlier versions of MINDSET but also catalyzed adjustments to user survey response options and algorithm repair. The value of the formative user experience functionality assessment was demonstrated to ensure a high-fidelity program prior to feasibility testing in neurology clinic settings.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e79540"},"PeriodicalIF":3.9,"publicationDate":"2026-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13440935/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148680200","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}
引用次数: 0
Strategic Use of Negative Emojis in Messaging-Based Interventions for Public Health Communication on Social Media: Mixed Methods Study. 消极表情符号在基于信息的社交媒体公共卫生传播干预中的策略性使用:混合方法研究
IF 3.9
JMIR Human Factors Pub Date : 2026-07-31 DOI: 10.2196/78824
Yue Luo, Shubin Yu
{"title":"Strategic Use of Negative Emojis in Messaging-Based Interventions for Public Health Communication on Social Media: Mixed Methods Study.","authors":"Yue Luo, Shubin Yu","doi":"10.2196/78824","DOIUrl":"10.2196/78824","url":null,"abstract":"<p><strong>Background: </strong>Despite the growing importance of social media in mobile health (mHealth) communication, we lack a clear understanding of how emotional elements like emojis shape message effectiveness. Furthermore, since emojis are inherently tied to text, their impact may be highly dependent on the relevance and context of the accompanying written content.</p><p><strong>Objective: </strong>This study aimed to investigate how the valence of emojis affects the effectiveness of mHealth messages and to determine the role of emoji-text congruence in shaping message outcomes.</p><p><strong>Methods: </strong>A mixed-method approach was used, encompassing 3 complementary studies. First, an analysis of real-world health-related tweets (N1=257,648) quantified social media engagement in relation to positive, negative, and absent emojis. Building on these insights, 2 controlled experiments (N2=220; N3=190) further explored how negative emojis influence preventative health behaviors under varying levels of text congruence.</p><p><strong>Results: </strong>The automatic content analysis revealed that messages containing negative emojis generated significantly higher social media engagement than those with positive emojis (β=0.24, SE=0.03, t257, 593=9.59; P<.001). Subsequently, experimental findings indicated that negative emojis can effectively promote preventative health behaviors (t218=-4.15; P<.001). However, messages with high negative emoji-text congruence are more persuasive in promoting preventive behavior than those with low congruence (F1, 186=5.46, η2=.028; P<.05), highlighting the complex interplay between emotional signaling and message consistency.</p><p><strong>Conclusions: </strong>These findings advance our theoretical understanding of emoji-based health communication and provide practical guidelines for public health organizations seeking to optimize their mHealth messaging strategies. Our results highlight the need for careful consideration of both emotional valence and message coherence when designing health communications in the digital age.</p>","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e78824"},"PeriodicalIF":3.9,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13427074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148649441","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}
引用次数: 0
User Experience of a Web-Based Mobile Health App Supporting Low-Income Pregnant Individuals With Diabetes: Mixed Methods Study. 支持低收入糖尿病孕妇的基于web的移动健康应用程序的用户体验:混合方法研究
IF 3.9
JMIR Human Factors Pub Date : 2026-07-31 DOI: 10.2196/84061
Sydney L Raucher, Layna Lu, Tazim Merchant, Elizabeth Soyemi, Charlotte Niznik, Rana Saber, Chen Yeh, Lynn M Yee
{"title":"User Experience of a Web-Based Mobile Health App Supporting Low-Income Pregnant Individuals With Diabetes: Mixed Methods Study.","authors":"Sydney L Raucher, Layna Lu, Tazim Merchant, Elizabeth Soyemi, Charlotte Niznik, Rana Saber, Chen Yeh, Lynn M Yee","doi":"10.2196/84061","DOIUrl":"10.2196/84061","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Diabetes mellitus management requires considerable patient self-efficacy, knowledge, and support for social determinants of health. These needs become particularly acute during pregnancy. Mobile health (mHealth) tools are a promising approach to enhance patient engagement with the health care system, education, and health promotion and may be particularly helpful during the period of rapid skills acquisition, which is a hallmark of experiencing diabetes during pregnancy. Therefore, we developed SweetMama, a web-based mHealth app designed to support and provide information to low-income pregnant individuals with gestational diabetes mellitus (GDM) or type 2 diabetes mellitus (T2DM).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to understand the user experiences of low-income pregnant people who were randomized to use SweetMama during a feasibility trial.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This mixed methods secondary analysis of data from a feasibility randomized controlled trial (RCT) included participants randomized to SweetMama, an interactive, web-based mHealth app with multiple motivational and educational features that help reduce barriers to care, offer health education, and aim to improve diabetes self-care for low-income pregnant people. In the parent trial, English-speaking pregnant individuals with GDM or T2DM were randomized to use SweetMama during pregnancy or usual care. SweetMama users experienced an individualized curriculum from enrollment through 6 weeks postpartum. Upon exit, users completed 2 qualitative interviews (during the delivery hospitalization and at the postpartum visit) and surveys assessing standardized usability metrics. The surveys included the System Usability Scale (SUS), the Usefulness, Satisfaction, Ease of Use (USE) scale, and the mHealth App Usability Questionnaire (MAUQ) to assess usability. Qualitative data were analyzed using constant comparative techniques.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of 30 SweetMama users, 60% (n=18) had GDM, 83.3% (n=25) had publicly funded prenatal care, and the majority identified as non-Hispanic Black (n=17, 56.7%) or Hispanic (n=11, 36.7%). Scores on the SUS (median 85.0/100, IQR 70.0-88.8; ≥71% indicates acceptable or higher usability), USE (overall median 84.5/100, IQR 81.0-91.4), and MAUQ (median 84.1/100, IQR 79.0-91.3) indicated favorable usability assessments, particularly for the \"ease of learning\" domain. Qualitative interviews supported these findings: participants described the app as easy to navigate, well organized, and helpful for staying on track, citing features such as clear visual design, timely text reminders, and actionable tips. Users valued motivational elements and content specificity, while recommending increased customization and enhanced esthetics.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;In this user experience evaluation of a web-based mHealth app for low-income pregnant individuals with diabetes, participants found the to","PeriodicalId":36351,"journal":{"name":"JMIR Human Factors","volume":"13 ","pages":"e84061"},"PeriodicalIF":3.9,"publicationDate":"2026-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13429574/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148649428","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}
引用次数: 0
Digital Mental Health Promotion Services for Youth: A Qualitative Study of Help-Seeking Through Mindhelper.dk. 青少年数码心理健康促进服务:透过Mindhelper.dk寻求帮助的质性研究
IF 3.9
JMIR Human Factors Pub Date : 2026-07-31 DOI: 10.2196/91017
Amalie Oxholm Kusier, Caroline Høier Dalsgaard, Sofie Have Hoffmann, Lau Caspar Thygesen, Anna Paldam Folker
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