JMIR Human Factors

Correction: Acceptability of a Digital Care App in Patients Undergoing Hip and Knee Arthroplasty: Prospective Cohort Study

2026-08-14T16:00:19-04:00

Correction: Quality of Informed Consent and Interface Usability in Primary Care e-Consultation: Cross-Sectional Study

2026-08-12T09:30:02-04:00

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

2026-08-11T17:00:23-04:00

Background: 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. Objective: 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). Methods: 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. Results: 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. Conclusions: 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 identified in this study are generalizable to other digital health interventions that are relevant to older users who are likely to be managing multimorbidity, are not digital natives, and are more likely than younger users to have physical or cognitive challenges. The integrated framework-based process described in this article can also serve as a model for optimizing other existing digital health interventions.

Designing a Trauma-Informed Safety by Design Framework for Nonconsensual Intimate Image Removal Platforms: A 2-Phase Sequential Exploratory Study

2026-08-10T12:30:14-04:00

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.

Human-AI Interaction With AI-Assisted Tumor Overlays in Pediatric Whole-Body Magnetic Resonance Imaging: Exploratory Reader Study

2026-08-07T21:00:21-04:00

Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.

An Online Epilepsy Self-Management Tool for Patients With Epilepsy: A Formative Usability Study

2026-08-05T15:30:13-04:00

Background: 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. Methods: 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. Results: 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. Conclusions: 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.

Digital Mental Health Promotion Services for Youth: A Qualitative Study of Help-Seeking Through Mindhelper.dk

2026-07-31T15:45:10-04:00

Background: Young people increasingly experience mental health challenges and often turn to the internet for support. Self-guided digital mental health promotion services have become widely used resources for youth seeking help and guidance. These platforms offer accessible, anonymous support, yet little is known about the concerns young people articulate when engaging with them. Objective: This study aims to examine inquiries submitted to the digital letter box of Mindhelper.dk, Denmark’s most widely used digital mental health promotion service. Using qualitative analysis, the study aims to identify recurring themes in young people’s mental health concerns, explore gender differences in engagement, and generate insights to inform the development of more relevant and targeted digital self-help interventions. Methods: Using an inductive thematic approach informed by a constructivist-grounded theory coding framework, this study analyzes 2523 inquiries submitted to the Mindhelper digital letter box between March 2016 and August 2023. The dataset provides unsolicited first-person accounts from young people in moments of emotional vulnerability, offering insights into how mental health concerns are articulated in naturalistic settings. Results: The analysis identifies 17 recurring themes reflecting the mental health challenges young people seek help for. These were grouped into 3 overarching analytical categories: Social Relationships and Social Contexts, Emotional Life, and Body and Illness, with the first 2 dominating the material. Prominent themes included Sociality, Love Life, Unease, Self-doubt and Insecurity, and Seeking Support. Across genders, inquiries frequently focused on social relationships, particularly Sociality and Love Life. However, girls were markedly overrepresented among users, while only minor gender differences were observed in the distribution of themes. Conclusions: The findings suggest that young people’s mental health concerns are closely tied to everyday developmental and relational challenges rather than severe psychopathology alone. Digital letter box services may capture early expressions of distress that might not otherwise reach formal support systems. This highlights the preventive potential of such services and the value of using self-initiated digital data to inform the development of relevant digital mental health support and better understand how young people articulate and act on emerging mental health concerns.

Strategic Use of Negative Emojis in Messaging-Based Interventions for Public Health Communication on Social Media: Mixed Methods Study

2026-07-31T15:30:12-04:00

Background: 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. Objective: 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. Methods: A mixed-method approach was used, encompassing 3 complementary studies. First, an analysis of real-world health-related tweets (N=257,648) quantified social media engagement in relation to positive, negative, and absent emojis. Building on these insights, 2 controlled experiments (N=220; N=190) further explored how negative emojis influence preventative health behaviors under varying levels of text congruence. Results: The automatic content analysis revealed that messages containing negative emojis generated significantly higher social media engagement than those with positive emojis (=0.24, SE=0.03, =9.59; <.001). Subsequently, experimental findings indicated that negative emojis can effectively promote preventative health behaviors (=−4.15; <.001). However, messages with high negative emoji-text congruence are more persuasive in promoting preventive behavior than those with low congruence (=5.46, =.028; <.05), highlighting the complex interplay between emotional signaling and message consistency. Conclusions: 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.

User Experience of a Web-Based Mobile Health App Supporting Low-Income Pregnant Individuals With Diabetes: Mixed Methods Study

2026-07-31T15:15:10-04:00

Background: 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). Objective: This study aimed to understand the user experiences of low-income pregnant people who were randomized to use SweetMama during a feasibility trial. Methods: 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. Results: 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. Conclusions: In this user experience evaluation of a web-based mHealth app for low-income pregnant individuals with diabetes, participants found the tool to be user-friendly, visually appealing, informative, and motivating. Constructive feedback for application improvement for use in a future larger trial of clinical effectiveness was collected. Trial Registration: ClinicalTrials.gov NCT03240874; https://clinicaltrials.gov/study/NCT03240874

Usability and User Experience Assessment of Health Care Conversational Agents Using Validated Subjective Instruments: Systematic Review and Comparative Analysis

2026-07-30T10:00:03-04:00

Background: Digital applications based on health care conversational agents (HCAs) are increasingly being developed to support health care provision. The usability and user experience of these solutions are critical determinants of their acceptability and, consequently, their impact on health-related outcomes. Objective: This systematic review aims to synthesize current evidence on the use of valid and reliable subjective instruments for assessing the usability and user experience of HCAs and to examine whether assessment outcomes vary according to their technical characteristics. Methods: A systematic search was conducted in PubMed, Web of Science, and Scopus from inception to February 2026. Studies were included if they used subjective instruments to evaluate the usability or user experience of HCAs. Results: A total of 127 studies met the inclusion criteria. The studies examined 3 categories of HCAs—text-based, voice-based, and embodied—applied to patient care, health education and prevention, health data collection, and support for daily activities among older adults. The System Usability Scale (SUS) was the most frequently used assessment instrument. Comparative analysis of SUS scores indicated higher usability ratings for text-based HCAs relative to voice-based and embodied systems. However, SUS and other subjective instruments used in the included studies may not fully capture key dimensions of usability and user experience of HCAs. Additionally, substantial heterogeneity was observed in assessment methodologies across studies. Conclusions: Comparative analysis suggested that text-based HCAs were associated with significantly higher SUS scores than voice-based and embodied HCAs. However, this finding should be interpreted with caution given the substantial heterogeneity across the included studies in health care application domains, study designs, evaluation contexts, participant populations, and HCAs’ implementation and use characteristics, as well as the limitations of the SUS in evaluating the usability of modern HCAs. The variability in assessment approaches underscores the need for standardized protocols and the development of more context-specific evaluation frameworks to enhance methodological consistency and comparability across studies.