JMIR Human Factors

Feasibility and Acceptability of a Prevention-Focused Screener for Perinatal Depression Risk: Mixed Methods Cohort Study

2026-05-05T16:15:13-04:00

Background: More than 20% of perinatal women experience depression, with suicide being a leading cause of maternal death in the United States. Professional societies emphasize the need to identify those at risk of developing perinatal depression to better target preventive care delivery during pregnancy. Objective: We evaluated receptivity to a machine learning–based predictive screener designed to identify women in the first trimester of pregnancy who were asymptomatic but were at risk for developing moderate to severe depression symptoms later in pregnancy. Methods: Our participants were adult pregnant women with negative first-trimester depression (Patient Health Questionnaire–9) screens at 1 of 4 obstetric practices. Of the 810 women who were clinically eligible, 787 were successfully contacted via their patient portal. Of these, 289 (36.7%) viewed the screener and 255 (88.2%) completed the 6-question predictive screener. In total, 51 (20%) were identified by the screener as being at risk for developing perinatal depression. Participants were asked a series of follow-up questions regarding the acceptability of the predictive screener and desired preventive resources. Chi-square tests were used to compare demographic characteristics, perceived benefits and concerns, and desired resources between those identified as at risk for depression and those who were not. Differences in acceptability ratings between the two risk groups were determined using nonparametric Mann-Whitney tests. Results: On a 5-point Likert scale of agreement, participants found the screener questions easy to complete (median score 5, IQR 5-5) and felt comfortable sharing their answers with their obstetric care providers (median 5, IQR 4-5). Key perceived benefits of completing the screener included opportunities to seek preventive care (75/255, 29.4%) and to receive education on depression risk (66/255, 25.9%). Primary concerns about knowing one’s risk of future depression included worrying about developing depression (90/255, 35.3%) and a lack of prevention opportunities (39/255, 15.3%). Desired preventive resources included counseling (197/255, 77.3%), mind-body interventions (166/255, 65.1%) such as exercise, and prenatal classes or support groups (81/255, 31.8%). Conclusions: Participants found the screener acceptable and felt comfortable receiving it through their patient portal. Specific preventive care options were commonly endorsed, several of which are scalable and evidence based. A minority of participants voiced addressable concerns about knowing their risk of developing depression in the future.

Service Users’ Views on Digital Remote Monitoring for Psychosis: Survey Study

2026-05-05T16:00:09-04:00

Background: Digital remote monitoring using smartphones and wearable devices is a promising solution for psychosis management, where precise, time-sensitive intervention is crucial. Combining active symptom monitoring (ASM) and passive sensing (PS) can support self-management by allowing remote, low-burden mental health monitoring. Objective: This study aimed to explore (1) views on collecting data using ASM and PS methods and comfort levels with different types of data gathered via these methods, (2) views on using smartphones and wearable devices in the context of mental health care, and (3) the ownership and usage of smartphones and wearable devices. Methods: We conducted a cross-sectional survey study with service users with psychosis in the United Kingdom between March 2023 and March 2024. Results: A total of 309 participants completed the survey. They reported mixed views on using ASM and PS technologies for monitoring mental health, with more participants endorsing the concept than opposing it (ASM: n=145, 46.9% and PS: n=132, 42.7%). However, the type of data gathered using these methods was an important factor. Collecting personal information was deemed less acceptable (<.001) than other data types (physical health, mental health, environment, and nonpersonal device information). Conclusions: We found that participants were comfortable with using apps and wearables for digital remote monitoring, though personal information was less acceptable than other data types due to privacy and surveillance concerns. This highlights the importance of further exploring trust issues related to digital monitoring and ensuring that end users have choices regarding the types of data that digital systems gather and share with mental health services.

Identifying Skill and Usability Barriers to Digital Health Tool Use Among Older Adult Patients in US Safety Net Clinics: Mixed Methods Study

2026-05-04T16:30:18-04:00

Background: Despite their benefits, digital health tools often face adoption barriers because of the digital divide. Identifying the fundamental user skills required to effectively navigate these tools and the usability barriers is essential to addressing disparities in use. Objective: This study aimed to identify the skill and usability barriers to using digital health tools. Methods: This study included English-, Spanish-, or Cantonese-speaking patients, aged ≥50 years, who received care at an urban safety net health system in the United States. Participants completed a survey examining sociodemographic characteristics and digital health tool use and were observed and video recorded as they navigated four digital health care tasks: (1) launch a video visit, (2) visit a health website through a URL, (3) log in to the patient portal, and (4) sign up for a patient portal account. Participants who could not independently perform the tasks received additional support. Tasks were conducted in English, while instructions and additional assistance were provided in each participant’s preferred language. Video recordings were thematically coded to identify the fundamental skills needed for effective digital tool use and usability barriers in the design of digital tools. We examined whether task independence was associated with participant demographics and thematic categories using Kruskal-Wallis, , and Fisher exact tests. Results: In total, 74% (34/46), 52% (31/60), 71% (44/62), and 70% (43/61) of participants (N=64) independently completed digital tasks 1, 2, 3, and 4, respectively. Older age, minoritized races and ethnicities, non-English language preference, lower educational attainment, access to cellular data only or no internet access, and lack of a portal account were associated with a higher likelihood of requiring assistance or being unsuccessful at completing each task (<.001, except for older age [=.004]). The qualitative coding of video recordings identified 3, 4, and 6 categories of typing, navigation, and human-computer interaction (HCI) skills, respectively, as fundamental skills required to independently complete digital tasks. and Fisher exact tests indicated significant associations between most typing, navigation, and HCI categories and independent task completion. We coded usability barriers as one of 6 learnability challenges or 3 operability challenges. Conclusions: This study identified that independent use of digital health tools requires fundamental typing, navigation, or HCI skills as well as high usability of digital tools. The inclusion of 4 different digital tasks added specificity to the type of skills and usability considerations necessary to ensure accessibility of digital health tools to diverse older adults. This study underscores the need for vendors to cocreate digital health tools with historically excluded end users in mind. As health care systems expand digital tool adoption, they must distinguish fundamental skill gaps from usability barriers, as each may require different intervention strategies.

High Screen Exposure and Its Association With Physical and Mental Well-Being Among School-Going Children and Adolescents in Bangladesh: Cross-Sectional Study

2026-05-04T16:30:18-04:00

Background: In Bangladesh, as well as throughout the world, children’s screen time has significantly increased. Children spend a lot of time on the internet and digital screens for entertainment, education, and communication, which has increased their daily screen time. However, the potential detrimental impacts of excessive screen time on children’s mental, physical, and social health have drawn attention. Objective: This study aimed to explore the effect of high exposure to screens on the health and mental well-being of school-going children and adolescents in Dhaka, Bangladesh. Methods: This cross-sectional descriptive study was conducted from July 2022 to June 2024. A total of 420 school-going children and adolescents aged 6 to 14 years were enrolled from 3 English-language and 3 Bangla-language schools in Dhaka using a stratified random sampling technique. Anthropometric measurements, a semistructured questionnaire, and the Pittsburgh Sleep Quality Index, the Development and Well-Being Assessment scale, and the Strengths and Difficulties Questionnaire, all of which were validated in Bangla, were used to gather data. We considered students who were exposed to screens for less than 2 hours a day as the low-exposure group and those who were exposed for more than 2 hours a day as the high-exposure group. Results: A total of 83.3% (350/420) of the students were in the high-exposure group, and their average screen time per day was 4.6 (SD 2.3) hours. Eye problems were reported by 35.7% (150/420) of the students, and a significant difference was found between the low- and high-exposure groups. In total, 96% (144/150) of the students with eye problems were from the high-exposure group, whereas 4% (6/150) were from the low-exposure group. Headaches were reported by 80% (336/420) of the students, and they were common in the high-exposure group (279/336, 83%). Moreover, students from the high-exposure group had a short duration and poor quality of sleep (mean 7.3, SD 1.4 hours), which was statistically significant. Furthermore, obesity was more predominant in the high-exposure group (<.001). Our study revealed that, overall, 31% (130/420) of the students had at least one mental health problem and 9.8% (41/420) had more than one mental health problem using the Development and Well-Being Assessment scale, and mental health problems were greater in the high-exposure group than the low-exposure group. Although behavioral problems such as conduct issues (119/420, 28.3%) and peer difficulties (121/420, 28.8%) were observed among the participants, no statistically significant difference was found between the 2 groups. Conclusions: A collaborative and coordinated multistage approach is essential to create effective and acceptable guidelines and policies for the optimum and positive use of digital screens for the children of Bangladesh. Further prospective studies on a larger scale can be conducted to determine the impacts of screen time on aspects of health.

The Role of Explanations in AI-Generated Alerts: Qualitative Study of Clinical Views on Explainable AI in Predictive Tools

2026-05-01T16:15:11-04:00

Background: Artificial intelligence (AI)–driven clinical decision support (CDS) tools offer promising solutions for health care delivery by optimizing resource allocation, detecting deterioration, and enabling early interventions. However, adoption remains limited due to insufficient validation and a lack of transparency and trust. Explainable AI (XAI) seeks to improve user understanding of AI outputs; however, how clinicians interpret and integrate these explanations into their decision-making remains underexplored. Furthermore, discrepancies in explanations, known as the “disagreement problem,” can undermine trust and, at worst, lead to poor clinical decisions. Objective: This study examines clinicians’ perspectives on the role and value of explainability in AI-driven CDS tools within Australian critical care settings and the impact of discrepancies in AI-generated explanations on clinical decision-making. Methods: Qualitative data were collected using semistructured interviews with 14 clinical experts, incorporating scenario-based exercises, and were analyzed using inductive thematic analysis. Results: Clinicians valued explainability, particularly in complex or unfamiliar situations, when explanations were clear, plausible, and actionable. Trust and perceived usefulness extended beyond explanation quality, encompassing factors such as system accuracy, alignment with clinicians’ reasoning, workflow integration, and perceived reliability. Discrepancies in explanations generated by different XAI methods were not a major concern, provided that the AI-generated predictive alerts were accurate. Conclusions: This study provides design recommendations for developing trustworthy, user-centric CDS tools that incorporate XAI. Findings highlight that explainability is critical for establishing initial trust in AI-driven tools by supporting perceived usefulness, but its importance diminishes over time and with user expertise and familiarity, as learned usefulness takes precedence. Recommendations highlight the importance of aligning the design and implementation of AI tools with clinicians’ needs to enhance trust, mitigate risks, and promote successful adoption for improved patient outcomes.

User-Centered Design for Digital Patient-Navigation Tools in Oncology: Scoping Review

2026-04-29T17:00:32-04:00

Background: Navigation programs for patients with cancer improve access and continuity of care, yet their digital transformation is often limited by poor usability and inadequate uptake. Applying user-centered and human-centered design (UCD/HCD) principles may close this gap, but the extent to which such design methods are used and evaluated in oncology navigation tools remains unclear. Objective: This scoping review identifies how UCD/HCD principles have been, and should be, applied in developing and implementing digital health tools for navigation for patients with cancer. Methods: A scoping review was conducted following PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) and Joanna Briggs Institute guidance. A total of 7 databases (PubMed/MEDLINE, Scopus, IEEE Xplore, Web of Science, Embase, ACM Digital Library, and CINAHL) were searched for English-language articles published between January 2015 and July 2025. Eligible studies reported original, peer-reviewed research on digital or mobile health interventions linked to cancer navigation and documented at least 1 UCD/HCD activity. Two reviewers independently screened records and charted data on context, target users, functions, tool modality, design phase, methods, and outcomes. Findings were synthesized descriptively and thematically. Results: A total of 36 studies met the inclusion criteria. Findings were organized into 4 domains: study characteristics, navigation functions and digital modalities, design processes and methods, and UCD/HCD application. Iterative prototyping and usability testing were the most common, while participatory design and implementation evaluation were underused. Conclusions: UCD/HCD approaches enhance usability and patient relevance of digital cancer navigation tools. However, their application remains limited across cancer types, regions, and functions. Broader stakeholder participation and evaluation beyond usability are needed to strengthen coordination, equity, and sustainability in cancer care.

Learning From the Adoption of a Readmission Clinical Decision Support Tool: Group Model Building Approach

2026-04-29T16:00:22-04:00

Background: Computerized clinical decision support (CDS) has the potential to improve patient outcomes by offering evidence-based guidance at the point of care—enhancing guideline adherence and diagnostic accuracy—and supporting system-level outcomes by enabling predictive analytics for more efficient resource planning. Prior work has identified factors that affect adoption, such as clinicians’ expectations of usefulness, ease of use, alignment with workflows, and resources to support utilization. However, CDS adoption is not static and changes according to dynamic systems of behaviors and workflows, requiring a deeper understanding of how evolving conditions affect implementation and outcomes. Objective: To explore the dynamic factors influencing CDS adoption, we examined the implementation of the “Unplanned readmission model version 1,” developed by Epic Medical Records System, at Duke University Health System, using group model building and system dynamics modeling. Methods: We first conducted group model-building workshops with staff (case managers, physical and occupational therapists, hospitalist faculty physicians, and resident physicians) who participate in decisions about discharging patients. Study team members guided participants to identify and connect variables in causal loop diagrams. We coded workshop transcripts in software designed for system dynamics analysis to identify themes, aggregated them into a causal loop diagram, and reviewed them with participants to converge on a common model. A team member applied equations to the pathways and tested data to simulate conditions leading to full, limited, or no adoption of a tool. Results: We identified key balancing loops driven by external pressure (eg, Centers for Medicare & Medicaid Services penalties) that motivated initial adoption and reinforcing loops based on perceived internal benefits to sustain use. While institutional incentives led to early training and tool use, efforts declined due to staff turnover, competing priorities (eg, COVID-19), and workflow changes. Reinforcing loops emerged when staff described clinical utility, such as improved discharge planning and team communication. However, staff also suggested that these loops were often weak due to difficulty linking the use of the tool to outcomes in real time. Simulation modeling showed that while strong external pressure and rapid training led to initial success, interest in using the tool waned as workflows improved and readmission rates approached Centers for Medicare & Medicaid Services goals. When conflicting priorities were introduced, adoption stalled earlier, and fewer staff were trained. In contrast, when internal motivation was strengthened by reducing the amount of evidence needed to perceive success, individual interest remained high even as institutional attention declined, sustaining tool use and further reducing readmissions. Conclusions: External pressure to improve can be a strong motivator for initial adoption, but in the face of conflicting demands for attention, it may fall short of sustained long-term tool use. Tools are more likely to have extensive and sustained use when those using the tools can perceive internal benefits.

Evaluation of Combined Educational Methods on Motivational Interviewing for Final-Year Medical Students: Mixed Methods Study

2026-04-29T16:00:22-04:00

Background: Motivational interviewing (MI) is a patient-centered communication approach that supports health behavior change; yet, its integration into undergraduate medical curricula remains inconsistent. Combined learning models that comprise face-to-face instruction with structured web-based components may strengthen MI training, but evidence supporting their effectiveness among medical students, particularly in Asian contexts, is limited. Objective: This study evaluated the impact of a combined MI educational model on final-year medical students’ MI knowledge, confidence, and application in real patient encounters during clinical rotations. Methods: This study used a sequential explanatory mixed methods design. The quantitative component used a before-and-after study to evaluate changes in MI knowledge and confidence among final-year medical students enrolled in an Ambulatory Care course in 2024. All 130 students participated in a 2-hour interactive MI workshop, and 120 completed pre- and postintervention questionnaires assessing MI knowledge and self-reported confidence. Students were also provided access to a 3-hour web-based MI learning module, and learning-management system analytics were used to track engagement. The qualitative component consisted of semistructured interviews with 12 purposively selected students, conducted to explore their experiences applying MI during clinical encounters. Quantitative data were analyzed using paired-samples tests, and qualitative data were analyzed using inductive conventional content analysis. Findings from both components were integrated during interpretation to provide a comprehensive understanding of the educational intervention. Results: Students demonstrated a significant improvement in MI knowledge following the educational intervention (pretest mean 8.87, SD 2.69; posttest mean 15.04, SD 2.99; ₁₁₉=–18.45; <.001; η²=0.74). After the workshop, 96.9% (126/130) of students reported applying MI with patients, and 92.3% (n=120) agreed that the combined learning approach was adequate for supporting clinical use. Learning analytics data showed that 76.9% (n=100) of students enrolled in the web-based MI module, and 51% (n=51) completed all lessons. Students most frequently applied MI when counseling patients with diabetes, hypertension, and dyslipidemia, especially related to diet, physical activity, and medication adherence. Interview findings indicated that students mainly used brief MI, were most comfortable with engaging and focusing, and developed greater empathy, confidence, and patient-centered communication skills. Challenges included limited time during consultations, clinical workload, and difficulty applying all MI processes to complex cases. Conclusions: A combined MI learning approach integrating a short workshop with a web-based course was associated with higher MI knowledge scores and greater self-reported confidence among students, as well as reported use of MI-informed communication strategies during clinical encounters. Students perceived MI as a practical and ethically grounded communication approach that can enhance patient engagement, particularly in the management of chronic diseases. Introducing MI training longitudinally through a spiral curriculum, with opportunities for repeated practice and reinforcement, may help strengthen behavior-change communication competencies in undergraduate medical education.

Development and Usability of a Dashboard for Quality Monitoring and Resident-Centered Care in Australian Residential Long-Term Care: Mixed-Methods Study

2026-04-29T16:00:22-04:00

Background: The Australian National Aged Care Mandatory Quality Indicator Program (QI Program) requires government-subsidized residential aged care service providers to report quarterly data on a set of quality indicators. These indicators measure provider performance across specific domains of care and are intended to support continuous quality improvement. Health care dashboards can enhance the use of indicators by presenting data in interactive and intuitive formats that enable actionable insights. Objective: This mixed methods study aimed to develop an electronic dashboard to assist service providers’ use of QI Program data to measure, track, and improve the quality of resident care. Methods: A participatory design methodology was used to co-design and co-develop the dashboard. Initially, stakeholder participants for the co-design were identified. A combination of workshops, meetings, and email communications with co-design participants was then used to iteratively define and refine user requirements and to develop and improve the dashboard prototype. A 3-month pilot of the dashboard was conducted with a convenience sample of 30 end-users across 12 nursing homes and a post-pilot survey based on the System Usability Scale (SUS) was used to assess end-users’ perceptions of the dashboard usability. Results: The dashboard supports multiple user roles by enabling comparisons across homes and detailed views of all indicators for individual homes. A key feature is the ability to progressively view data at various levels of detail: groups of homes, individual homes, resident groups, and individual residents. The resident-level view enables more targeted, personalized care by helping staff identify and prioritize the specific indicators triggered by each resident. The average SUS score was 75.2 (SD 16.3), indicating good usability for the dashboard. Most survey respondents (12/14, 85.7%) were likely or extremely likely to recommend the dashboard to a colleague and agreed the dashboard would support the delivery of personalized care for residents. Almost all respondents (13/14) agreed or strongly agreed that the dashboard would assist with quality monitoring and improvement activities, and some pilot participants also made suggestions for incorporating the dashboard into those activities. Conclusions: This study demonstrates the potential value of a co-designed dashboard to support the use of quality indicator data in residential aged care. Limitations of the current prototype include short pilot duration, convenience sampling, and reliance on manual quarterly data uploads, which constrain generalizability and scalability. Future work should explore long-term integration of the dashboard into routine quality improvement processes and evaluate its impact on resident outcomes and care quality over time.

Adaptation and Acceptability of a Low-Intensity Cognitive Behavioral Therapy App to Support Low Mood and Worry Management in Female Forces Veterans: Mixed Methods Study

2026-04-29T15:15:12-04:00

Background: Mental health help-seeking barriers experienced by female forces veterans result in them being underserved and underrepresented. Efforts are therefore required to adapt interventions for female veterans to enhance acceptability and maximize engagement. Given a smaller number and wider geographical distribution of female veterans, targeting adaptation efforts at a digital mobile phone app based on cognitive behavioral therapy (CBT) has potential for greatest impact to improve access to a scalable evidence-based psychological therapy. Objective: This study aimed to examine the adaptation of a low-intensity CBT app to support low mood and worry management in female forces veterans and examine acceptability and usability. Methods: Using a mixed methods methodology, this study comprises a focus group of female forces veterans to inform adaptation with extracted themes used as the basis of an adaptation framework. Following adaptation, a wider sample of female veterans was recruited to use the app and complete the mHealth App Usability Questionnaire to determine acceptability, usability, and usefulness. Results: Two main areas were identified as requiring adaptation to maximize acceptability and usability. While using imagery and quotes to reflect the armed forces was initially found helpful to initiate engagement, it was considered that continued reference to the armed forces should be dropped when progressing through the app. Most app features were found acceptable; however, adaptations were requested to the content and structure of signposting information, navigation, and the way progress was monitored. No adaptations were required, however, regarding the CBT techniques used, with specific app features motivating engagement. Following the adaptation, there were good levels of acceptability, usability, and usefulness. Conclusions: Involving female forces veterans as part of an intervention adaptation process has promise to improve acceptability and engagement with a digital CBT mobile phone intervention. Ensuring that the intervention represented the transition from serving to female forces veteran is of particular significance in enhancing acceptability.