JMIR Formative Research

Interactive dashboards have expanded public access to HIV surveillance and programmatic data, but existing tools do not synthesize implementation research evidence into formats accessible to the diverse stakeholders who could use it. Designing such tools requires deliberate alignment with users’ needs, language, and decision-making contexts.

Academic programs in health informatics have been urged to align curricula with evolving workforce needs to better prepare graduates for practice. Such alignment supports workforce readiness, addresses talent shortages, and reduces onboarding burdens for employers. Although employers increasingly seek graduates who can demonstrate applied skills and competencies beyond textbook knowledge, academic programs continue to face challenges in translating workforce demand into curricular design. This Viewpoint is directed at health informatics program faculty and administrators and presents the author’s perspective on a skills-first curriculum mapping approach aligned with current industry needs. The author argues that connecting program-level outcomes, course objectives, and learning activities to industry-recognized competencies strengthens workforce readiness while maintaining academic rigor. Drawing on the literature on competency-based education, workforce development, and health informatics training, this paper argues for intentional curriculum design that integrates transferable skills, stackable credentials, and stakeholder engagement. The key messages are as follows: (1) workforce demand should anchor curriculum design in health informatics programs, (2) curriculum mapping is a practical mechanism for operationalizing skills-first alignment, and (3) credential integration and continuous congruency evaluation support long-term program sustainability. This approach positions health informatics education to remain responsive, scalable, and aligned with the rapidly evolving professional landscape.

Sleep is essential for health, yet a large proportion of the population reports sleep complaints. The ASLEEP (Preventing and Treating Insomnia Symptoms in Mid-Life and Older Adults) intervention is conceptualized as an eCBT-I (digitally delivered cognitive behavioral therapy for insomnia) intervention aiming to prevent and treat insomnia in individuals aged 50 years and over through a novel, tiered approach. The first step, a basic course delivered via iPad through a dedicated app, includes educational videos grounded in sleep education and sleep hygiene advice, a 7-day digital sleep diary, and a postcourse digital sleep report providing personalized feedback on sleep efficiency via email.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with an active trial landscape that relies on the sensitivity of selected clinical trial endpoints. Traditional clinical outcome assessments perform well in trials but lack strong psychometric properties and may not detect small but clinically meaningful disease progression. Digital health technologies offer a promising alternative for tracking ALS disease progression.

People with dementia and their caregivers experience significant psychological distress, which may increase their vulnerability to trauma across the dementia diagnostic and caregiving trajectory. Specialist dementia helplines offer immediate emotional support, information, and signposting; however, little empirical evidence exists about how call handlers account for potential trauma in their responses.

Type 2 diabetes mellitus (T2DM) requires sustained self-management and lifestyle modification to achieve optimal glycemic control. Hybrid care models that combine digital health technologies with in-person clinical support may enhance patient engagement while improving the accessibility and scalability of diabetes care. However, evidence regarding their effectiveness and feasibility in Southeast Asian populations remains limited.

Sleep procrastination is a prevalent and detrimental behavior among university students. While digital interventions offer scalable solutions, they often lack a robust theoretical foundation and fail to differentiate themselves from clinical insomnia treatments.

Mental stress is a well-known trigger of cardiac symptoms in patients with coronary artery spasms. Hence, stress management is recommended along with medical therapy. However, specific programs for patients with coronary spasms are lacking. We collaborated with patients to develop a smartphone-based app as a tailored solution. The app provides biofeedback based on heart rate variability–driven stress level estimations.

The HIV epidemic remains a national priority in the United States, and the Ending the HIV Epidemic initiative has renewed the call for expanded prevention and treatment strategies capable of reducing new HIV infections by 90% by 2030. Achieving this goal requires robust, integrated data for understanding HIV-related needs, barriers to care, and the effectiveness of interventions. However, despite the existence of numerous publicly available datasets, few integrate multiple domains such as HIV outcomes, social determinants of health, and community-level factors. The lack of unified data and difficulty linking datasets hampers efforts for meaningful cross-domain analyses to tailor HIV management and treatment strategies. The resulting fragmentation constitutes a methodological gap: implementation teams lack replicable guidance for constructing unified HIV and contextual databases from public sources. In this viewpoint, we describe our experience building a unified compilation of publicly available HIV and community data to identify factors influencing HIV outcomes and interventions. The completed database comprises 242 variables drawn from 8 public sources mapped across clinic, zip code, county, and state levels of geography. Rather than simply reporting what we built, we position four core decisions as transferable methodological advances: (1) treating source identification as a bounded phase before construction begins, (2) adopting automated data engineering tools from the outset rather than manual entry, (3) establishing a shared data dictionary before the first variable is entered, and (4) integrating quality control throughout the workflow rather than as a final phase. The build required approximately 350 total project hours and revealed an initial spot-check error rate of approximately 33%, which we attribute primarily to manual data entry. By sharing the approach used to develop this database and making the final resource publicly accessible through the Yale Center for Methods in Implementation and Prevention Science, we aim to reduce barriers to data access and encourage similar data integration efforts. The methodological framework described in this paper is intentionally designed to be replicable with modest resources, and we present it as a practical model for research teams operating without specialized infrastructure. Consolidating HIV, social determinants of health, and contextual variables into a unified data source is a critical step toward enabling deeper, more comprehensive analysis and supporting ongoing efforts to end the HIV epidemic in the US.

The COVID-19 pandemic disrupted mobility globally, but its mental health implications remain difficult to characterize because most studies relied on lockdown status, population-level mobility indicators, or self-reported mobility. These approaches may miss individual differences in actual movement patterns and cannot fully examine bidirectional relationships between mobility and mental health. Individual-level smartphone geolocation data may provide a more objective and temporally aligned measure of mobility during periods of societal disruption.

Electrocardiograms (ECGs) are commonly stored in PDF, particularly as vector-based files generated by ECG management systems. Previous studies have demonstrated that ECG signals can be extracted through PDF-to-Scalable Vector Graphics (SVG) conversion, highlighting the potential to reconstruct waveform signals from vector graphics. These reconstructed signals further enable the derivation and prediction of clinically relevant ECG parameters.

Veterans face stigma, privacy concerns, and access barriers to HIV screening. For studies that use at-home HIV self-testing (HIVST) kits distributed through vending machines (VMs), recruitment and educational materials must communicate study purpose and participation options clearly, minimize confusion and stigma, and provide actionable next steps for participants who test outside of clinical settings.