Lyndsay A. Nelson

Objective: Mobile health (mHealth) interventions using text messages and phone calls are scalable strategies to improve health outcomes, yet sustaining mHealth engagement remains challenging. This observational study extends prior research by operationalizing engagement in novel ways, examining how human support influences engagement with automated components, and exploring how content with varying levels of reflection and response burden affects engagement. Methods: This analysis was conducted within the Family/Friend Activation to Motivate Self-care (FAMS) 2.0 randomized controlled trial. Participants with type 2 diabetes (N=160) received monthly coaching calls and two types of interactive texts over 9 months: daily medication adherence texts with low reflection/response burden and weekly reflection texts with high reflection/response burden. Engagement was defined as response to interactive texts. Generalized estimating equations examined associations between participants’ baseline characteristics and response rates longitudinally, and the association between proximity to coaching calls and odds of engagement. Results: Median response rates were 88% for daily adherence texts and 42% for weekly reflection texts, with average engagement declining over time. Lower income and higher perceived autonomy support were associated with less decline in engagement. Participants had 64% higher odds of responding to the daily adherence text (95% CI: 34%, 102%) and 36% higher odds of responding to the weekly reflection text (95% CI: 19%, 56%) within ±7 days of a coaching call. Conclusions: Augmenting automated mHealth with human support and careful consideration of reflection and response burden may be key for sustaining engagement. Ongoing evaluation of engagement is essential to optimize mHealth intervention design and impact.

Objective: To expand the My Diabetes Care (MDC) patient portal intervention by enhancing its user interface to display additional diabetes health metrics and developing a culturally adapted Spanish-language version to improve accessibility for Spanish-speaking patients. Methods: We applied a five-phase Design Sprint methodology and formative usability testing to guide the redesign of MDC. The expanded prototype incorporated additional health metrics (weight, BMI, and urine microalbumin) and educational resources. Usability testing was conducted remotely with 12 adult patients with type 2 diabetes recruited from primary care clinics. Participants completed standardized tasks using the MDC prototype and provided feedback via interviews and validated scales. A Community Engagement Studio (CES) with Spanish-speaking consultants informed cultural and linguistic adaptation of the Spanish-language prototype. Results: Twelve participants (50% female; 25% ≥65 years; 33% with limited health literacy) completed two rounds of formative usability testing. Iterative refinements addressed terminology and layout issues, improving task performance and usability. Task performance improved across rounds, with all participants successfully completing tasks in the final round. System Usability Scale scores averaged 92 in Round 1 and 95 in Round 2, indicating excellent usability. CES participants emphasized culturally sensitive language, visual design, and onboarding support, guiding the development of the Spanish-language prototype. Conclusion: User-centered design and formative testing supported development of an expanded, culturally responsive MDC intervention. Future work will include iterative usability testing and pilot evaluation of the Spanish-language version to assess real-world usability and implementation alongside further English-language testing. MDC demonstrates potential as a scalable digital health intervention for supporting diabetes self-management across diverse populations.

Background: Diabetes preventive care reduces complications, yet completion rates remain suboptimal. Patient portals may help close care gaps by enabling patients to initiate services, but their use for diabetes preventive care is understudied. Objective: To evaluate the acceptability and feasibility of the Diabetes Care Gaps Intervention (DCGI), a portal-based tool that notifies patients when preventive care is due and enables them to initiate orders. Methods: We conducted a single-arm pilot study at an academic medical center. Adult primary care patients with diabetes and ≥1 care gap (HbA1c, urine microalbumin, eye exam, or pneumococcal vaccine) received DCGI access for three months. Primary outcomes were usability (System Usability Scale, SUS) and user experience (qualitative interviews, Likert-scale items). Secondary outcomes included diabetes self-efficacy, distress, engagement (patient-initiated orders), and care gap closure. Participants received modest compensation for survey completion and first use of the DCGI to initiate or report care. Results: Among 50 participants (median age 58.3 [IQR: 45.9, 67.0], 52% female, and 40% from minoritized racial/ethnic groups), 78% (39/50) initiated or reported care through the DCGI. The median SUS score was 78.8 (IQR: 70.0, 90.0), significantly above the “good” usability threshold of 71 ( p =0.002). Interviews revealed two acceptability themes: (1) appreciation of the DCGI for helping keep up with preventive care, and (2) unease about using the DCGI due to limited portal confidence. Users showed improved diabetes self-efficacy and reduced distress. Of 110 total care gaps, 47 (43%) were addressed via patient-initiated orders, and 79% (37/47) led to completed care (gap closure). Conclusions: The DCGI was acceptable and feasible for empowering patients to address diabetes care gaps. Future randomized studies should evaluate effectiveness and scalability.

Background: PRECIDENTD (PRevention of CardIovascular and DiabEtic KidNey Disease in Type 2 Diabetes) is a PCORnet ^® Study evaluating 2 classes of medications, SGLT2 inhibitors and GLP-1 receptor agonists, among people with type 2 diabetes. Participants obtain their assigned medication through their health insurance and complete semi-annual study assessments. Objective: We engaged multiple partners to develop a centralized text message-based program to facilitate adherence and retention in PRECIDENTD and evaluated its performance from April 2024 to April 2025. Methods: The PRECIDENTD study team applied best practices in digital health tool design and built the program with technology company MEMOTEXT. Patient partners identified program goals, co-wrote message content, and completed internal testing. We then deployed the program to PRECIDENTD participants and analyzed responses. Measures: We assessed response rate to interactive text messages, proportion of messages flagging participants needing additional support, and the adherence problems identified. Results: The text messaging program includes interactive messages querying if participants are taking the study medication, as well as one-way study timeline messages. During the first year, 450 PRECIDENTD participants across 20 sites received texts. Interactive message response rate was 80%, and 25% of responses identified problems (ie, trouble getting fills/refills and experiencing a health concern or side effect), prompting an outreach call. Conclusions: We co-designed a digital tool that engaged participants and helped identify study participants needing assistance obtaining and adhering to study medications. Collaborative development of similar centralized tools may augment the capacity of national studies to answer important comparative effectiveness research questions.

Introduction/Objectives: Initiatives to identify and address health-related social needs (HRSN) are increasingly being implemented in clinical settings and have the potential to improve health outcomes. However, best practices for HRSN assessment and implementation are still needed. We gathered input to guide implementation of an HRSN initiative within adult primary care clinics at an academic health center. Methods: We conducted 6 focus groups to explore multiple perspectives (ie, clinicians, staff, patients, and community organization representatives) on optimal approaches to collecting HRSN data, processes for providing support to patients, and strategies for incorporating HRSN data into clinical workflows. Data were qualitatively analyzed to address the study’s research questions, resulting in themes stratified by each interest-holder group. Results: Themes centered on how the successful development and integration of HRSN initiatives require a multifaceted approach that includes dedicated staffing, standardized data collection, adequate resources for actionable support, streamlined EHR functionalities, and structured training for key personnel. HRSN initiatives must also consider local context, including the role of community organizations and their capacity to provide services that address social needs. Conclusions: Findings highlight perspectives from key interest-holders for shaping HRSN initiatives within primary care settings. We provide recommendations for developing organizational capabilities to effectively address HRSN.

Background: Observationally, family and social support are important for optimal diabetes self-management; however, interventions targeting family/social support have not consistently been effective. A novel, diabetes-specific family functioning typology offers the opportunity to classify types of baseline family functioning to determine for whom family interventions may be effective. Purpose: We examined the effects of an intervention by baseline type of family functioning post hoc, to inform differential benefit from interventions. Methods: Participants were randomized to enhanced treatment as usual or a 9-month, mobile phone-delivered, family-focused, self-care support intervention. Adults with type 2 diabetes (N = 318) who participated in the randomized clinical trial (RCT) and provided baseline data were included. We determined participants’ diabetes-specific family functioning types at baseline using a validated, survey-administered, typology assessment tool. We investigated the associations between type and engagement (eg, attending coaching sessions and responding to text messages) and psychosocial (eg, well-being and diabetes distress) and glycemic outcomes at mid- and post-treatment. Results: Despite overall high engagement, there was variability across types in engagement and effects. Want More Involvement benefited the most; Satisfied with Low Involvement showed early improvements that waned; Collaborative & Helpful were highly engaged but derived minimal benefits from the intervention; and Critically Involved benefitted the least and may have experienced some harm. Conclusions: We demonstrated the utility of a novel diabetes-specific family functioning typology to explain variability in response to a family-focused intervention. Findings from this work answer the calls for systems-level consideration in precision behavioral medicine and drive hypothesis generation for future, tailored interventions. Registration: The larger RCT is registered with ClinicalTrials.gov (NCT04347291).

Background: Memory and learning deficits are among the most impactful and longest-lasting symptoms experienced by people with chronic traumatic brain injury (TBI). Despite the persistence of post-TBI memory deficits and their implications for community reintegration, memory rehabilitation is restricted to short-term care within structured therapy sessions. Technology shows promise to extend memory rehabilitation into daily life and to increase the number and contextual diversity of learning opportunities. Ecological momentary assessment and intervention frameworks leverage mobile phone technology to assess and support individuals’ behaviors across contexts and have shown benefits in other chronic conditions. However, few studies have used regular outreach via text messaging for adults with chronic TBI, and none have done so to assess and support memory. Objective: This study aimed to develop and test the usability of memory ecological momentary intervention (MEMI), a text message–based assessment and intervention tool for memory in daily life. MEMI is designed to introduce new information, cue retrieval of the information, and assess learning across time and contexts. We tested MEMI via an iterative, user-centered design process to ready it for a future trial. Methods: We developed MEMI by leveraging automated text messages for prompts using a REDCap (Research Electronic Data Capture)/Twilio interface linking to the Gorilla web-based behavioral experimental platform. We recruited 14 adults with chronic, moderate-severe TBI from the Vanderbilt Brain Injury Patient Registry to participate in 3 rounds of usability testing: one round of ThinkAloud sessions using the platform and providing real-time feedback to an experimenter (n=4) and 2 rounds of real-world usability testing in which participants used MEMI in their daily lives for a week and provided feedback (n=5/round). We analyzed engagement and quantitative and qualitative user feedback to assess MEMI’s usability and acceptability. Results: Participants were highly engaged with MEMI, completing an average of 11.8 out of 12 (98%) possible sessions. They rated MEMI as highly usable, with scores on the System Usability Scale across all rounds equivalent to an A+ on a standardized scale. In semistructured interviews, they stated that MEMI was simple and easy to use, that daily retrieval sessions were not burdensome, and that they perceived MEMI as helpful for memory. We identified a few small issues (eg, instruction wording) and made improvements between usability testing rounds. Conclusions: Testing MEMI with adults with chronic TBI revealed that this technology is highly usable and favorably rated for this population. We incorporated feedback regarding users’ preferences and plan to test the efficacy of this tool in a future clinical trial.

This paper proposes an approach to assess digital health readiness in clinical settings to understand how prepared, experienced, and equipped individual people are to participate in digital health activities. Existing digital health literacy and telehealth prediction tools exist but do not assess technological aptitude for particular tasks or incorporate available electronic health record data to improve efficiency and efficacy. As such, we propose a multidomain digital health readiness assessment that incorporates a person’s stated goals and motivations for use of digital health, a focused digital health literacy assessment, passively collected data from the electronic health record, and a focused aptitude assessment for critical skills needed to achieve a person’s goals. This combination of elements should allow for easy integration into clinical workflows and make the assessment as actionable as possible for health care providers and in-clinic digital health navigators. Digital health readiness profiles could be used to match individuals with support interventions to promote the use of digital tools like telehealth, mobile apps, and remote monitoring, especially for those who are motivated but do not have adequate experience. Moreover, while effective and holistic digital health readiness assessments could contribute to increased use and greater equity in digital health engagement, they must also be designed with inclusivity in mind to avoid worsening known disparities in digital health care.

Background: Despite the potential to significantly reduce complications, many patients do not consistently receive diabetes preventive care. Our research team recently applied user-centered design sprint methodology to develop a patient portal intervention empowering patients to address selected diabetes care gaps (eg, no diabetes eye examination in last 12 months). Objective: This study aims to evaluate the effect of our novel diabetes care gap intervention on completion of selected evidence-based diabetes preventive care services and secondary outcomes. Methods: We are conducting a pragmatic randomized controlled trial of the effect of the intervention on diabetes care gaps. Adult patients with diabetes mellitus (DM) are recruited from primary care clinics affiliated with Vanderbilt University Medical Center. Participants are eligible if they have type 1 or 2 DM, can read in English, are aged 18-75 years, have a current patient portal account, and have reliable access to a mobile device with internet access. We exclude patients with medical conditions that prevent them from using a mobile device, severe difficulty seeing, pregnant women or women who plan to become pregnant during the study period, and patients on dialysis. Participants will be randomly assigned to the intervention or usual care. The primary outcome measure will be the number of diabetes care gaps among 4 DM preventive care services (diabetes eye examination, pneumococcal vaccination, hemoglobin A1c, and urine microalbumin) at 12 months after randomization. Secondary outcomes will include diabetes self-efficacy, confidence managing diabetes in general, understanding of diabetes preventive care, diabetes distress, patient portal satisfaction, and patient-initiated orders at baseline, 3 months, 6 months, and 12 months after randomization. An ordinal logistic regression model will be used to quantify the effect of the intervention on the number of diabetes care gaps at the 12-month follow-up. For dichotomous secondary outcomes, a logistic regression model will be used with random effects for the clinic and provider variables as needed. For continuous secondary outcomes, a regression model will be used. Results: This study is ongoing. Recruitment was closed in February 2022; a total of 433 patients were randomized. Of those randomized, most (n=288, 66.5%) were non-Hispanic White, 33.5% (n=145) were racial or ethnic minorities, 33.9% (n=147) were aged 65 years or older, and 30.7% (n=133) indicated limited health literacy. Conclusions: The study directly tests the hypothesis that a patient portal intervention—alerting patients about selected diabetes care gaps, fostering understanding of their significance, and allowing patients to initiate care—will reduce diabetes care gaps compared with usual care. The insights gained from this study may have broad implications for developing future interventions to address various care gaps, such as gaps in cancer screening, and contribute to the development of effective, scalable, and sustainable approaches to engage patients in chronic disease management and prevention. Trial Registration: ClinicalTrials.gov NCT04894903; https://classic.clinicaltrials.gov/ct2/show/NCT04894903 International Registered Report Identifier (IRRID): DERR1-10.2196/56123

Automated text messaging is a promising approach to monitor patients after hospital discharge and avert readmissions; however, it is not known to what extent patients would engage with this type of program and whether engagement may vary based on patients' characteristics. Using data from a 30‐day postdischarge texting program at a large university hospital, we examined engagement over time (operationalized as response rate to text messages) and patient characteristics associated with engagement. Of the 1324 patients in the study sample, 838 (63%) stayed in the program for the full duration. Among those retained, the median response rate was 33% (interquartile range: 11%–77%) and decreased over time. Patients who were male (p < .05), were Black/African American (p < .001), had lower health literacy (p < .01), or had not recently logged into the patient portal (p < .001), all had lower response rates. Results support closer examinations of patient engagement in hospital‐based texting programs and who is positioned to benefit.