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Estimates of the minimal clinically important difference (MCID) for physical activity (PA) in chronic obstructive pulmonary disease (COPD) are needed. The objective is to provide an anchor-based estimate of the MCID for daily step count. PA was promoted in persons with COPD using a pedometer (Omron HJ-720ITC) alone or a pedometer plus interactive website for 3 months. Participants wore the pedometer daily and received phone calls monthly to ascertain medical events. Medical events were counted when a participant self-reported that he/she had (1) worsening of breathing, (2) change to breathing medications, (3) medical care from an emergency room for any reason, or (4) hospitalization for any reason. Generalized linear regression models assessed daily step count as change at the end of study and averaged over the 15, 31, or 61 days centered on the event, in those with an event compared to those without one. All categories of events carried equal weight in the analyses. We studied 93 persons, 46 of whom had an event. Participants who experienced an event had a decrease of 1086 (95% confidence interval (CI): −2124 to −48) or 887 (95% CI: −2030 to 257) steps/day in the pedometer plus website or pedometer alone groups, respectively, compared to those without one. In the days centered on an event, participants who had an event experienced a decrease of 882–983 steps/day (pedometer plus website) or a decrease of 351–495 steps/day (pedometer alone), compared to those without one. The MCID for PA in COPD ranges from 350 steps/day to 1100 steps/day.

Introduction Almost half of US adults have hypertension (HTN) and those with low-income are more likely to have worse blood pressure (BP) control. To help manage BP, recent interventions have introduced remote, or at-home, BP monitoring. Objective To assess the feasibility of a subscriber identity module (SIM)-enabled remote BP monitoring (RBPM) intervention among individuals with HTN living in low-income housing. Methods A prospective, observational cohort pilot study of 15 low-income older adult participants was conducted. RBPM was delivered through CareSimple®, a cloud-based, SIM-enabled, remote BP cuff. Participants were asked to check their BP at least twice weekly for 4 months, and readings were monitored via a central dashboard. Feasibility and acceptability were measured by the feasibility of the intervention measure (FIM) and acceptability of the intervention measure (AIM) via survey and semi-structured interviews. Data analyses were by descriptive and paired t-test statistics, and qualitative descriptive analysis. Result Fourteen participants with an average age of 76.5 years (SD: 9.0) completed the study. The AIM and FIM mean scores at month 4 were 4.14 (SD: 0.70) and 4.27 (SD: 0.67), respectively (scale: 1–5). Facilitators of the intervention included positive perceptions of the BP device, text messaging, and the onsite champion. Barriers were BP measurement and accuracy concerns, lack of appropriate home furniture, and negative perception of text messaging. At month 4, there were non-statistically significant decreases in average systolic BP (mean difference −3.9 mm Hg), and diastolic BP (mean difference −1.4 mm Hg). Conclusion SIM-enabled BP remote monitoring with text messages was feasible and acceptable in older adult low-income housing residents with HTN.

Digital interventions have gained momentum in terms of behavioral health. However, owing to lacking standard approaches or tools for creating digital behavioral interventions, clinical researchers follow widely varying conceptions of how best to go about digital intervention development. Researchers also face significant cost-, time-, and expertise-related challenges in digital intervention development. Improving the availability of tools and guidance for researchers will require a thorough understanding of the motivations and needs of researchers seeking to create digital interventions. This study aims to understand the perceptions of behavioral researchers toward digital interventions, and inform the use of these interventions, by documenting the reasons why researchers are increasingly focusing their efforts on digital interventions and their perspectives on the perceived benefits that digital approaches can provide for researchers and intervention recipients. We conducted semistructured qualitative interviews with 18 researchers who had experience designing digital behavioral interventions or running studies with them. A convenience sample of interviewees was recruited from among users of the Computerized Intervention Authoring System platform, a web-based tool that facilitates the process of creating and deploying digital interventions in behavioral research. Interviews were conducted over teleconference between February and April 2020. Recordings from the interviews were transcribed and thematically analyzed by multiple coders. Interviews were completed with 18 individuals and lasted between 24 and 65 (mean 46.9, SD 11.3) minutes. Interviewees were predominantly female (17/18, 94%) and represented different job roles, ranging from researcher to project or study staff. Four major themes came out of the interviews concerning the benefits of digital interventions for behavioral health: convenience and flexibility for interventionists and recipients, support for implementing evidence-based interventions with fidelity, scaling and improving access to interventions, and getting a foot in the door despite stigma and disenfranchisement. Interviewees described a number of important potential benefits of digital interventions, particularly with respect to scientific rigor, scalability, and overcoming barriers to reaching more people. There are complex considerations with regard to translating behavior change strategies into digital forms of delivery, and interventionists make individual, sometimes unexpected, choices with minimal evidence of their relative effectiveness. Future research should investigate how behavioral researchers can be supported in making these choices toward usability, ease of access, and approachability of digital interventions. Our study underscores the need for authoring platforms that can facilitate the process of creating and deploying digital interventions to reach their full potential for interventionists and recipients alike.

Objectives/Goals: The University of Michigan (U-M) is a large research enterprise with a broad infrastructure. This poses challenges for clinical research professionals (CRPs) to create and utilize professional networks. To address this issue, we created a CoP to provide networking opportunities and support to CRPs at schools and colleges across the university. Methods/Study Population: We began by creating a document that detailed the needs of CRPs, defined CoP goals, and described the initial cohort, establishing a shared vision and structured guidance for recruitment. The CoP was designed to meet monthly for 6 months with the ability to continue participation as new cohorts are added. Facilitators identified 30 CRPs for cohort 1 representing a variety of locations and research types across the university. CRPs had at least 2 years of experience and demonstration of leadership responsibilities. CRPs were invited to submit a brief interest form committing to support the CoP. Communication tools were also provided so that participants could connect between meetings. Results/Anticipated Results: The program began in June 2025 with 15 participants accepting the initial invitation. Twelve CRPs attended the kick-off event, which included establishing group norms, goals, and a speed networking activity to promote cross-department networking. Participants ranged in experience from less than 3 years to over 10 years and represented 11 different departments. Of the 15 participants, 10 had 8 or more years of experience. Members selected topics including Breaking Out of Your Silo, Mentoring Up, and Time Management, and a mixed in-person and virtual schedule was chosen by the initial cohort members. Program evaluation is ongoing, including session attendance, participant willingness to continue in the CoP, sense of community, value provided by CoP elements, and feasibility of continued programming. Discussion/Significance of Impact: CoPs can be created at large institutions with careful planning and intentionality. We established a strong initial cohort that can maintain continuity and mentor future members. Communication tools for continued engagement between meetings help cross-department networking, which is challenging to maintain in a busy research environment.

Digital behavioral interventions have become increasingly popular for their ability to support patient diagnosis and treatment, chronic disease self-management, behavior change, and adherence to recommended care. However, digital intervention development is impeded by challenges such as limited technical skills, limited access to developers, and cost. The purpose of this study is to elicit in-depth qualitative feedback from intervention developers who have interest in digital behavioral interventions but lack programming skills regarding the barriers they experience and key considerations in the design and implementation of digital interventions. This study aims to understand barriers in the design and implementation of digital behavioral interventions, as well as to identify key considerations for researchers who are developing these interventions. We conducted semistructured qualitative interviews with 18 researchers who had experience either designing (but not coding) digital behavioral interventions or running research studies with them. Participants were a convenience sample of users of the Computerized Intervention Authoring System platform, an existing no-code development platform for building digital intervention content, and were recruited through either direct email solicitation or snowball sampling. All interviews were conducted and recorded over videoconference between February and April 2020. Recordings from interviews were transcribed and thematically analyzed by multiple coders. Interviews were completed with 18 participants and lasted between 24 and 65 (mean 46.9, SD 11.3) minutes. Interviewees were predominantly female (17/18, 94%) and represented different job roles, ranging from researcher to project/study staff. Three key barriers in the development of digital behavior interventions were identified during interviews: lack of cross-disciplinary understanding; variability in recipients' technology access, infrastructure, and literacy; and the idea that evidence-based in-person interactions do not translate directly to digital interactions. Interviewees identified several key considerations that interventionists learned to prioritize, which have the potential to overcome these barriers and lead to successful interventions. Barriers in the development of digital behavioral interventions are often created by a lack of cross-disciplinary understanding, which can lead to difficulties conceptualizing interventions, unrealistic expectations in terms of cost, and confusion about the development process. Moreover, concerns about research study participant characteristics and access to technology, as well as the translation of in-person interventions to digital, are apparent. Appropriate training in how to work with software development teams may help future digital behavior intervention creators overcome these barriers and may lead to new, exciting innovations in this space.

The COVID-19 pandemic resulted in rapid changes in how patient care was provided, particularly through the expansion of telehealth and audio-only phone-based care. The goal of this study was to evaluate inequities in video and audio-only care during various time points including the initial wave of the COVID-19 pandemic, later stages of the pandemic, and a historical control. We sought to understand the characteristics of care during this time for a variety of different groups of patients that may experience health care inequities. We conducted a retrospective analysis of electronic health record (EHR) data from encounters from 34 family medicine and internal medicine primary care clinics in a large, Midwestern health system, using a repeated cross-sectional, observational study design. These data included patient demographic data, as well as encounter, diagnosis, and procedure records. Data were obtained for all in-person and telehealth encounters (including audio-only phone-based care) that occurred during 3 separate time periods: an initial COVID-19 period (T2: March 16, 2020, to May 3, 2020), a later COVID-19 period (T3: May 4, 2020, to September 30, 2020), and a historical control period from the previous year (T1: March 16, 2019, to September 30, 2019). Primary analysis focused on the status of each encounter in terms of whether it was completed as scheduled, it was canceled, or the patient missed the appointment. A secondary analysis was performed to evaluate the likelihood of an encounter being completed based on visit modality (phone, video, in-person). In total, there were 938,040 scheduled encounters during the 3 time periods, with 178,747 unique patients, that were included for analysis. Patients with completed encounters were more likely to be younger than 65 years old (71.8%-74.1%), be female (58.8%-61.8%), be White (75.6%-76.7%), and have no significant comorbidities (63.2%-66.8%) or disabilities (53.2%-61.1%) in all time periods than those who had only canceled or missed encounters. Effects on different subpopulations are discussed herein. Findings from this study demonstrate that primary care utilization across delivery modalities (in person, video, and phone) was not equivalent across all groups before and during the COVID-19 pandemic and different groups were differentially impacted at different points. Understanding how different groups of patients responded to these rapid changes and how health care inequities may have been affected is an important step in better understanding implementation strategies for digital solutions in the future.

Objectives/Goals: Effective research relies on a well-trained study coordinator workforce, but mentorship programs are lacking. Retaining and empowering career development for skilled research staff is challenging. To address this, the Michigan Institute for Clinical and Health Research launched the STEP.up program. Methods/Study Population: The Staff Enrichment Program for Research Professionals (STEP.up) was created in 2018. To increase knowledge and awareness of our program, we developed an implementation guide to share best practices and open access to our program structure and content. We identified seven critical elements integral to program success. The implementation guide provides a description and rationale for these elements. We partnered with an instructional designer to build a descriptive and easy-to-use guide that describes insights into the successful implementation of the program, practical strategies for program management, and adaptable resources for institutions to use and tailor to their unique needs. Results/Anticipated Results: In the STEP.up program, early career, new-to-role, or new-to-organization research staff members are paired with senior research professionals in a 9-month structured mentorship and career development experience to promote professional development, job satisfaction, and retention for individuals currently working as research professionals. Of the 82 participants from 2018 to 2024, 76 (93%) have remained in their roles as study coordinators. The STEP.up program implementation guide provides the tools, resources, and insights senior research professionals need to implement this program successfully at their sites. Discussion/Significance of Impact: STEP.up program materials are available as an open-source resource on the DIAMOND portal. This resource can encourage others to invest in structured mentorship for research professionals to help establish a culture of growth and cultivate a resilient, skilled, and committed research workforce.

Objectives/Goals: To tailor support for behavioral and social science research (BSSR), it is helpful to understand this broad category. As a first step to characterizing BSSR at University of Michigan (UM), our goal is to use a large language model (LLM) to identify health-related BSSR from a database of funded studies. Methods/Study Population: We are using a private, secure version of Open AI ChatGPT-4.1 LLM to evaluate whether studies are health-related BSSR or not based on the study team’s (1) abstract, (2) objectives, and (3) key words entered into UM’s internal research proposal system for all studies funded over the last 10 years (i.e., 2014 – 2024). The model included a prompt with the National Institutes of Health (NIH) definition of BSSR and was instructed to categorize the research as being BSSR, not BSSR, or possibly BSSR. Results from the LLM were compared for consistency with assessments made by human-made decision rules. Results/Anticipated Results: Preliminary results from a pilot sample of 150 studies funded in 2024 (~5%) reviewed by ChatGPT for BSSR status revealed: 6 false positives, 128 true negatives, 14 true positives, and 2 false negatives. Accuracy = 95%, precision = 70%, recall (sensitivity) = 88%, specificity = 96%, and F1 Score = 0.78. ChatGPT and human-based decisions differed primarily on cognition and vehicle technology studies and studies for which information was sparse. Further refinements to the prompt are being made and applied to the remaining studies funded in 2024 before expanding to the entire sample of studies from the last 10 years. Discussion/Significance of Impact: It is time and cost prohibitive for a human to review and classify all funded studies at UM as BSSR or not. Using LLMs offers the potential to make this classification work feasible with limited resources, which is a necessary step toward understanding the state of BSSR.

There are growing efforts to recruit and retain individuals from various populations in clinical trials to increase trial representativeness. Nonetheless, these challenges can hamper the development of clinical trials, contributing to increased inequities. This study explored the barriers and facilitators of participating in a mobile health trial designed to improve blood pressure (BP) among Blacks with uncontrolled hypertension from underserved communities. Participants were recruited from a larger mHealth clinical trial, MI-BP, across emergency departments, mobile health units, and community-based settings. We conducted an explanatory sequential mixed methods design to quantitatively examine participants' experiences with the MI-BP trial including satisfaction and reasons for dropping out. The qualitative semi-structured interviews expanded on participant experiences based on the quantitative results. Quantitative and qualitative results were integrated to provide a more comprehensive understanding. Fifty-two participants completed the survey and a subset of 22 were interviewed. There were no statistically significant differences on reasons for joining the MI-BP study regardless of study completion. Participants were generally motivated to learn about ways to improve their BP, with many noting positive experiences, including completers and non-completers. Some who dropped out indicated meeting their goal of lowering their BP. Despite a robust consent process, some in the non-completer group reported not understanding certain components of the study compared to the completer group. Additional barriers included concerns over adverse effects and missing worktime. Findings illuminate the barriers and facilitators participants encountered in the MI-BP trial and provides considerations for reducing barriers among this population.

Hypertension is one of the most important cardiovascular disease risk factors and affects >100 million American adults. Hypertension-related health inequities are abundant in Black communities as Black individuals are more likely to use the emergency department (ED) for chronic disease-related ambulatory care, which is strongly linked to lower blood pressure (BP) control, diminished awareness of hypertension, and adverse cardiovascular events. To reduce hypertension-related health disparities, we developed MI-BP, a culturally tailored multibehavior mobile health intervention that targeted behaviors of BP self-monitoring, physical activity, sodium intake, and medication adherence in Black individuals with uncontrolled hypertension recruited from ED and community-based settings. We sought to determine the effect of MI-BP on BP as well as secondary outcomes of physical activity, sodium intake, medication adherence, and BP control compared to enhanced usual care control at 1-year follow-up. We conducted a 1-year, 2-group randomized controlled trial of the MI-BP intervention compared to an enhanced usual care control group where participants aged 25 to 70 years received a BP cuff and hypertension-related educational materials. Participants were recruited from EDs and other community-based settings in Detroit, Michigan, where they were screened for initial eligibility and enrolled. Baseline data collection and randomization occurred approximately 2 and 4 weeks after enrollment to ensure that participants had uncontrolled hypertension and were willing to take part. Data collection visits occurred at 13, 26, 39, and 52 weeks. Outcomes of interest included BP (primary outcome) and physical activity, sodium intake, medication adherence, and BP control (secondary outcomes). We obtained consent from and enrolled 869 participants in this study yet ultimately randomized 162 (18.6%) participants. At 1 year, compared to the baseline, both groups showed significant decreases in systolic BP (MI-BP group: 22.5 mm Hg decrease in average systolic BP and P<.001; control group: 24.1 mm Hg decrease and P<.001) adjusted for age and sex, with no significant differences between the groups (time-by-arm interaction: P=.99). Similar patterns where improvements were noted in both groups yet no differences were found between the groups were observed for diastolic BP, physical activity, sodium intake, medication adherence, and BP control. Large dropout rates were observed in both groups (approximately 60%). Overall, participants randomized to both the enhanced usual care control and MI-BP conditions experienced significant improvements in BP and other outcomes; however, differences between groups were not detected, speaking to the general benefit of proactive outreach and engagement focused on cardiometabolic risk reduction in urban-dwelling, low-socioeconomic-status Black populations. High dropout rates were found and are likely to be expected when working with similar populations. Future work is needed to better understand engagement with mobile health interventions, particularly in this population. ClinicalTrials.gov NCT02955537; https://clinicaltrials.gov/study/NCT02955537. RR2-10.2196/12601.