The Impact of Digital Mental Health Services on Loneliness and Mental Health: Results from a Prospective, Observational Study.

BACKGROUND: Loneliness has increased since the COVID-19 pandemic and negatively impacts mental health. This study examined relationships between loneliness and mental health among adults using a digital mental health platform. METHODS: A purposive sample of 919 participants (97% response rate) who were newly enrolled in the platform completed a survey on loneliness, depression, anxiety, well-being, stress, social support, and comorbidities at baseline and 3 months. Platform engagement was tracked during this period. We examined baseline differences between lonely and non-lonely participants; associations between loneliness, mental health symptoms, and comorbidities; and changes in loneliness and mental health through engagement in any form of care. RESULTS: At baseline, 57.8% of the sample were categorized as lonely. Loneliness was associated with younger age, fewer years of education, and the presence of a comorbidity (p values < .05). Baseline loneliness was associated with greater depression, anxiety, and stress and lower well-being and social support (ps < .001). The percentage of lonely participants decreased at follow-up (57.6% to 52.9%, p = .03). Those who improved in loneliness improved in mental health symptoms, well-being, and social support (ps < .001). Lonely participants who engaged in any form of care reported a greater reduction in loneliness than those who did not engage (p = .04). CONCLUSIONS: This study confirms previous findings of the high prevalence of loneliness among adults and risk factors for increased loneliness. Findings highlight the potential of digital platforms to reach lonely individuals and alleviate loneliness through remote mental health support.

Psychometric assessment of the Brief Weight-Loss-Related Behavior Self-Efficacy Survey in adults with prediabetes.

Self-efficacy is a commonly examined cognitive determinant of behavior change in weight-loss trials, but there has been little uniformity in its measurement. To address this, a recently developed survey captures self-efficacy as it relates to three behavioral domains of interest to weight-loss interventionists: physical activity (PA), healthful eating, and weight loss. The purpose of this study was to test the psychometric properties of the Brief Weight-Loss-Related Behavior Self-Efficacy Scales in a large sample (n = 599) of adults with prediabetes. Participants completed the self-efficacy survey, as well as measures of PA, dietary intake, weight, and height. The factor structure was scrutinized using exploratory and confirmatory factor analysis, which supported a factor structure with three correlated first-order latent self-efficacy factors, specific to PA, healthful eating, and weight loss. This model is statistically equivalent to a hierarchical model including a second-order factor for overall behavioral weight-management self-efficacy. Measurement equivalence/invariance between relevant demographic groups was also supported by tests for equivalence of covariance matrices. Bivariate correlations between self-efficacy factors and measures of PA, dietary intake, and weight support the concurrent validity of score interpretations. Overall, these psychometric analyses support the validity of these scales' scores as independently reflective of self-efficacy for PA, healthful eating, and weight loss. This instrument is useful in clinical research to identify the cognitive drivers of weight loss and weight loss-inducing behavior. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Cost Savings and Reduced Health Care Utilization Associated with Participation in a Digital Diabetes Prevention Program in an Adult Workforce Population.

BACKGROUND: Though in-person delivery of the Diabetes Prevention Program (DPP) has demonstrated medical cost savings, the economic impact of digital programs is not as well understood. OBJECTIVE: This study examines the impact of a digital DPP program on reducing all-cause health care costs and utilization among 2027 adult participants at 12 months. METHODS: A longitudinal, observational analysis of health care claims data was conducted on a workforce population who participated in a digital diabetes prevention program. Differences in utilization and costs from the year prior to program delivery through 1 year after enrollment were calculated using medical claims data for digital DPP participants compared to a propensity matched cohort in a differences-in-differences model. RESULTS: At 1 year, the digital DPP population had a reduction in all-cause health care spend of US$1169 per participant relative to the comparison group (P = 0.01), with US$699 of that savings coming from reduced inpatient spend (P = 0.001). Cost savings were driven by fewer hospital admissions and shorter length of stay (P < 0.001). No other significant results in cost differences were detected. There was a trend toward savings extending into the second year, but the savings did not reach statistical significance. CONCLUSIONS: These results demonstrated significant short-term health care cost savings at 1 year associated with digital DPP program delivery.

Preventing diabetes with digital health and coaching for translation and scalability (PREDICTS): A type 1 hybrid effectiveness-implementation trial protocol.

BACKGROUND: Diabetes prevention remains a top public health priority; digital approaches are potential solutions to existing scalability and accessibility challenges. There remains a gap in our understanding of the relationship between effectiveness, costs, and potential for sustained implementation of digital diabetes prevention strategies within typical healthcare settings. PURPOSE: To describe the methods and design of a type 1 hybrid effectiveness-implementation trial of a digital diabetes prevention program (DPP) using the iPARIHS and RE-AIM frameworks. METHODS: The trial will contrast the effects of two DPP interventions: (1) small group, in-person class, and (2) a digital DPP consisting of small group support, personalized health coaching, digital tracking tools, and weekly behavior change curriculum. Each intervention includes personal action planning with a focus on key elements of the lifestyle intervention from the CDC National DPP. Adults at risk for diabetes (BMI ≥25 and 5.7% ≤ HbA1c ≤ 6.4) will be randomly assigned to either the intervention group (n = 241) or the small group (n = 241). Assessment of primary (HbA1c) and secondary (weight loss, costs, cardiovascular risk factors) outcomes will occur at baseline, 4, and 12 months. Additionally, the trial will explore the potential for future adoption, implementation, and sustainability of the digitally-based intervention within a regional healthcare system based on key informant interviews and assessments of organizational administrators and primary care physicians. CONCLUSION: This trial of a digital DPP will allow the research team to determine the relationships between reach, effectiveness, implementation, and costs.

The Intersection of Behavioral Science and Digital Health: The Case for Academic-Industry Partnerships.

A decade after the first health app became available, the field of digital health has produced a range of health behavior insights and an expanding product portfolio. Despite sustained interest and growth fueled by academic and industry interests, the impact of digital health on health behavior change and related outcomes has been limited. This underperformance relative to expectations may be partially attributed to a gap between industry and academia in which both seek to develop technology-driven solutions but fail to converge around respective, unique strengths. An opportunity exists for new and improved collaborative models of research, innovation, and care delivery that disrupt the field of behavioral medicine and benefit academic and industry interests. For those partnerships to thrive, recognizing key differences between academic and industry roles may help smooth the path. Here we speak specifically to concerns particular to academics and offer suggestions for how to navigate related challenges.

Implementation-effectiveness trial of an ecological intervention for physical activity in ethnically diverse low income senior centers.

BACKGROUND: As the US population ages, there is an increasing need for evidence based, peer-led physical activity programs, particularly in ethnically diverse, low income senior centers where access is limited. METHODS/DESIGN: The Peer Empowerment Program 4 Physical Activity' (PEP4PA) is a hybrid Type II implementation-effectiveness trial that is a peer-led physical activity (PA) intervention based on the ecological model of behavior change. The initial phase is a cluster randomized control trial randomized to either a peer-led PA intervention or usual center programming. After 18 months, the intervention sites are further randomized to continued support or no support for another 6 months. This study will be conducted at twelve senior centers in San Diego County in low income, diverse communities. In the intervention sites, 24 peer health coaches and 408 adults, aged 50 years and older, are invited to participate. Peer health coaches receive training and support and utilize a tablet computer for delivery and tracking. There are several levels of intervention. Individual components include pedometers, step goals, counseling, and feedback charts. Interpersonal components include group walks, group sharing and health tips, and monthly celebrations. Community components include review of PA resources, walkability audit, sustainability plan, and streetscape improvements. The primary outcome of interest is intensity and location of PA minutes per day, measured every 6 months by wrist and hip accelerometers and GPS devices. Secondary outcomes include blood pressure, physical, cognitive, and emotional functioning. Implementation measures include appropriateness & acceptability (perceived and actual fit), adoption & penetration (reach), fidelity (quantity & quality of intervention delivered), acceptability (satisfaction), costs, and sustainability. DISCUSSION: Using a peer led implementation strategy to deliver a multi-level community based PA program can enhance program adoption, implementation, and sustainment. TRIAL REGISTRATION: ClinicalTrials.gov, USA ( NCT02405325 ). Date of registration, March 20, 2015. This website also contains all items from the World Health Organization Trial Registration Data Set.

Adaptation and Feasibility Study of a Digital Health Program to Prevent Diabetes among Low-Income Patients: Results from a Partnership between a Digital Health Company and an Academic Research Team.

Background. The feasibility of digital health programs to prevent and manage diabetes in low-income patients has not been adequately explored. Methods. Researchers collaborated with a digital health company to adapt a diabetes prevention program for low-income prediabetes patients at a large safety net clinic. We conducted focus groups to assess patient perspectives, revised lessons for improved readability and cultural relevance to low-income and Hispanic patients, conducted a feasibility study of the adapted program in English and Spanish speaking cohorts, and implemented real-time adaptations to the program for commercial use and for a larger trial of in multiple safety net clinics. Results. The majority of focus group participants were receptive to the program. We modified the curriculum to a 5th-grade reading level and adapted content based on patient feedback. In the feasibility study, 54% of eligible contacted patients expressed interest in enrolling (n = 23). Although some participants' computer access and literacy made registration challenging, they were highly satisfied and engaged (80% logged in at least once/week). Conclusions. Underserved prediabetic patients displayed high engagement and satisfaction with a digital diabetes prevention program despite lower digital literacy skills. The collaboration between researchers and a digital health company enabled iterative improvements in technology implementation to address challenges in low-income populations.