The RE-AIM planning and evaluation framework was conceptualized two decades ago. As one of the most frequently applied implementation frameworks, RE-AIM has now been cited in over 2,800 publications. ...This paper describes the application and evolution of RE-AIM as well as lessons learned from its use. RE-AIM has been applied most often in public health and health behavior change research, but increasingly in more diverse content areas and within clinical, community, and corporate settings. We discuss challenges of using RE-AIM while encouraging a more pragmatic use of key dimensions rather than comprehensive applications of all elements. Current foci of RE-AIM include increasing the emphasis on cost and adaptations to programs and expanding the use of qualitative methods to understand "how" and "why" results came about. The framework will continue to evolve to focus on contextual and explanatory factors related to RE-AIM outcomes, package RE-AIM for use by non-researchers, and integrate RE-AIM with other pragmatic and reporting frameworks.
Customer discovery, an entrepreneurial and iterative process to understand the context and needs of potential adoption agencies, may be an innovative strategy to improve broader dissemination of ...evidence-based interventions. This paper describes the customer discovery process for the Building Healthy Families (BHF) Online Training Resources and Program Package (BHF Resource Package) to support rural community adoption of an evidence-based, family healthy weight program.
The customer discovery process was completed as part of a SPeeding Research-tested INTerventions (SPRINT) training supported by the U.S. Centers for Disease Control and Prevention. Customer discovery interviews (n=47) were conducted with people that could be potential resource users, economic buyers, and BHF adoption influencers to capture multiple contextual and needs-based factors related to adopting new evidence-based interventions. Qualitative analyses were completed in an iterative fashion as each interview was completed.
The BHF Resource Package was designed to be accessible to a variety of implementation organizations. However, due to different resources being available in different rural communities, customer discovery interviews suggested that focusing on rural health departments may be a consistent setting for intervention adoption. We found that local health departments prioritize childhood obesity but lacked the training and resources necessary to implement effective programming. Several intervention funding approaches were also identified including (1) program grants from local and national foundations, (2) healthcare community benefit initiatives, and (3) regional employer groups. Payment plans recommended in the customer discovery interviews included a mix of licensing and technical support fees for BHF delivery organizations, potential insurance reimbursement, and family fees based on ability to pay. Marketing a range of BHF non-weight related outcomes was also recommended during the customer discovery process to increase the likelihood of BHF scale-up and sustainability.
Engaging in customer discovery provided practical directions for the potential adoption, implementation, and sustainability of the BHF Resource Package. However, the inconsistent finding that health departments are both the ideal implementation organization, but also see childhood obesity treatment as a clinical service, is concerning.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The implementation of evidence-based physical activity interventions is improved when integrated research-practice partnerships are used. These partnerships consider both research- and practice-based ...evidence that moves beyond only assessing program efficacy. Our novel hypothesis is that integrated research-practice partnerships may lead to interventions that are practical and effective, reach more participants, and are more likely to be sustained in practice.
We examined participation rates, engagement, and weight-loss outcomes of comparison group participants in a diabetes prevention trial who enrolled in a digitally delivered diabetes prevention program ...(ie, an active intervention) after the original trial ended. We evaluated these outcomes by using the Wilcoxon signed-rank test and 1-sample z test. We found a high participation rate (73%) among comparison group participants and comparable weight-loss outcomes at 12 months (6.8 lb) after initiating participation in the active intervention relative to intervention group participants during the original trial. Findings support providing evidence-based interventions for comparison or control group participants post-trial. Findings also support examining the cost-effectiveness of post-trial interventions, regardless of the limitations of acquiring post-trial data on weight in an uncontrolled setting.We examined participation rates, engagement, and weight-loss outcomes of comparison group participants in a diabetes prevention trial who enrolled in a digitally delivered diabetes prevention program (ie, an active intervention) after the original trial ended. We evaluated these outcomes by using the Wilcoxon signed-rank test and 1-sample z test. We found a high participation rate (73%) among comparison group participants and comparable weight-loss outcomes at 12 months (6.8 lb) after initiating participation in the active intervention relative to intervention group participants during the original trial. Findings support providing evidence-based interventions for comparison or control group participants post-trial. Findings also support examining the cost-effectiveness of post-trial interventions, regardless of the limitations of acquiring post-trial data on weight in an uncontrolled setting.
Effects of a Digital Diabetes Prevention Program: An RCT Katula, Jeffrey A.; Dressler, Emily V.; Kittel, Carol A. ...
American journal of preventive medicine,
April 2022, 2022-04-00, 20220401, Volume:
62, Issue:
4
Journal Article
Peer reviewed
Open access
In light of the need to expand the reach and access of clinically proven digital Diabetes Prevention Programs (d-DPPs) and the need for rigorous evidence of effectiveness, the purpose of this study ...was to determine the effectiveness of a digital Diabetes Prevention Program for improving weight, HbA1c, and cardiovascular risk factors among people with prediabetes compared to enhanced standard care plus waitlist control.
This was a single-blind RCT among participants at risk of developing type 2 diabetes and included 12 months of follow-up.
A total of 599 volunteer patients with prediabetes were recruited primarily through electronic medical records and primary care practices.
Participants were randomized to either a d-DPP (n=299) or a single-session small-group diabetes-prevention education class (n=300) focused on action planning for weight loss. The d-DPPs consisted of 52 weekly sessions, lifestyle coaching, virtual peer support, and behavior tracking tools.
The primary outcome was a change in HbA1c from baseline to 12 months using intent-to-treat analyses. On the basis of multiple comparisons of endpoints, 95% CIs are presented and 2-sided p<0.025 was required for statistical significance. Secondary outcomes included body weight and cardiovascular disease risk factors.
Among 599 randomized participants (mean age=55.4 years, 61.4% women), 483 (80%) completed the study. The d-DPPs produced significantly greater reductions in HbA1c (0.08%, 95% CI= −0.12, −0.03) and percentage change in body weight (−5.5% vs −2.1%, p<0.001) at 12 months. A greater proportion of the d-DPPs group achieved a clinically significant weight loss ≥5% (43% vs 21%, p<0.001), and more participants shifted from prediabetes to normal HbA1c range (58% vs 48%, p=0.04). Engagement in d-DPPs was significantly related to improved HbA1c and weight loss.
This d-DPPs demonstrated clinical effectiveness and has significant potential for widespread dissemination and impact, particularly considering the growing demand for telemedicine in preventive healthcare services.
Trial Registration: This study is registered at www.clinicaltrials.gov (ClinicalTrials.gov Identifier: NCT03312764).
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Summary
Rural adults have a higher risk of developing obesity than urban adults. Several evidence‐based interventions have targeted rural regions, but their impact, defined as reach (number and ...representativeness of participants) by effectiveness, has not been examined. The purpose of this review was to determine the impact of rural weight loss interventions and the availability of data across dimensions of the reach, effectiveness, adoption, implementation, and maintenance (RE‐AIM) framework. A systematic review was conducted to identify rural weight loss interventions that targeted adults. RE‐AIM‐related data were ed from each article. We performed a meta‐analysis to examine effectiveness. Sixty‐four articles reported on rural weight loss interventions, describing 50 unique interventions. The median number of participants was 107. Median participation rate differed between values reported by the authors (62%) and values computed using a standard method (32%). Two studies reported on sample representativeness; none reported comparisons made between target and actual delivery settings. Median weight loss per participant was 3.64 kg. Meta‐analyses revealed the interventions achieved a significant weight reduction, and longer‐duration interventions resulted in greater weight loss. Rural weight loss interventions appear to be effective in supporting clinically meaningful weight loss but reach and cost outcomes are still difficult to determine.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The purpose of this investigation was to understand perspectives of physicians, nurses, and staff regarding the feasibility of implementing an evidence-based weight management program to support ...primary care practice. An exploratory aim was to examine differences in responses based on the clinic location. Ten focus groups were conducted with primary care staff from rural, micropolitan, and metropolitan clinics. The Promoting Action on Research in Health Services (PARIHS) framework was used to inform the interview guide. Transcripts were reviewed to identify common themes among PARIHS constructs (evidence, context, and facilitation). Presence of comorbidities (e.g., diabetes, hypertension) were typical prompts for provider-led discussions about patient weight. Metropolitan clinics reported the availability of health coaching, diabetes education, or dietician consultation, but no clinic reported offering a comprehensive weight management program. Participants agreed it is possible to implement a weight management program through primary care, but cited potential facilitation challenges such as costs, clinic resources, and individual patient barriers. More enthusiasm arose for a referral program with patient tracking. Program characteristics such as proven efficacy, individual tailoring, program accessibility, and patient feedback to the providers were desired. Rural focus group participants reported unique barriers (lack of local resources) and facilitators (more flexibility in practice changes) to weight management when compared to metropolitan and micropolitan focus groups. Primary care staff are interested in weight management solutions for their patients and would prefer an evidence-based program to which they could refer patients, receive feedback on patient progress, and sustainably include as part of their regular services.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objectives. Despite evidence of self-efficacy and physical function’s influences on functional limitations in older adults, few studies have examined relationships in the context of complex, ...real-world tasks. The present study tested the roles of self-efficacy and physical function in predicting older adults’ street-crossing performance in single- and dual-task simulations. Methods. Lower-extremity physical function, gait self-efficacy, and street-crossing success ratio were assessed in 195 older adults (60–79 years old) at baseline of a randomized exercise trial. During the street-crossing task, participants walked on a self-propelled treadmill in a virtual reality environment. Participants crossed the street without distraction (single-task trials) and conversed on a cell phone (dual-task trials). Structural equation modeling was used to test hypothesized associations independent of demographic and clinical covariates. Results. Street-crossing performance was better on single-task trials when compared with dual-task trials. Direct effects of self-efficacy and physical function on success ratio were observed in dual-task trials only. The total effect of self-efficacy was significant in both conditions. The indirect path through physical function was evident in the dual-task condition only. Conclusion. Physical function can predict older adults’ performance on high fidelity simulations of complex, real-world tasks. Perceptions of function (i.e., self-efficacy) may play an even greater role. The trial is registered with United States National Institutes of Health ClinicalTrials.gov (ID: NCT01472744; Fit & Active Seniors Trial).
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
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.
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.
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.
This trial of a digital DPP will allow the research team to determine the relationships between reach, effectiveness, implementation, and costs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
To examine changes in cardiovascular disease (CVD) risk outcomes of overweight/obese adults with prediabetes.
Using data from a randomized control trial of digital diabetes prevention program (d‐DPP) ...with 599 participants. We applied the atherosclerotic CVD (ASCVD) risk calculator to predict 10-year CVD risk for d‐DPP and small education (comparison) groups. Between-group risk changes at 4 and 12 months were compared using a repeated measures linear mixed-effect model. We examined within-group differences in proportion of participants over time for specific CVD risk factors using generalized estimating equations.
We found no differences between baseline 10-year ASCVD risk. Relative to the comparison group, the d‐DPP group experienced greater reductions in predicted 10-year ASCVD risk at each follow-up visit and a significant group difference at 4 months (−0.96%; 95% confidence interval: −1.58%, −0.34%) (but not at 12 months). Additionally, we observed that the d‐DPP group experienced a decreased proportion of individuals with hyperlipidemia (18% and 16% from baseline to 4 and 12 months), high-risk total cholesterol (8% from baseline to 12 months), and being insufficiently active (26% and 22% from baseline to 4 and 12 months at follow-up time points.
Our findings suggest that a digitally adapted DPP may promote the prevention of cardiometabolic disease among overweight/obese individuals with prediabetes. However, given the lack of maintenance of effect on ASCVD risk at 12 months, there may also be a need for additional interventions to sustain the effect detected at 4 months.
•The 10-year CVD risk was reduced by 0.96% with a d‐DPP at 4 months.•The proportion of people with cardiometabolic risk factors was reduced in a d‐DPP.•Targeting peoples with prediabetes at intermediate or high ASCVD risk at baseline.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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