Evaluating an Insurance-Sponsored Weight Management Program With the RE-AIM Model, West Virginia, 2004-2008

Introduction: Evaluations of weight management programs in real-world settings are lacking. The RE-AIM model (reach, effectiveness, adoption, implementation, maintenance) was developed to address this deficiency. Our primary objective was to evaluate a 12-week insurance-sponsored weight management intervention by using the RE-AIM model, including short-term and long-term individual outcomes and setting-level implementation factors. Our secondary objective was to critique the RE-AIM model and its revised calculation methods. Methods: We created operational definitions for components of the 5 RE-AIM indices and used standardized effect size values from various statistical procedures to measure multiple components or outcomes within each index. We used chi(2) analysis to compare categorical variables and repeated-measures analysis of variance to assess the magnitude of outcome changes over time. Results: On the basis of data for 1,952 participants and surveys completed by administrators at 23 sites, RE-AIM indices ranging from 0 to 100 revealed low program reach and adoption (5.4 and 8.8, respectively), moderate effectiveness (43.8), high implementation (91.4), low to moderate individual maintenance (21.2), and moderate to high site maintenance (77.8). Median (interquartile range) weight loss was 13 lb (6.5-21.4 lb) among participants who completed phase I (12 weeks; 76.5%) and 15 lb (6.1-30.3 lb) among those who completed phase II (1 year; 45.7%). Conclusion: This program had a significant, positive effect on participants and has been sustainable but needs to be expanded for more public health benefit. The RE-AIM model provided a useful framework to determine program strengths and weaknesses and to present them to the insurance agency and public health decision makers

Evaluability Assessment of “Growing Healthy Communities,” a Mini-grant Program to Improve Access to Healthy Foods and Places for Physical Activity

Mini-grants have been used to stimulate multisector collaboration in support of public health initiatives by funding non-traditional partners, such as economic development organizations. Such mini-grants have the potential to increase access to healthy foods and places for physical activity through built environment change, especially in small and rural towns in the United States. Although a promising practice, few mini-grant evaluations have been done. Therefore, our purpose was to conduct an Evaluability Assessment (EA), which is a process that can help promising programs that lack evidence advance toward full-scale evaluation. Specifically, we conducted an Evaluability Assessment of a statewide mini-grant program, called “Growing Healthy Communities” (GHC), to determine if this program was ready for evaluation and identify any changes needed for future implementation and evaluation that could also inform similar programs

Factors Associated with Physical Activity Increases and Decreases Among a Sample of Appalachian Residents During the COVID-19 Pandemic: A Cross-Sectional Study

Introduction: Physical activity (PA) can prevent and reduce the deleterious physical and mental health effects of COVID-19 and associated lockdowns. Research conducted early in the pandemic demonstrates that a greater proportion of adults in the U.S. have decreased than increased PA, and the effects vary by sociodemographic factors. Ongoing evidence is important to identify patterns in PA changes during the pandemic. Purpose: This study aims to identify factors associated with increases and decreases in PA during the COVID-19 pandemic in a convenience sample of adults residing in Appalachia. Methods: Surveys were collected from a convenience sample of adults from eight counties in West Virginia from January to March 2021. Logistic regression analysis was used to identify sociodemographic, health, and rurality factors associated with (1) increased PA and (2) decreased PA during the pandemic, assessed retrospectively via self-report. Results: Analysis of 1,401 survey responses revealed that better self-rated health, lower body mass index, and higher income and education were associated with a greater likelihood of more time spent doing PA during the pandemic (p ≤ .05). Respondents with lower self-rated health, higher body mass index, lower income, and lower levels of education—plus females and those living in a more urban county—were more likely to spend less time doing PA during the pandemic (p ≤ .05). Implications: Analyses suggest that pre-pandemic disparities in PA by health, wealth, and education were exacerbated during the pandemic. These must be addressed before physical inactivity and ill health become endemic to the Appalachian Region

What Sets Physically Active Rural Communities Apart from Less Active Ones? A Comparative Case Study of Three US Counties

Background: Rural US communities experience health disparities, including a lower prevalence of physical activity (PA). However, “Positive Deviants”—rural communities with greater PA than their peers—exist. The purpose of this study was to identify the factors that help create physically active rural US communities. Methods: Stakeholder interviews, on-site intercept interviews, and in-person observations were used to form a comparative case study of two rural counties with high PA prevalence (HPAs) and one with low PA prevalence (LPA) from a southern US state, selected based on rurality and adult PA prevalence. Interview transcripts were inductively coded by three readers, resulting in a thematic structure that aligned with a Community Capital Framework, which was then used for deductive coding and analysis. Results: Fifteen stakeholder interviews, nine intercept interviews, and on-site observations were conducted. Human and Organizational Capital differed between the HPAs and LPA, manifesting as Social, Built, Financial, and Political Capital differences and a possible “spiraling-up” or cyclical effect through increasing PA and health (Human Capital), highlighting a potential causal model for future study. Conclusions: Multi-organizational PA coalitions may hold promise for rural PA by directly influencing Human and Organizational Capital in the short term and the other forms of capital in the long term

An Evaluability Assessment of the West Virginia Physical Activity Plan, 2015: Lessons Learned for Other State Physical Activity Plans

Background The US National Physical Activity Plan (NPAP) was released in 2009 as a national strategic plan to increase physical activity (PA). The NPAP emphasized implementing state and local PA pro- grams. Dissemination of information about NPAP has been lim- ited, however. Community Context West Virginia is a predominantly rural state with high rates of chronic diseases associated with physical inactivity. In 2015 an evaluability assessment (EA) of the West Virginia Physical Activ- ity Plan (WVPAP) was conducted, and community stakeholders were invited to participate in updating the plan. Methods A good EA seeks stakeholder input, assists in identifying program areas that need improvement, and ensures that a full evaluation will produce useful information. Data for this EA were collected via national stakeholder interviews, document reviews, discussions among workgroups consisting of state and local stakehold- ers, and surveys to determine how well the WVPAP had been im- plemented. Outcome The EA highlighted the need for WVPAP leaders to 1) establish a specific entity to implement local PA plans, 2) create sector-spe- cific logic models to simplify the WVPAP for local stakeholders, 3) evaluate the PA plan’s implementation frequently from the out- set, 4) use quick and efficient engagement techniques with stake- holders when working with them to select strategies, tactics, and measurable outcomes, and 5) understand the elements necessary to implement, manage, and evaluate a good PA plan. Interpretation An EA process is recommended for other leaders of PA plans. Our project highlights the stakeholders’ desire to simplify the WVPAP so that it can be set up as a locally driven process that engages communities in implementation

What Sets Physically Active Rural Communities Apart from Less Active Ones? A Comparative Case Study of Three US Counties

Background: Rural US communities experience health disparities, including a lower prevalence of physical activity (PA). However, “Positive Deviants”—rural communities with greater PA than their peers—exist. The purpose of this study was to identify the factors that help create physically active rural US communities. Methods: Stakeholder interviews, on-site intercept interviews, and in-person observations were used to form a comparative case study of two rural counties with high PA prevalence (HPAs) and one with low PA prevalence (LPA) from a southern US state, selected based on rurality and adult PA prevalence. Interview transcripts were inductively coded by three readers, resulting in a thematic structure that aligned with a Community Capital Framework, which was then used for deductive coding and analysis. Results: Fifteen stakeholder interviews, nine intercept interviews, and on-site observations were conducted. Human and Organizational Capital differed between the HPAs and LPA, manifesting as Social, Built, Financial, and Political Capital differences and a possible “spiraling-up” or cyclical effect through increasing PA and health (Human Capital), highlighting a potential causal model for future study. Conclusions: Multi-organizational PA coalitions may hold promise for rural PA by directly influencing Human and Organizational Capital in the short term and the other forms of capital in the long term

Evaluating an insurance -sponsored weight management mprogram using the RE-AIM model.

Determining the public health impact of behavioral obesity treatment programs and industries with whom to ally in disseminating successful programs is critical to our nation\u27s health. In a recent report the National Institute for Health Care Management (NIHCM) Foundation (2005) recognized the leverage that health plans might have by establishing incentives for member participation in obesity treatment programs (i.e., weight management). The RE-AIM model (reach, effectiveness, adoption, implementation, maintenance; Glasgow, Vogt, & Boles, 1999) is designed to summarize the public health impact of health promotion programs and assist decision makers in understanding the ability of programs to: (a) reach large numbers of people representative of the target population, (b) be effective in promoting the targeted health outcome (c) be widely adopted by different and representative settings; (d) be consistently implemented by staff members of various levels of training and expertise; and (e) promote long-term maintenance of health outcomes in individuals and implementation in various sites (Glasgow, Klesges, Dzewaltowski, Estabrooks, & Vogt, 2006). The study used the RE-AIM model to evaluate the public health impact of a 12-week insurance-sponsored behavioral weight management program conducted throughout the state of West Virginia. Phase I (12 weeks) and Phase II (1 year) completion rates (77.5% and 45.7%, respectively) were lower than behavioral programs of similar length (Brownell & Wadden, 1992). Average weight loss of Phase I completers (M = 14.8, SD = 12.3) was comparable to, and Phase II completers (M = 20.9, SD = 22.3) higher than, behavioral programs of similar length (Brownell & Wadden, 1992). Using RE-AIM summary indices ranging from zero to 100, findings indicate the program has low reach and adoption (5.4 and 8.8), moderate short-term effectiveness (43.8), high component implementation (91.4), low to moderate long-term individual maintenance (21.2), and moderate to high site maintenance (77.8). Reasons for these index values, including site and individual performance barriers and facilitators, and six suggestions for improvement are explained using supporting data from index component calculations, site surveys, and focus groups to offer a comprehensive look at what works and potential explanations why

Context, classification and study methodologies in research into nature-based therapies: protocol for a scoping review

Introduction Nature provides an array of health benefits, and recent decades have seen a resurgence in nature-based interventions (NBI). While NBI have shown promise in addressing health needs, the wide variety of intervention approaches create difficulty in understanding the efficacy of NBI as a whole. This scoping review will (1) identify the different nomenclature used to define NBI, (2) describe the interventions used and the contexts in which they occurred and (3) describe the methodologies and measurement tools used in NBI studies. Methods and analysis Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols Extension for Scoping Reviews, four databases will be searched (PubMed, Web of Science, Scopus, ProQuest Dissertations and Theses Global) as well as cross-referencing for published and unpublished (masters theses and dissertations) studies on NBI in humans. Eligible studies must employ intervention or observational designs, and an English-language abstract will be required. Database searches will occur from inception up to the date of the search. Animal-based therapies and virtual-reality therapies involving simulated nature will be excluded. Independent dual screening and data abstraction will be conducted. Results will be analysed qualitatively as well as with simple descriptive statistics (frequencies and percentages). Ethics and dissemination Since this is a scoping review of previously published summary data, ethical approval for this study is not needed. Findings will be published in a peer-reviewed journal. This protocol has been registered with Open Science Framework (https://osf.io/mtzc8)

Field Test of a Passive Infrared Camera for Measuring Trail-Based Physical Activity

Introduction: Trails are ubiquitous and far-reaching, but research on the impact trails have on physical activity is limited by the lack of resource-efficient, accurate, and practical systematic observation tools. Commonly used infrared trail sensors count trail use and may broadly differentiate activity (i.e., bicyclist vs. pedestrian), but cannot detect nuances needed for outcomes research such as frequency, intensity, time, and type of activity. Motion-activated passive infrared cameras (PICs), used in ecological research and visitor management in wildlife areas, have potential applicability as a systematic observation data collection tool. Materials and Methods: We conducted a 7-month field test of a PIC as a systematic observation data collection tool on a hiking trail, using photos to identify each trail user\u27s physical activity type, age, sex, and other characteristics. We also tallied hourly trail use counts from the photos, using Bland–Altman plots, paired t-tests, Concordance Correlation Coefficient, Kendall\u27s Tau-b, and a novel inter-counter reliability measure to test concordance against concurrent hourly counts from an infrared sensor. Results: The field test proved informative, providing photos of 2,447 human users of the trail over 4,974 h of data collection. Nearly all of the users were walkers (94.0%) and most were male (69.2%). More of the males used the trail alone (44.8%) than did females (29.8%). Concordance was strong between instruments (p \u3c 0.01), though biased (p \u3c 0.01). Inter-counter reliability was 91.1% during the field study, but only 36.2% when excluding the hours with no detectable trail use on either device. Bland–Altman plots highlighted the tendency for the infrared sensor to provide higher counts, especially for the subsample of hours that had counts \u3e0 on either device (14.0%; 694 h). Discussion: The study\u27s findings highlight the benefits of using PICs to track trail user characteristics despite the needs to further refine best practices for image coding, camera location, and settings. More widespread field use is limited by the extensive amount of time required to code photos and the need to validate the PICs as a trail use counter. The future potential of PICs as a trail-specific PA research and management tool is discussed