Int.J. Behav. Med. DOI 10.1007/s12529-014-9438-y

Translation of Lifestyle Modification Programs Focused on Physical Activity and Dietary Habits Delivered in Community Settings Mark Stoutenberg & Katie Stanzilis & Ashley Falcon

# International Society of Behavioral Medicine 2014

Abstract Background Lifestyle modification programs (LMPs) can provide individuals with behavioral skills to sustain longterm changes to their physical activity (PA) levels and dietary habits. Yet, there is much work to be done in the translation of these programs to community settings. Purpose This review identified LMPs that focused on changing both PA and dietary behaviors and examined common features and barriers faced in their translation to community settings. Methods A search of multiple online databases was conducted to identify LMPs that included participants over the age of 18 who enrolled in LMPs, offered in community settings, and had the goal of improving both PA and dietary behaviors. Data were extracted on participant demographics, study design characteristics, and study outcome variables including changes in PA, dietary habits, body weight, and clinical outcomes. Results We identified 27 studies that met inclusion criteria. Despite high levels of retention and adherence to the interventions, varying levels of success were observed in increasing PA levels, improving dietary habits, reducing body weight, and improving clinic outcomes. Conclusion LMPs addressing issues of PA and dietary habits can be successfully implemented in a community setting. However, inconsistent reporting of key components in the translation of these studies (participant recruitment, utilization of behavioral strategies) may limit

M. Stoutenberg (*) : K. Stanzilis : A. Falcon Department of Public Health Sciences, University of Miami, 1120 NW 14th Street, Suite 1008, Miami, FL 33136, USA e-mail: [email protected] A. Falcon Department of Wellness and Recreation, University of Miami, Coral Gables, FL, USA

their replication and advancement of future programs. Future efforts should better address issues such as identifying barriers to participation and program implementation, utilization of community resources, and evaluating changes across multiple health behaviors. Keywords Translation . Physical activity . Dietary habits . Implementation . Lifestyle modification

Introduction In recent decades, there has been a shift in the disease burden from infectious to noncommunicable diseases (NCDs) as result of various interrelated factors including the following: an aging population, the introduction of new technologies, advancements in medicine and public health, and changes in diets and lifestyles [1, 2]. NCDs are on the rise and are now documented as the leading cause of mortality globally [3]. In the USA, seven in ten deaths were attributed to NCDs [4] accounting for an estimated economic burden as high as $1.1 trillion after assessing for lost productivity and treatment [5]. According to the Centers for Disease Control and Prevention (CDC), the treatment of NCDs accounts for approximately 75 % of national health care expenditures [5]. Health systems are not equipped to deal with this growing burden of chronic illness that requires years of ongoing care [6]. The alarming growth of NCDs has catalyzed discussions across all levels of society on solutions and best practices for containing or mitigating this epidemic [7–9]. Prevention strategies have been successfully used to alleviate disease burden and improve general well-being [10, 11]. Efforts in cancer prevention, for example, have decreased overall morbidity and long-term health care costs through screening and early treatment [12, 13]. However, NCDs resulting from unhealthy lifestyles, such as poor diet and

Int.J. Behav. Med. Fig 1 Flow diagram of the initial study search in the PubMed electronic database

2,171 Articles in initial PubMed search

181 Articles after applying “MESH” terms in PubMed

41 Articles after “group review”

17 Articles met all search criteria

1 Randomized Control Trial

physical inactivity, pose a new and growing challenge to conventional prevention strategies. Dietary habits and physical activity (PA) are two key modifiable risk factors that can have a significant impact on reducing NCDs [14–16]. The promotion of PA and improved dietary choices are highlighted as two of the “best buy” strategies in the World Health Organization’s 2008–2013 Action Plan for the Global Strategy for the Prevention and Control of NCDs [17]. These modifiable risk factors are highly associated with obesity, which in turn is associated with diabetes, cardiovascular disease (CVD), and other leading causes of mortality and morbidity [18]. According to Prevention for a Healthier America, an investment of $10 per person in proven community-based programs can yield a $16 billion savings annually [19]. Thus, prevention strategies aimed at reducing rates of NCDs provide an important alternative to rising health care costs while improving quality of life. There have been numerous approaches utilized in various settings that target the prevention of NCDs through weight loss, PA promotion, healthy eating, or a combination of these components. The Diabetes Prevention Program (DPP) serves as a landmark study linking weight loss, dietary modifications, and increased PA to a reduction in the incidence of diabetes [20]. Other large clinical trials, such as the Trial of Nonpharmacologic Interventions in the Elderly (TONE; [21]), the Dietary Approaches to Stop Hypertension (DASH; [22]), the PREMIER trial [23], and the Look Ahead trial [24] have provided encouraging evidence of similar approaches to primary disease prevention or treatment. Together, these trials have

1,990 Didn’t have any of the “MESH” terms

140 Articles didn’t meet search criteria

24 Articles didn’t meet search criteria

5 QuasiExperimental Studies

11 Single Arm Trials

shown that, in a controlled environment, significant positive health outcomes can be attained through lifestyle modification. However, many of these studies were conducted in time and resource intensive settings among highly selective populations with limited generalizability, rendering the results less conducive to real world environments [25, 26]. The challenge then remains translating the results from these clinical trials to large-scale, population health practices. Several individuals and organizations have suggested that the community setting can be a prime location for lifestyle modification programs (LMPs) and the translation of evidence-based practices into real world settings across a wide and diverse population of individuals [27, 28]. Analysis of models utilizing behavior change strategies for the reduction of NCDs suggests that these LMPs can be implemented in a cost-effective manner in community-based settings [29, 30]. Furthermore, the use of behavioral strategies provides individuals with the skills and techniques to sustain changes in their diet and activity levels over an extended period of time. Nonetheless, there is still much work left to do in the implementation of these LMPs within the context of existing community resources, opportunities, and constraints. Therefore, the objectives of this review are to: (1) identify studies that have attempted to implement evidence-based LMPs, (2) examine common components and strategies used by these LMPs, (3) identify barriers faced during the implementation of these LMPs, and (4) provide suggestions for the implementation of future community-based LMPs.

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Methods Data Sources A comprehensive search of the PubMed database was conducted between June and December 2012. The initial search of published literature included combinations of several keywords (“lifestyle modification,” “behavior,” “community,” “community-based,” “interventions,” “programs,” “physical activity,” and “nutrition”) and medical risk factors and comorbidities (“obesity,” “diabetes mellitus,” “cardiovascular disease,” “blood pressure,” “metabolic syndrome”). In addition, other sources of candidate studies, including reference lists of relevant articles and reviews, were referenced to identify any studies that were missed. An additional search of literature published since our original review was conducted in July 2014 with the previously employed search strategy in the Ovid MEDLINE and Scopus online databases to ensure comprehensive retrieval of eligible studies. Study Selection The following criteria were used to determine inclusion in the study: (i) publications were written in English, (ii) studies involved participants over the age of 18, (iii) participants were engaged in group-based LMPs offered in community settings, (iv) interventions that utilized behavioral counseling as a primary component of the LMP, and (v) LMPs that focused on changing both PA and dietary behaviors. Exclusion criteria included the following: (i) reviews or meta-analyses; (ii) studies utilizing technology (i.e., cell phones, internet-based programs) to deliver the intervention; and (iii) studies deemed not to have taken place in a community setting, such as worksite wellness programs or those that were performed in a clinical setting or primary care settings. Studies that were hosted or utilized space at health care settings or worksites, but were not a direct part of integrated care or a program offered through these sites, were included. Since the focus of this review was to identify programs that promoted self-managed behavioral and lifestyle changes, studies that included structured or prescribed exercise training and/or diet programs were not included. Finally, given the growing and diverse field of technological innovations being tested in program implementation, we chose to exclude studies that utilized technology as the primary delivery tool, but did not exclude studies that used technology to support the in-person, group-based LMP. We elected not to apply traditional standards for assessing study quality, many of which are used in determining research validity and the existence of causal relations [31, 32], to the studies selected in this review due to the multiple complexities involved in implementing community-based LMPs, many of which are not covered under previously established criteria [33].

An initial review of the PubMed database identified 2,171 studies for further review (Fig. 1). Of these 1,943 studies, 181 were selected based on relevant key MESH terms. The relevance of these studies was further assessed by each team member who independently examined the title and abstracts of these articles to determine which ones appeared to meet the pre-determined inclusion criteria. Following consensus of the research team, 41 articles were selected for full review by each team member, from which a total of 17 were selected for inclusion in the review. A review of the references used in these articles led to the inclusion of four additional studies. Finally, the most recent database search using the Ovid MEDLINE and Scopus online databases led to the identification of an additional five studies. In reviewing the articles referenced within these five studies, one final study was identified for inclusion. Data Extraction The following study characteristics were extracted from the original studies including: participant demographic information such as age and gender, individuals who delivered the intervention and the level of training that they received, location of the community setting, participant recruitment strategies, the length (number of weeks) and intensity (hours per week) of the LMP, and post-program follow-up support. Next, data on behavior change models and strategies and the following study outcomes were extracted by members of the research team: participant adherence and retention rates, assessment of PA and dietary habits and the changes seen in these variables postintervention, weight loss, clinical outcomes including lipid, blood sugar, triglyceride, and hemoglobin A1c concentrations, as well as barriers to the implementation of the LMP. All investigators assisted in the data extraction process and collection of reports. Disagreements were resolved by consensus of the group.

Results The review process resulted in 27 articles that were deemed acceptable for inclusion. Table 1 presents the basic characteristics of the studies included in this review. Studies were categorized into one of three categories based on their research design: (a) single-arm trials with no comparison group, (b) quasi-experimental trials that utilized a comparison group, and (c) randomized controlled trials. Data extracted from these trials included descriptive information on the study setting, recruitment techniques, personnel and training, program characteristics such as the intensity of the intervention (frequency and duration of intervention sessions), descriptive characteristics of the study participants, and study outcomes on changes

Int.J. Behav. Med. Table 1 Key features of cognitive behavioral, lifestyle modification programs included in review. min minute, hr hours, wk week, mo(s) month(s), yo years old, yrs years, kcal kilocalorie, lb(s) pound(s), BMI body mass index, BP blood pressure, CBPR community-based participatory research, CHIP Coronary Health Improvement Project, CVD cardiovascular disease, DE-PLAN Diabetes in Europe-Prevention using

Lifestyle, Physical Activity and Nutritional Intervention, DPP Diabetes Prevention Program, GLB Group Lifestyle Balance, HbA1c hemoglobin A1c, MetS metabolic syndrome, NHOPI Native Hawaiian and other Pacific Islanders, NIH National Institutes of Health, PA physical activity, PREDIAS Prevention of Diabetes Self-Management Program, T2D type 2 diabetes

in body weight, clinical outcomes (blood pressure, lipid concentrations, fasting blood glucose), psychosocial variables, PA levels, and dietary habits.

control subjects were recruited from secondary sites or communities that were not selected for the intervention [48–50, 52] or through participant self-selection to the control arm [51]. Finally, of the randomized controlled trials, three were considered feasibility or pilot studies [53–55], while the other five focused on translation of evidence-based LMPs [56–60]. These studies allocated participants to comparison groups that had delayed or wait-list controls [53, 56], provided information via written materials [58], basic general education [54, 60], or used a form of usual care [55, 57, 59]. Five of the studies included in this review employed community-based participatory (CBPR) methodologies in tailoring their programs to the local communities [34, 38, 40, 42, 53]. Collectively, six studies targeted individuals with at least one CVD risk factor or individuals with an elevated risk of CVD [37, 44, 45, 49, 56], five targeted overweight/obese individuals [38–40, 42, 52], as well as cancer survivors [55] and individuals with the metabolic syndrome [43]. Two

Description of the Selected Studies Of the 27 studies selected for this review, 14 were classified as single-arm trials that did not use a comparison group. Seven of these single-arm trials were considered feasibility or pilot studies [34–40], three were classified as translation studies [41–43], and the remaining four were considered implementation studies across a larger (or multiple) communities or cities [44–47]. Five studies were categorized as quasiexperimental studies: two pilot studies [48, 49], one translation study [50], one implementation trial [51], and one comparative effectiveness trial in which one arm involved the translation of an evidence-based LMP in a community setting [51]. Of these studies that used a quasi-randomized design,

Int.J. Behav. Med. Table 1 (continued)

studies did not specify the disease or risk factor(s) that they targeted [47, 60]. The remaining 12 studies were targeted to prediabetic individuals or those who were considered at high risk for diabetes. Four studies in this review were conducted in Europe [46, 55, 58, 60], one was conducted in Japan [51], and the remaining studies took place in the USA. Characteristics of the Community Setting, Delivery Personnel, and Staff Training The majority of the studies in this review were conducted in local community centers and churches. Other community locations that were used included meetings in home settings, community worksites, and senior centers. Eight studies did not specify where in the community setting their study was conducted [43, 45, 51–53, 55, 56, 58]. There was a great deal of variability in the personnel who delivered the LMPs. Commonly used personnel included registered dietitians [39, 43, 46, 57], diabetes educators [41, 58], research team members [49, 60], study nurses or nurse educators [35, 39], volunteer medical staff [36, 51], psychologists [58], and exercise

physiologists [43]. In ten cases, local community resources, such as community [42, 44, 48, 50, 54] or church [38] staff, as well as volunteers from the community [34, 47, 52, 59], were utilized. Commonly used staff training methods included either the 2-day intensive Coronary Health Improvement Project (CHIP) training protocol [37, 45, 47], a 2-day intensive group lifestyle balance training program for diabetes prevention [39, 41, 43, 52], or the 2-day Fit Body and Soul training [38]. One study conducted their staff training over a 2.5-day time period [48], and three others conducted “extensive training” with their community health workers and volunteers [34, 42, 59]. Twelve studies did not report training procedures used with their intervention staff [35, 36, 40, 44, 46, 49–51, 54, 55, 58, 60]. Description of Program Participants Eighteen studies enrolled participants with a mean, or median, age between 50 and 65 years, five enrolled participants between the ages of 40–50 years [38–40, 53, 60], while two other studies enrolled participants with a mean age less than

Int.J. Behav. Med. Table 1 (continued)

40 years [42] or greater than 65 years of age [49]. Two studies did not report the mean age of their participants [35, 50]. Ten studies had a female enrollment between 60 and 80 %, nine others had a female enrollment greater than 80 %, and two studies recruited exclusively females [55, 60]. Only three studies had a male enrollment rate greater than 40 % [49, 57, 58]. Participants were recruited through a variety of methods with 11 studies reporting the use of more than one recruitment strategy. The most commonly used strategies included the following: local TV and newspaper ads [40, 41, 43, 44, 52, 59], newsletters and flyers [34, 40, 41, 46, 49, 52, 54], advertisements in physician offices and physician referrals [41, 46, 47, 54, 57, 59], promotion to church groups [34–36, 38, 43, 44, 54], health fairs and information sessions [39, 42, 49, 57, 60], direct postal mailings [41, 48, 51, 55, 57], and worksite recruitment [44, 46, 57]. Nineteen of the studies included in this review provided comprehensive details of their recruitment efforts, including the total eligible population, numbers of individuals prescreened and screened for study eligibility, the number eligible, and those who agreed to participate in the study.

Program Characteristics, Adherence, and Retention The majority of studies included in this review conducted their program sessions either weekly [34–36, 38, 39, 41, 44, 52–55, 57] or one to three times per month [40, 42, 43, 48, 51, 58, 59]. Four other studies, those using the CHIP program [37, 45, 47, 56], conducted sessions more frequently than one time per week, while two studies conducted their intervention sessions less than once per month [46, 60]. One other study allowed the community health advisors to tailor the number and frequency of sessions to their participants’ needs [50]. Fourteen of the studies in this review consisted of program interventions lasting 60–90 min, six were greater than 90 min [37, 45, 47, 51, 54, 56], and six did not report the duration of their program sessions [35, 40, 46, 50, 55, 57, 60]. Seven programs offered additional 3–6 monthly booster sessions after the conclusion of the main intervention program [39, 41, 42, 44, 48, 49, 54], and two studies conducted bimonthly follow-up sessions for the subsequent 9 [51] and 18 months [57]. Six other studies did not conduct booster sessions, but did assess the long-term impact of the program three or more months after the end of

Int.J. Behav. Med. Table 1 (continued)

the intervention [35, 36, 43, 53, 55, 59]. The remaining 12 studies did not conduct follow-up sessions or assessments [34, 37, 38, 40, 45–47, 50, 52, 56, 58, 60]. A wide range of participant retention was reported across the studies included in this review. Two studies reported dropout rates between 0 and 5 % [36, 45], six studies reported a rate between 6 and 10 % [35, 37, 56–59], eight reported rates of 10 and 20 % [38, 39, 41, 44, 49, 52, 53, 55, 60], three reported rates between 20 and 30 % [43, 48, 51], and five reported dropout rates greater than 30 % [34, 42, 46, 50, 54]. Two studies did not report participant retention levels [40, 47]. High levels of program adherence, defined as attendance at 70 % or more of the primary intervention sessions, were reported in nine studies [35, 37, 39, 41, 44, 49, 52, 56, 57]. Twelve studies did not report participant attendance levels [38, 40, 43, 45, 47, 50, 51, 53–55, 58, 60]. Behavior Change Theories and Constructs Nine of the studies in this review reported one or more established behavior change theories or models, including

the Health Belief Model, Self-Management Theory, Social Action Theory, and Social Learning Theory. Twenty-two of the studies mentioned one or more behavioral constructs, many of which were not discussed in the context of an associated theory. Self-monitoring (of food intake, PA, or body weight) was the most commonly discussed construct followed by goal setting and problem-solving. Additionally, perceived barriers, social support, perceived benefits, and stimulus control were frequently indicated, largely through referencing the rationale and key features of the DPP Intensive Lifestyle Intervention [61]. Six additional constructs that were not mentioned, but were alluded to in the studies, included the following: behavioral capacity, consciousness raising, counterconditioning, decisional balance, emotional coping responses, and selfliberation. Five of the reviewed studies did not mention or directly reference any behavior change theories or constructs [37, 41, 45–47]. Behavioral theories, models, and constructs were included whether they were discussed directly within the current article or were referred in a previously published study or article. A breakdown of

Int.J. Behav. Med. Table 1 (continued)

theoretical models and behavioral constructs used in the selected studies can be found in Table 2.

provided information on the cost of implementing their program [35, 41].

Barriers to Implementation of the Lifestyle Modification Programs

Physical Activity and Dietary Outcomes

Four studies directly assessed (i.e., through surveys, individual interviews, or focus groups at the conclusion of the program) and reported barriers that affected the implementation of their LMP [34, 53, 55, 59]. Barriers that were identified in these studies included the following: high rates of illiteracy, time requirements and the burden of the program on the participants, scheduling issues and competing interests in the lives of the participants, participant satisfaction with the LMP, difficulties conducting the study assessments, and maintaining fidelity to the LMP curriculum by the group leaders, especially the community health workers and volunteers. Several other investigators discussed the barriers, as well as the strengths, of their respective studies, but did so primarily within the context of explaining their study outcomes. Two additional studies

Sixteen of the 27 studies included in this review assessed and reported changes in PA and/or physical fitness. Among these studies, four [39, 41, 44, 58] used a form of self-monitoring (i.e., PA logs), 10 utilized a variety of self-report questionnaires [34, 39, 40, 42, 45, 49, 51, 53, 59], two included the use of daily step counts [51, 56], one used a PA recall log [50], and another performed physical fitness testing (6-min walk test; [40]). The different self-report questionnaires included the following: the Global PA Questionnaire [53], the International PA Questionnaire Short Version (IPAQ-Short; [42]), the Rapid Eating and Activity Assessment for Patients (REAP; [49]), the Godin Leisure Time Questionnaire [55], a modified DPP PA questionnaire [39], an exercise frequency questionnaire [45], three unspecified selfadministered questionnaire [34, 40, 51], and information

Int.J. Behav. Med. Table 1 (continued)

collected as a part of a 24-hr dietary recall [59]. Overall, the majority of these studies reported significant increases in PA, or physical fitness, with participants attaining a range of 52.5–70 % of PA goals. Four studies reported no changes in the following: (a) leisure or total daily PA [34, 53, 59] or (b) female participants meeting PA study goals [51]. Of the five studies that employed a control group, two reported a significant interaction between the intervention and control conditions [55, 58]. Fifteen of the 27 studies included in this review assessed and reported dietary modifications. Of the studies that assessed dietary changes, ten used self-report questionnaires [38, 40, 45, 49–51, 53, 54, 56, 58], three used self-monitoring food logs [41, 44, 55], and two others used the 24-hr dietary recall [39, 59]. The different self-report questionnaires included the following: the Three-Factor Eating Questionnaire [58], the full length Block 98 [56], the REAP [49], the Diet Habits Questionnaire [38], a Food Frequency Questionnaire [42], two used self-monitoring food logs [41, 44], an Eating Habit Questionnaire [40], two used self-monitoring food logs [41, 44], a Lifestyle Nutrition Test [45], and unspecified selfadministered questionnaires [51, 54]. All but one study [51] found improvements in the dietary outcomes that were assessed. However, of the nine studies that employed a control group and assessed dietary habits [49–51, 53–56, 58, 59], only one reported significant decreases in fat intake [59] while

another reported an increase in green salads and a decrease in sugar-sweetened beverages [53] between study groups. Weight Loss Outcomes Only one study did not assess changes in body weight or composition [49]. Four studies reported a mean weight loss of 0–2.49 kg [40, 42, 46, 53], seven reported a mean weight loss of 2.50–4.99 kg [35, 36, 39, 47, 54, 55, 58], and five others reported a mean weight loss of 5.0–7.5 kg [41, 44, 48, 52, 57]. There was a similar distribution of changes in BMI. The remaining studies reported individuals achieving study goals [43], changes in body mass index (BMI) only [56, 60], number of participants that met different levels of percentages of weight change [38, 59], or reported results by gender only [37, 45, 51]. Only two interventions did not result in significant changes in body weight or BMI [34, 50]. Nine studies assessed waist circumference (WC; [39–43, 46, 47, 54, 58]). Seven reported significant improvements [39, 41, 42, 54, 58], particularly in those with an unhealthy WC [43] or in those who achieved a “healthy” WC [47], while two reported nonsignificant changes over the course of the intervention [40, 46]. Finally, one study assessed, but did not observe, significant changes in body fat percentage in comparison to their control group [51]. Of the 12

Int.J. Behav. Med. Table 2 Use of theoretical models and behavioral constructs in selected studies # Directly discussed (frequency)

Relevant articles

# Indirectly referenceda

Relevant articles

1

(57)

Theoretical models Continuous Care ProblemSolving Model Health Belief Model Maxwell’s 5 M training model Patient-Centered Counseling Model Self-Efficacy Theory Self-Management Theory Social Action Theory Social Cognitive Theory Social Learning Theory Behavioral Constructs Cognitive Restructuring Empowerment Goal Setting Locus of Control Outcome Expectations Perceived Barriers Perceived Benefits Perceived Severity Perceived Susceptibility Problem-Solving Relapse Prevention Self-Efficacy Self-Esteem Self-Monitoring Social Support Stimulus Control

0 1

(39)

0

.

1 2

(34) (54,59)

0 0

.

1 1 0 3 0

(53) (58)

0 0 1 1 1

. . (49) (57) (39)

1 1 10

(57) (53) (34,36,38,41-44,50,52, 55)

0 1 12 13 1 1 11 14 1 1 8 11 14

. (57) (35,36,38,39,42,44,48,49,50,53,54,57) (35,36,38,40,42-44,48-50,52,54,57) (39) (39) (35,36,38,42-44,50, 52–55) (35,36,38,39,40,42-44, 48–50,52,54,57) (57) (53) (34,36,38,44,50,53,54,57) (36,39,40,42-44,48,52, 53,57,59) (35,36,38,39,40,42-44, 48–50,52,54,57)

0 1 9 1 0 2 1 0 0 7 1 4 0 11 3 0

(54,55,59)

(60) (35,39,40,48,49,51,55,57,59) (58) . (43,52) (39)

(39,40,48,49,54,57,59) (55) (53–55,59) . (35,39,40-43,48,49,52, 55,59) (35,50,54)

a

Theories and/or constructs that are referenced in previously published work but not directly discussed in the current article. Current articles that directly discussed and referenced other work were only counted in the directly discussed category

studies that used control groups and assessed changes in body weight or BMI, seven reported significant betweengroup interactions [48, 51–53, 57–59].

mentioned in six other studies, but the results were not reported [39, 42, 45, 52, 56, 57].

Clinical Outcomes Psychosocial Outcomes Only three studies in this review assessed and reported psychosocial outcomes [50, 58, 59]. The psychosocial variables that were assessed and reported included anxiety (The StateTrait Anxiety Inventory; [58]), depression (Center for Epidemiologic Studies Depression scale; [58, 59]), social support [50], and general well-being (WHO-5 Well-Being Index; [58]). In only one case was there a significant decrease in anxiety compared to the control group [58]. Different psychosocial outcomes (stress levels, quality of life, physical and mental functioning, barriers to PA, and healthy eating) were

Of the 27 studies selected for this review, only six did not measure or report any clinical outcomes [38, 39, 42, 44, 50, 55]. Seventeen studies assessed changes in fasting blood glucose (FBG) concentrations. One other study completed a comprehensive assessment of changes in FBG, hemoglobin A1c, and oral glucose tolerance [60]. Of the studies that assessed changes in FBG, 11 showed significant improvements over the course of the intervention [35, 36, 37, 41, 45, 46, 47, 51, 57, 58, 60]. Of the eight studies that employed a control condition, only three reported significant betweengroup differences in FBG [57, 58, 60] with a fourth reporting

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significant between-group changes in only the female participants [51]. Of the five studies that examined hemoglobin A1c levels [48, 51, 53, 58–60], two reported significant reductions in their participants [51, 59]. Fourteen studies did not assess or report changes in cholesterol concentrations [34–36, 38–40, 42, 44, 49, 50, 54, 55, 57, 59]. Of those that did, a total of nine studies reported varying levels of improvements in cholesterol levels while four others reported no significant changes as a result of the intervention [43, 51, 53, 60]. Four studies reported significant reductions in LDL concentrations [37, 41, 45, 46] while three studies reported no significant improvements in LDL concentrations [46, 51, 53]. Two studies reported significant changes in high-density lipoprotein (HDL) concentrations [37, 58] while six other studies reported no improvements in HDL concentrations [41, 43, 46, 48, 51, 60] and three others reported significant decreases [47, 52, 56]. Of the nine studies that examined changes in triglyceride concentrations, six reported significant decreases [37, 41, 45, 47, 56, 58], while three others reported no significant changes [46, 51, 60]. Of the seven studies [28, 51–53, 56, 58, 60] that used a control group and assessed participant lipid profiles or triglyceride concentrations, only one noted significant between-group changes in total cholesterol concentrations [28]. Of the 27 studies included in this review, seven did not assess or report changes in blood pressure (BP; [38, 39, 42, 44, 50, 54, 55]). Nine studies reported varying levels of improvements in systolic BP [35–37, 40, 41, 45, 46, 49, 58] and ten studies reported varying levels of improvements in diastolic BP [35–37, 40, 41, 45, 49, 51, 58, 60]. Two studies did not report absolute changes, but did mention a significant decrease in the proportion of individuals who were hypertensive [43, 52], while two others reported decreases across ranges of BP [47, 56]. Only three studies did not report significant improvements in either systolic or diastolic BP [34, 48, 53]. Of the eight studies that employed a comparison group, only one reported a significant improvement in systolic BP in men compared to the control condition [51].

characteristics of these studies and provide recommendations for future efforts. Study Design, Characteristics, and Participants The types of studies in this review varied both in study design (i.e., single arm, quasi-experimental, randomized control trial) and the purpose of the study (i.e., serving as a feasibility or pilot trial). There was a great deal of heterogeneity of the studies included in this review as several were conducted as pilot studies examining the feasibility of conducting larger implementation trials [35, 36, 39, 43, 48], others examined the translation of evidence-based programs, such as the DPP, to community settings [41, 51, 52], while others were conducted as implementation programs across several communities [37, 44, 45, 47]. This heterogeneity leads to varying implementation procedures and methods of program evaluation. Within the studies selected, multiple strategies were employed for participant recruitment, often varying by the location of the program (i.e., programs adapted for church versus community settings). Given the difficulty of participant recruitment often experienced by most investigators [65], we found it interesting that only ten studies used multiple recruitment strategies. Furthermore, most of the studies enrolled a high proportion of female participants, presenting an opportunity for future studies to concentrate on better engaging male participants. Greater discussion of recruitment strategies, as well as lessons learned during this process, may help future studies employ more effective strategies in engaging community members. Similarly, few studies in this review discussed steps taken to adapt their study to the local community. Studies that adapted their intervention for the local community setting typically employed one of two techniques; the intervention was modified by the research team to fit the local context in which it was delivered [36, 49] or the research team hosted focus groups with community members and/or worked with the local community leaders who assisted in its cultural adaptation [34, 39, 40, 42, 44, 53, 59]. Given that the end goal of implementation research is to ensure that evidence-based LMPs are acceptable to the local community, we feel it is imperative that community members and leaders are involved in the adaptation process.

Discussion Participant Retention and Adherence Substantial efforts and resources have been dedicated toward conducting efficacy trials that investigate the health benefits of LMPs [62, 63]. However, efforts to translate and implement these evidence-based programs into real-world settings have lagged far behind [64]. In this review, we identified 27 studies that implemented LMPs in community settings focusing on changing both the PA and dietary behaviors of the participants. In the following, we discuss key methodological

One encouraging finding of this review was that most of studies reported high levels of participant retention and adherence to the interventions. We identified three main formats for the delivery of the program materials: studies that followed a more traditional weekly intervention schedule (similar to the DPP), those that decreased the number and frequency of intervention sessions (biweekly or less), and those that

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delivered their curriculum in an intense format over a short period of time, usually over several weeks. Retention rates varied equally among the different implementation formats (i.e., daily, weekly, or bimonthly sessions) from those that had high levels (>90 %) to those that had dropout rates as high as one third of all participants. However, few studies reported participant barriers that contributed to participant loss to follow-up and low retention levels, information that could be of great usefulness in the translation of future LMPs. Similarly, participant attendance rates appeared to vary among the different studies, independent of the delivery and intensity of the program. However, few studies directly assessed levels of participant adherence and the resulting impact on study outcomes. This information may prove to be critical in a future pooled analysis for determining the optimal number (or threshold) of sessions to achieve meaningful results. Given the challenges of translating evidence-based LMPs in a realworld setting, this information is crucial, and efforts should be made to assess the factors influencing participant adherence and retention to better inform future studies. This review focused primarily on the implementation of the LMP and changes seen at the end of the intervention phase. However, tracking of long-term behaviors and outcomes is an area that should also receive greater attention. While many studies performed assessments several months after the end of the intervention to observe the long-term impact of their program, less than half of these studies provided ongoing follow-up sessions for their participants. To ensure long-term maintenance and determine the sustainability of these LMPs, research teams should consider frameworks that provide program “graduates” with continuing support and reassess maintenance of study outcomes on a long-term basis. Utilization of Behavior Change Strategies The use and reporting of behavioral theories employed in the implementation of LMPs are of critical importance. While a majority of the studies in this review did refer to using behavior change methodologies, few provided details on how these theories and/or constructs were formally integrated into their program or clearly outlined the role of these strategies and how they matched with program activities. Baker et al. [66], in a review of DPPs, found that of the 95 studies reviewed, few directly specified a behavioral theory that underpinned their approach. Given that the goal of the programs in this review was to elicit change through behavioral processes, and not just the prescription of exercise or diet regimens, these studies should be grounded in a theoretical frameworks customized for each community setting. Furthermore, few of the studies in this review examined changes in behavioral attitudes or mechanisms responsible for the observed behavior changes. It may be particularly useful

for future studies to explicitly examine changes in specific social cognitive processes of the participants (i.e., increases in self-efficacy). Identifying these meditators will also better inform future studies as to which behavioral strategies may be the best avenue for allocating their time and resources. Employing existing behavior change taxonomy [67] to systematically quantify and report the behavior change techniques utilized in an LMP will also allow for greater replication of successful strategies and comparison across studies. Study Outcomes Given that studies in this review were selected because of their emphasis on modifying PA levels and dietary habits, it is surprising that few directly measured changes in these behaviors, instead focusing primarily on weight loss and clinical outcomes. Studies that did assess changes in PA and dietary habits used a wide variety of assessments, several of which have not been validated or were not fully described. Although conducting objective measures of PA levels or more detailed measures of dietary intake may not be feasible in large implementation trials, multiple dietary [68, 69] and PA [70, 71] assessment measures have been validated for use in population studies, as well as various measures to assess cardiorespiratory fitness adapted for use in community settings [72–74]. The utilization of basic and commonly used selfreport questionnaires is necessary in providing useful information as to the direct impact of these programs, as well as mediators that account for observed changes in body weight, clinical outcomes, and disease status. The assessment of changes in BMI and/or body weight was common across nearly all of the studies in this review. While changes in BMI and body weight have been traditionally measured as an indication of health risk, we suggest that future investigations consider the role of other key mediators, such as cardiorespiratory fitness [75]. Additionally, we recommend that all future studies consider assessing WC given its ease of measurement, low cost, and its growing importance in determining future health risk [76]. Finally, the majority studies included in this review collected a standardized set of clinical outcomes—most notably FBG, BP, and cholesterol concentrations. Standardization in the collection and evaluation of FBG, BP, and cholesterol concentrations allows for a greater level of comparison of study results and pooling of results. However, despite the relative ease and inexpensiveness of collecting these variables, it is often difficult to administer them to a large number of participants (i.e., need for specialized personnel, increased cost, and time commitments) and may limit the desired reach and impact of the LMP. While these variables certainly offer greater detail into the impact of the intervention, future translation studies may be better served by collecting these

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outcomes, whenever possible, to supplement the changes in PA levels, dietary habits, and changes in body weight and WC. Study Outcomes and Evaluation The purpose of this review was not to provide a quantitative analysis of study outcomes. However, it is important to note that 65, 45, 69, and 92 % of studies included in this review reported significant improvements in FBG, BP, total cholesterol concentrations, and reductions in body weight, respectively, providing evidence that translation of LMPs in a community setting can be effective in improving participant health profiles. However, these studies lacked a common methodology for assessing data collected and reporting it in a consistent manner. For example, several studies did not report baseline or post-intervention values, nor the magnitude of change across the duration of the study. Instead, percentages of individuals who demonstrated levels of change or those who met certain guidelines or study goals were reported. We feel that it is important that future studies follow a standard format that includes: (a) reporting baseline and post-intervention values of all participants, (b) presenting absolute levels of change during the intervention, and finally (c) including additional subgroup (i.e., gender) analyses. Similarly, we feel that it is important to establish consistency for determining the inclusion of participants in the final analyses. Several studies analyzed the results of participants who completed the program or attended a majority of the sessions—thereby skewing their results by not including noncompleters or nonadherent individuals, both key factors with implementation studies. Other studies included all of the individuals who enrolled in the program, regardless of their participation level or completion status, providing a potentially very different series of results. One potential strategy is to conduct primary analyses of all participants who enroll in the LMP (similar to intent-to-treat strategies commonly used in randomized control trials), using secondary analyses to present differences in various subgroups, such as program completers. Last, we found that there was a wide range of control conditions employed in the studies included in our review. In many cases, the use of a comparison group may be neither feasible nor practical due to logistical reasons. Fifty-two percent of our studies, many of them in the early stages of intervention development, did not employ comparison groups. When feasible, the use of comparison groups can provide several benefits, such as accounting for natural deterioration of health outcomes due to aging or seasonal variations over a prolonged study period. For example, in the study conducted by Fernandez et al. [49], participants in the treatment arm did not increase their PA levels. However, during the same time period, those in the comparison group

significantly reduced their PA, which was attributed to the aging process. For those studies that do include a comparison group, it is important that appropriate statistic methodology is used to examine the interaction effects between intervention and comparison groups. This was not the case for several studies that reported results for within-group differences, but not the interaction effect with their control participants. Barriers to Program Implementation in Community Settings One area of concern identified in this review is a lack of a formal assessment and reporting of barriers in translating the LMPs to community settings. While several studies conducted focus groups, worked with community advisory boards, and collaborated with local coalitions in culturally tailoring the intervention prior to the study, few performed systematic evaluations after the actual implementation of the program. These post-intervention evaluations could include the assessment and reporting of the following: challenges to participant recruitment, barriers that contribute to low study adherence or retention levels, difficulties working with the local communities, fidelity of the intervention using local volunteers as leaders, and cultural barriers that may have limited the effectiveness of the program. Several studies included in this review discussed perceived facilitators for their interventions, factors that included establishing strong partnerships with local organizations and leaders, adapting the program to the local community and culture, use of local study personnel (i.e., community health workers). However, these facilitators were not identified through a formal process and were, more often than not, discussed in relation to the significant findings (or lack of) reported in their study. Based on the findings of this review, we recommend that future trials include in their study planning a formal post-intervention assessments of the program implementation with the participants, team leaders, and community stakeholders through surveys, individual interviews, and focus group sessions. Given the challenges of translating evidence-based LMPs in a real-world setting, this information is crucial and greater efforts should be made to collect it to better inform future studies. The present study has a number of limitations that should be considered. First, as with most review articles, publication bias remains a possibility. It is possible that other communitybased LMPs that did not experience significant improvements that were not published, may provide important information on the lessons learned in the translation of their program to community settings. Additionally, it is possible that articles that may have been eligible for this review were not identified and retrieved during our literature search. Finally, 82 % of the studies included in this review were conducted in the USA suggesting either that few community-based LMPs are being implemented around the world or that our literature review did not adequately identify studies in other countries or that these

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studies were not published in English. However, our intention was not to provide an exhaustive search of all existing LMPs, but rather to discuss key concepts related to common features seen among these programs in their translation to community settings. Future Direction Based on this review of LMPs conducted in a community setting, we recommend several strategies that should be employed in the future. First, more rigorous efforts should be made in the collection and reporting of study-related information (i.e.,recruitment strategies, participant adherence, outcomes). Second, translational studies should have a greater focus on assessing not only the success of the program, but also the barriers to implementation and participation, both at the individual and community levels. Third, we feel that future studies should make greater efforts to utilize existing community resources, such as local community centers and churches (as site locations), established local communication networks (for recruitment efforts), community leaders and stakeholders (for study promotion and community acceptance), and local personnel that may be more culturally competent in implementing the program. Additionally, only a small number of studies in this review discussed sharing their results with the local community. Given the recommendation to increase the involvement of local stakeholders and community leaders at the onset of the study, investigators should, at a minimum, strive to create a bidirectional flow of information that provides communities with the results of the studies and assistance in the long-term sustainability of the program. Fourth, although not discussed in this review, the use of technology, such as text messaging [77], the Internet [78, 79], and mobile phone applications [80], may play an important role in future translation efforts and that evidence-based strategies to incorporate these tools should be considered. Fifth, we recommend that future investigators include more comprehensive evaluation frameworks, such as the Reach Effectiveness Adoption Implementation Maintenance framework (RE-AIM; [81]), that provides for a more comprehensive assessment of the sustainable adoption and overall impact of the implementation of their community-based program. Finally, given page and word limitations of manuscripts, it may be difficult for investigators to include all relevant information on their study design and methodology in their main outcome paper. Increasing the publication of methodoligical and lesson learned papers may be particularly useful in describing key intervention components, participant recruitment, staff selection and training, study setting, and adaptation of the intervention. There needs to be a greater emphasis on making public work describing the translation and implementation of interventions, as well as lessons learned, to better inform future program iterations.

Conclusions Translation research is a multifactorial process that engages individuals and communities on several different levels; therefore, the evaluation schemes that are used should assess many, if not all, of these processes [27]. Overall, our review revealed that LMPs addressing PA and diet habits can be successfully implemented in a community setting. Many programs included in this review were successful in their efforts, despite limited financial resources, by using existing community resources and personnel. Even though many of the studies included in this review were designed as translation or implementation trials, and not as highly controlled experimental trials, a high-level scientific rigor should be maintained in their design, implementation, evaluation, and reporting of results. It is encouraging that large-scale implementation trials focusing on LMPs are currently in progress in locations such as the USA (CDC National DPP; [82]) and in Australia (Sydney Prevention Program; [83]). However, more effort and attention need to be dedicated to continuing the expansion of implementing evidence-based LMPs as a direct form of primary prevention in our communities.

Conflict of Interest Mark Stoutenberg, Katie Stanzilis, and Ashley Falcon declare that they have no conflict of interest. Ethical Standard All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.

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