- Systematic review
- Open Access
What strategies are used to build practitioners’ capacity to implement community-based interventions and are they effective?: a systematic review
Implementation Science volume 10, Article number: 80 (2015)
Numerous agencies are providing training, technical assistance, and other support to build community-based practitioners’ capacity to adopt and implement evidence-based prevention interventions. Yet, little is known about how best to design capacity-building interventions to optimize their effectiveness. Wandersman et al. (Am J Community Psychol.50:445–59, 2102) proposed the Evidence-Based System of Innovation Support (EBSIS) as a framework to guide research and thereby strengthen the evidence base for building practitioners’ capacity. The purpose of this review was to contribute to further development of the EBSIS by systematically reviewing empirical studies of capacity-building interventions to identify (1) the range of strategies used, (2) variations in the way they were structured, and (3) evidence for their effectiveness at increasing practitioners’ capacity to use evidence-based prevention interventions.
PubMed, EMBASE, and CINAHL were searched for English-language articles reporting findings of empirical studies of capacity-building interventions that were published between January 2000 and January 2014 and were intended to increase use of evidence-based prevention interventions in non-clinical settings. To maximize review data, studies were not excluded a priori based on design or methodological quality. Using the EBSIS as a guide, two researchers independently extracted data from included studies. Vote counting and meta-summary methods were used to summarize findings.
The review included 42 publications reporting findings from 29 studies. In addition to confirming the strategies and structures described in the EBSIS, the review identified two new strategies and two variations in structure. Capacity-building interventions were found to be effective at increasing practitioners’ adoption (n = 10 of 12 studies) and implementation (n = 9 of 10 studies) of evidence-based interventions. Findings were mixed for interventions’ effects on practitioners’ capacity or intervention planning behaviors. Both the type and structure of capacity-building strategies may have influenced effectiveness. The review also identified contextual factors that may require variations in the ways capacity-building interventions are designed.
Based on review findings, refinements are suggested to the EBSIS. The refined framework moves the field towards a more comprehensive and standardized approach to conceptualizing the types and structures of capacity-building strategies. This standardization will assist with synthesizing findings across studies and guide capacity-building practice and research.
Public health and other community-based practitioners have access to a growing menu of evidence-based interventions (EBIs) to promote health and prevent disease. These EBIs include a range of programs, policies, and practices that have been shown to be effective at improving environments, behaviors, and health outcomes . Practitioners continue to underuse prevention EBIs, in part because they lack the ability and motivation to do so [2, 3]. In response to this challenge, a growing number of agencies are intervening to build practitioners’ capacity [4, 5], which we define as the provision of ongoing support for the purpose of increasing practitioners’ awareness, knowledge, skills, self-efficacy, and motivation to adopt and implement EBIs . Despite extensive investments in capacity building, little is known about how best to design capacity-building interventions to optimize their effectiveness .
Wandersman and colleagues have proposed two frameworks that describe constructs central to capacity building [8, 9]. The Interactive Systems Framework (ISF) for Dissemination and Implementation (2008) posits that transferring EBIs into practice requires interaction among three systems: (1) prevention synthesis and translation systems that disseminate EBIs (e.g., Guide to Community Preventive Services), (2) prevention delivery systems that use EBIs to promote health (e.g., community coalitions, health departments, community-based organizations), and (3) prevention support systems that bridge the gap between the two other systems by disseminating tools and providing training and technical assistance (TA) to build prevention delivery system capacity to effectively use EBIs in practice . Prevention support systems build the organizational capacity of delivery systems and also build the capacity of public health practitioners, coalition members, and others working within those systems. Building on the ISF, Wandersman and colleagues (2012) proposed a second framework—the Evidence-Based System for Innovation Support (EBSIS). The EBSIS describes training, TA, tools, and quality assurance/quality improvement as four strategies that support systems use to build capacity, as well as salient variations in the way those strategies are structured according to their dosage, delivery mode, collaborative design, or proactive design .
Research has demonstrated that capacity-building interventions can be effective at increasing the adoption and implementation of EBIs [6, 7, 10], yet little is known about how best to design capacity building to maximize its effectiveness. The EBSIS offers a framework for building the evidence base to guide the design of capacity-building interventions. The purpose of this review was to contribute to the further development of the EBSIS by systematically reviewing empirical studies of capacity-building interventions to identify (1) the range of strategies used, (2) variations in the way they were structured, and (3) evidence for their effectiveness at increasing public health and other community-based practitioners’ capacity to adopt and implement evidence-based prevention interventions.
We built on the EBSIS to create a conceptual framework to guide the review (Fig. 1). The framework includes capacity-building strategies and variations in the ways strategies are structured (see definitions of strategies and structures in Table 1.) The framework also describes intended outcomes (EBI adoption and implementation) and the mechanisms or mediating variables through which capacity building is hypothesized to affect those outcomes (practitioner capacity and EBI planning behaviors). Practitioner capacity is defined as the awareness, knowledge, skills, self-efficacy, and motivation to engage in EBI planning generally and/or to adopt and implement a specific EBI . Although we recognize the importance of organization- and system-level capacity, the focus of the framework and this review is on practitioner-level capacity. EBI planning behaviors include collective behaviors such as assessing the community, identifying and prioritizing intervention options, developing an action plan, and evaluating processes and outcomes [6, 7, 10, 11].
The proposed conceptual framework modifies EBSIS terminology in three ways to fit the focus of the review. First, rather than the term “innovations”, we use the term “EBIs.” Both the ISF and EBSIS are used as frameworks for building capacity to use innovations, which are not restricted to EBIs and may include any practice that is new to practitioners. In contrast, the current review focuses on EBIs, which are defined as programs, policies, and practices that have been shown to be effective at improving environments, behaviors, and health outcomes .
Secondly, we use the term “assessment and feedback” to refer to the EBSIS strategy “quality assurance/quality improvement” because our terminology more clearly describes a strategy that might be employed in a capacity-building intervention as opposed to a strategy that might be employed by the delivery system to monitor and improve the quality of its own performance. Lastly, the framework also adds a distinction related to the overall “orientation (push versus pull)” of capacity building. Within a “push” orientation, support systems promote a small number of EBIs and build delivery systems’ capacity to use those EBIs. Within a “pull” orientation, the support system does not limit its focus to a few EBIs and instead builds delivery system capacity to select and use the EBIs that best fit their needs from a menu or from the universe of available EBIs . Orientation (push versus pull) is added to the Framework (Fig. 1) as a variation in the structure of support.
We systematically reviewed tests of interventions to build practitioners’ capacity to adopt and implement community-based prevention interventions. The review addressed the following questions:
What types of capacity-building strategies are reported in the literature and how does their delivery structure vary across capacity-building interventions?
Are capacity-building interventions effective at improving practitioners’ capacity to use EBIs, their EBI planning behaviors, and their adoption and implementation of EBIs?
What contextual factors influence the design and effectiveness of capacity-building interventions?
A systematic review of the literature was conducted by representatives of the Cancer Prevention and Control Research Network, a network of ten centers nationwide that is funded by the Centers for Disease Control and Prevention and the National Cancer Institute to accelerate the adoption and implementation of EBIs to prevent and control cancer, in partnership with a wide range of delivery systems . Thus, members of the review team had extensive experience building practitioners’ capacity to use EBIs and were authors of a number of the publications included in the review.
We searched PubMed, EMBASE, and CINAHL for peer-reviewed, English-language articles reporting the findings of studies of capacity-building interventions with a focus on interventions to promote public health and community-based practitioners’ use of prevention EBIs. The search was limited to articles published between January 2000 and January 2014 with the goal of assessing contemporary approaches to capacity building. We defined capacity building as the provision of interactive, ongoing support for the purpose of increasing practitioners’ ability and motivation to adopt and implement EBIs . Community-based prevention EBIs were defined as EBIs that focused on primary prevention in a non-clinical context. In addition to the term “capacity building,” the search included terms commonly used to refer to ongoing interaction between support providers and recipients: “technical assistance” OR “knowledge transfer” OR “knowledge broker” OR “linking agent”. These terms were combined with the following: “community-based” OR “health promotion” OR “prevent*” OR “public health.” The search string also was designed to identify intervention studies and to exclude studies conducted in low and middle income countries because limitations in their financing, infrastructure, and information systems require distinct approaches to capacity building that fall outside the scope of this review . The complete string of terms used to search PubMed is detailed in Fig. 2. Searching for literature in this area is difficult because the vocabulary has yet to be standardized . To be more comprehensive, we also solicited recommendations from members of the Cancer Prevention and Control Research Network.
Two members of the research team reviewed the title and, as needed, the abstracts and full articles of identified publications. Articles were included if they were empirical studies of the provision of capacity-building interventions to promote the use of primary prevention EBIs in non-clinical settings. Capacity building had to be interactive and ongoing; thus, studies were excluded if they included only training or the online dissemination of information. We also excluded studies conducted in a single site, reports of “lessons learned” that lacked a description of the methods for collecting and analyzing data, and studies that only reported findings related to changes in population health behaviors/health status and did not include findings related to capacity, adoption, or implementation. To maximize the amount of data included in the review, we did not exclude studies a priori based on their design or quality. Instead, the following factors that contribute to validity were identified during abstraction: study design, sample size (practitioners and settings), data collection methods, and other factors (e.g., response rates). Potential threats to validity were taken into account in the report of synthesis findings .
Data abstraction and synthesis
The findings from reports on capacity building are not amenable to meta-analysis due to their methodological and conceptual diversity. Therefore, quantitative (vote counting)  and qualitative (meta-summary) methods were used to summarize and synthesize both qualitative and quantitative findings . Two reviewers independently abstracted the following information from each article: study characteristics (location, settings, participants, methods); focus of capacity building (EBIs, population behavior targeted); strategies and structure of capacity building (coded using Table 1 constructs); outcomes related to practitioners’ capacity (knowledge, skills, attitude, or beliefs) or intervention planning behaviors; outcomes related to setting/sector-level adoption and implementation of EBIs; and any qualitative findings related to variations in context and/or the structure of capacity-building strategies. To appraise potential threats to validity, the following data also were abstracted: design, sample size, and response rates . The lead author trained all nine reviewers, who completed a pilot abstraction prior to participating in the review. The two reviewers for each publication compared their abstractions and resolved discrepancies by consensus.
Findings were then summarized and synthesized. The Table 1 codes were iteratively revised to capture the information derived from the review . Vote counting methods were used to summarize data on the type and structure of capacity-building strategies and their effects on practitioner- and setting-level outcomes . For findings on effectiveness, potential threats to validity were described as they related to each category of cumulative findings. Two authors applied meta-summary methods to iteratively review, summarize, and integrate qualitative findings into themes related to context and to variations in capacity-building strategies . Once data were summarized and synthesized, findings were presented back to the full group of abstractors to ensure agreement.
The initial search yielded 1437 publications of which 42 publications reporting the findings from 29 studies met inclusion criteria (see Fig. 3 for PRISMA diagram). Table 2 provides an overview of the included studies. One study was conducted in Sweden and the remainder in the United States. A variety of frameworks and theories informed the studies included in the review. The three most frequently cited were the Diffusion of Innovations Theory (eight studies), the Interactive Systems Framework (seven studies), and Getting to Outcomes or Assets Getting to Outcomes (five studies). Others that were cited more than once included Social Cognitive Theory (three studies), Empowerment Evaluation (two studies), and Communities that Care (two studies).
The most common settings for capacity-building interventions were communities (including those done with community-based coalitions; ten studies), schools (ten studies), and community-based organizations (five studies). Other settings included worksites, churches, pools, health departments, AIDs service organizations, and club houses for the mentally ill. The most frequently targeted behaviors included drinking and substance abuse (nine studies), sun exposure and youth problem behaviors (four studies each), HIV risk behaviors, healthy diet, physical activity, and tobacco use (three studies each). Study designs included 12 group randomized trials, 4 group non-randomized trials, 8 single group before-after studies, and 5 case studies that reported no pre-test or comparison group data.
Review findings are organized in response to the study’s research questions.
What types of capacity-building strategies are reported in the literature?
The literature review confirmed that the EBSIS framework captured most of the strategies that were used to build practitioners’ capacity (see Additional file 1: Table S1). All 29 studies included TA as one of the capacity-building strategies. In the majority of studies, capacity building also included training (n = 27) and tools (n = 25). Among the tools described were manuals designed to guide practitioners in conducting an overall planning process (e.g., Chinman et al., ) or delivering a specific intervention (e.g., Harshbarger et al., ), e-newsletters (e.g., Beam et al., ; ), intervention materials (e.g., Glanz et al., ), evaluation tools (e.g., Emmons et al., ), and site-specific written recommendations (e.g., Hannon et al., ). Only three interventions included assessment and feedback; in each of these studies, capacity building included monitoring and feedback on the fidelity of EBI implementation [27–29].
The review identified two capacity-building strategies not described by the EBSIS: opportunities for peer networking and incentives. Opportunities for peer networking included bringing practitioners together to learn from each other via in-person trainings and TA sessions [28, 30–32], interactive conference calls , and web-based discussion forums . Many of the capacity-building interventions provided incentives to motivate practitioners to participate in the capacity-building intervention or to adopt and implement EBIs, such as scholarships to participate in trainings , mandating participation in training as a requirement for funding , or provision of free resources (e.g., sunscreen to pool staff) .
How does delivery structure vary across capacity-building interventions?
The way that capacity building was structured varied across the dimensions detailed in the EBSIS: orientation, dosage, delivery mode, and collaborative and proactive design (see Additional file 1: Table S1). In ten of the studies, the intervention orientation was towards “pushing” one or two specific EBIs (e.g., Pool Cool, VOICES/VOCES). In the remaining 19 studies, capacity building was oriented towards building practitioners’ capacity to “pull” EBIs from a wider range of options. Dosage varied widely, with authors often providing only limited information. In 19 of the studies, authors provided information on training dosage, typically in the format of number of trainings and their duration (e.g., 1 day). Authors provided almost no information on TA dosage in 15 studies. Authors did provide data on TA frequency (e.g., bi-weekly ) but not overall amount in three studies, overall amount of TA provided but not frequency (e.g., average of 76.2 h of TA per organization ) in five studies, and data on both the frequency and amount of TA provided in six studies. In some studies, authors provided overall exposure scores that combined dosage of training and TA with use of tools (e.g., Chinman et al., ). Authors also reported the mode through which TA was delivered, via face-to-face, by phone, or through combination of those media and email.
The collaborative design of capacity-building interventions also varied. The review revealed multiple related dimensions across which variation occurred in the collaborations between those providing and those receiving the capacity-building intervention. Those providing the intervention may work directly with delivery systems or may use a two-level or train-the-trainer model to build the capacity of intermediaries (e.g., field coordinators  or TA providers ) who then build the capacity of delivery systems. Capacity building also varied in whether it was provided to those who were planning or overseeing EBI implementation (e.g., members of a coalition ) versus those who actually delivered the EBI (e.g., teachers delivering a substance abuse intervention ). In most interventions, TA was provided proactively.
The review identified an additional dimension of variation in the structure of capacity building not specified by EBSIS. Capacity-building interventions varied in whether or not they were delivered within the context of an overall planning model (e.g., Getting to Outcomes). Planning models walk delivery systems through an overall planning process that includes stages such as assessing the context, selecting an EBI, implementing the EBI, and evaluating processes and outcomes. The most commonly used planning models were variations on Getting to Outcomes (n = 5 studies) [20, 28, 37, 38], Communities that Care (n = 2 studies) [27, 39], and one study each using PROSPER , the Healthy Schools Program , STAR , the Strategic Prevention Framework , and a locally developed logic model .
Are capacity-building interventions effective at improving practitioners’ capacity to use EBIs, their EBI planning behaviors, and their adoption and implementation of EBIs?
As summarized in Table 3, studies were more likely to report findings related to effects on adoption (n = 12) or implementation (n = 11) than they were to report the effect that capacity building had on practitioners’ capacity (n = 7) or planning behaviors (n = 7) (see Additional file 2: Table S2 for a more detailed breakdown of findings for each study).
Effects on practitioners’ capacity to use EBIs
In the seven studies reporting findings related to intervention effects on capacity, findings were mixed. Studies reported response rates of 75% or better and had sample sizes of 120 or more, with the exception of Florin et al. (n = 9, ) and Little et al. (n = 50, ). Researchers operationalized capacity as self-efficacy (or self-report of skills), awareness, knowledge, attitudes, and/or beliefs about the value of the EBI. In two cases, group randomized trials found significantly greater improvements in capacity in the intervention versus the comparison group (self-efficacy  and knowledge ) and in two they did not (self-efficacy  and beliefs ). Neither of the two group non-randomized trials found significant between group differences in capacity (awareness  and self-efficacy and attitude ) following the intervention. Two studies found significant within group increases in capacity (awareness, skills  and self-efficacy ).
In one study, researchers analyzed the role that capacity played as both a mediator and moderator of capacity building’s effects on implementation . They found that changes in practitioners’ self-efficacy (but not in their beliefs) mediated the effects that training and TA had on implementation fidelity. They also found that beliefs about an EBI’s value moderated the effects of Training/TA on EBI implementation fidelity, with Training/TA more effective for those practitioners who had more favorable beliefs at baseline.
Effects on EBI planning behaviors
The review found mixed evidence for the effects that interventions had on practitioners’ collective EBI planning behaviors (see Table 3). Behaviors included, for example, developing an implementation plan and evaluating processes and outcomes . Seven studies assessed planning behaviors. The unit of analysis for assessing behaviors was at the level of the setting (e.g., community, program, or school) and sample sizes ranged from 6 to 134. The three studies with the largest sample sizes tested for effectiveness. Of those, two group trials found significant differences, one randomized (n = 24, ) and one not (n = 134, schools ); and one group randomized trial found no significant differences in improvement between groups (n = 30 programs, ). In four studies, authors described improvements in planning behaviors without reporting significance [20, 31, 38, 46].
Effects on adoption and implementation
The review found evidence that capacity building affects delivery system adoption and implementation of EBIs (Additional file 2: Table S2). Of the 12 studies that assessed adoption, four found a significant within group difference [22, 24, 26, 40] and two found significant between group differences in adoption rates with the intervention group having higher rates than the comparison [39, 47]; four additional studies found an increase in adoption following the capacity-building intervention without testing for significance [21, 25, 46, 48]. Findings were mixed, however, as four studies found non-significant group differences in adoption rates [24, 26, 44, 49]. Of the 11 studies that assessed effects on the extent or fidelity of implementation, all but one reported that capacity building had a positive effect. In five group trials (four of which were randomized), researchers compared differences between groups and found that the intervention group had better implementation outcomes than the comparison. In one of the five trials, findings were mixed and the intervention group performed significantly better on only some of the outcomes .
Findings on the effects that variations in strategy type and structure have on outcomes
Review findings suggest that both the type and structure of prevention support strategies influence outcomes. In four studies, researchers compared the effectiveness of different combinations of prevention support strategies and found that interventions that provide TA in addition to training and tools have a greater impact on adoption and implementation [24, 33, 48, 50] than those that do not. In six of eight studies that assessed the relationship between dosage and outcomes, researchers found that dosage is related to the effect of prevention support on capacity [20, 43], planning behaviors [20, 43], adoption [22, 23], and implementation [32, 33, 50], such that higher dose or more engagement with the capacity-building intervention was associated with greater improvements in capacity, behaviors, adoption, and/or implementation (Additional file 2: Table S2). Riggs et al.  did not find a significant relationship between capacity-building dose and coalition capacity , and Spoth et al.  found no significant relationship between frequency of TA requests and the quality of planning behaviors or fidelity of implementation .
What contextual factors influence the design and effectiveness of capacity-building interventions?
The review identified evidence on the following factors that may influence the types and structure of capacity-building strategies that will be most effective: setting capacity, attributes of the EBI, EBI fit with the setting, and the stage of the intervention planning process. In six studies, authors reported that setting-level capacity played an important role in determining the effects that capacity-building interventions have on adoption and implementation. Setting-level capacity included resources (e.g., time, staff, computers, funding, leadership) [20, 31, 41, 48] and collective attitude or willingness . In prevention interventions, the “setting” may be the community, with a community coalition taking the lead in adopting and implementing EBIs as was the case in Brown et al. , which found that the quality of a coalition’s functioning (e.g., funding, leadership, internal and external relationships) was associated positively with the number of EBIs a coalition supported and their efforts to maintain implementation fidelity . In a seventh study, Nargiso et al.  found that settings with lower initial capacity utilized more training and TA . In two studies, authors suggested that EBIs with more components and less prescriptive implementation guidance are more difficult or require more effort to support than other EBIs [28, 32]. Study investigators also reported on the challenges created when EBIs did not fit a particular setting’s funding streams, values, or their clients’ cultures [26, 48]. Multiple studies reported differences in the types and/or amounts of prevention support required at different stages in the intervention planning process (e.g., Chinman et al. ).
Wandersman et al.  created the EBSIS as a framework to guide creation of an evidence base for capacity-building interventions . To further advance the science of improving practitioners’ capacity, we have used an adapted EBSIS framework to guide a systematic review of the capacity-building literature. The findings from our review confirm the usefulness of EBSIS constructs and identify further refinements. Figure 4 presents the refined framework, which includes two new capacity-building strategies (peer networking and incentives) and two additional ways that the structure of those strategies differs across studies (intended recipients and whether provided within the context of a planning model). The review also provides details on the different types of tools being used to build practitioners’ capacity—a strategy that is only minimally described in the EBSIS framework. Lastly, the refined framework includes the review’s exploratory findings related to contextual factors that may moderate the effectiveness of capacity-building interventions and need to be considered in their design. These factors include setting capacity, attributes of the EBI, EBI/setting fit, and stage of the intervention planning process.
Similar to prior reviews, we found that capacity-building interventions can be effective at increasing EBI adoption and implementation [6, 7, 10]. These effectiveness findings are based on vote counting rather than meta-analysis and therefore should be interpreted with caution . The review found that only seven of the 29 studies tested the effects that interventions had on capacity and only one assessed its role as mediator of an intervention’s effects on implementation. EBSIS posits that capacity is the primary mechanism through which prevention support affects the adoption and implementation of EBIs, and yet findings on interventions’ effects on capacity were mixed, with non-significant effects in three of the five studies that compared outcomes in the intervention group to a comparison group. Non-significant findings could have resulted from either limitations in the interventions or in the measurement of effects. Additional research focusing on identifying the capacities required to adopt and to implement EBIs and developing measures that are sensitive to change in those capacities will advance the science of capacity building. Limited evidence exists to support interventions’ effectiveness at improving practitioners’ intervention planning behaviors. Capacity was assessed at the level of individual practitioners, whereas planning behaviors were assessed at the organizational or coalition level, resulting in sample sizes that were often too small to assess for statistically significant change.
One of the review’s central purposes was to describe capacity-building strategies and synthesize evidence related to variations in their types and structures. The lack of information that authors provided about their capacity-building strategies and the way they were structured make it difficult to transfer successful strategies to new settings or to develop guidance for how best to structure capacity building. The need for specific guidance on how to structure capacity building is evidenced by findings that TA providers often experience their role as vague and ill-defined . The lack of information related to capacity-building strategy types and structures also limits the potential to synthesize findings across studies. Use of standardized reporting such as CONSORT, TREND, or TIDieR may help practitioners or researchers disseminating results of interventions to include all relevant elements and ensure that reviewers can find more detailed information about intervention components [54, 55]. Synthesis is further constrained by the limited use of theory in the design and testing of capacity-building interventions.
The review of the literature was systematic but not comprehensive. Searches for literature related to implementation science are difficult because the field is still in the early stages of development, and consistent terminology has not been adopted [15, 56]. Because of these challenges, we cannot claim to have identified all reports of community-based interventions to build practitioners’ capacity to adopt and implement primary prevention EBIs. Of particular concern is the limited number of studies identified in countries other than the United States. The fact that a number of the reviewers were also authors on studies included in the review may have contributed to a biased conceptualization of what constitutes “capacity building.” However, having two individual abstract data from each article limited the potential for bias in data abstractions. The review’s findings were further limited by weaknesses in the included studies’ methods. Although 12 of the 29 studies were group randomized trials, small sample sizes limited the potential to identify significant differences between groups and the remaining studies employed weaker designs. In many of the publications, authors provided only limited detail on their interventions. Although this is similar to other types of intervention research where authors often include little detail on the dosage or mode of delivery , it limits analyses.
Implications for future research
The EBSIS and our refined framework both move the field towards a more standardized approach to conceptualizing the types and structures of capacity-building strategies. This standardization will assist in synthesizing findings across studies and building the evidence base for what works under which circumstances. However, for findings to contribute to the evidence base, it is essential that researchers provide complete descriptions of how they designed and delivered their capacity-building interventions. Capacity building is a complex, behavioral change intervention. The prevention support field could benefit from guidance that the United Kingdom’s Medical Research Council and others have developed to facilitate the development, testing, and translation of complex interventions [58, 59]. Of greatest relevance to the present discussion are recommendations that researchers identify and evaluate the theory of change and provide detailed descriptions of the intervention “to enable replication, evidence synthesis, and wider implementation” (p. 2) .
EBSIS and the refined framework could also advance the field towards the development of theory. Since capacity is hypothesized as the primary causal mechanism, further research is needed to better understand the capacities that practitioners require to successfully adopt and implement EBIs and to develop measures of those capacities. Additional research is also needed to identify salient contextual factors that moderate the effects of prevention support and the best approaches to customizing prevention support contingent on those factors. The framework’s depiction of prevention support as a linear process is an oversimplification, and more research is needed to understand bi-directional interactions between support providers and practitioners and their effects.
The number of researchers and agencies providing technical assistance and other capacity-building strategies to promote the use of evidence in practice is on the rise. However, the science to guide the design of prevention support is nascent. Only a limited number of researchers have taken a rigorous approach to designing, describing, and testing capacity-building strategies. As a result, little is known about how capacity-building strategies may vary across projects and how those variations may affect outcomes. This review contributes to the understanding of the types of capacity-building strategies and their effects thereby building the knowledge base on how to build practitioners’ capacity to use EBIs.
consolidated standards of reporting trials
Communities that Care
Evidence-Based System for Innovation Support
Getting to Outcomes
Interactive Systems Framework
Social Cognitive Theory
transparent reporting of evaluations with non-randomized designs
Rabin BA, Brownson RC, Haire-Joshu D, Kreuter MW, Weaver NL. A glossary for dissemination and implementation research in health. J Public Health Manag Pract. 2008;14:117–23.
Dodson EA, Baker EA, Brownson RC. Use of evidence-based interventions in state health departments: a qualitative assessment of barriers and solutions. J Public Health Manag Pract. 2010;16:E9–15.
Steele CB, Rose JM, Chovnick G, Townsend JS, Stockmyer CK, Fonseka J, Richardson LC. Use of evidence-based practices and resources among Comprehensive Cancer Control Programs. J Public Health Manag Pract. 2014. Epub ahead of print
Collins C, Harshbarger C, Sawyer R, Hamdallah M. The diffusion of effective behavioral interventions project: development, implementation, and lessons learned. AIDS Educ Prev. 2006;18(supp):5–20.
Rabin BA, Glasgow RE, Kerner JF, Klump MP, Brownson RC. Dissemination and implementation research on community-based cancer prevention: a systematic review. Am J Prev Med. 2010;38:443–56.
Flaspohler P, Duffy J, Wandersman A, Stillman L, Maras MA. Unpacking prevention capacity: an intersection of research-to-practice models and community-centered models. Am J Community Psychol. 2008;41:182–96.
Mitton C, Adair CE, McKenzie E, Patten SB, Perry BW. Knowledge transfer and exchange: review and synthesis of the literature. Milbank Q. 2007;85:729–68.
Wandersman A, Duffy J, Flaspohler P, Noonan R, Lubell K, Stillman L, et al. Bridging the gap between prevention research and practice: the interactive systems framework for dissemination and implementation. Am J Community Psychol. 2008;41:171–81.
Wandersman A, Chien VH, Katz J. Toward an evidence-based system for innovation support for implementing innovations with quality: tools, training, technical assistance, and quality assurance/quality improvement. Am J Community Psychol. 2012;50(3-4):445–59.
Durlak JA, DuPre EP. Implementation matters: a review of research on the influence of implementation on program outcomes and the factors affecting implementation. Am J Community Psychol. 2008;41:327–50.
Brownson RC, Fielding JE, Maylahn CM. Evidence-based public health: a fundamental concept for public health practice. Annu Rev Public Health. 2009;30:175–201.
Orleans CT, Barker DC, Kaufman NJ, & Marx JF. Helping pregnant smokers quit: meeting the challenge in the next decade. Tobacco Control. 2000; 9: iii6-iii11.ᅟ
Ekwenugo L, Benard VB, Vinson C. News from the CDC: collaborations to build capacity at the community level in cancer prevention and control. Transl Behav Med. 2013;3:3–5.
Ali MK, Rabadán-Diehl C, Flanigan J, Blanchard C, Narayan KM, Engelgau M. Systems and capacity to address noncommunicable diseases in low- and middle-income countries. Sci Transl Med. 2013;5:181–4.
McKibbon KA, Lokker C, Wilczynski NL, Ciliska D, Dobbins M, Davis DA, et al. A cross-sectional study of the number and frequency of terms used to refer to knowledge translation in a body of health literature in 2006: a Tower of Babel. Implement Sci. 2010;5:16.
Cooper H, Hedges LV, Valentine JC. The Handbook of research synthesis and meta-analysis. New York: Russell Sage Foundation; 2009.
Sandelowski M, Barroso J. Handbook for synthesizing qualitative research. New York: Springer Publishing Company; 2007.
Pluye P, Gagnon MP, Griffiths F, Johnson-Lafleur J. A scoring system for appraising mixed methods research, and concomitantly appraising qualitative, quantitative and mixed methods primary studies in mixed studies reviews. Int J Nurs Stud. 2009;46:529–46.
Hsieh H-F, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15:1277–88.
Chinman M, Hunter SB, Ebener P, Paddock SM, Stillman L, Imm P, et al. The Getting to Outcomes demonstration and evaluation: an illustration of the prevention support system. Am J Community Psychol. 2008;41:206–24.
Harshbarger C, Simmons G, Coelho H, Sloop K, Collins C. An empirical assessment of implementation, adaptation, and tailoring: the evaluation of CDC’s National diffusion of VOICES/VOCES. AIDS Educ Prev. 2006;18(supp):184–97.
Beam M, Ehrlich G, Donze Black J, Block A, Leviton LC. Evaluation of the healthy schools program: part I. Interim progress. Prev Chronic Dis. 2012;9:110106.
Beam M, Ehrlich G, Donze Black J, Block A, Leviton LC. Evaluation of the healthy schools program: part II. The role of technical assistance. Prev Chronic Dis. 2012;9, E64.
Glanz K, Steffen A, Elliott T, O’Riordan D. Diffusion of an effective skin cancer prevention program: design, theoretical foundations, and first-year implementation. Health Psychol. 2005;24:477–87.
Emmons KM, Geller AC, Viswanath V, Rutsch L, Zwirn J, Gorham S, et al. The SunWise policy intervention for school-based sun protection: a pilot study. J Sch Nurs. 2008;24:215–21.
Hannon PA, Harris JR, Sopher CJ, Kuniyuki A, Ghosh DL, Henderson S, et al. Improving low-wage, midsized employers’ health promotion practices: a randomized controlled trial. Am J Prev Med. 2012;43:125–33.
Brown LD, Feinberg ME, Greenberg MT. Determinants of community coalition ability to support evidence-based programs. Prev Sci. 2010;11:287–97.
Flaspohler PD, Meehan C, Maras MA, Keller KE. Ready, willing, and able: developing a support system to promote implementation of school-based prevention programs. Am J Community Psychol. 2012;50:428–44.
Mihalic SF, Fagan AA, Argamaso S, et al. Implementing the LifeSkills training drug prevention program: factors related to implementation fidelity. Implement Sci. 2008;3:1–16.
Riggs NR, Nakawatase M, Pentz MA. Promoting community coalition functioning: effects of project STEP. Prev Sci. 2008;9:63–72.
Duffy JL, Prince MS, Johnson EE, Alton FL, Flynn S, Faye AM, et al. Enhancing teen pregnancy prevention in local communities: capacity building using the interactive systems framework. Am J Community Psychol. 2012;50:370–85.
Florin P, Friend KB, Buka S, Egan C, Barovier L, Amodei B. The Interactive Systems Framework Applied to the Strategic Prevention Framework: the Rhode Island experience. Am J Community Psychol. 2012;50:402–14.
Rabin BA, Nehl E, Elliott T, Deshpande AD, Brownson RC, Glanz K. Individual and setting level predictors of the implementation of a skin cancer prevention program: a multilevel analysis. Implement Sci. 2010;5:40.
Rohrbach LA, Gunning M, Sun P, Sussman S. The Project Towards No Drug Abuse (TND) dissemination trial: implementation fidelity and immediate outcomes. Prev Sci. 2010;11:77–88.
Feinberg ME, Ridenour TA, Greenberg MT. The longitudinal effect of technical assistance dosage on the functioning of Communities That Care prevention boards in Pennsylvania. J Prim Prev. 2008;29:145–65.
Spoth R, Guyll M, Redmond C, Greenberg M, Feinberg M. Six-year sustainability of evidence-based intervention implementation quality by community-university partnerships: the PROSPER study. Am J Community Psychol. 2011;48:412–25.
Chinman M, Acosta J, Ebener P, Burkhart Q, Malone PS, Paddock SM, et al. Intervening with practitioners to improve the quality of prevention: one-year findings from a randomized trial of assets-getting to outcomes. J Prim Prev. 2013;34:173–91.
Chinman M, Ebener P, Burkhart Q, Osilla KC, Imm P, Paddock SM, et al. Evaluating the impact of Getting to Outcomes—underage drinking on prevention capacity and alcohol merchant attitudes and selling behaviors. Prev Sci. 2014;15:485–96.
Fagan AA, Hanson K, Briney JS, Hawkins JD. Sustaining the utilization and high quality implementation of tested and effective prevention programs using the Communities that Care prevention system. Am J Community Psychol. 2012;49:365–77.
Elinder LS, Heinemans N, Hagberg J, Quetel A-K, Hagströmer M. A participatory and capacity-building approach to healthy eating and physical activity—SCIP-school: a 2-year controlled trial. Int J Behav Nutr Phys Act. 2012;9:145.
Little MA, Sussman S, Sun P, Rohrbach LA. The effects of implementation fidelity in the Towards No Drug Abuse dissemination trial. Am J Health Educ. 2013;113:281–96.
Crowley DM, Greenberg MT, Feinberg ME, Spoth RL, Redmond CR. The effect of the PROSPER partnership model on cultivating local stakeholder knowledge of evidence-based programs: a five-year longitudinal study of 28 communities. Prev Sci. 2012;13:96–105.
Acosta J, Chinman M, Ebener P, Malone PS, Paddock S, Phillips A, et al. An intervention to improve program implementation: findings from a two-year cluster randomized trial of Assets—Getting to Outcomes. Implement Sci IS. 2013;8:87.
Brownson RC, Ballew P, Dieffenderfer B, Haire-Joshu D, Heath GW, Kreuter MW, et al. Evidence-based interventions to promote physical activity: what contributes to dissemination by state health departments. Am J Prev Med. 2007;33(1 Suppl):S66–73. quiz S74–78.
Gingiss P, Boerm M, Roberts-Gray C. Follow-up comparisons of intervention and comparison schools in a state tobacco prevention and control initiative. J Sch Health. 2006;76:98–103.
Batchelor K, Freeman AC, Robbins A, Dudley T, Phillips N. Formative assessment of use of behavioral data in HIV prevention: Texas. AIDS Behav. 2005;9:S29–40.
Kelly JA, Somlai AM, DiFranceisco WJ, Otto-Salaj LL, McAuliffe TL, Hackl KL, et al. Bridging the gap between the science and service of HIV prevention: transferring effective research-based HIV prevention interventions to community AIDS service providers. Am J Public Health. 2000;90:1082–8.
Philliber S, Nolte K. Implementation science: promoting science-based approaches to prevent teen pregnancy. Prev Sci. 2008;9:166–77.
Buller DB, Reynolds KD, Ashley JL, Buller MK, Kane IL, Stabell CL, et al. Motivating public school districts to adopt sun protection policies: a randomized controlled trial. Am J Prev Med. 2011;41:309–16.
Cooper BR, Bumbarger BK, Moore JE. Sustaining evidence-based prevention programs: correlates in a large-scale dissemination initiative. Prev Sci. 2013;16:145–57.
Nargiso JE, Friend KB, Egan C, Florin P, Stevenson J, Amodei B, et al. Coalitional capacities and environmental strategies to prevent underage drinking. Am J Community Psychol. 2013;51:222–31.
Pope C, Mays N, Popay J. Synthesizing qualitative and quantitative health evidence: a guide to methods. Berkshire, England: McGraw Hill; 2007.
Clavier C, Sénéchal Y, Vibert S, Potvin L. A theory-based model of translation practices in public health participatory research. Sociol Health Illn. 2012;34:791–805.
Armstrong R, Waters E, Moore L, Riggs E, Cuervo LG, Lumbiganon P, et al. Improving the reporting of public health intervention research: advancing TREND and CONSORT. J Public Health. 2008;30:103–9.
Hoffmann TC. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;348:g1687–7.
Greenhalgh T, Robert G, Macfarlane F, Bate P, Kyriakidou O. Diffusion of innovations in service organizations: systematic review and recommendations. Milbank Q. 2004;82:581–629.
Leeman J, Jackson B, Sandelowski M. An evaluation of how well research reports facilitate the use of findings in practice. J Nurs Scholarsh. 2006;38:171–7.
Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008;337:a1655.
Davidson KW, Goldstein M, Kaplan RM, Kaufmann PG, Knatterud GL, Orleans CT, et al. Evidence-based behavioral medicine: what is it and how do we achieve it? Ann Behav Med. 2003;26:161–71.
Escoffery C, Glanz K, Elliott T. Process evaluation of the Pool Cool diffusion trial for skin cancer prevention across 2 years. Health Educ Res. 2008;23:732–43.
Escoffery C, Glanz K, Hall D, Elliott T. A multi-method process evaluation for a skin cancer prevention diffusion trial. Eval Health Prof. 2009;32:184–203.
Hall D, Dubruiel N, Elliott T, Glanz K. Linking agents’ activities and communication patterns in a study of the dissemination of an effective skin cancer prevention program. J Public Health Manag Pract. 2009;15:409–15.
Valente TW, Chou CP, Pentz MA. Community coalitions as a system: effects of network change on adoption of evidence-based substance abuse prevention. Am J Public Health. 2007;97:880.
Hunter SB, Paddock SM, Ebener P, Burkhart AK, Chinman M. Promoting evidence-based practices: the adoption of a prevention support system in community settings. J Community Psychol. 2009;37:579–93.
Hunter SB, Chinman M, Ebener P, Imm P, Wandersman A, Ryan GW. Technical assistance as a prevention capacity-building tool: a demonstration using the getting to outcomes framework. Health Educ Behav. 2009;36:810–28.
Brown LD, Feinberg ME, Shapiro VB, Greenberg MT. Reciprocal relations between coalition functioning and the provision of implementation support. Prev Sci. 2013;16:101–9.
McCracken JL, Friedman DB, Brandt HM, Adams SA, Xirasagar S, Ureda JR, et al. Findings from the Community Health Intervention Program in South Carolina: implications for reducing cancer-related health disparities. J Cancer Educ. 2013;28:412–9.
Honeycutt S, Carvalho M, Glanz K, Daniel SD, Kegler MC. Research to reality: a process evaluation of a mini-grants program to disseminate evidence-based nutrition programs to rural churches and worksites. J Public Health Manag Pract JPHMP. 2012;18:431–9.
Lee JG, Ranney LM, Goldstein AO, McCullough A, Fulton-Smith SM, Collins NO. Successful implementation of a wellness and tobacco cessation curriculum in psychosocial rehabilitation clubhouses. BMC Public Health. 2011;11:702.
The authors declare that they have no competing interests.
JL conceived of the study, identified relevant literature, developed abstraction process, abstracted data, analyzed findings, prepared figures, and drafted the manuscript. LC coordinated data abstraction, abstracted data, prepared tables, and helped draft the manuscript. AAM coordinated phone discussions with author group, abstracted data, and helped prepare the manuscript. CTE, AKH, MAH, KMW, MS, CSH, and LET abstracted data and assisted in data interpretation and manuscript preparation. All authors read and approved the final manuscript.
This publication was supported by Cooperative Agreement Numbers U48DP00194409, U48DP001949, U48DP0010909, and U48DP001934 from the Centers for Disease Control and Prevention and the National Cancer Institute to Cancer Prevention and Control Research Network sites. Marieke A. Hartman was supported by the postdoctoral fellowship, University of Texas School of Public Health Cancer Education and Career Development Program, National Cancer Institute (NIH Grant R25CA57712) and NIH Grant R01CA163526. Michelle Schreiner was supported by the National Institute of Nursing Research (Grant 5T32NR00856). The findings and conclusions presented here are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention or the National Institutes of Health.
Content of support strategies used in publications included in this review. For each publication, details are provided on the planning model, training, technical assistance, tools, and other strategies used.
Evidence for capacity-building intervention effectiveness. Evidence is summarized on each study’s findings on the effects capacity building had on capacity, planning behaviors, adoption, and implementation.
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Leeman, J., Calancie, L., Hartman, M.A. et al. What strategies are used to build practitioners’ capacity to implement community-based interventions and are they effective?: a systematic review. Implementation Sci 10, 80 (2015). https://doi.org/10.1186/s13012-015-0272-7
- Capacity building
- Prevention support
- Interactive Systems Framework
- Technical assistance
- Evidence-based practice