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Open Access

Peer-reviewed

Research Article

Consolidated Framework for Collaboration Research derived from a systematic review of theories, models, frameworks and principles for cross-sector collaboration

  • Larissa Calancie ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Project administration, Supervision, Writing – original draft, Writing – review & editing

    larissa.calancie@tufts.edu

    Affiliation Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States of America

    ⨯
  • Leah Frerichs,

    Roles Formal analysis, Investigation, Writing – original draft, Writing – review & editing

    Affiliation Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America

    ⨯
  • Melinda M. Davis,

    Roles Formal analysis, Writing – original draft, Writing – review & editing

    Affiliation Oregon Rural Practice-based Research Network, School of Medicine, Oregon Health and Science University, Portland, OR, United States of America

    ⨯
  • Eliana Sullivan,

    Roles Data curation, Writing – review & editing

    Affiliation Oregon Rural Practice-based Research Network, Oregon Health and Science University, Portland, OR, United States of America

    ⨯
  • Ann Marie White,

    Roles Formal analysis, Writing – review & editing

    Affiliation Department of Psychiatry, School of Medicine and Dentistry, University of Rochester Medical Center, Rochester, NY, United States of America

    ⨯
  • Dorothy Cilenti,

    Roles Formal analysis, Writing – review & editing

    Affiliation Department of Maternal and Child Health, National Maternal and Child Health Workforce Development Center, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America

    ⨯
  • Giselle Corbie-Smith,

    Roles Formal analysis, Writing – review & editing

    Affiliation Departments of Social Medicine and Internal Medicine, UNC Center for Health Equity Research, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America

    ⨯
  • Kristen Hassmiller Lich

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Supervision, Writing – original draft, Writing – review & editing

    Affiliation Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America

    ⨯

Abstract

Cross-sector collaboration is needed to address root causes of persistent public health challenges. We conducted a systematic literature review to identify studies describing theories, models, frameworks and principles for cross-sector collaboration and synthesized collaboration constructs into the Consolidated Framework for Collaboration Research (CFCR). Ninety-five articles were included in the review. Constructs were abstracted from articles and grouped into seven domains within the framework: community context; group composition; structure and internal processes; group dynamics; social capital; activities that influence or take place within the collaboration; activities that influence or take place within the broader community; and activities that influence or take place both in the collaboration and in the community. Community engagement strategies employed by collaborations are discussed, as well as recommendations for using systems science methods for testing specific mechanisms of how constructs identified in the review influence one another. Researchers, funders, and collaboration members can use the consolidated framework to articulate components of collaboration and test mechanisms explaining how collaborations function. By working from a consolidated framework of collaboration terms and using systems science methods, researchers can advance evidence for the efficacy of cross-sector collaborations.

Citation: Calancie L, Frerichs L, Davis MM, Sullivan E, White AM, Cilenti D, et al. (2021) Consolidated Framework for Collaboration Research derived from a systematic review of theories, models, frameworks and principles for cross-sector collaboration. PLoS ONE 16(1): e0244501. https://doi.org/10.1371/journal.pone.0244501

Editor: Joseph Telfair, Georgia Southern University, UNITED STATES

Received: August 4, 2020; Accepted: December 10, 2020; Published: January 4, 2021

Copyright: © 2021 Calancie et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Collaboration across sectors has long been a strategy for addressing entrenched social problems such as addiction, environmental health justice, and health disparities [1–3]. Cross-sector collaborations are groups whose members represent different sectors in a community, such as healthcare, education, community residents, and government, who contribute their unique perspectives, resources, capabilities and social capital toward a shared vision that could not be achieved by organizations acting within a single sector [4, 5]. Recognizing that social determinants of health and other factors are influenced by many sectors, in 2019 the Robert Wood Johnson Foundation called for on-going collaborations between sectors to create healthy communities where all individuals can lead healthy lives [6]. The National Academy of Medicine, the Centers for Disease Control and Prevention, Centers for Medicaid and Medicare Services and health care systems such as Kaiser Permanente have all called for, and funded, cross-sector collaboration efforts to promote health and reduce disease in communities [7–10]. In addition, states like Oregon have implemented policies to support cross-sector collaborations between medical (hospital, primary care), public health, patients as a stakeholder group, and other community-based services providers (behavioral health, criminal justice, education) [11]. Cross-sector collaboration approaches are likely to continue being applied to complex social problems within communities.

A variety of theories, models, frameworks and principles for cross-sector collaborations are proposed in the scientific literature as well as through practitioner-oriented organizations and publications [12]. In 2002 Butterfoss and Kegler noted that “the practice of coalition building has outpaced the development of coalition theory” (p 161, [1]) and went on to propose an initial version of the Community Coalition Action Theory (CCAT) that integrated published and grey literature to describe the formation, maintenance, and function of coalitions in communities. Since then practitioners and researchers have expanded the repertoire of cross-sector collaboration frameworks used to plan, support, and evaluate such entities. Collective Impact, first proposed by Kania & Kramer in 2011 [13], has become particularly popular, despite some concerns that it does not acknowledge decades of cross-sector collaboration scientific literature and “misses the social justice core that exists in many coalitions” (p4, [14]). Some studies of Collective Impact report positive results [15, 16], while others report mixed findings and limitations of the model [17–19]. Practitioners, researchers, and funders would benefit from an analysis of commonalities between frameworks and an exploration of the community engagement strategies they employ to create change in their communities.

In order to advance the science of the processes through which cross-sector collaborations engage community members and influence change, the field needs a comprehensive view of existing frameworks as a step toward developing cross-sector collaboration theories that can guide research and practice. While several reviews of cross-sector collaboration studies have been conducted [2, 20, 21], they were conducted thirteen to twenty years ago. Cross-sector collaboration literature has expanded significantly since those reviews were conducted and thus an updated review is warranted. The purpose of our review is to inform cross-sector collaboration research and practice by identifying concepts and community engagement strategies in the literature that are relevant to cross-sector collaboration planning, implementation, and evaluation. Our objective is to provide a consolidated presentation of constructs with consistent terminology and definitions from across multiple theories and frameworks. Researchers and practitioners can select constructs and engagement strategies from our consolidated framework that are most relevant to their context and use them for further theory development and verification, evaluation of collaboration progress over time, and to help diagnose or explain variation in collaboration process and outcomes. In summary, we aimed to identify and describe constructs within theories, models, frameworks and principles for cross-sector collaborations published in the peer-reviewed scientific literature; document the community engagement approaches they employ; and synthesize constructs into a comprehensive framework. This thorough, up-to-date review provides a foundation for collaborations, funders, and researchers to practice, build upon, and rigorously test models of cross-sector collaboration.

Methods

We conducted a systematic review using PRISMA guidelines to identify peer-reviewed publications describing theories, models, frameworks and principles (hereafter referred to as “models”) for cross-sector collaboration [22]. To synthesize these results, we created a conceptual framework–the Consolidated Framework for Collaboration Research (CFCR)—integrating the constructs for models identified in the review. “We” are a team of researchers who study approaches to addressing a variety of public health challenges, such as mental health concerns, chronic disease prevention and management, obesity prevention, cancer prevention, and maternal and child health concerns. We work with community members and groups and saw a need for a comprehensive model of how community collaborations operate in order to further study and inform community-based work.

Search strategy

With assistance of a health science research librarian, we searched PubMed, Embase, and EBSCO (CINHAL Plus with Full Text and Social Work Abstracts) from date of database initiation to November 2016 for published cross-sector collaboration models. The first author met with the librarian to establish a specific search strategy that was likely to return articles that were relevant to the review. After discussing the goals of the review, we provided several articles that were illustrative of the types of articles we expected our review to return and worked with the librarian to develop a strategy to systematically identify relevant articles. Within that strategy, the librarian suggested databases to search, recommended searching variations on search terms, and advised on the search logic within each database in order to keep the search consistent across databases. We conducted a complicated search using 48 search terms, including ‘cross sector collaboration,’ ‘cross-sector collaboration,’ ‘cross-sector network,’ ‘multisector network,’ multi-system collaboration,’ ‘council,’ ‘coalition,’ ‘collective impact,’ ‘framework,’ ‘theory,’ and ‘model.’ A full list of search terms is available in S1 Table. Search results were merged and de-duplicated. Articles were excluded if they were not written in English; if the full text was not available; if they mentioned a collaboration but did not describe a generalizable model; referred to an existing model without adding or revising constructs; or described a collaboration within a single sector. Two authors reviewed all titles and abstracts for inclusion/exclusion and reconciled any disagreements. The full text of selected articles was then read by two authors to determine whether screened articles met the inclusion criteria. The search was updated in 2020 by repeating the search to include articles published between December 2016 and July 2020. One author reviewed all titles, abstracts, and full text to update the list of included articles.

Data abstraction

Three authors created a data abstraction form and then revised the form based on input from the larger author group. We pilot-tested the revised abstraction form with the large group and further revised the form to create a final abstraction form. The final form was programmed into Qualtrics, an online survey platform, and contained a mix of multiple-choice format questions (e.g., What type of cross-sector collaboration does this article describe?) and open text boxes (e.g., What is the stated objective of cross-sector collaboration described in this article?) to abstract relevant information in each article. Two-member co-author teams abstracted text from included articles using the final form. One author abstracted the information from each included article and then another member reviewed the abstractions–adding to or editing the abstraction as needed. We used the five following major domains to guide text abstraction: constructs described in the model; definitions of “system”; organizational structure; community engagement activities; and evaluation descriptions. In addition, we abstracted details on the study design, collaboration type (e.g., coalition, council, collaborative as defined by the authors), topic(s) the collaboration focused on, objective(s) of the collaboration, geographic catchment area, sectors represented, collaboration stage, and any steps and specific actions that were recommended to support collaboration activities.

Coding process

We analyzed abstracted text using content analysis [23]. Abstracted textual data were uploaded into Dedoose [24] and coded. The first author reviewed included articles and generated an initial codebook based on Allen and colleagues’ model [5] and Butterfoss and Kegler’s CCAT [25]. Allen’s model shows how internal capacity constructs, such as leadership and member empowerment relate to collaboratives’ goal of changing systems through institutionalized policies and practices [5]. The CCAT is a theory that contains similar constructs to Allen’s model, but includes stages of coalition formation, implementation of strategies, and community health outcomes [25]. CCAT and Allen’s model were selected because they can be applied to a range of public health challenges and have been empirically tested with coalitions [5, 26, 27].

Two authors pilot-tested the codebook by coding abstracted text from 10 randomly selected articles using the initial codebook. Testing and refining a codebook is recommended when conducting qualitative analysis with a team of researchers [28]. They met to discuss how they applied codes and opportunities to revise the codebook in order to capture relevant concepts across a range of article types. Based on the pilot-test, we refined code definitions, added new codes, and removed or consolidated redundant codes. Subsequently, the two authors coded additional sets of 10 articles using the revised codebook until they reached at least 65% agreement for each category within the codebook. Percent agreement ranged from 67–100% with an average of 84% agreement. Then the first author coded all definitions of “system”; organizational structure; community engagement activities; and descriptions of evaluation. Two authors double-coded constructs, then the research team members reconciled discrepancies by discussing the rationale behind applied codes and selecting an agreed upon code(s) for each excerpt. Final codes and definitions are in Table 2.

Analysis and synthesis

We calculated code frequencies for abstracted text that could be categorized and counted (e.g., collaboration type, focus area, sectors represented) and synthesized our findings. Using an iterative process, we grouped and synthesized the coded constructs into a conceptual model called the Consolidated Framework for Collaboration Research (CFCR), to visually show the frequency with which constructs were abstracted from included articles and to hypothesize how groups of constructs might relate to one other. The CFCR is inspired by the Consolidated Framework for Implementation Research that was similarly developed through a literature review and sought to inventory and consolidate constructs within the implementation field [29]. CCAT, Allen’s model, and findings from this review informed CFCR. Constructs that occurred in five percent or more of the articles included in this review are included in the framework.

Results

Included articles

A total of 4,923 articles were identified across the three databases searched, resulting in 2,677 unique articles (Fig 1). We reviewed the full text of 286 articles; 95 (33%) articles met inclusion criteria. Most articles excluded during the full text review mentioned a collaboration but did not describe generalizable models that can inform other collaborations (51%) or referred to existing theories, models, frameworks and principles and did not make significant modifications to the model (22%).

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Fig 1. PRISMA diagram showing review search results, included articles, excluded articles and reasons for article exclusion.

https://doi.org/10.1371/journal.pone.0244501.g001

Study characteristics

As detailed in Table 1, included articles used diverse research designs and addressed a variety of topics. Over half of the articles were case studies or lessons from the field (57%). Cross-sectional studies of one or more collaborations were the next most common study type (26%) followed by conceptual papers, which reviewed the literature and proposed a new model (12%); two articles (2%) described trials where community-level outcomes were evaluated. Topics addressed included healthcare access, broad community health, and other specific disease or health-related foci (e.g., obesity, teen pregnancy). Promoting health, improving health systems, and reducing substance abuse were the most common topics.

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Table 1. Study types and descriptions of collaborations presented in reviewed articles.

https://doi.org/10.1371/journal.pone.0244501.t001

The geographic scope that collaborations were working to influence was described in 72 articles (76%). “Community” was the most frequently mentioned geographic target area (24%), followed by counties (15%), cities or municipalities (14%), state or province-level focus areas (11%), neighborhood (7%), and regional (6%). The number of sectors involved in collaborations ranged from two to ten, including social services, public health, education, criminal justice, public safety, government, healthcare, military, housing, faith organizations, and community members. Healthcare (57%), government (37%), and community-based organizations (35%) were the most common sectors included in collaborations. Caregivers (4%), military (2%), and transportation (2%) were the least frequently mentioned sectors. Described cross-sector collaborations spanned the formation, maintenance, and institutionalization stages of collaboration, with many articles applicable to multiple stages. Articles described a variety of collaborative objectives including coordinate a system or multi-sector response to complex issues [30–33] such as health disparities [34–37]; engage community in multi-sector approaches to change [38–45]; avoid duplicating efforts to address a complex problem [46, 47]; work together to create structural change [48]; build public health or health care infrastructure and coordination [49–57]; institutionalize partnerships [58]; mobilize resources [59]; and implement multi-sector programs and policies [60, 61].

Construct code results

Construct code results are presented in Table 2, including construct code names, percent of articles containing each construct, and construct definitions. Sample article excerpts for each construct are presented in S2 Table. Articles often described collaboration goals in terms of improving a system and/or community-level outcome(s) related to health. The most commonly applied construct codes were “broad, active membership” (construct code contained in 61% of articles), followed by “interventions” (58%), “organizational structure and processes” (51%), and “shared vision” (51%). These are arguably defining features of collaborations, which were repeatedly described as being composed of members that work together through formal and informal processes to apply their perspective and experience to build a future that the groups agree is better in some specific ways than the current state. About 30% of articles acknowledged that the context in which a cross-sector collaboration is working matters. Some articles (12–14%) recommended or reported that collaborations sought to learn about specific contexts, such as political or economic contexts. Cross-sector collaborations undertake activities that operate within the collaboration, such as planning, and externally to the collaboration, often in partnership with communities. Examples of external activities are needs assessments and community education. Activities keep collaboration members engaged, build credibility within their communities, and move the collaboration toward realizing its goals. More than half of the articles described community engagement approaches, indicating that community engagement is a common element of cross-sector collaborations. Community representation within collaboratives was critical in many of the identified studies. Additional strategies to engage community members included seeking input about collaboration priorities directly from community members, community mobilizing around specific initiatives, offering training and capacity building opportunities for community members, and involving community members in data collection or implementation activities. Primary data collection from community members, including focus groups, surveys, and interviews, was mentioned in 20% of articles.

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Table 2. Construct codes, percent of articles containing each construct code, and sample construct excerpts or excerpt summaries from articles included in the review.

https://doi.org/10.1371/journal.pone.0244501.t002

Conceptual diagram

We synthesized findings from this review in the Consolidated Framework for Collaboration Research (CFCR) (Fig 2). The domains in Table 2 directly map onto the domains and constructs presented in Fig 2. Domains include community context; group composition; structure and internal processes; group dynamics; social capital; activities that influence or take place within the collaboration; activities that influence or take place within community; and activities that influence or take place both in the collaboration and in the community. The CFCR is shaded to show code frequencies and organizes constructs into domains that theoretically influence one another as indicated with arrows, based on their timing or function within a collaboration. For example, structure and internal processes are ideally established early in a collaboration’s timeline and they help guide aspects of a collaboration’s group dynamics and social capital. Community engagement is integrated throughout the figure, including in the group composition and in activities that influence or take place within communities.

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Fig 2. Consolidated Framework for Collaboration Research (CFCR) conceptual diagram synthesizing constructs that appeared in five or more of the articles included in the review.

https://doi.org/10.1371/journal.pone.0244501.g002

The CFCR acknowledges the role of context and evaluation opportunities within cross-sector collaboration work. Elements of community context influence all aspects of collaborations and are therefore depicted in a box with a dashed perimeter in the top left of the framework. An evaluation continuum spans the bottom of the figure. The continuum shows evaluation activities that align with the boxes above. Evaluation activities are internally focused on the left-hand side of the continuum and then move from proximal to community-level outcome evaluation activities, which are shown on the right-hand side of the continuum. CFCR includes feedback loops through which domains that occur later in a collaboration’s timeline, such as activities, can affect earlier collaboration conditions, such as group composition and social capital, which later affect activities. Community-level outcomes, such as changes in norms, perceptions, behaviors, environments, policies, systems, health outcomes, and community capacity are contained within a dashed box in Fig 2 because change in community-level or population outcomes are the ultimate goal of most cross-sector collaborations’ work; however their detailed coding was out of the scope of this review because these outcomes are inconsistently described in publications focused on collaboration model structure and would require further follow-up with authors.

Discussion

We identified, described, and synthesized 95 articles’ theories, models, frameworks and principles for cross-sector collaboration into the Consolidated Framework for Collaboration Research (CFCR). This framework organizes constructs into seven domains: community context; group composition; structure and internal processes; group dynamics; social capital; activities that influence or take place within the collaboration; activities that influence or take place within the broader community; and activities that influence or take place both in the collaboration and in the community. The domains, particularly the distinction between activities that take place in collaboration and activities that influence the t he community, build upon existing cross-sector collaboration literature and add new concepts to help move the field forward. The constructs mentioned in the most articles were breadth of active membership, organizational structure and processes, shared vision, and interventions. These may be the most fundamental components of cross-sector collaborations. The CFCR can be used by researchers, practitioners, funders and collaboration members to conceptualize and name elements of collaboration and to consider how those elements, if strengthened, can improve collaboration. More broadly, the framework could be a useful tool when starting, maintaining, or evaluating a collaboration, since it provides a comprehensive view of collaboration elements. We also recommend considering how these constructs relate to each other and desired outcomes. More specifically, as a synthesis across multiple theories and frameworks, the CFCR offers an overarching typology from which researchers and practitioners can select and use the constructs to promote theory development about what works where and why across multiple contexts. Thus, it is a framework that provides flexibility for use across diverse settings, contexts, and topics.

Our study expands existing literature and reviews to provide a broad, unified framework of constructs that have been described and/or tested within the cross-sector collaboration literature and synthesizes these findings into a conceptual model. Our framework includes almost all the constructs present in the CCAT and Allen’s model, though CFCR includes more constructs, an updated organization of constructs, and is based on a systematic review identifying and integrating constructs from a broader body of research. Foster-Fishman and colleagues conducted a similar review of 80 articles in 2001 and proposed a framework detailing critical elements of collaborative capacity at four levels: member, relational, organizational, and programmatic capacity [21]. de Montigny and colleagues’ 2019 review examining cross-sector collaborations for social change to promote population health built upon the five conditions described in Collective Impact and added a new condition: collective learning [12]. Our review offers a more detailed inventory of constructs to consider for cross-sector collaboration design, maintenance, and evaluation and offers an example for how complex relationships between those constructs could be tested. In 2006, Zakocs and Edwards published a comprehensive review of the factors that are related to health coalition effectiveness [20]. Our review identified many of the same factors present in that study and added more constructs to the unified framework. Roussos and Fawcett (2000) reviewed the evidence for whether collaborative partnerships influence environmental changes, community-wide behavior changes, and population-level health indicators [2]. They found some evidence of collaborations’ impact within the 34 studies they reviewed but noted that evaluation of community and population-level outcomes is challenging, as is assessing causality between partnerships’ actions and community-level outcomes. Our review differed from those by Zakocs and Roussos in that we did not assess cross-sector collaboration effectiveness, but instead focused on synthesizing the concepts found within the existing cross-sector collaboration theories, models, frameworks and principles described in the published literature–a necessary step before future research can test models stemming from this more complete framework.

This study highlighted community engagement approaches employed by cross-sector collaborations, including involving community members as collaboration members and mobilizing community members around specific collaboration priorities. Involvement of community members as active partners in addressing health and social concerns have become increasingly valued because of the potential to increase relevance of research findings, increase community capacity to affect change long-term, and alleviate persistent health disparities in historically underserved communities [122–125]. A study of coalition health equity capacity found that coalitions can increase their capacity with on-going training and technical assistance [126]. Our findings suggest that community engagement is an essential aspect of many cross-sector collaborations, though the specific approaches and extent of engagement appear to vary widely. The variation is important for cross-sector collaborations to consider as they use the CFCR to guide their planning and evaluation efforts. For example, we found evidence of engagement strategies across a spectrum from consultation to shared leadership within cross-sector collaborations. The strategies across the spectrum all have a role in engagement, and collaboratives need to carefully consider and evaluate of each for their specific context.

Our study has limitations. We did not assess the relationship between theories, models, frameworks and principles and effectiveness at changing community-level outcomes because very few included articles tested such relationships [42, 79]. Our inclusion criteria captured articles that described models; articles that evaluated a collaboration’s effectiveness, but did not describe the coalition’s model, were excluded. For example, several Allies Against Asthma community coalition studies [127, 128] and a national evaluation of state coalitions aiming to reduce underage drinking [129] were excluded because the studies tested the collaborations’ impact on community-level outcomes but did not describe the collaborations’ models. Comparing and testing theories, models, frameworks and principles to determine which are most effective under specific circumstances is an area for future research. Recognizing the variation in and complexity of collaboration models, this research must be undertaken with methods capable of accommodating this complexity (e.g., mediation, moderation, and dynamics illustrated in Fig 2).

In this review, we identified constructs but did not analyze how constructs were combined or sequenced within articles, or how constructs related to specific collaboration objectives. Future research could test the relationships between constructs to elucidate the mechanisms through which collaborations influence change in their communities [130]. Systems thinking tools, such as causal loop diagrams (CLDs) and network analysis, are designed to accommodate complexity and could facilitate such analysis.

As an example of how systems thinking tools may be used, Fig 3 presents an illustrative CLD that shows hypothesized interactions between several constructs within CFCR described in reviewed articles. The CLD hypothesizes that breadth of active membership increases the need for group structure and processes, which can lead to positive group dynamics if the group processes are successfully implemented. Positive group dynamics can generate social capital within collaborations, leading to collaboration-led activities. However, as the rate of collaboration-led activities increases, members’ time and resources may become depleted and that can reduce the rate of collaboration-led activities (Fig 3, B1) and can reduce the implementation of group processes (B2). Depletion of collaboration members’ time may also reduce member recruitment initiatives, which can limit growth in the breadth of active membership (Fig 3, B3). The dynamics in this CLD begin to illustrate the complexity and interrelationships between constructs proposed by some of the articles included in this review, as well as in CCAT and Allen’s model (e.g., when coupling of constructs was recommended or one is described as setting the stage for or triggering another). Future research should test the relationships such as those in Fig 3 and other complex collaboration mechanisms to advance our understanding of not only what constructs are important for studying collaborations, but how those constructs are interrelated. Moreover, CLDs and a participatory approach to developing them called Group Model Building, can be used within collaborations to guide group members’ understanding of complex problems, and then to identify, prioritize, and learn about the potential impact of alternative actions designed to effect positive change [131–133].

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Fig 3. Causal loop diagram showing how several constructs identified in the review may relate to each other over time.

In a CLD, a change in a variable at the tail end of an arrow is said to cause a change in the variable at the head end of that same variable, all else equal (e.g., an increase in the number of patrons at a popular restaurant leads to an increase in the wait time for a table, all else being equal). The direction of change is indicated by polarity symbol on the arrowhead. If a change in one variable (e.g., an increase) causes a change in the same direction for the other variable (e.g., it also increases), the polarity is positive (+), or said to be in the “same” direction (s). If a change in once variable causes a change in the opposite direction (e.g., an increase in one variable leads to a decrease in another variable), the polarity is negative (-) or said to be in the “opposite” direction (o). An important feature of CLDs is their ability to show feedback loops, or connections between variables where a chain of variables end up “feeding back” to the starting variable, and thus changing it. A critical CLD symbol is the nature of feedback loops, designated as either reinforcing (R) if the polarity within a feedback loops indicates that a change in one direction will be perpetuated throughout the loop, or as balancing (B) if changes within variables counteract each other, leading to a steady state or oscillation between states.

https://doi.org/10.1371/journal.pone.0244501.g003

Conclusion

We conducted a systematic review of articles describing theories, models, frameworks and principles of cross-sector collaborations and synthesized our findings into the Consolidated Framework for Collaboration Research (CFCR). This review and the resulting CFCR extends prior work by showing constructs and community engagement strategies that are important to consider when creating, sustaining, funding or studying cross-sector collaborations. Fig 3 is an example of how dynamic relationships within collaborations can be diagramed and tested. Systems science tools, such as CLDs, can improve our understanding of how and why cross-sector collaborations may or may not function to influence health outcomes in their communities.

Supporting information

S1 Checklist. PRISMA 2009 checklist.

https://doi.org/10.1371/journal.pone.0244501.s001

(DOC)

S1 Table. Systematic search conducted in PubMed.

Equivalent searches were performed in Embase and EBSCO (CINHAL Plus with Full Text and Social Work Abstracts).

https://doi.org/10.1371/journal.pone.0244501.s002

(DOCX)

S2 Table. Construct codes and sample construct excerpts or excerpt summaries from articles included in the review.

https://doi.org/10.1371/journal.pone.0244501.s003

(DOCX)

References

  1. 1. Butterfoss F, Kegler M. Toward a comprehensive understanding of community coalitions. In: Emerging theories in health promotion practice and research. 2002. p. 157–93.
  2. 2. Roussos ST, Fawcett SB. A Review of Collaborative Partnerships as a Strategy for Improving Community Health. Annu Rev Public Health. 2000;21(1):369–402. pmid:10884958
  3. 3. Mitchell RE, Stevenson JF, Florin P. A typology of prevention activities: Applications to community coalitions. J Prim Prev. 1996;16(4):413–36. pmid:24254855
  4. 4. Bryson JM, Crosby BC, Stone MM. The Design and Implementation of Cross-Sector Collaborations: Propositions from the Literature. Public Adm Rev. 2006 Dec;66(s1):44–55.
  5. 5. Allen NE, Javdani S, Lehrner AL, Walden AL. “Changing the text”: modeling council capacity to produce institutionalized change. Am J Community Psychol. 2012 Jun;49(3–4):317–31. pmid:21842302
  6. 6. Robert Wood Johnson Foundation. Fostering Cross-Sector Collaboration to Improve Well-Being [Internet]. 2018 [cited 2018 Oct 2]. Available from: https://www.rwjf.org/en/cultureofhealth/taking-action/fostering-cross-sector-collaboration.html
    • 7. Kottke TE, Stiefel M, Pronk NP. “Well-Being in All Policies”: Promoting Cross-Sectoral Collaboration to Improve People’s Lives. Prev Chronic Dis. 2016;13:E52. pmid:27079650
    • 8. Wizemann T. Collaboration Between Health Care and Public Health: Workshop Summary. National Academies Press; 2016.
      • 9. Bailey SBC. Focusing on Solid Partnerships Across Multiple Sectors for Population Health Improvement. Prev Chronic Dis. 2010 Nov;7(6):A115. pmid:20950522
      • 10. Alley DE, Asomugha CN, Conway PH, Sanghavi DM. Accountable Health Communities—Addressing Social Needs through Medicare and Medicaid. N Engl J Med. 2016 Jan 7;374(1):8–11. pmid:26731305
      • 11. Stock R, Goldberg BW. Health Reform Policy to Practice—Oregon’s Path to a Sustainable Health System: A Study in Innovation. 1st ed. Academic Press; 2017. 362 p.
        • 12. de Montigny JG, Desjardins S, Bouchard L. The fundamentals of cross-sector collaboration for social change to promote population health. Glob Health Promot. 2019 Jun 14;26(2):41–50. pmid:28805502
        • 13. Kania J, Kramer M. Collective impact. Stanford Soc Innov Rev. 2011;36–41.
        • 14. Wolff T. Ten places where collective impact gets it wrong. Glob J Community Psycology Pract. 2016;7(1):1–11.
        • 15. Grossi T, Thomas F, Held M. Making a collective impact: A School-to-Work Collaborative model. J Vocat Rehabil. 2019;51(3):395–407.
        • 16. Gutmanis I, Speziale J, Hillier LM, van Bussel E, Girard J, Simpson K. Health system redesign using Collective Impact: implementation of the Behavioural Supports Ontario initiative in Southwest Ontario. Neurodegener Dis Manag. 2017 Aug 1;7(4):261–70. pmid:28853640
        • 17. Demant L, Lawrence J. Back on Track: The challenges of implementing a small place-based Collective Impact initiative. Health Promot J Austr. 2018;29(3):360–2. pmid:30511492
        • 18. Ennis G, Tofa M. Collective Impact: A Review of the Peer-reviewed Research. Aust Soc Work. 2020 Jan 2;73(1):32–47.
        • 19. Meinen A, Hilgendorf A, Korth AL, Christens BD, Breuer C, Joyner H, et al. The Wisconsin Early Childhood Obesity Prevention Initiative: An Example of Statewide Collective Impact. WMJ. 2016;115(5):269–74. pmid:29095590
        • 20. Zakocs RC, Edwards EM. What Explains Community Coalition Effectiveness?: A Review of the Literature. Am J Prev Med. 2006 Apr;30(4):351–61. pmid:16530624
        • 21. Foster-Fishman PG, Berkowitz SL, Lounsbury DW, Jacobson S, Allen NA. Building Collaborative Capacity in Community Coalitions: A Review and Integrative Framework. Am J Community Psychol. 2001 Apr;29(2):241–61. pmid:11446279
        • 22. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009 Jul 21;6(7):e1000097. pmid:19621072
        • 23. Hsieh H-F, Shannon SE. Three Approaches to Qualitative Content Analysis. Qual Health Res. 2005 Nov;15(9):1277–88. pmid:16204405
        • 24. Lieber E, Weisner TS. Dedoose. Web-based Qual Mix Comput Softw. 2013;
        • 25. Butterfoss FD, Kegler MC. The community coalition action theory. In: DiClemente RJ, Crosby RA, Kegler MC, DiClemente RJ(Ed), Crosby RA(Ed), Kegler MC(Ed), editors. Emerging theories in health promotion practice and research (2nd ed). San Francisco, CA, US: Jossey-Bass; 2009. p. 237–76.
          • 26. Calancie L, Allen NE, Ng SW, Weiner BJ, Ward DS, Ware WB, et al. Evaluating Food Policy Councils Using Structural Equation Modeling. Am J Community Psychol. 2018 Mar;61(1–2):251–64. pmid:29251343
          • 27. Kegler MC, Swan DW. An initial attempt at operationalizing and testing the Community Coalition Action Theory. Heal Educ Behav Off Publ Soc Public Heal Educ. 2011 Jun;38(3):261–70. pmid:21393621
          • 28. MacQueen KM, McLellan E, Kay K, Milstein B. Codebook development for team-based qualitative analysis. Cult Anthropol Methods. 1998;10(2):31–6.
          • 29. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009 Dec 7;4(1):50. pmid:19664226
          • 30. Downey LM, Ireson CL, Slavova S, McKee G. Defining elements of success: a critical pathway of coalition development. Health Promot Pract. 2008 Apr;9(2):130–9. pmid:18340088
          • 31. Nowell B, Foster-Fishman P. Examining Multi-Sector Community Collaboratives as Vehicles for Building Organizational Capacity. Am J Community Psychol. 2011 Dec;48(3–4):193–207. pmid:21061057
          • 32. Smith BD, Mogro-Wilson C. Multi-level influences on the practice of inter-agency collaboration in child welfare and substance abuse treatment. Child Youth Serv Rev. 2007 May;29(5):545–56.
          • 33. Kumpfer KL, Turner C, Hopkins R, Librett J. Leadership and team effectiveness in community coalitions for the prevention of alcohol and other drug abuse. Health Educ Res. 1993 Sep 1;8(3):359–74.
          • 34. Giachello AL, Arrom JO, Davis M, Sayad J V, Ramirez D, Nandi C, et al. Reducing diabetes health disparities through community-based participatory action research: The Chicago Southeast diabetes community action coalition. Public Health Rep. 2003;118(4):309–23. pmid:12815078
          • 35. Jenkins C, Myers P, Heidari K, Kelechi TJ, Buckner-Brown J. Efforts to decrease diabetes-related amputations in African Americans by the Racial and Ethnic Approaches to Community Health Charleston and Georgetown Diabetes Coalition. Fam Community Health. 2011;34 Suppl 1:S63–78. pmid:21160332
          • 36. Tucker P, Liao Y, Giles WH, Liburd L. The REACH 2010 logic model: an illustration of expected performance. Prev Chronic Dis. 2006 Jan;3(1):A21. pmid:16356374
          • 37. Cooper DG, Christens BD. Justice System Reform for Health Equity: A Mixed Methods Examination of Collaborating for Equity and Justice Principles in a Grassroots Organizing Coalition. Heal Educ Behav Off Publ Soc Public Heal Educ. 2019;46(1_suppl):62S–70S.
          • 38. Amed S, Naylor P-J, Pinkney S, Shea S, Mâsse LC, Berg S, et al. Creating a collective impact on childhood obesity: Lessons from the SCOPE initiative. Can J Public Heal. 2015 Sep 1;106(6):e426–33. pmid:26680435
          • 39. Fisher EB, Strunk RC, Sussman LK, Arfken C, Sykes RK, Munro JM, et al. Acceptability and feasibility of a community approach to asthma management: the Neighborhood Asthma Coalition (NAC). J Asthma. 1996;33(6):367–83. pmid:8968292
          • 40. Horne L, Miller K, Silva S, Anderson L. Implementing the ACHIEVE model to prevent and reduce chronic disease in rural Klickitat County, Washington. Prev Chronic Dis. 2013 Apr 18;10:E56. pmid:23597394
          • 41. Johnson JC, Hayden UT, Thomas N, Groce-Martin J, Henry T, Guerra T, et al. Building community participatory research coalitions from the ground up: the Philadelphia area research community coalition. Prog Community Health Partnersh. 2009;3(1):61–72. pmid:20208302
          • 42. Kubik MY, Lytle LA, Story M. A practical, theory-based approach to establishing school nutrition advisory councils. J Am Diet Assoc. 2001;101(2):223–8. pmid:11271696
          • 43. Shapiro VB, Oesterle S, Abbott RD, Arthur MW, Hawkins JD. Measuring Dimensions of Coalition Functioning for Effective and Participatory Community Practice. Soc Work Res. 2013 Dec 1;37(4):349–59. pmid:24778545
          • 44. Thompson LS, Story M, Butler G. A Collaboration Model for Enhanced Community Participation. Policy, Polit Nurs Pract. 2002 Aug 13;3(3):264–73.
          • 45. Kristjansson AL, Mann MJ, Sigfusson J, Thorisdottir IE, Allegrante JP, Sigfusdottir ID. Implementing the Icelandic Model for Preventing Adolescent Substance Use. Health Promot Pract. 2020;21(1):70–9. pmid:31162979
          • 46. Bertam RM. Establishing a basis for multi-system collaboration: systemic team development. J Sociol Soc Welf. 2008;35(4):9–27.
          • 47. Barnes P, Erwin P, Moonesinghe R, Brooks A, Carlton EL, Behringer B. Functional Characteristics of Health Coalitions in Local Public Health Systems: Exploring the Function of County Health Councils in Tennessee. J Public Health Manag Pract. 2017;23(4):404–9. pmid:28079644
          • 48. Chutuape KS, Willard N, Walker BC, Boyer CB, Ellen J, Adolescent Medicine Trials Network for HIVAIDS Interventions. A Tailored Approach to Launch Community Coalitions Focused on Achieving Structural Changes: Lessons Learned From a HIV Prevention Mobilization Study. J Public Health Manag Pract. 2015;21(6):546–55. pmid:26785397
          • 49. Courie AF, Rivera MS, Pompey A. Managing public health in the Army through a standard community health promotion council model. US Army Med Dep J. 2014;82–90. pmid:25074607
          • 50. Felland LE, Ginsburg PB, Kishbauch GM. Improving health care access for low-income people: lessons from ascension health’s community collaboratives. Health Aff (Millwood). 2011 Jul;30(7):1290–8. pmid:21734203
          • 51. Hupert N, Biala K, Holland T, Baehr A, Hasan A, Harvey M. Optimizing Health Care Coalitions: Conceptual Frameworks and a Research Agenda. Disaster Med Public Health Prep. 2015;9(6):717–23. pmid:26545194
          • 52. Lara M, Cabana MD, Houle CR, Krieger JW, Lachance LL, Meurer JR, et al. Improving quality of care and promoting health care system change: The role of community-based coalitions. Health Promot Pract. 2006 Apr;7(2 Suppl):87S–95S. pmid:16636159
          • 53. Nicola RM. Turning Point’s National Excellence Collaboratives: assessing a new model for policy and system capacity development. J Public Heal Manag Pract. 2005;11(2):101–8. pmid:15711439
          • 54. Packard T, Patti R, Daly D, Tucker-Tatlow J. Implementing Services Integration and Interagency Collaboration: Experiences in Seven Counties. Adm Soc Work. 2013 Sep;37(4):356–71.
          • 55. Rosenthal MP, Butterfoss FD, Doctor LJ, Gilmore LA, Krieger JW, Meurer JR, et al. The coalition process at work: Building care coordination models to control chronic disease. Health Promot Pract. 2006;7(2 Suppl):117S–126S. pmid:16636162
          • 56. Salem E, Hooberman J, Ramirez D. MAPP in Chicago: a model for public health systems development and community building. J Public Health Manag Pract. 2005;11(5):393–400. pmid:16103812
          • 57. Weiner BJ, Alexander JA, Shortell SM. Management and governance processes in community health coalitions: a procedural justice perspective. Health Educ Behav. 2002;29(6):737–54. pmid:12462195
          • 58. Fagan M, Wong C, Morrison M, Lewis-O’Connor A. Patients, Persistence, and Partnership: Creating and Sustaining Patient and Family Advisory Councils in a Hospital Setting. J Clin Outcomes Manag. 2016;23(5).
          • 59. Kramer JS, Philliber S, Brindis CD, Kamin SL, Chadwick AE, Revels ML, et al. Coalition models: Lessons learned from the CDC’s Community Coalition Partnership Programs for the Prevention of Teen Pregnancy. J Adolesc Heal. 2005 Sep;37(3):S20–30.
          • 60. Powell KG, Peterson NA. Pathways to Effectiveness in Substance Abuse Prevention: Empowering Organizational Characteristics of Community-Based Coalitions. Hum Serv Organ Manag Leadersh Gov. 2014 Oct 20;38(5):471–86.
          • 61. Powell KG, Gold SL, Peterson NA, Borys S, Hallcom D. Empowerment in Coalitions Targeting Underage Drinking: Differential Effects of Organizational Characteristics for Volunteers and Staff. J Soc Work Pract Addict. 2017 Apr 3;17(1–2):75–94.
          • 62. Baranowski T. Agency coalitions for targeted service delivery: foiled designs, failed development, but final delight. Int Q Community Health Educ. 1982 Jan 1;3(1):67–88. pmid:20841100
          • 63. Behringer B, Lofton S, Knight ML. Models for local implementation of comprehensive cancer control: meeting local cancer control needs through community collaboration. Cancer Causes Control. 2010 Dec 12;21(12):1995–2004. pmid:20938731
          • 64. Brady C, Johnson F. Integrating the life course into MCH service delivery: from theory to practice. Matern Child Health J. 2014 Feb 3;18(2):380–8. pmid:23456413
          • 65. Braithwaite RL, Murphy F, Lythcott N, Blumenthal DS. Community organization and development for health promotion within an urban black community: a conceptual model. Health Educ. 1989 Dec;20(5):56–60. pmid:2516062
          • 66. Butterfoss FD, Morrow AL, Rosenthal J, Dini E, Crews RC, Webster JD, et al. CINCH: an urban coalition for empowerment and action. Consortium for the Immunization of Norfolk’s Children. Health Educ Behav. 1998 Apr 30;25(2):212–25. pmid:9548061
          • 67. Butterworth J, Christensen J, Flippo K. Partnerships in Employment: Building strong coalitions to facilitate systems change for youth and young adults. J Vocat Rehabil. 2017;47(3):265–76.
          • 68. Carman AL, McGladrey ML. Cross Jurisdictional Boundaries to Build a Health Coalition: A Kentucky Case Study. Front public Heal. 2018;6:189. pmid:30042938
          • 69. Choy LB, Maddock JE, Brody B, Richards KL, Braun KL. Examining the role of a community coalition in facilitating policy and environmental changes to promote physical activity: the case of Get Fit Kaua’i. Transl Behav Med. 2016 Dec 23;6(4):638–47. pmid:27848212
          • 70. Clark NM, Doctor LJ, Friedman AR, Lachance LL, Houle CR, Geng X, et al. Community coalitions to control chronic disease: Allies against asthma as a model and case study. Health Promot Pract. 2006;7(2 Suppl):14S–22S. pmid:16636152
          • 71. Cramer ME, Atwood JR, Stoner JA. A conceptual model for understanding effective coalitions involved in health promotion programming. Public Health Nurs. 2006 Jan;23(1):67–73. pmid:16460423
          • 72. Davidson J, Wiens S, Anderson K. Creating a provincial family council to engage youth and families in child & youth mental health systems. J Can Acad Child Adolesc Psychiatry. 2010 Aug;19(3):169–75. pmid:20842271
          • 73. Diehl D, Gray C, O’Connor G. The school community council: creating an environment for student success. New Dir Youth Dev. 2005;(107):65–72, table of contents. pmid:16315518
          • 74. Dunlop J, Angell G. Inside-outside: Boundary-spanning challenges in building rural health coalitions. Prof Dev. 2001;4(1):40–8.
          • 75. Edwards L, Gibson R, Carson SR, Sampalli T. Development and evaluation of a "working together" framework and a tool kit to enhance inter-organizational relationships in healthcare. Healthc Q. 2013;16(2):36–42.
          • 76. Ehrlich C, Kendall E. Integrating collaborative place-based health promotion coalitions into existing health system structures: the experience from one Australian health coalition. Int J Integr Care. 2015 Dec 15;15(4):e047. pmid:27118964
          • 77. Feinberg ME, Greenberg MT, Osgood DW. Readiness, functioning, and perceived effectiveness in community prevention coalitions: a study of communities that care. Am J Community Psychol. 2004 Jun;33(3–4):163–76. pmid:15212176
          • 78. Fleury M-J, Grenier G, Vallée C, Hurtubise R, Lévesque P-A. The role of advocacy coalitions in a project implementation process: the example of the planning phase of the At Home/Chez Soi project dealing with homelessness in Montreal. Eval Program Plann. 2014 Aug;45:42–9. pmid:24709631
          • 79. Flewelling RL, Hanley SM. Assessing Community Coalition Capacity and its Association with Underage Drinking Prevention Effectiveness in the Context of the SPF SIG. Prev Sci. 2016 Oct 9;17(7):830–40. pmid:27392783
          • 80. Flood J, Minkler M, Hennessey Lavery S, Estrada J, Falbe J. The Collective Impact Model and Its Potential for Health Promotion: Overview and Case Study of a Healthy Retail Initiative in San Francisco. Health Educ Behav. 2015 Oct 25;42(5):654–68. pmid:25810470
          • 81. Galvez M, Collins G, Amler RW, Dozor A, Kaplan-Liss E, Forman J, et al. Building New York State Centers of Excellence in Children’s Environmental Health: A Replicable Model in a Time of Uncertainty. Am J Public Health. 2019;109(1):108–12. pmid:30496005
          • 82. Gomez BJ, Greenberg MT, Feinberg ME. Sustainability of community coalitions: an evaluation of communities that care. Prev Sci. 2005;6(3):199–202. pmid:16079961
          • 83. Green A, DiGiacomo M, Luckett T, Abbott P, Davidson PM, Delaney J, et al. Cross-sector collaborations in Aboriginal and Torres Strait Islander childhood disability: A systematic integrative review and theory-based synthesis. Int J Equity Health. 2014;13(1). pmid:25519053
          • 84. Hanson RF, Schoenwald S, Saunders BE, Chapman J, Palinkas LA, Moreland AD, et al. Testing the Community-Based Learning Collaborative (CBLC) implementation model: a study protocol. Int J Ment Health Syst. 2016 Dec 18;10(1):52. pmid:27547240
          • 85. Hardy LJ, Wertheim P, Bohan K, Quezada JC, Henley E. A model for evaluating the activities of a coalition-based policy action group: the case of Hermosa Vida. Health Promot Pract. 2013 Jul 6;14(4):514–23. pmid:23132841
          • 86. Huberty JL, Balluff M, O’Dell M, Peterson K. From good ideas to actions: a model-driven community collaborative to prevent childhood obesity. Prev Med (Baltim). 2010 Jan;50 Suppl 1:S36–43. pmid:19769997
          • 87. Kegler MC, Williams CW, Cassell CM, Santelli J, Kegler SR, Montgomery SB, et al. Mobilizing communities for teen pregnancy prevention: associations between coalition characteristics and perceived accomplishments. J Adolesc Health. 2005 Sep;37(3 Suppl):S31–41. pmid:16115569
          • 88. Kegler MC, Swan DW. Advancing coalition theory: the effect of coalition factors on community capacity mediated by member engagement. Health Educ Res. 2012 Aug;27(4):572–84. pmid:21911845
          • 89. Ken-Opurum J, Darbishire L, Miller DK, Savaiano D. Assessing Rural Health Coalitions Using the Public Health Logic Model: A Systematic Review. Am J Prev Med. 2020;58(6):864–78. pmid:32444004
          • 90. Koelen MA, Vaandrager L, Wagemakers A. The Healthy ALLiances (HALL) framework: prerequisites for success. Fam Pract. 2012 Apr 1;29 Suppl 1(suppl 1):i132–8.
          • 91. Korn AR, Hennessy E, Tovar A, Finn C, Hammond RA, Economos CD. Engaging Coalitions in Community-Based Childhood Obesity Prevention Interventions: A Mixed Methods Assessment. Child Obes. 2018 Dec 6;14(8):537–52. pmid:30188181
          • 92. Kreger M, Sargent K, Arons A, Standish M, Brindis CD. Creating an environmental justice framework for policy change in childhood asthma: a grassroots to treetops approach. Am J Public Health. 2011 Dec;101 Suppl 1(S1):S208–16. pmid:21836108
          • 93. Laraia BA, Dodds J, Eng E. A framework for assessing the effectiveness of antihunger advocacy organizations. Heal Educ Behav. 2003 Dec 30;30(6):756–70. pmid:14655868
          • 94. Lewis LB, Galloway-Gilliam L, Flynn G, Nomachi J, Keener LC, Sloane DC. Transforming the urban food desert from the grassroots up: a model for community change. Fam Community Health. 2011;34 Suppl 1:S92–101.
          • 95. Loh LC, Valdman O, Dacso MM. Coalicion de Salud Comunitaria (COSACO): using a Healthy Community Partnership framework to integrate short-term global health experiences into broader community development. Global Health. 2016 Dec 2;12(1):15. pmid:27138490
          • 96. Marchand L, Fowler KJ, Kokanovic O. Building successful coalitions for promoting advance care planning. Am J Hosp Palliat Med. 2006;23(2):119–26. pmid:16572750
          • 97. McClure LF, DePiano LG. School advisory council participation and effectiveness. Am J Community Psychol. 1983 Dec;11(6):687–704. pmid:6666754
          • 98. McFall SL, Norton BL, McLeroy KR. A Qualitative Evaluation of Rural Community Coalitions. Int Q Community Health Educ. 2004 Jan 1;23(4):311–26.
          • 99. Metzger ME, Alexander JA, Weiner BJ. The effects of leadership and governance processes on member participation in community health coalitions. Heal Educ Behav. 2005 Aug;32(4):455–73. pmid:16009744
          • 100. Mulroy EA. Building a neighborhood network: interorganizational collaboration to prevent child abuse and neglect. Soc Work. 1997 May;42(3):255–64. pmid:9153094
          • 101. Norris T, Pittman M. The healthy communities movement and the coalition for healthier cities and communities. Public Health Rep. 2000;115(2–3):118–24. pmid:10968742
          • 102. O’Neill M, Lemieux V, Groleau G, Fortin J-P, Lamarche PA. Coalition theory as a framework for understanding and implementing intersectoral health-related interventions. Health Promot Int. 1997 Jan 1;12(1):79–87.
          • 103. Palafox NA, Reichhardt M, Taitano JR, Nitta M, Garstang H, Riklon S, et al. A Socio-Ecological Framework for Cancer Control in the Pacific: A Community Case Study of the US Affiliated Pacific Island Jurisdictions 1997–2017. Front public Heal. 2018;6:313. pmid:30483488
          • 104. Paine-Andrews A, Fawcett SB, Richter KP, Berkly JY, Williams EL, Lopez CM. Community coalitions to prevent adolescent substance abuse: The case of the “project freedom” replication initiative. J Prev Interv Community. 1996;14(1–2):81–99.
          • 105. Pierre J, Letamendi C, Sleiter L, Bailey Z, Dannefer R, Shiman L, et al. Building a Culture of Health at the Neighborhood Level Through Governance Councils. J Community Health. 2020; pmid:32166523
          • 106. Polivka BJ. A conceptual model for community interagency collaboration. Image J Nurs Sch. 1995;27(2):110–5. pmid:7622161
          • 107. Revell CC, Meriwether MB. Applying the performance partnership model to smoking cessation: lessons learned by the smoking cessation leadership center. Health Promot Pract. 2011 Nov 21;12(6 Suppl 2):125S–9S. pmid:22068575
          • 108. Sánchez V, Andrews ML, Carrillo C, Hale R. New Mexico Community Health Councils: Documenting Contributions to Systems Changes. Prog Community Heal Partnerships. 2015;9(4):471–81. pmid:26639373
          • 109. Sharma AE, Willard-Grace R, Willis A, Zieve O, Dubé K, Parker C, et al. "How Can We Talk about Patient-centered Care without Patients at the Table?" Lessons Learned from Patient Advisory Councils. J Am Board Fam Med. 2016 Nov 12;29(6):775–84.
          • 110. Shenson D, Benson W, Harris AC. Expanding the delivery of clinical preventive services through community collaboration: the SPARC model. Prev Chronic Dis. 2008 Jan;5(1):A20. pmid:18082009
          • 111. Silverman B, Champney J, Steber S-A, Zubritsky C. Collaborating for consensus: Considerations for convening Coalition stakeholders to promote a gender-based approach to addressing the health needs of sex workers. Eval Program Plann. 2015 Aug;51:17–26. pmid:25559949
          • 112. Stevens G, Rice K, MR C. Children’s health initiatives in California: the experiences of local coalitions pursuing universal coverage for children. Am J Public Health. 2007 Apr;97(4):738–43. pmid:17329648
          • 113. Teaster PB, Wangmo T. Kentucky’s local elder abuse coordinating councils: A model for other states. J Elder Abus Negl. 2010;22(1–2):191–206.
          • 114. Towe VL, Leviton L, Chandra A, Sloan JC, Tait M, Orleans T. Cross-Sector Collaborations And Partnerships: Essential Ingredients To Help Shape Health And Well-Being. Health Aff (Millwood). 2016 Nov 1;35(11):1964–9. pmid:27834234
          • 115. Travis R, Leech TGJ. The Community Action Framework in Practice: An Illustration Based on the Ready by 21 Coalition of Austin/Travis County. J Community Pract. 2011 Jul;19(3):252–73.
          • 116. hsien Tseng S, Liu K, Wang W-L. Moving toward being analytical: A framework to evaluate the impact of influential factors on interagency collaboration. Child Youth Serv Rev. 2011 Jun 1;33(6):798–803.
          • 117. Valentijn PP, Vrijhoef HJM, Ruwaard D, de Bont A, Arends RY, Bruijnzeels MA. Exploring the success of an integrated primary care partnership: a longitudinal study of collaboration processes. BMC Health Serv Res. 2015 Jan 22;15(1):32. pmid:25609186
          • 118. Walter UM, Petr CG. A Template for Family-Centered Interagency Collaboration. Fam Soc J Contemp Soc Serv. 2000 Oct 22;81(5):494–503.
          • 119. Wandersman A, Valois R, Ochs L, de la Cruz DS, Adkins E, Goodman RM. Toward a social ecology of community coalitions. Am J Health Promot. 1996 Mar 26;10(4):299–307. pmid:10172711
          • 120. Watson-Thompson J, Fawcett SB, Schultz JA. A framework for community mobilization to promote healthy youth development. Am J Prev Med. 2008 Mar;34(3 Suppl):S72–81. pmid:18267205
          • 121. Wunrow JJ, Einspruch EL. Promoting youth/adult partnerships: The seven circles coalition in Sitka, Alaska. J Prim Prev. 2001;22(2):169–85.
          • 122. Jagosh J, Bush PL, Salsberg J, Macaulay AC, Greenhalgh T, Wong G, et al. A realist evaluation of community-based participatory research: partnership synergy, trust building and related ripple effects. BMC Public Health. 2015 Dec 30;15(1):725. pmid:26223523
          • 123. Butterfoss FD. Process Evaluation for Community Participation. Annu Rev Public Health. 2006 Apr 13;27(1):323–40. pmid:16533120
          • 124. Butterfoss FD, Goodman RM, Wandersman A. Community Coalitions for Prevention and Health Promotion: Factors Predicting Satisfaction, Participation, and Planning. Health Educ Q. 1996 Feb 4;23(1):65–79. pmid:8822402
          • 125. Minkler M, Wallerstein N. Community-based participatory research for health: From process to outcomes. Jossey-Bass; 2013.
            • 126. Inzeo PT, Christens BD, Hilgendorf A, Sambo A. Advancing Coalition Health Equity Capacity Using a Three-Dimensional Framework. Heal equity. 2019;3(1):169–76. pmid:31289776
            • 127. Lachance L, Benedict MB, Doctor LJ, Gilmore LA, Kelly C, Krieger J, et al. Asthma coalition effects on vulnerable sub groups of children: the most frequent users of health care and the youngest. J Asthma. 2014 Jun 7;51(5):474–9. pmid:24552195
            • 128. Clark NM, Lachance LL, Benedict MB, Doctor LJ, Gilmore L, Kelly CS, et al. Improvements in health care use associated with community coalitions: long-term results of the allies against asthma initiative. Am J Public Health. 2013 Jun;103(6):1124–7. pmid:23597384
            • 129. Wagenaar AC, Erickson DJ, Harwood EM, O’Malley PM. Effects of State Coalitions to Reduce Underage Drinking. A National Evaluation. Am J Prev Med. 2006;31(4):307–15. pmid:16979455
            • 130. Anderson LM, Adeney KL, Shinn C, Safranek S, Buckner-Brown J, Krause LK. Community coalition-driven interventions to reduce health disparities among racial and ethnic minority populations. Cochrane Database Syst Rev. 2015 Jun 15;(6):CD009905. pmid:26075988
            • 131. Vennix JAM. Group model building: Facilitating team learning using system dynamics. John Wiley & Sons; 1996. 297 p.
              • 132. Nelson D, Simenz C, O’Connor S. Using Group Model Building to Understand Factors That Influence Childhood Obesity in an Urban Environment. J Public Heal Manag Pract. 2015;21:S74–8.
              • 133. Loyo H, Batcher C, Wile K, Huang P. From model to action: using a system dynamics model of chronic disease risks to align community action. Heal Promot. 2013; pmid:22491443