Key considerations for logic model development in research partnerships: A Canadian case study

https://doi.org/10.1016/j.evalprogplan.2007.01.002Get rights and content

Abstract

Community-academic partnership research is a fairly new genre of community-based participatory research. It has arisen in part, from recognition of the potential role of alliances in the development and translation of applied knowledge and the elimination of health disparities. This paper reports on the learning process of academic and community members who worked together in developing a logic model for a research program focusing on partnerships with vulnerable populations. The Partners in Community Health Research is a 6-year training program that seeks to combine research, training, and practice through the work of its “learning clusters”. As these types of partnerships proliferate, the articulation and exploration of clear models will assist in their implementation. The authors, coming from both academia and community agencies, present a logic model meant to facilitate program management. Key considerations in the model's development are discussed in the context of an ongoing research partnership; namely, the complexity of the research partnership, power and accountability, alignment with health promotion policy, and the iterative nature of program design. Recommendations challenge academics, policy-makers, service providers, and community members to reflect on the elements needed to support and manage research partnerships and the tools necessary to ensure continued collaboration.

Introduction

Health research in Canada is experiencing a metamorphosis in response to the paradigm shift toward Population Health, the creation of broader training programs within the Canadian Institutes of Health Research (CIHR), and the voices of a sometimes disenfranchised public. Community-based participatory research (CBPR) is meant to foster research that is collaborative, participatory, empowering, systematic, and transformative (Hills & Mullett, 2000), alternative to traditional methods of generating knowledge. In the past decade, CBPR projects have proliferated as an approach to research that seeks to involve community members, organizational representatives, and researchers in all aspects of the research process while sharing expertise, responsibilities and ownership (Israel, Schultz, Parker, & Becker, 2000). As such it invokes in its actors intersubjective and self-reflexive processes.

Community-academic research partnership is a fairly new genre of CBPR. It has arisen from recognition of the potential role of alliances in the development of and the need for translation of applied knowledge and the elimination of health disparities. Research collaborations and the use of quality improvement processes guided by Plan-Study-Do-Act cycles (Speroff & O’Connor, 2004) are most common in the health sector and are believed to lead to more effective clinical programs. Frankish and colleagues provide a summary of the underlying theoretical and empirical reasons for collaboration between the health sector and academe or the public (Frankish, Kwan, Larsen, Ratner, Wharf-Higgins, 2002; Frankish, Larsen, Ratner, Wharf-Higgins, & Kwan, 2002). It remains unclear as to how, and if such partnerships can also lead to enhanced community health and development (Currie et al., 2005).

In parallel, there is an increased call for research that is relevant to decision-making at all levels: from individual health choices to national and international health systems and policy. Partnerships between academic institutions and organizations such as those that deliver healthcare and social services represent one strategy that offers promise in terms of bridging the gap between knowledge and practice. As a result of this perceived benefit, agencies in North America such as the Canadian Institute of Health Research (2005) the Michael Smith Foundation for Health Research (MSFHR) (2006) and the Centre for Disease Control (1994) have earmarked funds for collaborative health research initiatives with industry, community organizations, clients, and researchers.

In recent years, as research partnerships establish themselves, researchers have begun to identify the strengths and challenges of particular research partnerships (Bazzoli et al., 2003; Elsinger & Senturia, 2001; Israel, Schulz, Parker, & Becker, 1998). They have also begun to uncover some of the elements useful to their evaluation (Currie et al., 2005; Winnipeg Inner City Alliance, 2005). However, the structure of these collaborations is highly variable and, due to their infancy and uniqueness, few tools exist to guide the development, implementation, and evaluation of such projects.

Logic models have been espoused as essential for delivering theoretically sound, evidence-based programs (Moyer Verhovsek, & Wilson, 1997). As such, they may be instrumental in conceptualizing, planning and implementing successful research-community partnerships. This paper highlights a partnership program that focuses on populations experiencing health disparities. It describes the “Vulnerable Populations Cluster”—a “learning cluster” of the Partners in Community Health Training Program. During cluster development and evolution, the perceived need and potential benefit of a more detailed framework for action was identified. We present the resulting logic model developed to facilitate future program management. We then discuss key considerations that were identified by cluster members during the development of the model, and lessons learned by these members.

Section snippets

Program description

The Partners in Community Health Research (PCHR) training program is a collaborative 6-year training initiative based out of university and health region research institutes in British Columbia, Canada and funded by the CIHR and MSFHR. The program is based on the following fundamental principles: co-learning, power sharing in all stages of research design and sharing resources. Its objectives are multi-sectoral and include research training, capacity-building, fostering evidence-based

Understanding logic models

Logic models have proliferated over the past three decades through their use in the planning and evaluation of various types of programs (Dykeman, MacIntosh, Seaman, & Davidson, 2003; Kaplan & Garrett, 2005; Levin, Weiner, Saravay, & Deakins, 2004; Mulroy & Lauber, 2004; Stinson & Wilkinson, 2004). According to Millar, Simeone, and Carnevale (2001), logic models “are useful to any person trying to plan, manage, account for, audit, evaluate, or explain the connections between what a program

Methods

Many variations of logic models exist and there are various approaches to developing a logic model described in the literature (Dwyer & Makin, 1997; McLaughlin & Jordan, 1999). The VP clusters’ model is similar to that promoted by the W.K. Kellogg Foundation (2004) and was based on the original logic model proposed for the PCHR program in its entirety (Best & Frankish, 2002). It was developed using the knowledge and experiences of cluster members and reflecting the program's community-based

Key considerations

Many researchers have attempted to characterize the elements of community-based, partnership research (Alexander et al., 2003; Granner & Sharpe, 2004; Green et al., 1995; Israel et al., 1998; Potvin, Cargo, McComber, Delormier, & Macaulay, 2003). Evidence indicates that CBPR may confer a number of benefits to community-academic partnerships including an emergence of new social relationships and trust as well as social efficacy in preventing, mitigating and remedying problems (Sclove, Scammell,

Lessons-learned and recommendations

A number of recommendations came out of the process of logic model development as part of the VP cluster:

  • Logic models can contribute to comprehensive program planning when academic-community partnerships include not only good faith but also clear missions and a sense of common purpose.

  • Funding agencies need to be open to refinement and revisions in program models and integrate flexibility into the process of accountability.

  • Agencies that support researchers should revise their notions of academic

Conclusions

Partnership implies a complementarity of roles and contributions (Green & Kreuter, 2005). In recent years, community-based research partnerships have proliferated with the intent of providing research, services, and programs of increased relevance and utility to communities. The components of research partnerships often exist at the intersection of several conceptual enigmas such as participatory community-based research, the notion of “vulnerability”, and the construct of partnership. Logic

Acknowledgements

We would like to acknowledge that S. Fielden, M. Rusch, are supported by studentships from the Michael Smith Foundation for Health Research (MSFHR). S. Fielden and B. Evoy also hold doctoral awards with the Canadian Institute of Health Research. Dr. Jim Frankish is a Senior Scholar of MSFHR. The Partners in Community Health Research Training Program has joint operating grant funding from the MSFHR and CIHR. We would like to especially acknowledge the contributions to the members of the VP

References (55)

  • G. Bazzoli et al.

    Collaborative initiatives: Where the rubber meets the road in community partnerships

    Medical Care Research and Review

    (2003)
  • Best, A., & Frankish, J. (2002). Partners in Community Health Research. Canadian Institutes of Health Research,...
  • P. Braveman et al.

    Defining equity in health

    Journal of Epidemiology and Community Health

    (2003)
  • Canadian Institute of Health Research. (2005). Retrieved December 11, 2005, from...
  • Centre for Disease Control. (1994). Urban Centres for Applied Research in Urban Health, No...
  • L. Decker et al.

    Home, school & community partnerships

    (2003)
  • J.S. Dryzek

    Deliberative democracy and beyond: Liberals, critics and contestations

    (2000)
  • J. Dwyer et al.

    Using a program logic model that focuses on performance measurement to develop a program

    Canadian Journal of Public Health

    (1997)
  • A. Elsinger et al.

    Doing community-drive research: A description of Seattle partners for healthy communities

    Journal of Urban Health: Bulletin of the New York Academy of Medicine

    (2001)
  • Federal, Provincial and Territorial (FTP) Advisory Committee on Population Health. (1999). Towards a healthy future....
  • J. Flaskerud et al.

    Health disparities among vulnerable populations

    Nursing Research

    (2002)
  • J. Flaskerud et al.

    Conceptualizing vulnerable populations health-related research

    Nursing Research

    (1998)
  • Frank, F., & Smith, A. (2000). The Partnership Handbook. Minister of Public Works and Government Services,...
  • J. Frankish et al.

    Challenges of community participation in health-system decision making

    Social Science & Medicine

    (2002)
  • J. Frankish et al.

    Social and political factors influencing the functioning of regional health boards in British Columbia (Canada)

    Health Policy

    (2002)
  • S. Funnell

    Developing and using a program theory matrix for program evaluation and performance monitoring

    Program Theory in Evaluation: Challenges and Opportunities

    (2000)
  • R. Goodman et al.

    Identification and defining the dimensions of community capacity to provide a basis for measurement

    Health Education and Behavior

    (1998)
  • Cited by (47)

    • Improving the reporting of sport imagery interventions with TIDieR

      2022, Asian Journal of Sport and Exercise Psychology
      Citation Excerpt :

      In this paper, we developed a logic model for PACING that aligns the target population, assumptions, inputs, activities, implementation evaluation, output, and outcomes (Kaplan & Garrett, 2005). A logic model informs what resources are needed to realize the intervention's intended outcomes and guides the monitoring and evaluating of the intervention's effectiveness and accountability by understanding its underlying “logic” (Kaplan & Garrett, 2005; Fielden et al., 2007; Cooksy et al., 2001). Through having a logic model, researchers are encouraged to go beyond simply examining cause and effect (e.g., did it work?)

    • The My Strengths Training for Life™ program: Rationale, logic model, and description of a strengths-based intervention for young people experiencing homelessness

      2022, Evaluation and Program Planning
      Citation Excerpt :

      The logic model describes and graphically represents how the program is intended to work by aligning its target population, assumptions, inputs, activities, output, and outcomes (Kaplan & Garrett, 2005). It is intended to serve as a guide for monitoring and evaluation of programs to ensure effectiveness and accountability by helping people to understand its underlying “logic” (Fielden, Rusch, Masinda, Sands, Frankish, & Evoy, 2007; Kaplan & Garrett, 2005). The target population is young people experiencing homelessness aged 16–24 years old and living in long-term supported accommodation (e.g., 6–12 months), NEET and eligible to become EET (as opposed to NEET young people who are unable to participate in work due to disability or health condition) or at risk of falling out of EET, or identified by frontline staff as someone who would benefit from a group-based program to further develop their mental skills.

    • Using a logic model to develop an intervention for improving miscarriage care in the emergency department

      2021, Evaluation and Program Planning
      Citation Excerpt :

      In addition, this approach appeared to be beneficial for each participant, in terms of enhanced inclusion, leadership, partnership, co-learning, and trust (Stack & McDonald, 2018). Combined with a reflective and self-reflexive process that was actively encouraged in planning groups, it appeared to positively influence individual empowerment (Fielden et al., 2007; Gustafsson & Fagerberg, 2004; Stack & McDonald, 2018). In evaluation forms completed after each meeting, parents revealed that they had gained awareness of their experience, felt less frustration about services received at the ED, and felt their contributions could help other parents facing similar situations and improve miscarriage care practices.

    • Systemic evaluation of community environmental management programmes

      2021, European Journal of Operational Research
      Citation Excerpt :

      Bellamy et al. (2001, p.408) note that “natural resource management initiatives need to be evaluated as a system that links the objectives and instrumental rationale of the policy or program to actual performance on the ground”. Unpacking the programme logic, or making it explicit, provides the basis for evaluation because it describes the relationship between context, programme inputs, activities, outputs and intended outcomes (Cox, 2000; Fielden et al., 2007). Towards the end of the boundary critique, as we were finalizing the remit of the project in discussion with key stakeholders and Māori, the research team met with the RCS manager to discuss how a systems approach might strengthen the resource care logic.

    • THE ROLE OF COMMUNITYBASED RESEARCH IN ACHIEVING COMMUNITY IMPACT

      2023, Community-Based Research: Teaching for Community Impact
    View all citing articles on Scopus
    View full text