Key considerations for logic model development in research partnerships: A Canadian case study
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:
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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.
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Funding agencies need to be open to refinement and revisions in program models and integrate flexibility into the process of accountability.
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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)
- et al.
Conference report: Community-based health promotion—State of the art and recommendations for the future
American Journal of Preventive Medicine
(1997) - et al.
A model of impacts of research partnerships in heath and social services
Evaluation and Program Planning
(2005) - et al.
Development of a program logic model to measure the processes and outcomes of a nurse-managed community health clinic
Journal of Professional Nursing
(2003) - et al.
The use of logic models by community-base initiatives
Evaluation and Program Planning
(2005) - et al.
Logic models: A tool for telling your program's performance story
Evaluation and Program Planning
(1999) - et al.
Logic models: A systems tool for performance management
Evaluation and Program Planning
(2001) - et al.
Implementing participatory intervention and research communities: Lessons from the Kahnawake Schools Diabetes Prevention Project in Canada
Social Science & Medicine
(2003) Income inequality, poverty, and population health: Evidence from recent data for the United States
Social Science & Medicine
(2005)- et al.
Sustainability of collaborative capacity in community health partnerships
Medical Care Research and Review
(2003) - et al.
Reflexive methodology: New vistas for qualitative research
(2000)
Collaborative initiatives: Where the rubber meets the road in community partnerships
Medical Care Research and Review
Defining equity in health
Journal of Epidemiology and Community Health
Home, school & community partnerships
Deliberative democracy and beyond: Liberals, critics and contestations
Using a program logic model that focuses on performance measurement to develop a program
Canadian Journal of Public Health
Doing community-drive research: A description of Seattle partners for healthy communities
Journal of Urban Health: Bulletin of the New York Academy of Medicine
Health disparities among vulnerable populations
Nursing Research
Conceptualizing vulnerable populations health-related research
Nursing Research
Challenges of community participation in health-system decision making
Social Science & Medicine
Social and political factors influencing the functioning of regional health boards in British Columbia (Canada)
Health Policy
Developing and using a program theory matrix for program evaluation and performance monitoring
Program Theory in Evaluation: Challenges and Opportunities
Identification and defining the dimensions of community capacity to provide a basis for measurement
Health Education and Behavior
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