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Title: CBPR Variable Matrix: Research for improved health in academic/community partnerships


Abstract: Community-based participatory research (CBPR) is a collaborative approach that equitably involves partners in the research process and recognizes the unique strengths that each partner brings. CBPR begins with a research topic important to a community, combining knowledge construction, education, and action for social change towards improving community health. To advance community-engaged research, investigators from the Universities of New Mexico and Washington and the National Congress of American Indians Policy Research Center, in collaboration with a National Advisory Board of academic and community experts,* created a variable matrix to support a conceptual logic model of CBPR processes and outcomes. Details on the creation of this model are found in Wallerstein et al. 2008 [1].1 The variable matrix provides measurements to support the four dimensions of CBPR characteristics and relationships within each domain of the interactive CBPR model. First, contextual factors shape the nature of the research and the conditions under which partnerships can develop and be sustained. Next, group dynamics, consisting of three sub-dimensions, structural factors (i.e., collaborative agreements), individual partner characteristics, and relational dynamics (i.e., group decision-making); interact with contextual factors to co-produce the intervention and its research design. Finally, CBPR system changes and health outcomes result directly from the research. In sum, we provide items and scales from over 46 instruments representing 60% of the 40 domains in the CBPR logic model.


Type of Product: Website


Year Created: 2010


Date Published: 12/19/2011

Author Information

Corresponding Author
Cynthia Pearson
Indigenous Wellness Research Institute -University of Washington
Box 354900
Seattle, WA 98105-6299
United States
p: (206) 330-1997
pearsonc@uw.edu

Authors (listed in order of authorship):
Cynthia Pearson
Indigenous Wellness Research Institute -University

Bonnie Duran
Indigenous Wellness Research Institute -University

Julie Lucero
University of New Mexico Center for Participatory

Jennifer Sandoval
University of Central Florida

John Oetzel
University of Waikato

Greg Tafoya
University of New Mexico Center for Participatory

Lorenda Belone
University of New Mexico Center for Participatory

Magdalena Avila
University of New Mexico Center for Participatory

Diane Martin
University of Washington

Nina Wallerstein
University of New Mexico Center for Participatory

Sarah Hicks
National Indian Child Welfare Association

Product Description and Application Narrative Submitted by Corresponding Author

What general topics does your product address?

Public Health, Social & Behavioral Sciences


What specific topics does your product address?

Community engagement, Health services research, Partnership building , Community-based participatory research


Does your product focus on a specific population(s)?

n/a


What methodological approaches were used in the development of your product, or are discussed in your product?

Community needs assessment, Community-academic partnership, Community-based participatory research , Quantitative research


What resource type(s) best describe(s) your product?

Evaluation tool, Reference material (i.e. annotated bibliography)


Application Narrative

1. Please provide a 1600 character abstract describing your product, its intended use and the audiences for which it would be appropriate.*

Community-based participatory research (CBPR) is a collaborative approach that equitably involves partners in the research process and recognizes the unique strengths that each partner brings. CBPR begins with a research topic important to a community, combining knowledge construction, education, and action for social change towards improving community health. To advance community-engaged research, investigators from the Universities of New Mexico and Washington and the National Congress of American Indians Policy Research Center, in collaboration with a National Advisory Board of academic and community experts,* created a variable matrix to support a conceptual logic model of CBPR processes and outcomes. Details on the creation of this model are found in Wallerstein et al. 2008 [1].1 The variable matrix provides measurements to support the four dimensions of CBPR characteristics and relationships within each domain of the interactive CBPR model. First, contextual factors shape the nature of the research and the conditions under which partnerships can develop and be sustained. Next, group dynamics, consisting of three sub-dimensions, structural factors (i.e., collaborative agreements), individual partner characteristics, and relational dynamics (i.e., group decision-making); interact with contextual factors to co-produce the intervention and its research design. Finally, CBPR system changes and health outcomes result directly from the research. In sum, we provide items and scales from over 46 instruments representing 60% of the 40 domains in the CBPR logic model.


2. What are the goals of the product?

The goals of the CBPR variable matrix are to 1) help facilitate research on CBPR and to provide measures (items and scales) for partnerships looking to evaluate their partnership and partnership characteristics at a variety of levels throughout the research process and 2) to annually update the matrix to represent available and validated CBPR measures. We provide measures from instruments identified through a review of the literature (detailed in Wallerstein et al., 2008 [1] and through Sandoval 2011 [2]), a Google search of key CBPR terms, and contributions from our national advisory board of experts in CBPR. The instruments were categorized according to the CBPR model at two levels: a) domains: context, group dynamics, outcomes and b) specific characteristic within each domain. The variable matrix consists of specific individual items and scales that have been used, adapted, or sampled by CBPR practitioners.


3. Who are the intended audiences or expected users of the product?

The CBPR variable matrix provides questionnaire items and scales which may be useful for evaluating CBPR partnerships and assessing their characteristics. This matrix provides a place to start for new and continuing partnerships seeking to evaluate their progress. The project's collaborative team is now pleased to share a web-based tool allowing community and academic investigators to interact with the CBPR Conceptual Model, which is linked to CBPR instruments and measures from the literature.


4. Please provide any special instructions for successful use of the product, if necessary. If your product has been previously published, please provide the appropriate citation below.

The link to our product provided to CES4Health.info users links to our Interactive - CBPR Conceptual Model in order to provide users with the context of our work and to present Conceptual Model upon which the Variable Matrix is grounded. From this page, the user can navigate to the Variable Matrix.
How to use: 1) Navigate using the menu bar on the left-side of this webpage to select the matrix; 2) select Variable; 3) select dimensions within our CBPR model for downloadable materials for a) Context, b) Dynamics and c) Outcomes; 4) waive your mouse/pointer over these regions and click to download searchable Adobe pdf format files; 5) Full references in alphabetical order are available by clicking on the link “references here” located immediately under the title at the top of the page.


5. Please describe how your product or the project that resulted in the product builds on a relevant field, discipline or prior work. You may cite the literature and provide a bibliography in the next question if appropriate.

The CBPR variable matrix expands Wallerstein et al., 2008 [1]1theoretically-driven CBPR framework and Sandoval et al. [2]2 inventory of CBPR instruments. Guided by Wallerstein et al., 2008 CBPR logic model, the Research for Improved Health research team (Sandoval et al. [2] identified, from 273 articles, 46 unique instruments that measured many of the process and outcome constructs of the CBPR logic model. Sandoval et al. then used the CBPR logic model to categorize the items contained within these instruments. From the Sandoval et al. instrument matrix, we abstracted and categorized measurements and scales into a matrix by construct and domain that mapped them to Wallerstein et al., 2008 CBPR logic model. Our combined efforts represent the state of the art of CBPR research, provide an evaluation framework for partnership effectiveness and collective reflection among partners, and provide the tools for further directions in research on what constitutes successful CBPR.


6. Please provide a bibliography for work cited above or in other parts of this application. Provide full references, in the order sited in the text (i.e. according to number order). .

1. Wallerstein N, Oetzel J, Duran B, Tafoya G, Belone L, & , Rae R. CBPR: What predicts outcomes? . . In: Minkler M, Wallerstein N, eds. Community-based participatory research for health (2nd ed.). San Francisco: Jossey Bass; 2008.
2. Sandoval J, Lucero J, Oetzel J, et al. Matrix of Instruments to Measure CBPR Health Education Research 2011; http://hsc.unm.edu/SOM/fcm/cpr/cbprmodel.shtml. doi: 10.1093/her/cyr087 First published online: September 21, 2011
3. Viswanathan, M. Ammerman, A. Eng, E. Gartlehner, G. Lohr, K.N. Griffith, D. Rhodes, S. Samuel-Hodge, C. Maty, S. Lux, L. Web, L. Sutton, S. F. Swinson, T. Jackman A.and Whitener, L. Community-Based Participatory Research: Assessing the Evidence. Evidence Report/Technology Assessment No. 99, 2004 (Prepared by RTI–University of North Carolina Evidence-based Practice Center under Contract No. 290-02-0016). AHRQ Publication 04-E022-2. Rockville, MD: Agency for Healthcare Research and Quality


7. Please describe the project or body of work from which the submitted product developed. Describe the ways that community and academic/institutional expertise contributed to the project. Pay particular attention to demonstrating the quality or rigor of the work:

  • For research-related work, describe (if relevant) study aims, design, sample, measurement instruments, and analysis and interpretation. Discuss how you verified the accuracy of your data.
  • For education-related work, describe (if relevant) any needs assessment conducted, learning objectives, educational strategies incorporated, and evaluation of learning.
  • For other types of work, discuss how the project was developed and reasons for the methodological choices made.

The University of New Mexico Center for Participatory Research (http://hsc.unm.edu/SOM/fcm/cpr/index.shtml), the University of Washington Indigenous Wellness Research Institute (http://www.iwri.org) and a national advisory group* of academic and community CBPR experts have collaborated to better understand how CBPR works to improve health and health equity. This team of academic and community CBPR experts created a conceptual CBPR logic model, research design and identified measurements to assess construct and domains of the CBPR logic model.
Our collaboration process began in 2006 with a three year pilot study, funded by the National Center for Minority Health and Health Disparities administered through the Native American Research Centers for Health Supplement, (U26IHS300009/03). Through this pilot funding, we partnered with a “think tank” of 25 national academic and community CBPR experts, to begin to study the science of CBPR. The national advisory committee provided overall guidance and direction for the pilot study with the major focus to develop a conceptual logic model that represents the state of community-based research, provides an evaluation framework for partnership effectiveness and collective reflection among partners, and indicates further directions for research on what constitutes successful CBPR. (go to Research for Improved Health at the page linked through CES4Health.info )
The CBPR logic model in Wallerstein et. al., 2008 [1] identifies and dissects the primary components, describing how CBPR may be implemented across diverse settings, studies and populations. The model contains four major components including context, group dynamics, interventions, and outcomes and identifies a number of specific characteristics (i.e., concepts within each component) of each of the four primary components.
In 2009, the National Congress of American Indians Policy Research Center (NCAI-PRC) joined as lead investigators in a NIH – Native American Research Center for Health project, Research for Improved Health: A National Study of Community-Academic Partnerships (http://narch.ncaiprc.org/).** NCAI-PRC brought together and expanded the national advisory team to provide guidance in this new phase of the research process. The aims are:
1) Describe the variability of CBPR characteristics across dimensions in the CBPR conceptual model to identify differences and commonalities across partnerships.
2) Describe and assess the impact of governance on CBPR processes and outcomes across AI/AN and other communities of color.
3) Examine the associations among diverse contexts and partnering processes with major CBPR outcomes, such as culturally-centered interventions and health-enhancing policies, found to be linked to health disparities, by testing the CBPR conceptual model.
4) Identify, translate, and disseminate best practices in CBPR for tribal leaders and other community and academic partners to improve health status and health equity.
* National Advisory Board: CBPR Research and Evaluation Community of Practice: Margarita Alegria, Elizabeth Baker, Beverly Becenti-Pigman, Charlotte Chang, Eugenia Eng, Shelley Frazier, Ella Greene-Morton, Lyndon Haviland, Jeffrey Henderson, Sarah Hicks, Barbara Israel, Loretta Jones, Michele Kelley, Paul Koegel, Laurie Lachance, Marjorie Mau, Meredith Minkler, Naeema Muhammad, Lynn Palmanteer-Holder, Tassy Parker, Victoria Sanchez, Amy Schulz, Lauro Silva, Edison Trickett, Jesus Ramirez-Valles, Kenneth Wells, Earnestine Willis, Kalvin White.
**NCAI PRC Team: Sarah Hicks (initial PI), Malia Villegas, current PI, Emily Whitehat, Puneet Sahota
UNM Team: Nina Wallerstein, co-PI, Magdalena Avila, Lorenda Belone, Julie Lucero, Michael Muhammad, John Oetzel, Jennifer Sandoval, Vanessa Simonds, Andrew Sussman, Greg Tafoya
UW Team: Bonnie Duran, co-PI, Cynthia Pearson, Diane Martin, Leo Egashira


8. Please describe the process of developing the product, including the ways that community and academic/institutional expertise were integrated in the development of this product.

In the development of the model and the instrument and variable matrices, we used multiple methods in an iterative process. Our national advisory board identified and provided feedback on the appropriateness of the concepts and domains in the model. During model development, we conducted consultations with six academic-community partnerships to ensure the model resonated with community experiences. These consultations included a detailed review of the model and discussion of ways it could be improved. The model was revised to reflect this community engagement.
Advisory board members accessed their professional networks to identify and obtain the most salient measures available. Our collaborative effort included a comprehensive literature review of public health and social science databases replicating and expanding the AHRQ 2004 study [3]; an internet survey with 96 CBPR project participants that included pilot-tested components uncovered in the literature review; ongoing reflection and input by our national academic and community CBPR experts*; and ongoing revision by our research team [1].
Once the instruments were identified, academic team members began coding the instruments and measures/items mapping them to the CBPR logic model. Two coders reviewed and coded each instrument. Coding consisted of: a) clarifying definitions of model characteristics and how to code instruments, b) coding 10% of the total instruments together to establish intercoder reliability, and c) coding remaining instruments independently. When there were difficulties determining appropriate categorization, the coders worked together with one other member of the research team to determine the best category. Intercoder reliability was .90 (Cohen’s kappa). Some instruments were not classified as a whole; the subscales or even several items became the coding unit. Our goal was to provide the most accurate and thorough inventory possible as it relates to the CBPR model. Thus, we were not concerned with retaining the intention of the original instrument, but rather what instruments measure characteristics in the CBPR model (and thus some instruments are listed multiple times).
The logic model offered a theory-based consensus framework for CBPR, and the instrument matrix provided a thorough review of the CBPR literature and a mapping of measures to the CBPR model. The next step was to develop a variable matrix that would allow users easy access to a wide range of measurement tools to further research on CBPR. Items were abstracted from articles and surveys and entered into Excel. All entries were reviewed by an editor to ensure accuracy and an investigator reviewed entries to verify accuracy in mapping to the instrument matrix. Finally, one more review was conducted by another academic team ensuring the variable matrix mapped to the instrument matrix that mapped to the CBPR logic model. Throughout this process, our national advisory team provided ongoing feedback and clarification as needed. This matrix provides access to partnership measurement tools, current up to 2008, and should serve as a useful resource for researchers and practitioners of CBPR.
The matrix is organized in the following manner: First, the primary domain and specific constructs of the CBPR model are established. Second, the number of measures and items for each particular measure are listed. Third, the response category for these items is included. Finally, the source for the measure is listed. In some cases, we do not have the individual items listed even though we have established that the measure is appropriate for a construct. In places where we could not locate a measure, the construct is highlighted yellow.
Context. The context section includes measures of five constructs in the model: Community Capacity (n = 9); Organizational Capacity and Health Issues (n = 4); Historical Context of Collaboration (n = 4); and National Local Policies, Trends, and Political Governance (n = 1) and perceived severity of health issues (n = 5).
Group Dynamics. The group dynamics section includes measures of relational dynamics, structural dynamics, and individual dynamics. In the Relational category, the eight characteristics that had the highest number of individual measures in the instruments included; Participatory Decision Making and Negotiation (n = 22); Dialogue and Mutual Learning (n = 20); Leadership and Stewardship (n = 19); Task Communication and Action (n = 17); Self and Collective Reflection (n = 13); Influence and Power (n = 9); Conflict (n = 3); and Congruence of Core Values (n = 1). No measures were identified for the characteristics of Flexibility and Integration of Local Beliefs to the Group Process. For Structural Dynamics, the characteristic of Complexity had a total of 16 measures followed by Agreements (n = 10), Diversity (n = 6), Length of Time in Partnership (n = 10), and Power and Resource Sharing (n = 3). For Individual Dynamics, measures are available for Individual Beliefs (n = 10) and Community Reputation of the Principal Investigator (n = 1). The characteristic of Conflict was not originally identified in the logic model as a separate sub-category for Relational Dynamics, but was added based on the information that emerged in the coding.
Outcomes. The outcome section includes measures for five constructs: Empowerment and Community Capacity outcomes (n = 27); Change in Practice or Policy (n = 10); Unintended Consequences (n = 1) and Health Outcomes (n = 8). No measures were found for the final category, Culturally Based Effectiveness.


9. Please discuss the significance and impact of your product. In your response, discuss ways your product has added to existing knowledge and benefited the community; ways others may have utilized your product; and any relevant evaluation data about impact, if available. If the impact of the product is not yet known, discuss its potential significance.

The variable matrix establishes a set of preliminary measures that map on the CBPR logic model and will assist community and academic researchers in understandings of how academic-community partnerships contribute to changes in health outcomes. The variable matrix allows users easy access to a wide range of measurement tools to further research in CBPR and to assess partnerships. This matrix provides access to partnership measurement tools, current up to 2008, and should serve as a useful resource for researchers and practitioners of CBPR.
Given the value of CBPR for communities, such a compilation of tools should be of great value to academics, community members, and practitioners. We need tools in order to develop knowledge about CBPR and to evaluate/assess the practice of CBPR. Such a matrix has not been developed before. While there are tools in the literature and in practice, these are scattered and are not organized. Our own advisory board lauded the development of this matrix and the publishing it on a resource that is accessible to community members. Because this is new, we do not have concrete information about how it is being used and thus we it is potential significance at this time.
Furthermore, we will continue to integrate the variable matrix with the interactive CBPR model towards a completely seamless product for a more user friendly and functional relational database. Our vision of a final interactive model product includes an ability to navigate the model, e.g. users will be able to easily zoom in and out of the model dimensions (context, group dynamics etc) and better interact with variable/instrument measures. We also plan to develop multimedia clips that will be embedded in the interactive model, where people explain and discuss the dimensions and measures. Lastly, an important barrier to information is being addressed through our interactive CBPR model because we are providing this product through an open-source approach, e.g. information that is freely available to the public in terms of access. This open-source approach promotes dissemination of the product by reducing potential information access barriers by removing the need for costly journal subscriptions or requiring users to register - promoting accessibility for both academic and community researchers who may have limited resources.
We are pleased to share a web-based tool for community and academic investigators to interact with the CBPR Conceptual Model, instruments and measures.


10. Please describe why you chose the presentation format you did.

The Interactive - CBPR Conceptual Model allows users to easily identify and download scales and individual item measures (variables) with associated information useful for evaluating CBPR partnerships and assessing partnership characteristics.


11. Please reflect on the strengths and limitations of your product. In what ways did community and academic/institutional collaborators provide feedback and how was such feedback used? Include relevant evaluation data about strengths and limitations if available.

We have provided a thorough review of the literature up to 2008 and provided access to partnership measurement tools used to create the variable matrix. However, as reported in Sandoval et al.2011 [2] a limitation is that few of these instruments (25%) reported validation of the measure’s psychometric properties. Furthermore, among those that have psychometric properties reported, their relevance across a variety of partnerships types have yet to be determined. However, since the matrices are web based and in a dynamic medium, we can provide ongoing updates. CBPR academic and community investigators have the option of contributing measures to the instrument and measurement matrix. Contributors would 1) identify the construct and domain, 2) provide validation of the measure’s psychometric properties, and 3) submit the proposed measure in excel format for review by this team. If determined relevant to the CBPR model, the measure would be incorporated into the instrument and variable matrix. Updates will occur once a year.
Ideally it would be beneficial if the complete survey from where the scales and measure were obtained would be available for download. However copyright regulations restrict us from providing free access to these instruments. We do provide complete references to all measures.


12. Please describe ways that the project resulting in the product involved collaboration that embodied principles of mutual respect, shared work and shared credit. If different, describe ways that the product itself involved collaboration that embodied principles of mutual respect, shared work and shared credit. Have all collaborators on the product been notified of and approved submission of the product to CES4Health.info? If not, why not? Please indicate whether the project resulting in the product was approved by an Institutional Review Board (IRB) and/or community-based review mechanism, if applicable, and provide the name(s) of the IRB/mechanism.

The CBPR variable matrix is a product of engaged scholarship. Funding for both the pilot and the current study is provided through the Native American Research Centers for Health (NARCH III Supplement, U26IHS300009/03 and NARCH V: U261HS300293 2009-2013, respectively). NARCH is a collaboration between the National Institutes for Health and Indian Health Service with all funds provided to a tribal community partner as the primary grantee with subcontracts to the academic partner. In addition to the funding, both academic and community partners worked together over the last six years to develop the CBPR logic model from which the variable matrix arose. In addition to frequent conference calls, annual in-person meetings were held from 2006 to date to ensure that community voice was reflected in the development of the model. To reach community members that were not at the meetings or on the calls, the national advisory board members took the model to their communities where community partners provided in-depth feedback as to the community-reflectiveness and face validity of the model. The feedback provided from the community significantly altered the logic model. Additionally, that the partnership continues to date demonstrates a commitment to principles of mutual respect, shared work, and shared credit.