摘要：Although the intent of community-based participatory research (CBPR) is to include community voices in all phases of a research initiative, community partners appear less frequently engaged in data analysis and interpretation than in other research phases. Using 4 brief case studies, each with a different data collection methodology, we provide examples of how community members participated in data analysis, interpretation, or both, thereby strengthening community capacity and providing unique insight. The roles and skills of the community and academic partners were different from but complementary to each other. We suggest that including community partners in data analysis and interpretation, while lengthening project time, enriches insights and findings and consequently should be a focus of the next generation of CBPR initiatives. In 2001, the Agency for Health Care Research and Quality commissioned a systematic review of published work describing community-based participatory research (CBPR) approaches to improving health. From this review, CBPR was defined as follows: A collaborative research approach that is designed to ensure and establish structures for participation by communities affected by the issue being studied, representatives of organizations, and researchers in all aspects of the research process to improve health and well-being through taking action, including social change. 1 (p3) As reported in the 60 studies reviewed, community involvement extended through all areas of research, and many study authors argued that the involvement of community partners encouraged greater participation rates, strengthened external validity, decreased loss to follow-up, and increased individual and community capacity. 1 These positive attributes notwithstanding, the strongest and most common engagement occurred in recruiting study participants and designing and implementing the research and interventions; less common was community participation in data analysis and interpretation of findings. It is unclear whether community partner involvement in these phases of research has simply been reported less frequently in peer-reviewed publications or whether community partners have actually been less engaged in data analysis and interpretation. It has been suggested that diverting community expertise, time, and attention to acquiring analytic skills, both quantitative and qualitative, may be misplaced, particularly when balanced against the (1) efficiencies of drawing on analytic skills and resources that academic partners bring to the research enterprise and (2) priorities focused on enhancing existing community expertise. 2 It also has been asserted that both the community and academic partners for a single study could be overwhelmed by the commitment of time and resources necessary to prepare for equitable engagement in all phases of the research, especially data analysis and interpretation. 3 , 4 Some community partners have argued that their involvement—particularly in data analysis—is not always the best use of their time. Nevertheless, most academic partners engaged in CBPR stress the fundamental value of the community–academic partnership deciding on specific roles and responsibilities. Although these may be fluid as they adjust to a project’s unique needs, the critical role of community partners in interpreting and synthesizing findings—even if they are not involved fully in data analysis—remains a hallmark of CBPR. Through the participatory process of jointly interpreting data, differing perspectives are articulated and integrated, thereby enriching insights and discoveries. 5 – 7 With little empirical evidence on the implications of engaging community partners in data analysis, interpretation, or both, we are at the beginning stages of understanding the benefits and challenges of bringing them into these phases of research. We may find that working in partnership on data analysis and interpretation could require skills—still to be articulated fully—from community partners that are different from but complementary to those of the academic partners, thereby increasing the credibility of outcomes and likelihood for translation into practice. We present 4 case studies from our own CBPR studies. The cases represent a range of methods for data analysis or interpretation of findings. We (1) review the collaborative processes used; (2) identify challenges met in data analysis, interpretation of findings, or both, and the impact each partnership had; (3) discuss how community–academic collaboration added value to the analytic and interpretive phases of research; and (4) highlight lessons learned across the 4 cases. The first case is a partnership between faculty and students from the University of New Mexico, the Albuquerque Area Indian Health Board, and members of a nearby tribal community. This partnership was forged to assess the tribe’s public health infrastructure and capacity to improve health. Participants used mixed qualitative and quantitative analytic methods. The second case is a partnership carried out in Detroit’s east side involving participants from community-based organizations, the local health department, an integrated care system, and faculty, students, and staff from the University of Michigan School of Public Health. In it, community partners interpreted results from a community survey aimed at examining and addressing social determinants of health. The third case, a partnership between a North Carolina Latino men’s soccer league, other community-based organizations, and faculty at the University of North Carolina’s School of Public Health, used focus group methodology to understand issues related to sexually transmitted infections, particularly HIV. In the final case, a partnership between neighborhood organizations in Brooklyn in New York City and faculty from Hunter College, Queens College, and City University of New York used mapping as a methodology for documenting environmental health. Table 1 ▶ presents a summary of these cases, with the challenges faced by the partnerships and the impacts the projects had. TABLE 1— A Summary of Case Studies of Community-Based Participatory Research (CBPR) Case Composition Structure Colearning Methodology Type of Data Community Partner Role Academic Partner Role Time Required to Analyze/Interpret Data Techniques to Make Data Accessible Challenges Impact Ramah Navajo (New Mexico) Diverse volunteer advisory board: health staff service providers, educators, elders. Elected tribal school board authorized the project. Participants were predominantly volunteers, although the director encouraged selected health staff to participate. Decisions were made by consensus, and the structure was informal and fluid, with two thirds of participants coming regularly.This group reported to the Ramah Navajo School Board, which was a formal elected body. Visioning; guidance in use of assessment and priority setting tools; discussions of meanings contained in analytic results; copresentations. Phase I: quantitative (data analyzed by CDC); phase II: qualitative (survey data). Collaborated on analysis and interpretation of CDC’s LPHSPA instrument; set priorities for action; codeveloped survey instrument content and language; conducted interviews and shaped interpretation. Led instrument adaptation; developed explanatory worksheets; documented advisory board’s quantitative scoring and led qualitative analysis discussions. 4 meetings in a 2-month period; 1 full day for priority setting of LPHSPA. Survey data not reported on. For LPHSPA, bar graph and ranking of qualitative results; narrative chart summary of strengths and weaknesses from qualitative data; for survey data, pie charts/graphs. Time; retaining community partners; need to adapt professional jargon of LPHSPA; need to translate survey into Navajo; maintaining tribal elders’ participation. Local community profile developed and administered; improved cultural competence; modification of federally developed LPHSPA assessment tool; capacity building.a East Side Village Health Worker Partnership (Detroit, Michigan) Representatives from local health deptartment, CBOs, integrated care system, and academia composed steering committee and local lay health advisors referred to as village health workers or VHWs. Steering committee met monthly and followed adopted CBPR principles and operating procedures; VHWs met monthly. Discussed and interpreted data feedback materials and results; identified priorities and action strategies; shared descriptive results; selected research questions. Quantitative (derived from random-sample household survey). Defined scope of work; developed conceptual framework; identified key variables; selected/modified measures for questionnaire; interpreted and disseminated data; applied data to guide intervention; reviewed pie charts and bar graphs for wider community distribution. Facilitated steering committee meetings; provided data; helped revise questionnaire; hired, trained, and supervised interviewers; analyzed data; developed data feedback materials. Over 6-month period, monthly meetings of steering committee and VHWs and half-day retreat. Placed frequencies on questionnaire; used pie charts and bar graphs to present results; engaged in experiential learning activities to examine results and set priorities. Time; determining community and academic partner roles; identifying mechanisms for data sharing. Neighborhood residents hired and trained to conduct interviews; increased knowledge of community strengths and stressors; enhanced understanding of social determinants of health; network of local lay health advisors instituted; capacity building.a Latino Men (rural North Carolina) Hispanic soccer league, Latino grocery store, leadership development coalition, farm worker advocacy group, Latino-serving CBOs. Community-based, health-focused coalition met monthly and followed adopted CBPR principles. Partner in all phases of data analysis and interpretation. Qualitative (derived from focus groups). Set priorities; moderated and hosted focus groups; read transcripts; with academic partners, developed coding system and data dictionary; assigned codes to text; refined and interpreted themes; provided cultural knowledge. Provided leadership and expertise in data analysis; used Nvivo software (QSR International, Cambridge, MA) to code and retrieve text. 8 months. Systematic, multistage process; data analysis teams had lay and professional members; flipcharts were used throughout the process for review, revision, and final presentation of approved themes. Time; racial tensions in larger community reflected in community partners; concern about suitability of topic selected; tension between research process and immediate action. HIV and STD prevention initiative developed; capacity building.a Greenpoint/Williamsburg Latino, Polish (Brooklyn, New York City) Local students; immigrant, and Hasidic Jewish community members. Participants partnered with academic scientists; map making was done by both community members and professionals. Partner in all phases of data gathering and analysis. Qualitative and quantitative; mapping; air pollution samples. Introduced professionals to neighborhood; contributed knowledge of local environmental hazards; produced visuals on map depicting polluters; distributed maps in neighborhood; galvanized community to action. Provided GIS to help local people map what was important to them; learned from community about existence of specific hazardous locations that professionals routinely overlooked; participated in public action for reduction in pollutants. 6–9 months. Maps provided “common language” for all participants; visuals allowed the individuals not technically trained to participate in technical data analysis and interpretation. Time; retaining complexity while simplifying; recognition of maps as provisional products that complement other sources of information; capturing community knowledge in quantitative format. Neighborhood residents activated; project aim altered to focus on pollution; EPA’s decision regarding pilot community exposure project affected; new pollution prevention programs developed; capacity building.a Open in a separate window Note. CDC = Centers for Disease Control and Prevention; LPHSPA = Local Public Health System Performance Assessment; CBO = community-based organization; STD = sexually transmitted disease; GIS = geographic information system; EPA = Environmental Protection Agency. aFor discussion of capacity building, see sections on specific case studies in text.
