The data needs of community-based organizations (CBOs) have increased in recent years as a result of funders' interest in more formalized program accountability and evaluations1–3
and evidence-based decision-making.4–6
Moreover, there is a growing emphasis on community-based participatory research (CBPR) approaches in which CBOs partner with academic or other investigators on research.7,8
Indeed, building CBO research capacity is a core principle of CBPR.9–15
Community organizations are better equipped to participate equitably and with shared control over research processes in their community if they possess adequate knowledge and skills related to research terminology and methodologies.9
Emerging evidence also suggests that there are increases in the quality of research when investigators partner with the communities being studied.15–17
For example, a 2001 review of 60 published CBPR studies found greater participation rates, strengthened external validity, and decreased loss to follow-up as a result of community partnerships.15
Community organizations also have a need for data that will inform their programs, service delivery, and advocacy. Yet CBOs in underserved communities that are rapidly changing because of immigration, residential mobility, and other demographic shifts have difficulty finding secondary data sources that accurately capture the characteristics and experiences of the communities they serve.18–22
Despite these clear needs, little is known about the data or research capacity of CBOs. Initial evidence suggests that CBOs and local health departments fall short of the data and research skills required for service delivery,23,24
or partnering effectively with public health researchers,26
although there is variability in these skills among nonprofits.27
Overall, however, the evidence suggests that their capacity is not keeping pace with increased demand.
Innovative programs that aim to increase CBO research capacity are growing in frequency,28–34
although published evaluations of such capacity-building programs are limited and often appear in the literature as program descriptions or evaluations of program implementation. Moreover, there are few community research capacity programs that focus on the general research capacity of participants independent of a specific health topic (e.g., environmental health35–37
) or the aims of a concurrent CBPR or other research project.15
We present evaluation data from Data & Democracy, a community capacity building initiative of the Health DATA (Data. Advocacy. Training. Assistance.) program of the University of California Los Angeles Center for Health Policy Research. The goal of Data & Democracy was to increase the data and research capacity of community-based health organizations by increasing the knowledge and skills of CBO staff to plan and conduct a community health assessment. By “research capacity,” we refer to skills related to the design and methods of collecting primary data. In CBOs this may involve a community needs assessment, program evaluation, or other type of community placed research. We distinguish that from “data capacity,” or a subset of research skills related to finding and using secondary data, as well as data management, analysis, and reporting.
Data & Democracy employed 4 strategies: (1) strong community partnerships that led to trusted endorsements supporting outreach and recruitment of prospective participants; (2) a comprehensive curriculum organized around core data and research skills using adult learning theory and popular education methods38
; (3) a train-the-trainer model to ensure diffusion of innovation39
into the community and increase retention of course knowledge and skills for participants as they teach others; and (4) extensive technical assistance and follow-up.
Data & Democracy courses were offered to representatives of CBOs, nonprofits, advocacy networks, and coalitions serving underserved communities, such as low-income, immigrant, homeless, and racial/ethnic minority populations. The purpose of inclusion criteria was to provide capacity-building opportunities to organizations with fewer research training opportunities and limited research infrastructure.
The course curriculum focused on 6 steps for planning and conducting a community health assessment,40
using the assessment framework to teach the terminology and skills of a participatory research process. The first step addressed identifying and engaging key partners to plan and conduct a community assessment, pooling resources and skills, and partnering with researchers. The second step, determining an assessment focus, was designed to assist participants, who were more accustomed to writing program goals and objectives, to choose a focal issue(s) and develop clear research questions and assessment goals and objectives. The course's third step guided participants to determine the data needed to answer their research questions, starting first with identifying appropriate secondary data. The fourth step provided an introduction to data collection methods for collecting primary data when adequate existing data are not available. The fifth step reviewed strategies for basic descriptive analysis of quantitative and qualitative data, including the creation and interpretation of graphs and tables. The sixth step covered communicating data and findings in a strategic way to various audiences. Course material was taught through a combination of didactic learning, interactive exercises, homework, and real-world simulations in which participants applied research terms and methods to a community assessment partnership planning process.
After an initial pilot phase, Data & Democracy was funded for 2 cycles. This article combines evaluation findings from the first cycle (2005–2007), implemented in 6 California counties, and the second cycle (2008–2010), implemented in 4 counties. Program efforts in these 10 cohorts reached a total of 171 course participants (108 in cycle 1 and 63 in cycle 2). Sixty-four percent (n = 105) of participants went on to teach 993 coworkers, community partners, and community members as part of the train-the-trainer model, a proportion considerably higher than previous public health train-the-trainer programs.41
To better understand the broader context of data and research capacity building in which the Data & Democracy training initiative lies, we present a conceptual model in , adapted from Kirkpatrick's hierarchical model of training effectiveness.42
As can be seen in the figure, this is a straightforward model containing 4 stages of capacity building: reaction, learning, behavior, and results. Kirkpatrick's theory was first developed in 1959 and has arguably become the most widely used model for the evaluation of training and learning.
Conceptual model of community-based organization data and research capacity building: Data & Democracy training initiative, University of California, Los Angeles Health DATA (Data. Advocacy. Training. Assistance.) Program.
We focused on components of stages 2 (learning) and 3 (behavior) of the model. The learning stage focuses on increases in capacity, and the behavior stage focuses on the extent of applied learning or implementation back on the job. This study first aims to demonstrate whether a capacity-building program can increase the self-efficacy of CBO staff related to data and research knowledge and skills. The second aim takes a longer-term view with the second cycle of participants to determine if new knowledge and skills were translated into changes in behavior, such as the increased use of data and research in their work and the work of their organization.