ArticleImplementation science communications2025
Methods for community-engaged data collection and analysis in implementation research.
Article in Implementation science communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Community-Led Transformation in Practice: A Framework for Trust-Driven Community-Academic Partnerships to Advance Public Health.Journal of immigrant and minority health · 2026Review
- Bridging the divide in digital therapeutics (DTx): Partnership strategies for broader representation across DTx development and deployment.PLOS digital health · 2026Article
- Mitigating Home Environmental Asthma Triggers in Subsidized Housing: Experiences of Caregivers and Healthcare Workers.Healthcare (Basel, Switzerland) · 2026Article
- Cultural adaptations made to existing implementation science theories, models, frameworks, or outcomes: a scoping review.Translational behavioral medicine · 2026Article
- Addressing a gap in community-engaged research: reporting results of congregations' implementation capacity assessment to research participants.Frontiers in public health · 2026Article
- Critical matriarchal futures: reimagining public health communication leadership as response to state-sanctioned violence.Frontiers in public health · 2026Article
- Navigating qualitative methods choices in dissemination and implementation research.Implementation science : IS · 2025Article
- Qualitative Mediation Analysis: an Important Method for Exploring Mediating Mechanisms in Prevention Science.Prevention science : the official journal of the Society for Prevention Research · 2025Article
- Integrating qualitative insights with large secondary data: a protocol for a community-engaged mixed-methods study on adolescent substance use.Frontiers in public health · 2025Article
- Reaching Across the Divide: Integrating Equitable Community-Based Qualitative Methods and Trusted Engagement Strategies Into Arizona's Statewide Maternal and Child Community Assessment.Journal of primary care & community healthArticle
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7 authors.
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Abstract
backgroundCommunity engagement is widely recognized as critical to successful and equitable implementation of evidence-based practices, programs, and policies. However, there are no clear guidelines for community involvement in data collection and analysis in implementation research.
methodsWe describe three specific methods for engaging community members in data collection and analysis: concept mapping, rapid ethnographic assessment, and Photovoice. Common elements are identified from a case study of each method: 1) selection and adaptation of evidence-based strategies for improving adolescent HPV vaccine initiation rates in disadvantaged communities, 2) strategies for implementing medication for opioid use disorders among low-income Medicaid enrollees during natural disasters, and 3) interventions to improve the physical health of adults with severe mental illness living in supportive housing.
resultsIn all three cases, community members assisted in participant recruitment, provided data, and validated preliminary findings created by researchers. In the Photovoice case study, community members participated in both data collection and analysis, while in the concept mapping, community members also participated in the initial phase of organizing and prioritizing evidence-based strategies during the data analysis.
conclusionsCommunity involvement in implementation research data collection and analysis contributes to greater engagement and empowerment of community members and validation of study findings. Use of methods that exhibit both scientific rigor and community relevance of implementation research also contributes to greater community investment in successful implementation outcomes. Nevertheless, the case studies point to the importance and efficiency of the division of labor embedded in community-engaged implementation research. Building capacity for community members to assume greater roles in obtaining and organizing data for preliminary analysis prior to interpretation is recommended.
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