ArticleInternational journal of qualitative methods
Community Activation to TrAnsform Local sYSTems (CATALYST): A qualitative study protocol.
Article in International journal of qualitative methods. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Bridging work: Community health workers' role as a continuum of building, guiding, sustaining and transforming the path to health equity.SSM. Qualitative research in health · 2026Article
- Structural Supports and Challenges for Community Health Worker Models: Lessons from the COVID-19 Response in Orange County, California.SSM. Qualitative research in health · 2025Article
- Article
- Practical qualitative data analysis for public health research: a guide to a team-based approach with flexible coding.International journal of qualitative methodsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Community Health Workers, promotores, and navigators (henceforth, CHWs) emerged as critical members of the public health workforce addressing social, economic, and health inequities worsened by the COVID-19 pandemic. While there is increasing appreciation for and utilization of CHW models, and recognition of the importance of tailoring and innovating these models during the pandemic, few studies have examined the processes of change by which CHW models operated during the COVID-19 pandemic, and factors that facilitated or constrained CHW health equity efforts. This protocol paper describes and reflects on the research methodology used in our qualitative study focused on CHWs. The CATALYST study aims to examine the roles that CHWs served during the COVID-19 pandemic and facilitators and barriers related to CHW health equity strategies. This qualitative study incorporates the lived experiences of CHWs, low-income communities of color whom CHWs engaged, and institutional representatives and policymakers familiar with locally implemented CHW models during the pandemic. Through a community-based participatory research process, this study involves an abductive qualitative approach to data collection and analysis. We integrate community member expertise alongside CHW and health equity frameworks in designing the research questions and data collection process. Additionally, we use an analytic approach that combines inductive (drawn from qualitative data) and deductive codes (drawn from theoretical frameworks and practice-based evidence integrated through a participatory research process) and nimbly leverages flexible coding to address inductive themes and practice-based questions. Our collaborative process offers concrete strategies to develop qualitative research protocols with community partners, with evidence used to inform policy, programmatic, and relational changes to support and amplify CHW models to promote community health and health equity.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.