ArticleJournal of clinical and translational science2018
Lessons learned from developing and sustaining a community-research collaborative through translational research.
Article in Journal of clinical and translational science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Assessing impact on health, health care, and public support: The evolution of a CTSA hub's evaluation and continuous improvement program.Journal of clinical and translational science · 2025Article
- Using the Researcher Investment Tool to inform a clinical and translational research initiative.Journal of clinical and translational science · 2025Article
- A Collaborative Approach to Address Racism in a Community-Academic Partnership.Preventing chronic disease · 2023Article
- A conceptual framework for clinical and translational virtual community engagement research.Journal of clinical and translational science · 2022Article
- A stakeholder engagement strategy for an ongoing research program in rural dementia care: Stakeholder and researcher perspectives.PloS one · 2022Article
- Community Engagement Practices at Research Centers in U.S. Minority Institutions: Priority Populations and Innovative Approaches to Advancing Health Disparities Research.International journal of environmental research and public health · 2021Article
- Rural Community Engagement for Health Disparities Research: The Unique Role of Historically Black Colleges and Universities (HBCUs).International journal of environmental research and public health · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
introductionThe goal of this project was to document the current state of a community-academic partnership, identifying early successes and lessons learned.
methodsWe employed qualitative methods, semi-structured interviews and document analysis, from 2 data sources to (1) show how the principles of community-based participatory research are enacted through the activities of Addressing Disparities in Asian Populations through Translational Research (ADAPT) and (2) elucidate the barriers and facilitators to adhering to those principles from the perspectives of the members themselves.
resultsIn addition to established community-based participatory research values, understanding individuals' motivations for participation, the challenges aligning the priorities of community organizations and academic partners, and definitions of success are themes that emerged as key to the process of maintaining this partnership.
conclusionAs the emphasis on community-academic partnerships grows, there is potential for clinical and translational science awards to use community engagement to facilitate translational research beyond the traditional medical spheres of influence and to forge relationships with affected communities.
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.