Dataset Information

A successful model for longitudinal community-engaged health research: the 2040 Partners for Health Student Program.

ABSTRACT:

Introduction

Community-based participatory research [CBPR] is an emerging approach to collaborative research aimed at creating locally effective and sustainable interventions. The 2040 Partners for Health student program was developed as a unique model of longitudinal CBPR. Analysis of this program and its components illuminates both the challenges and the opportunities inherent in community engagement.

Methods

The program rests on a foundation of a community-based, non-profit organization and a supportive academic university centre. Inter-professional health students and community members of underserved populations work together on different health projects by employing an adapted CBPR methodology. Three successful examples of sustainable CBPR projects are briefly described.

Results

The three projects are presented as primary outcomes resulting from this model. Benefits and challenges of the model as an approach to community-engaged research are discussed as well as secondary benefits of student participation.

Conclusion

The 2040 Partners for Health student program represents a successful model of CBPR, illuminating common challenges and reiterating the profound value of community-engaged research.

SUBMITTER: Redman RM

PROVIDER: S-EPMC6390419 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A successful model for longitudinal community-engaged health research: the 2040 Partners for Health Student Program.

Redman Romany M RM Reinsvold Magdalena C MC Reddy Anireddy A Bennett Paige E PE Hoerauf Janine M JM Puls Kristina M KM Ovrutsky Alida R AR Ly Alexandra R AR White Gregory G McNeil Owetta O Meredith Janet J JJ

Family practice 20170601 3

<h4>Introduction</h4>Community-based participatory research [CBPR] is an emerging approach to collaborative research aimed at creating locally effective and sustainable interventions. The 2040 Partners for Health student program was developed as a unique model of longitudinal CBPR. Analysis of this program and its components illuminates both the challenges and the opportunities inherent in community engagement.<h4>Methods</h4>The program rests on a foundation of a community-based, non-profit org ...[more]

PMID: 28407068

Similar Datasets

Project description:The degree to which artificial intelligence healthcare research is informed by data and stakeholders from community settings has not been previously described. As communities are the principal location of healthcare delivery, engaging them could represent an important opportunity to improve scientific quality. This scoping review systematically maps what is known and unknown about community-engaged artificial intelligence research and identifies opportunities to optimize the generalizability of these applications through involvement of community stakeholders and data throughout model development, validation, and implementation. Embase, PubMed, and MEDLINE databases were searched for articles describing artificial intelligence or machine learning healthcare applications with community involvement in model development, validation, or implementation. Model architecture and performance, the nature of community engagement, and barriers or facilitators to community engagement were reported according to PRISMA extension for Scoping Reviews guidelines. Of approximately 10,880 articles describing artificial intelligence healthcare applications, 21 (0.2%) described community involvement. All articles derived data from community settings, most commonly by leveraging existing datasets and sources that included community subjects, and often bolstered by internet-based data acquisition and subject recruitment. Only one article described inclusion of community stakeholders in designing an application-a natural language processing model that detected cases of likely child abuse with 90% accuracy using harmonized electronic health record notes from both hospital and community practice settings. The primary barrier to including community-derived data was small sample sizes, which may have affected 11 of the 21 studies (53%), introducing substantial risk for overfitting that threatens generalizability. Community engagement in artificial intelligence healthcare application development, validation, or implementation is rare. As healthcare delivery occurs primarily in community settings, investigators should consider engaging community stakeholders in user-centered design, usability, and clinical implementation studies to optimize generalizability.

Dataset Information

A successful model for longitudinal community-engaged health research: the 2040 Partners for Health Student Program.

Introduction

Methods

Results

Conclusion

Publications

A successful model for longitudinal community-engaged health research: the 2040 Partners for Health Student Program.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets