Dataset Information

Best practices for community-engaged participatory research with Pacific Islander communities in the USA and USAPI: protocol for a scoping review.

ABSTRACT: INTRODUCTION:Community-based participatory research is a partnership approach to research that seeks to equally involve community members, organisational representatives and academic partners throughout the research process in a coequal and mutually beneficial partnership. To date, no published article has synthesised the best practices for community-based participatory research practices with Pacific Islanders. METHODS AND ANALYSIS:The reviewers will examine studies' titles, abstracts and full text, comparing eligibility to address discrepancies. For each eligible study, data extraction will be executed by two reviewers and one confirmation coder, comparing extracted data to address any discrepancies. Eligible data will be synthesised and reported in a narrative review assessing coverage and gaps in existing literature related to community-based participatory research with Pacific Islanders. DISCUSSION AND DISSEMINATION:The purpose of this review is to identify best practices used when conducting community-based participatory research with Pacific Islanders; it will also extrapolate where the gaps are in the existing literature. This will be the first scoping review on community-based participatory research with Pacific Islanders. To facilitate dissemination, the results of this scoping review will be submitted for publication to a peer-reviewed journal, presented at conferences and shared with community-based participatory research stakeholders.

SUBMITTER: McElfish PA

PROVIDER: S-EPMC5786128 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Best practices for community-engaged participatory research with Pacific Islander communities in the USA and USAPI: protocol for a scoping review.

McElfish Pearl Anna PA Ayers Britni L BL Purvis Rachel S RS Long Christopher R CR Sinclair Ka'imi K Esquivel Monica M Steelman Susan C SC

BMJ open 20180124 1

<h4>Introduction</h4>Community-based participatory research is a partnership approach to research that seeks to equally involve community members, organisational representatives and academic partners throughout the research process in a coequal and mutually beneficial partnership. To date, no published article has synthesised the best practices for community-based participatory research practices with Pacific Islanders.<h4>Methods and analysis</h4>The reviewers will examine studies' titles, abst ...[more]

PMID: 29371285

Similar Datasets

Project description:BackgroundFacilitation is an implementation strategy that supports the uptake of evidence-based practices. Recently, use of virtual facilitation (VF), or the application of facilitation using primarily video-based conferencing technologies, has become more common, especially since the COVID-19 pandemic. Thorough assessment of the literature on VF, however, is lacking. This scoping review aimed to identify and describe conceptual definitions of VF, evaluate the consistency of terminology, and recommend "best" practices for its use as an implementation strategy.MethodsWe conducted a scoping review to identify literature on VF following the PRISMA-ScR guidance. A search of PubMed, Embase, Web of Science, and CINAHL databases was conducted in June 2022 for English language articles published from January 2012 through May 2022 and repeated in May 2023 for articles published from January 2012 through April 2023. Identified articles, including studies and conference abstracts describing VF, were uploaded into Covidence and screened independently by two reviewers. Data extraction was done by two reviewers in Microsoft Excel; additionally, studies were evaluated based on the Proctor et al. (2013) reporting guidelines for specifying details of implementation strategies.ResultsThe search strategy identified 19 articles. After abstract and full-text screening, eight studies described by 10 articles/abstracts were included in analysis. Best practices summarized across studies included (1) stakeholder engagement, (2) understanding the recipient's organization, (3) facilitator training, (4) piloting, (5) evaluating facilitation, (6) use of group facilitation to encourage learning, and (7) integrating novel tools for virtual interaction. Three papers reported all or nearly all components of the Proctor et al. reporting guidelines; justification for use of VF was the most frequently omitted.ConclusionsThis scoping review evaluated available literature on use of VF as a primary implementation strategy and identified significant variability on how VF is reported, including inconsistent terminology, lack of details about how and why it was conducted, and limited adherence to published reporting guidelines. These inconsistencies impact generalizability of these methods by preventing replicability and full understanding of this emerging methodology. More work is needed to develop and evaluate best practices for effective VF to promote uptake of evidence-based interventions.Trial registrationN/A.

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

Best practices for community-engaged participatory research with Pacific Islander communities in the USA and USAPI: protocol for a scoping review.

Publications

Best practices for community-engaged participatory research with Pacific Islander communities in the USA and USAPI: protocol for a scoping review.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets