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Record W2072679176 · doi:10.1155/2015/191856

Successful Strategies to Engage Research Partners for Translating Evidence into Action in Community Health: A Critical Review

2015· review· en· W2072679176 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental and Public Health · 2015
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsWestern UniversityMcGill University
FundersLawson Foundation
KeywordsAction (physics)MEDLINEPublic relationsMedicinePsychologyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVES: To undertake a critical review describing key strategies supporting development of participatory research (PR) teams to engage partners for creation and translation of action-oriented knowledge. METHODS: Sources are four leading PR practitioners identified via bibliometric analysis. Authors' publications were identified in January 1995-October 2009 in PubMed, Embase, ISI Web of Science and CAB databases, and books. Works were limited to those with a process description describing a research project and practitioners were first, second, third, or last author. RESULTS: Adapting and applying the "Reliability Tested Guidelines for Assessing Participatory Research Projects" to retained records identified five key strategies: developing advisory committees of researchers and intended research users; developing research agreements; using formal and informal group facilitation techniques; hiring co-researchers/partners from community; and ensuring frequent communication. Other less frequently mentioned strategies were also identified. CONCLUSION: This review is the first time these guidelines were used to identify key strategies supporting PR projects. They proved effective at identifying and evaluating engagement strategies as reported by completed research projects. Adapting these guidelines identified gaps where the tool was unable to assess fundamental PR elements of power dynamics, equity of resources, and member turnover. Our resulting template serves as a new tool to measure partnerships.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.102
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.955
GPT teacher head0.797
Teacher spread0.158 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it