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Paper 6: engaging racially and ethnically diverse interest holders in evidence syntheses

2024· review· en· W4403616350 on OpenAlexaff
Nila A Sathe, Colleen Ovelman, Naykky Singh Ospina, Omar Dewidar, Elizabeth Terhune, Damian Francis, Vivian Welch, Patricia Heyn, Tiffany Duque, Meera Viswanathan

Bibliographic record

VenueJournal of Clinical Epidemiology · 2024
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of OttawaBruyère
FundersRobert Wood Johnson Foundation
KeywordsEthnically diverseHealth equityEquity (law)Systematic reviewMEDLINEMedicinePsychologyBusinessPublic healthPolitical scienceEnvironmental healthNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: To inform methods for centering racial health equity in syntheses, we explored (1) how syntheses that assess health-related interventions and explicitly address racial health inequities have engaged interest holders and (2) guidance for engaging racially and ethnically diverse interest holders. STUDY DESIGN AND SETTING: We systematically identified evidence syntheses (searches limited to January 1, 2020, through January 25, 2023) and guidance documents (no search date limits) for this overview. From syntheses we extracted data on engagement rationale and processes and extracted approaches suggested from guidance documents. We summarized findings qualitatively. RESULTS: Twenty-nine of the 157 (18%) eligible syntheses reported using engagement. Syntheses typically lacked robust detail on why and how to use and structure engagement and outcomes/effects of engagement, though syntheses involving Indigenous populations typically included more detail. When reported, engagement typically occurred in early and later synthesis phases. We did not identify guidance documents that specifically intended to provide guidance for engaging racially/ethnically diverse individuals in syntheses; some related guidance described broader equity considerations or engagement in general. CONCLUSION: This review highlights gaps in understanding of the use of engagement in racial health equity-focused syntheses and in guidance specifically addressing engaging racially and ethnically diverse populations. Syntheses and guidance materials we identified reported limited data addressing the whys, hows, and whats (ie, rationale for, approaches to, resources needed and effects of) of engagement, and we lack information for understanding whether engagement makes a difference to the conduct and findings of syntheses and when and how engagement of specific populations may contribute to centering racial health equity. A more informed understanding of these issues, facilitated by prospective and retrospective descriptions of engagement of diverse interest holders, may help advance actionable guidance and reviews. PLAIN LANGUAGE SUMMARY: We identified evidence syntheses (a kind of research that identifies and summarizes findings of individual studies or publications to address research questions) that looked at studies of interventions to improve differences in effects on health for racial or ethnic populations to see (1) if and how they incorporated perspectives of interest holders, people with an interest in the subject being studied; (2) what guidance for how to engage or involve racially or ethnically diverse interest holders exists. We found that 29 of 157 syntheses addressing interventions to improve differences in effects on health reported involving interest holders but typically did not provide much detail about how to involve people. Syntheses that involved Indigenous people usually had more information, but overall, the syntheses did not have much information about how to involve people and what the impact of involving them may be. We did not find guidance information that specifically set out to provide information about engaging racially/ethnically diverse individuals in syntheses; some related guidance described considerations about involving people in syntheses in general. This review highlights gaps in understanding of how to engage people in racial health equity-focused syntheses and in guidance specifically addressing engaging racially and ethnically diverse populations. Syntheses and guidance materials we identified reported limited information about whys, hows, and whats (ie, reasons to use, how to do, and resources needed and effects of) related to engagement, and we lack information to help understand whether engagement makes a difference in doing syntheses and when and how engagement of specific populations may help to address racial health equity.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.232
metaresearch head score (Gemma)0.441
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score0.947

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2320.441
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0060.007
Science and technology studies0.0020.004
Scholarly communication0.0090.011
Open science0.0030.010
Research integrity0.0100.008
Insufficient payload (model declined to judge)0.0260.003

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 head0.981
GPT teacher head0.835
Teacher spread0.146 · 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

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractno

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