Organizational participatory research: a systematic mixed studies review exposing its extra benefits and the key factors associated with them
Bibliographic record
Abstract
BACKGROUND: In health, organizational participatory research (OPR) refers to health organization members participating in research decisions, with university researchers, throughout a study. This non-academic partner contribution to the research may take the form of consultation or co-construction. A drawback of OPR is that it requires more time from all those involved, compared to non-participatory research approaches; thus, understanding the added value of OPR, if any, is important. Thus, we sought to assess whether the OPR approach leads to benefits beyond what could be achieved through traditional research. METHODS: We identified, selected, and appraised OPR health literature, and at each stage, two team members independently reviewed and coded the literature. We used quantitative content analysis to transform textual data into reliable numerical codes and conducted a logistic regression to test the hypothesis that a co-construction type OPR study yields extra benefits with a greater likelihood than consultation-type OPR studies. RESULTS: From 8873 abstracts and 992 full text papers, we distilled a sample of 107 OPR studies. We found no difference between the type of organization members' participation and the likelihood of exhibiting an extra benefit. However, the likelihood of an OPR study exhibiting at least one extra benefit is quadrupled when the impetus for the study comes from the organization, rather than the university researcher(s), or the organization and the university researcher(s) together (OR = 4.11, CI = 1.12-14.01). We also defined five types of extra benefits. CONCLUSIONS: This review describes the types of extra benefits OPR can yield and suggests these benefits may occur if the organization initiates the OPR. Further, this review exposes a need for OPR authors to more clearly describe the type of non-academic partner participation in key research decisions throughout the study. Detailed descriptions will benefit others conducting OPR and allow for a re-examination of the relationship between participation and extra benefits in future reviews.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| grok | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| opus | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.202 | 0.421 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.022 | 0.026 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".