Towards an assessment for organizational participatory research health partnerships: A systematic mixed studies review with framework synthesis
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.
Bibliographic record
Abstract
Within the health sciences, organizational participatory research (OPR) is defined as a blend of research and action, in which academic researchers partner with health organization members. OPR is based on a sound partnership between all stakeholders to improve organizational practices. However, little research on the evaluation of OPR health partnership exists. This systematic mixed studies review sought to produce a new theoretical model that structures the evaluation of the OPR processes and related outcomes of OPR health partnerships. Six bibliographic databases were searched together with grey literature sources for OPR health partnership evaluation questionnaires. Six questionnaires were included, from which a pool of 95 OPR health partnership evaluation items were derived. The included questionnaires were appraised for the quality of their origin, development and measurement properties. A framework synthesis was performed using an existing OPR framework by organizing questionnaire items in a matrix using a hybrid thematic analysis. This led to our proposed Organizational Participatory Research Evaluation Model (OPREM) that includes three axes, Trust, Collective Learning and Sustainability (with specific dimensions) and 95 items. This model provides information to help stakeholders comprehensively structure the evaluation of their partnerships and subsequent improvement; thus, potentially helping to improve health organization practices.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.084 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it