Public and professional involvement in a systematic review investigating the impact of occupational therapy on the self-management of rheumatoid arthritis
Bibliographic record
Abstract
Introduction: Public and health professional involvement (PHPI) is essential in healthcare research yet uncommonly integrated into systematic reviews. We incorporated and evaluated PHPI in a mixed methods review of occupational therapy for self-management of rheumatoid arthritis (RA). Methods: Public partners were living with or caring for someone with RA. Our steering group comprised two public, two professionals (one occupational therapist, one rheumatologist), and one reviewer who planned the review’s PHPI (August 2021). Involvement was evaluated from public and health professional (PHP) perspectives using a survey and workshops (August–October 2022) exploring reasons for involvement, challenges and learning opportunities. Results: Alongside the steering group, 16 public and 6 professionals were involved throughout the review. Five public refined the search strategy, with three assisting in subsequent review activities. PHPs helped interpret findings during three public ( n = 12) and one professional workshop ( n = 4). Three occupational therapists and one public co-authored (ED) publications. In evaluation, PHPs felt valued and that their involvement was well-integrated. The researchers underestimated the time required for communicating and conducting PHPI in the review. Conclusions: PHPI is worthwhile, feasible and can be integrated within a systematic review. PHP partners considered participation valuable; researchers must prioritise time to prepare and communicate PHPI activities.
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How this classification was reachedexpand
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 | 0.138 | 0.349 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.005 |
| 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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".