Patient involvement in preparing health research peer-reviewed publications or results summaries: a systematic review and evidence-based recommendations
Bibliographic record
Abstract
BACKGROUND: There are increasing calls for patient involvement in sharing health research results, but no evidence-based recommendations to guide such involvement. Our objectives were to: (1) conduct a systematic review of the evidence on patient involvement in results sharing, (2) propose evidence-based recommendations to help maximize benefits and minimize risks of such involvement and (3) conduct this project with patient authors. METHODS: To avoid research waste, we verified that no systematic reviews were registered or published on this topic. We co-created, with patients, a PRISMA-P-compliant protocol. We included peer-reviewed publications reporting the effects of patient involvement in preparing peer-reviewed publications or results summaries from health research studies. We searched (9/10/2017) MEDLINE, EMBASE and the Cochrane Database of Systematic Reviews, and secondary information sources (until 11/06/2018). We assessed the risk of bias in eligible publications and extracted data using standardized processes. To evaluate patient involvement in this project, we co-created a Patient Authorship Experience Tool. RESULTS: All nine eligible publications reported on patient involvement in preparing publications; none on preparing results summaries. Evidence quality was moderate. A qualitative synthesis of evidence indicated the benefits of patient involvement may outweigh the risks. We have proposed 21 evidence-based recommendations to help maximize the benefits and minimize the risks when involving patients as authors of peer-reviewed publications. The recommendations focus on practical actions patient and non-patient authors can take before (10 recommendations), during (7 recommendations) and after (4 recommendations) manuscript development. Using the Patient Authorship Experience Tool, both patient and non-patient authors rated their experience highly. CONCLUSIONS: Based on a systematic review, we have proposed 21 evidence-based recommendations to help maximize the benefits and minimize the risks of involving patients as authors of peer-reviewed publications.
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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 | 0.400 | 0.670 |
| Meta-epidemiology (narrow) | 0.003 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.015 |
| Bibliometrics | 0.032 | 0.023 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.013 | 0.025 |
| Open science | 0.009 | 0.009 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".