Development and pre-testing of the Patient Engagement In Research Scale (PEIRS) to assess the quality of engagement from a patient perspective
Bibliographic record
Abstract
OBJECTIVES: To develop and examine the content and face validity of the Patient Engagement In Research Scale (PEIRS) for assessing the quality of patient engagement in research projects from a patient partner perspective. METHODS: Our team of researchers and patient partners conducted a mixed qualitative and quantitative study in three phases. Participants were English-speaking adult patients (including informal caregivers, family members, and friends) with varying experiences as partners in research projects in Canada. 1) Questionnaire items were generated following thematic analysis of in-depth interviews and published literature. 2) A three-round e-Delphi survey process via email correspondence was undertaken to refine and select the items for a provisional PEIRS. 3) Two rounds of cognitive interviewing elicited participants' understanding and opinions of each item and the structure of the PEIRS. RESULTS: One hundred and twenty items were generated from 18 interviews and organized across eight themes of meaningful engagement of patients in health research to form an initial questionnaire. The e-Delphi survey and cognitive interviewing each included 12 participants with a range of self-reported diseases, health-related conditions, and use of healthcare services. The e-Delphi survey yielded a 43-item provisional PEIRS. The PEIRS was then reduced to 37 items organized across seven themes after 1) refinement of problems in its instructions and items, and 2) the combining of two themes into one. CONCLUSIONS: We developed a 37-item self-reported questionnaire that has demonstrated preliminary content and face validity for assessing the quality of patient engagement in research.
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".