Developing the First Pan-Canadian Survey on Patient Engagement in Patient Safety
Bibliographic record
Abstract
Abstract Background: Patient safety is a worldwide problem, and the patient contribution to mitigate the risk of patient harm is now recognized as a cornerstone to its solution. In order to understand the nature of integrating patients into patient safety and healthcare organizations and to monitor their integration, a Canadian survey tool has been co-constructed by patients, researchers and the Canadian Patient Safety Institute (CPSI). This questionnaire has been adapted from the French version of the patient engagement (PE) in patient safety (PS) questionnaire created for the province of Quebec, Canada. Methodology: The pan-Canadian PE in PS survey tool was developed in a five-step process: (1) a literature review and revision of the initial tool developed in the province of Quebec; (2) translation of the French questionnaire into an English version tool; (3) creation of a Canadian expert advisory group; (4) adaptation of the English version tool based on feedback from the expert advisory group (assessment and development of the construct’s dimensions, wording assessment and adaptation for pan-Canadian use, technical testing of the online platform for the survey); and (5) pilot testing and pre-validation of the tool before pan-Canadian use. Results and Conclusion: The pan-Canadian PE in PS survey tool comprises 5 sections: (1) demographic identification of the participants (Q1 to Q5); (2) general questions (Q6 to Q17); (3) the patient engagement process (experience level of participants and organizational incentives for PE in general) (Q18 to Q33); (4) PE in PS processes, such as current activities, strategies, structures, resources and factors (Q34 to Q67); and (5) the context and impact of PE in PS initiatives in Canadian healthcare organizations (CHOs) (Q68 to Q75), including outcome identification, improvement mechanisms and strategies, evaluation mechanisms, and indicators.
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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 | 0.020 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".