Safety participation at the direct care level: Results of a patient questionnaire
Bibliographic record
Abstract
Understanding how patients can be engaged in safety-related activities at the direct care level is of current relevance given global efforts to reduce harm in hospitals. As part of a multiphase study, including a descriptive, exploratory qualitative study (Duhn & Medves, 2018), patients were asked to respond to a brief questionnaire to quantify how they viewed their patient-reported safety participation behaviours while in hospital. This paper is a summary of those responses. The 8-item questionnaire was, in part, used to help address a secondary research question of the larger qualitative study, specifically: What behaviours do patients report in promoting their safety while receiving care in hospital? Patients completed the questionnaire at the end of the face-to-face in-hospital interviews. Twenty-eight adult inpatients completed the questionnaire. Fifteen participants indicated that they ‘always’ or ‘usually’ checked their hospital medications; this was the second lowest rated activity. Most participants (n=20) believed they could rely on their knowledge and alertness to protect them from health-care error. Seventeen participants were in the high participation category. Given the prevalence of medication errors, patient involvement warrants further examination, including system supports to increase feasibility. Overall, a standardized, valid and reliable patient engagement in safety measure for the direct care level is required. Experience Framework This article is associated with the Policy & Measurement lens of The Beryl Institute Experience Framework. (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".