Scoping review of patients’ attitudes about their role and behaviours to ensure safe care at the direct care level
Bibliographic record
Abstract
BACKGROUND: To improve harm prevention, patient engagement in safety at the direct care level is advocated. For patient safety to most effectively include patients, it is critical to reflect on existing evidence, to better position future research with implications for education and practice. METHODS: As part of a multi-phase study, which included a qualitative descriptive study (Duhn & Medves, 2018), a scoping review about patient engagement in safety was conducted. The objective was to review papers about patients' attitudes and behaviours concerning their involvement in ensuring their safe care. The databases searched included MEDLINE, CINAHL and EMBASE (year ending 2019). RESULTS: This review included 35 papers about "Patient Attitudes" and 125 papers about "Patient Behaviours"-indicative of growing global interest in this field. Several patterns emerged from the review, including that most investigators have focused on a particular dimension of harm prevention, such as asking about provider handwashing, and there is less known about patients' opinions about their role in safety generally and how to actualize it in a way that is right for them. While patients may indicate favourable attitudes toward safety involvement generally, intention to act or actual behaviours may be quite different. CONCLUSION: This review, given its multi-focus across the continuum of care, is the first of its kind based on existing literature. It provides an important international "mapping" of the initiatives that are underway to engage patients in different elements of safety and their viewpoints, and identifies the gaps that remain.
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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 | 0.020 | 0.101 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.021 | 0.022 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".