Theory in quality improvement and patient safety education: A scoping review
Bibliographic record
Abstract
INTRODUCTION: Theory plays an important role in education programming and research. However, its use in quality improvement and patient safety education has yet to be fully characterized. The authors undertook a scoping review to examine the use of theory in quality improvement and patient safety education. METHODS: Eligible articles used theory to inform the design or study of a quality improvement or patient safety curriculum. The authors followed scoping review methodology and searched articles referenced in 20 systematic reviews of quality improvement and patient safety education, or articles citing one of these reviews, and hand searched eligible article references. Data analysis involved descriptive and interpretive summaries of theories used and the perspectives the theories offered. RESULTS: Eligibility criteria were met by 28 articles, and 102 articles made superficial mention of theory. Eligible articles varied in professional group, learning stage and journal type. Theories fell into two broad categories: learning theories (n = 20) and social science theories (n = 11). Theory was used in the design (n = 12) or study (n = 17) of quality improvement and patient safety education. The range of theories shows the opportunity afforded by using more than one type of theory. DISCUSSION: Theory can guide decisions regarding quality improvement and patient safety education practices or play a role in selecting a methodology or lens through which to study educational processes and outcomes. Educators and researchers should make deliberate choices around the use of theory that relates to aspects of an educational program that they seek to illuminate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.046 | 0.141 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.030 | 0.035 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".