USING PROFESSIONAL PRACTICE MODELS: A PHENOMENOGRAPHIC STUDY OF PROFESSIONAL PRACTICE EXPERTS' CONCEPTIONS
Bibliographic record
Abstract
<strong>Abstract</strong> Health care practice environments are central to the safety and quality of patient care. Hospitals often develop and implement a professional practice model (PPM) to improve practice environments. In the United States, magnet hospital designation is a driving force in PPM implementation. In Ontario, Canada, despite the lack of magnet hospital designation, many hospitals have implemented PPMs. There appear to be differences in how PPMs are implemented in Ontario. This phenomenographic study examined professional practice experts’ conceptions of PPM implementation and use in Ontario acute care hospitals. The findings indicate that PPM implementation is a dynamic and emergent phenomenon that occurs in cyclical phases of growth and reduced activity. Seven categories of PPM use are described (a) creating alignment/consistency, (b) supporting evidence-based practice, (c) enabling interprofessional practice, (d) enhancing professional accountability, (e) enabling patient-centred care, (f) creating/ strengthening linkages, and (g) strategic positioning of professional practice. Categories exhibited hierarchical relationships, with more foundational uses providing support for higher level uses. Three structural themes are identified (a) model design/structure, (b) professional practice leadership, and (c) organizational support. These themes work individually and synergistically, within and across the categories to influence use and potential impact of the PPM. Progressively fuller and more complex use of the PPM appears to occur under increasingly intense influence of the structural themes. The analysis provides unique information about relationships within and among categories of PPM use. This provides insight regarding how organizations might maximize return on investment with PPM implementation. Seven recommendations are identified.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".