The Definitions and Conceptualizations of the Practice Context in the Health Professions: A Scoping Review
Bibliographic record
Abstract
INTRODUCTION: Health care professionals work in different contexts, which can influence professional competencies. Despite existing literature on the impact of context on practice, the nature and influence of contextual characteristics, and how context is defined and measured, remain poorly understood. The aim of this study was to map the breadth and depth of the literature on how context is defined and measured and the contextual characteristics that may influence professional competencies. METHODS: A scoping review using Arksey and O'Malley's framework. We searched MEDLINE (Ovid) and CINAHL (EBSCO). Our inclusion criteria were studies that reported on context or relationships between contextual characteristics and professional competencies or that measured context. We extracted data on context definitions, context measures and their psychometric properties, and contextual characteristics influencing professional competencies. We performed numerical and qualitative analyses. RESULTS: After duplicate removal, 9106 citations were screened and 283 were retained. We compiled a list of 67 context definitions and 112 available measures, with or without psychometric properties. We identified 60 contextual factors and organized them into five themes: Leadership and Agency, Values, Policies, Supports, and Demands. DISCUSSION: Context is a complex construct that covers a wide array of dimensions. Measures are available, but none include the five dimensions in one single measure or focus on items targeting the likelihood of context influencing several competencies. Given that the practice context plays a critical role in health care professionals' competencies, stakeholders from all sectors (education, practice, and policy) should work together to address those contextual characteristics that can adversely influence practice.
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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 | 0.034 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.028 | 0.036 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.004 |
| 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 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".