A scoping review to improve conceptual clarity of interprofessional interventions
Bibliographic record
Abstract
Interprofessional education (IPE) and interprofessional collaboration (IPC) have been identified in health education and health care as playing an important role in improving health care services and patient outcomes. Despite a growth in the amount of research in these areas, poor conceptualizations of these interprofessional activities have persisted. Given the conceptual challenges, a scoping review of the interprofessional field was undertaken to map the literature available in order to identify key concepts, theories and sources of evidence. The objective of this review was to develop a theoretically based and empirically tested understanding of IPE and IPC. A total of 104 studies met the criteria and were included for analysis. Studies were examined for their approach to conceptualization, implementation, and assessment of their interprofessional interventions. Half of the studies were used for interprofessional framework development and half for framework testing and refinement. The final framework contains three main types of interprofessional interventions: IPE; interprofessional practice; and interprofessional organization; and describes the nature of each type of intervention by stage, participants, intervention type, interprofessional objectives, and outcomes. The outcomes are delineated as intermediate, patient, and system outcomes. There was very limited use of theory in the studies, and thus theoretical aspects could not be incorporated into the framework. This study offers an initial step in mapping out the interprofessional field and outlines possible ways forward for future research and 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 | 0.064 | 0.206 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.051 | 0.040 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".