Survey of Interprofessional Collaboration Learning Needs and Training Interest in Health Professionals, Teachers, and Students: An Exploratory Study
Bibliographic record
Abstract
AbstractBackground: Researchers and trainers from many professions and settings have emphasized the importance of explicit training in interprofessional collaboration (IPC), but interest in and best practice for training for IPC remains unknown.Methods and Findings: A 33-item Internet-based survey was completed by 486 practicing professionals and students from the sectors of health and education. The survey assessed experiences and knowledge of IPC as well as interest in and barriers to further training in IPC. Overall, there was agreement among respondents regarding the importance of IPC. Satisfaction with IPC was associated with higher self-ratings of knowledge and skills related to IPC. Interest in further IPC training was high, especially for one- or two-day workshops or web-based modules. Qualitative analysis of responses to an open-ended question about IPC skills and knowledge revealed seven networks of common themes that can serve as a framework for training and theory development.Conclusions: IPC training should provide knowledge about IPC models and research, leadership styles, team stages, and conflict management, while also ensuring that training applies to the workplace or practicum placement. Efforts should be made to promote awareness of the need for training in areas where trainees already feel competent.
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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 | 0.035 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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".