Through the Lens of the Donabedian Structure-Process-Outcomes Model: Lessons Learned and Recommendations for Interprofessional Collaboration in Higher Education
Bibliographic record
Abstract
Through interprofessional collaboration (IPC), scholars with diverse knowledge and skills enhance the integration and communication of ideas and services in the pursuit of high-quality education. This article explores the structure, process, and outcomes of IPC and proposes recommendations to create a culture of interprofessional collaboration in higher education. Semi-structured interviews were conducted with 17 participants with extensive IPC experience in a research-intensive university. Results regarding IPC were organized around structure-related factors, including physical structure, organizational characteristics, external and internal factors, and group structure, as well as process-related factors, which include intrapersonal, interpersonal, and institutional facilitators and barriers. Outcomes included intrapersonal, interpersonal, and institutional, including drawbacks and benefits. Structure-process-outcomes of IPC inform recommendations to strategically create a culture of IPC in higher education. Transformative culture change begins with the identification of champions of IPC, who spearhead the implementation of IPC goals within an organization’s strategic plan. Policies, procedures, and resources of an organization are needed for successful interprofessional collaborations.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.048 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.018 | 0.024 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".