Attitudes of Undergraduate Social Work Students Toward Interprofessional Health Care Practice and Interprofessional Health Care Education
Bibliographic record
Abstract
In 2005, the Centre for Collaborative Health Professional Education at Memorial University in Canada commenced an inquiry into the interprofessional education (IPE) of social work students. In the 2005/2006 academic year, undergraduate social work students were introduced to an IPE program at Memorial University for the first time. This interdisciplinary initiative brought together students from pharmacy, nursing, medicine, and social work to develop and encourage interprofessional educational activities with the purpose of increasing collaborative patient-centered practice competencies of students and professionals (Sharpe & Curran, 2006). In the subsequent three academic years (2005/2006, 2006/2007, 2007/2008) Bachelor of Social Work (BSW) students explored a variety of IPE modules. This paper summarizes the available literature on the topic of IPE and reports on data collected from three cohorts of undergraduate social work students regarding their attitudes toward interdisciplinary team practice. Data collected are in relation to the Health and Wellbeing of Children module, one of the five module topics in which these students participated over the three-year period. It is proposed that by understanding student attitudes as they are evidenced at this early stage of professional development, valuable information will be provided to educators to inform best practices in the teaching and learning of interprofessional practice skills within the discipline of social work. Finally, the authors provide suggested directions for future research.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".