The Readiness of Postgraduate Health Sciences Students for Interprofessional Education in Iran
Bibliographic record
Abstract
AIM: Interprofessional education has been recognized as an effective educational approach towards enabling students to provide comprehensive and safe team care for promotion of health outcomes of patients. This study was conducted in order to assess the readiness of postgraduate health science students for interprofessional education/learning, as well as identify barriers to the implementation of such an approach in Iran from the students' point of view. METHODS: This was a cross-sectional and descriptive-analytical study conducted in 2013 on 500 postgraduate students in three main professional groups: medical, nursing and other allied health professions across a number of Iranian Universities using the convenience sampling method. Quantitative Data were collected through self-administering the Readiness for InterProfessional Learning Scale (RIPLS) questionnaire with acceptable internal consistency (? = 0.86). The data were analyzed by SPSS18. Qualitative data were gathered by an open-ended questionnaire and analyzed by qualitative content analysis method. RESULTS: The mean score of the students' readiness (M=80, SD=8.6) was higher than the average score on the Scale (47.5). In comparison between groups, there was no statistically significant difference between groups in their readiness (p>0.05). Also four main categories were identified as barriers to implementation of interprofessional education from the students' point of view; the categories were an inordinately profession-oriented, individualistic culture, style of management and weak evidence. CONCLUSION: An acceptable degree of readiness and a generally favorable attitude among students towards interprofessional education show that there are appropriate attitudinal and motivational backgrounds for implementation of interprofessional education, but it is necessary to remove the barriers by long-term strategic planning and advancing of interprofessional education in order to address health challenges.
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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 | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".