Interprofessional education can improve learning outcomes on school health among nursing students in Thailand
Bibliographic record
Abstract
Background and objective: Interprofessional education (IPE) is an important step in advancing the education of health professionals. This study aimed to evaluate IPE learning outcomes and satisfaction of students that participated in a school-health program. The program was delivered as a joint collaborative topic among nursing, dental public health, and public health students. We also sought to examine students’ understanding of roles and teamwork, as well as their satisfaction with IPE.Methods: This study had a quasi-experimental design. Third-year nursing students were randomly divided into 2 groups, the IPE and non-IPE groups. All third-year dental public health students and public health students were enrolled in the IPE group. All IPE students were stratified and randomized into interprofessional teams of ten or eleven students. The program included 3 modules: 1) foundational workshops for IPE role clarification in the school-health program and situation analysis of school-health problems, 2) project planning and implementation, and 3) evaluation and sharing. Non-IPE nursing students also received the same 3 modules of the school-health learning program without working in the interprofessional team. A pretest and posttest on school-health theoretical content were completed by both groups of nursing students. In the IPE group, we collected data regarding the understanding of students’ roles within their teams before and after the course. Satisfaction with IPE learning was only asked after the course. Results: The IPE group (n = 164) consisted of 60 nursing, 59 dental public health, and 45 public health students. There were 63 nursing students in the non-IPE group. For knowledge on school health, the nursing students in the non-IPE group had a significantly higher pretest score compared to the IPE group; while there was no significant difference in post-test scores between both groups. All aspects of the interprofessional collaboration among the three health professional student groups in the IPE group increased, with a significant difference for 4 out of 6 aspects. Students were satisfied with the IPE program and wished to extend their time spent in the program.Conclusions: IPE learning provides a better understanding of different healthcare roles and enhanced teamwork between multidisciplinary teams. Incorporating IPE as a learning strategy is recommended for health professional students.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".