Student-led interprofessional global health course: learning impacts during a global crisis
Bibliographic record
Abstract
BACKGROUND: This study assesses the impact of the Interprofessional Global Health Course (IPGHC) on students' fundamental global health knowledge and personal viewpoints on global health domains. It explores the evolution of students' understanding of global health specifically in relation to the COVID-19 pandemic. METHODS: Ninety-nine students were selected from 123 McGill student applicants based on their motivation and commitment to take part in IPGHC's ten-week 2020 curriculum. These IPGHC students were eligible to participate in the study. The study's design is sequential explanatory mixed methods. The cross-sectional survey (quantitative phase) appraises students' global health learning outcomes using pre- and post-course surveys, with the use of 5-point Likert-scale questions. The descriptive qualitative survey (qualitative phase) further explores the impact of IPGHC on student's understanding of global health and the reflections of students on the COVID-19 pandemic after IPGHC. The post-course survey included a course evaluation for quality improvement purposes. RESULTS: Of the 99 students, 81 students across multiple undergraduate and graduate disciplines participated in the study by completing the course surveys. Mean knowledge scores of the following 11 global health topics were increased between pre- and post-course survey: Canadian Indigenous health (P < 0.001), global burden of disease (P < 0.001), global surgery (P < 0.001), infectious diseases and neglected tropical diseases (P < 0.001), refugee and immigrant health (P < 0.001), research and development of drugs (P < 0.001), role of politics and policies in global health (P = 0.02), role of technology in global health (P < 0.001), sexual violence (P < 0.001), systemic racism in healthcare (P = 0.03), and trauma in the global health context (P < 0.001). A positive change in student viewpoints was observed in response to questions regarding their perception of the importance of global health education in their own professional health care programs (P < 0.001), and their understanding of the roles and responsibilities of other healthcare professionals (P < 0.001). In the post-course survey open-ended questions, students exemplified their knowledge gained during the course to create a more informed definition of global health. Several recurring themes were identified in the student reflections on the COVID-19 pandemic, notably policy and politics, followed by access to healthcare and resources. CONCLUSION: This study emphasizes the need for interprofessional global health education at the university level and demonstrates how rapidly global health learners can apply their knowledge to evolving contexts like the COVID-19 pandemic.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".