Research-related attitudes among Chinese medicine students at a Canadian college: a mixed-methods study
Bibliographic record
Abstract
BACKGROUND: Previous studies have suggested that American Chinese medicine students' research interest declines as their training progresses. Many students further express low confidence in the congruence ('model validity') of bioscientific research methods in relation to the Chinese medicine paradigm. However, prior research has not assessed the impacts of research-related coursework on student perspectives in this regard. METHODS: First-, second- and third-year Chinese medicine students were surveyed regarding their research-related views. Final year students were re-surveyed after completing the research course. Qualitative analyses of the participating students' coursework were also undertaken. RESULTS: Over 80% of all participants showed high research interest and engagement, and viewed research as both relevant to clinical practice and important for the profession's socioeconomic legitimation. Male students were significantly more likely to view scientific evidence as improving the quality of Chinese medicine care (p = 0.021). A view that conventional research methods have low model validity for Chinese medicine interventions was higher among third year students than those in their first or second years of study (p = 0.001). Research coursework appeared to increase self-assessed research interest and skill. Concern regarding model validity was strongly evident in student coursework. CONCLUSION: Research-related curricular interventions in the Chinese medicine field should directly address model validity, as it is of significant interest to a majority of students.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".