Intellectual stimulation in family medicine: an international qualitative study of student perceptions
Bibliographic record
Abstract
BACKGROUND: Globally, medical schools struggle to ensure there is a sufficient number of graduates choosing family medicine as a career to meet societal needs. While factors impacting career choice are complex, one possible disincentive to choosing family medicine is the perception that it is less intellectually stimulating than specialty care. AIM: The study sought to elicit student views on intellectual stimulation in family medicine, and their understanding of academic family medicine. DESIGN & SETTING: This is a qualitative focus group study of volunteer students from the University of Calgary, Canada, and Newcastle University, UK. METHOD: Six focus groups were conducted with 51 participants. The data were analysed thematically. RESULTS: Students associated intellectual stimulation in family medicine with clinical practice. Intellectual stimulation was related to problem solving and the challenge of having to know a little about everything, along with clinical uncertainty and the need to be vigilant to avoid missing diagnoses. Student awareness of academic family medicine was limited, and students identified it with teaching rather than research. CONCLUSION: Promoting intellectual stimulation in family medicine requires educators to highlight the breadth and variety of knowledge required in family medicine, as well as the need to manage clinical uncertainty and to be vigilant to avoid missing diagnoses. Exposure to academic family medicine could enhance students' understanding and appreciation of the role of research in family medicine.
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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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".