Choosing a Career in Psychiatry: Factors Associated with a Career Interest in Psychiatry among Canadian Students on Entry to Medical School
Bibliographic record
Abstract
OBJECTIVE: To report the proportion of Canadian medical students interested in a career in psychiatry at medical school entry and to describe the unique demographics and career influences associated with this early interest. METHODS: From 2001 to 2004, during the first 2 weeks of medical school, a 41-item survey of career choice, demographics, and attitudes toward various aspects of medical practice was distributed to all students in 18 classes at 8 Canadian medical schools. Associations between early career interest, demographics, and career influences were explored. RESULTS: Of the 2096 completed surveys, 3.2% of students named psychiatry as their first career choice. While 34% of students considered psychiatry a possible career option, 54.9% stated that they had not considered this option. Students interested in psychiatry were more likely than other students to have an undergraduate education in the arts, to have close family or friends practicing medicine, and to have worked voluntarily with people with mental illness. Students interested in psychiatry had a lesser social orientation than students interested in family medicine but had a greater social orientation and lesser hospital orientation than students interested in other specialties. CONCLUSIONS: Enhanced psychiatric care may be aided by the selective recruitment into medical school of students with a demonstrated empathy toward people with mental illness, an educational background in the arts, and a strong social orientation. As career influences change throughout medical school, participants in this study will be re-surveyed at graduation to better understand the evolution of career choice decision-making throughout medical school.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".