Choosing Psychiatry as a Career: Motivators and Deterrents at a Critical Decision-Making Juncture
Bibliographic record
Abstract
OBJECTIVE: To examine factors influencing the choice of psychiatry as a career between residency program application and ranking decision making. METHODS: Using an online questionnaire, applicants to the largest Canadian psychiatry residency program were surveyed about the impact of various factors on their ultimate decision to enter psychiatry residency training. RESULTS: Applicants reported that patient-related stigma was a motivator in considering psychiatry as a career, but that negative comments from colleagues, friends, and family about choosing psychiatry was a deterrent. Training program length, limited treatments, and insufficient clerkship exposure were noted as deterrents to choosing psychiatry, though future job prospects, the growing role of neuroscience, and diagnostic complexity positively influenced choosing psychiatry as a specialty. Research and elective time away opportunities were deemed relatively unimportant to ranking decisions, compared with more highly weighted factors, such as program flexibility, emphasis on psychotherapy, service- training balance, and training program location. Most applicants also reported continuing to fine tune ranking decisions between the application and ranking submission deadline. CONCLUSIONS: Stigma, exposure to psychiatry, diagnostic complexity, and an encouraging job market were highlighted as positive influences on the choice to enter psychiatry residency. Interview and information days represent opportunities for continued targeted recruitment activity for psychiatry residency programs.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".