Predictors of Success and Satisfaction in the Practice of Psychiatry: A Preliminary Follow-up Study
Bibliographic record
Abstract
BACKGROUND: Few studies have examined the predictors of psychiatrists' perceived success and personal satisfaction with their careers. The present study examines self-reported success and personal satisfaction with their careers in a cohort of psychiatrists followed for more than 20 years. METHODS: A total of 29 psychiatrists, all of whom had participated in a study during their residency 21 to 24 years earlier, completed a self-report questionnaire. The first set of questions addressed the type and characteristics of their professional practice; the second set assessed aspects of their nonprofessional practice; and the third set assessed aspects of their nonprofessional, personal lifestyles. The personality traits of neuroticism and extraversion were assessed during the residency years and were used as predictors. Composite measures of self-perceived external success and personal satisfaction were computed. Regression models were constructed to determine the best predictors of these composite measures. RESULTS: Neuroticism proved to be a significant predictor of external success but not of personal satisfaction, with higher scores predicting a lower rating of perceived external success. There were 2 practice characteristics--involvement with research and practising from an orientation other than psychoanalytic--that predicted perception of success. One personal lifestyle characteristic--the perception that one's nonprofessional life sustained professional life--also predicted perception of success. The best predictor of personal satisfaction was overall satisfaction with nonprofessional aspects of life. CONCLUSIONS: Personality, nonprofessional social support, and engaging in research are associated with greater perceived success and personal satisfaction with a career in psychiatry.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".