Analysis of Canadian Physician Obituaries Between 2000 and 2023 to Investigate Trends in Death Between Specialties: A Retrospective Cross‐Sectional Study
Bibliographic record
Abstract
ABSTRACT Objectives A physician's work environment varies greatly depending on their medical specialty. As such, it may dictate their stress levels, work‐life balance, satisfaction, and, ultimately, expected age of death. This paper aims to determine trends in Canadian physician deaths and determine the median age of death for different specialties. Methods We examined physician obituaries from the Canadian Medical Association Journal ( CMAJ ) published between 2000 and 2023, extracting age at death and medical specialty. Results The median age of death for doctors had a steady incline between 1999 and 2023 with a median age of 80 years. Careers in psychiatry ( p = 0.020, 95% confidence interval [CI] [1.00, 4.00]) and emergency medicine ( p = 0.025, 95% CI [7.00, 26.00]) were associated with decreased average ages of death, while careers in surgery ( p < 0.001, 95% CI [−4.00, −2.00]), internal medicine ( p = 0.038, 95% CI [−3.00, −1.00]), and public health ( p = 0.016. 95% CI [−9.00, −2.00]) correlated with older ages of death. Of the statistically significant specialties, emergency medicine physicians had the lowest median age at death (59 years) while surgery and public health had the highest (81.5 and 83.5, respectively). Conclusion Our findings indicate that the median age of death differs across different medical specialties. Moving forward, the CMAJ should report physician obituaries consistently in a standardized format as it holds the most extensive obituary dataset despite missing significant data between 2008 and 2022.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".