Impact of the COVID-19 Pandemic on Retirement Among Canadian Otolaryngologists
Bibliographic record
Abstract
Introduction Otolaryngologists were among the physicians with the highest risk of exposure to SARS-CoV-2, and more than half of them reported anxiety and distress during the pandemic. Consequences of this experience on retirement plans among otolaryngologists are unknown. This study aimed to describe the effect of the pandemic on retirement plans among otolaryngologists. Methods A cross-sectional survey assessed retirement plans of physicians in the Canadian Society of Otolaryngology-Head and Neck Surgery (CSOHNS) between May and June 2023. Participants were recruited through CSOHNS membership lists. Respondents shared demographic information and rated 4 pandemic-related factors and 13 independent factors on a 5-point Likert scale from least important to most important in influencing retirement. Results Eighty-two members responded, of which 20 (24.4%) were females. All female participants were 65 or younger, whereas 25 (40.3%) males were 65 or older. Half of the participants were in academic practice; 39% reported no change to their anticipated retirement date prior to the pandemic, whereas 25% reported either earlier or later dates. A greater proportion of female otolaryngologists reported earlier dates of retirement than originally planned compared with males (40% vs 19.3%). The factors most commonly rated as “important” were the desire for time with loved ones (mean: 3.82, SD: 1.179), the desire to improve their quality of life (mean: 3.65, SD: 1.344), and increased workload (mean: 3.26, SD: 1.210). Significant differences were observed between genders and age groups (≤55 years vs >55 years) regarding increased workload, desire for improved quality of life, personal and loved ones’ health concerns, pandemic-related concerns, psychological/emotional issues, and burnout ( P < .05). Conclusions Pandemic-related factors play a limited role in retirement decisions made by otolaryngologists. More females reported earlier retirement dates after the pandemic, which may further exacerbate preexisting gender inequalities in the otolaryngology workforce.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".