High Psychosocial Work Demands, Decreased Well-Being, and Perceived Well-Being Needs Within Veterinary Academia During the COVID-19 Pandemic
Bibliographic record
Abstract
Higher psychosocial work demands in veterinary and academic professions are associated with decreased occupational, physical, and mental well-being. COVID-19 introduced far-reaching challenges that may have increased the psychosocial work demands for these populations, thereby impacting individual- and institutional-level well-being. Our objective was to investigate the psychosocial work demands, health and well-being, and perceived needs of faculty, staff, residents and interns at the Ontario Veterinary College, in Ontario, Canada, during COVID-19. A total of 157 respondents completed a questionnaire between November 2020 and January 2021, that included the Third Version of the Copenhagen Psychosocial Questionnaire (COPSOQ-III) and open-text questions on perceived needs for well-being. Results showed that COPSOQ-III dimensions of quantitative demands, recognition, sense of community, burnout, stress, and depressive symptoms, were significantly worse in our study population than the Canadian norm. Quantitative and emotional demands, health and well-being (including depressive symptoms, stress, cognitive stress, somatic stress, and burnout), and work-life conflict were also reported to have worsened since the COVID-19 restrictions for most respondents. Females and caregivers had higher odds of experiencing increased work demands, and decreased health and well-being, compared to males and non-caregivers. However, male caregivers experienced worsened supervisor relations, compared to female caregivers. Social capital also worsened for clinical and part-time employees, compared to full-time and non-clinical employees. Respondents identified increased workload support, community-building, recognition of employees' capacities and personal needs, flexible work schedules, and consistent communication, as strategies to increase well-being during COVID-19 and generally. Overall, our findings suggest that COVID-19 has increased occupational demands, work-life conflicts, and decreased well-being in veterinary academia. Institutional-level interventions are discussed and recommended to aid individual and institutional well-being.
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".