Meaningful work and well‐being: a study of the positive side of veterinary work
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: Mental health is a growing concern in many healthcare professions, including veterinary medicine, as research suggests that veterinarians report higher levels of distress, burnout and suicidal ideation than other healthcare occupations and the general public. A recent literature review found that about twice as many articles published on veterinary wellness refer to the negative aspects of mental health (eg, stress and depression) compared with the positive aspects of well-being. Little attention has been devoted to examining the positive aspects of veterinarians' work, and few models have been developed to explain their well-being. This paper empirically assesses a veterinary model of work-derived well-being based on the theory of eudaimonia. Eudaimonic well-being reflects having fulfilling work that contributes to the greater good. Three core clusters of job characteristics are hypothesised relevant to veterinarian well-being that include: actualising self, helping others (animals or people) and a sense of belonging (to team or profession). In addition, meaningful work is proposed as the mechanism through which situational job characteristics may exert a positive influence on well-being. METHODS: Survey data from 376 veterinarians in clinical practice were analysed using path analysis. DISCUSSION: Meaningful work is important in understanding the well-being of veterinarians. Job characteristics (self-actualising work, helping animals and people and a sense of belonging) contribute to a sense of meaningful work, which in turn is related to eudaimonic well-being. Excessive job demands (work overload, financial demands and physical health risks) appear less relevant in understanding meaningful work but are clearly important in having negative consequences for veterinarians' well-being.While strategies that cultivate meaningful work may be effective in nurturing veterinarians' well being, several limitations of this study should be noted. First, due to the cross-sectional data, definitive statements about the causal ordering of variables cannot be made. Second, the data were derived from a single source such that monomethod bias may be an issue. Third, the data rely on self-report measures and the responses may be influenced by social desirability or response biases. Lastly, while the sample may be representative of the veterinarians throughout a large geographic area in Canada, it may not represent the work arrangements of veterinarians in other countries. CONCLUSIONS: The significance of these findings is that they may shift research attention from focusing on the harmful, demanding aspects of veterinary work to better understanding the deeply meaningful aspects that improve veterinarians' well-being. In addition, the results may stimulate consideration of strategies that move beyond individual-level interventions that focus on veterinarians adopting better coping strategies and becoming more resilient. This may lead to adopting organisational and occupational-level strategies that can involve promoting more positive and supportive workplace cultures and developing more professional resources for promoting wellness and meaning in the profession of veterinary medicine.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it