Workplace psychosocial factors are associated with veterinary employees’ organizational commitment to their current veterinary hospital
Bibliographic record
Abstract
OBJECTIVE: To classify a sample of veterinary professionals into distinct organizational-commitment profiles and to identify associations between psychosocial aspects of the workplace and organizational-commitment profile membership. SAMPLE: 487 veterinary employees who worked for a corporate veterinary organization in Canada. METHODS: Survey components measured for this study included the Three-Component Model (TCM) Employee Commitment Survey-Revised, the Copenhagen Psychosocial Questionnaire, and participant demographics. First, latent profile analysis was used to identify distinct organizational-commitment profiles based on 3 components of commitment (affective, continuance, and normative). Next, the Mann-Whitney U test was used to compare participants' intention to leave their hospital on the basis of organizational-commitment profile. Finally, logistic regression was performed to assess the association between perceived psychosocial workplace characteristics and organizational-commitment profile membership. RESULTS: 2 organizational-commitment profiles were identified: Affective/Normative (AC/NC) Dominant (n = 388) and Mid-Low Commitment (99). Participants in the Mid-Low Commitment Profile had a significantly higher intention-to-leave score (median, 3.0) than participants in the AC/NC Dominant Profile (median, 2.0; P < .001). Psychosocial factors found to predict membership in the AC/NC Dominant Profile included the following: influence at work (OR, 2.08; P < .001), meaning of work (OR, 1.38; P = .067), rewards/recognition (OR, 1.63; P = .007), and quality of leadership (OR, 1.85; P = .0003). Members of the AC/NC Dominant Profile also experienced greater work-life conflict (OR, 1.65; P = .003) compared to the Mid-Low Commitment Profile. CLINICAL RELEVANCE: Findings identified potential psychosocial aspects of the workplace that can be considered to support more desirable organizational-commitment profiles that are likely to lead to favorable outcomes for veterinary practices and their employees.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".