What Factors Influence the Perceptions of Job Satisfaction in Registered Veterinary Nurses Currently Working in Veterinary Practice in the United Kingdom?
Bibliographic record
Abstract
The Royal College of Veterinary Surgeons is dedicated to empowering registered veterinary nurses (RVNs) and ensuring that they are valued members of the workforce within the United Kingdom. However, this is not always reported by the RVNs themselves, who state that although they derive satisfaction from working with animals and within a profession that makes a difference, there are areas in which they are not currently satisfied, such as pay scale and recognition. Responses to a questionnaire were analyzed using a mixed-methods design to determine current factors affecting job satisfaction utilizing a deductive and inductive approach. The questionnaire reached 205 RVNs currently working in practice within the UK; respondents were divided between remaining at their current practice ( n = 101) and finding alternative employment ( n = 80). Those who stated that they were happy in their job role were more likely to want to remain there. Themes relating to positive and negative job satisfaction were reported and used to devise strategies employers and employees could use to increase or maintain RVNs’ overall satisfaction. More focus is needed on support and communication within veterinary practices, support for appropriate delegation linked to recognition of the RVN role, and support from educators to prepare students for the RVN role. Although the questionnaire did not reach the targeted sample size, responses agree with previous data indicating that changes made to the RVN role in the UK have not sufficiently improved job satisfaction scores.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 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".