A comparative study of job satisfaction among nurses, psychologists/psychotherapists and social workers working in Quebec mental health teams
Bibliographic record
Abstract
BACKGROUND: This study identified multiple socio-professional and team effectiveness variables, based on the Input-Mediator-Output-Input (IMOI) model, and tested their associations with job satisfaction for three categories of mental health professionals (nurses, psychologists/psychotherapists, and social workers). METHODS: Job satisfaction was assessed with the Job Satisfaction Survey. Independent variables were classified into four categories: 1) Socio-professional Characteristics; 2) Team Attributes; 3) Team Processes; and 4) Team Emergent States. Variables were entered successively, by category, into a hierarchical regression model. RESULTS: Team Processes contributed the greatest number of variables to job satisfaction among all professional groups, including team support which was the only significant variable common to all three types of professionals. Greater involvement in the decision-making process, and lower levels of team conflict (Team Processes) were associated with job satisfaction among nurses and social workers. Lower seniority on team (Socio-professional Characteristics), and team collaboration (Team Processes) were associated with job satisfaction among nurses, as was belief in the advantages of interdisciplinary collaboration (Team Emergent States) among psychologists. Knowledge sharing (Team Processes) and affective commitment to the team (Team Emergent States) were associated with job satisfaction among social workers. CONCLUSIONS: Results suggest the need for mental health decision-makers and team managers to offer adequate support to mental health professionals, to involve nurses and social workers in the decision-making process, and implement procedures and mechanisms favourable to the prevention or resolution of team conflict with a view toward increasing job satisfaction among mental health professionals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".