Supervision and Wellness: A Survey of Human Service Practitioners
Bibliographic record
Abstract
Organizationally provided workplace-based supervision is important for human services as it impacts service delivery, client outcomes, and organizational efficacy. Surveying human service practitioners in Ontario, Canada (N = 207), this study examined the relationship between supervision effectiveness and practitioner wellness using the Manchester Clinical Supervision Scale and the Professional Quality of Life – Health Scale, conducting a MANCOVA and fitting a Structural Equation Model. Of the participants, 37% received effective supervision as defined by MCSS-26 developers, 40% non-effective supervision, and 23% no supervision. Participants whose scores reflected non-effective supervision experienced the worst wellness outcomes, worse than no supervision. Results indicate effective supervision, particularly the strength of supervisory relationship and administrative (i.e. normative) function, predicts practitioner wellness, increasing perceived support and compassion satisfaction while decreasing burnout, secondary traumatic stress, and moral distress. Findings emphasize the need for organizations to dedicate resources to effective supervision to improve practitioner wellbeing and, in turn, client outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".