Re-examining the role of counsellor empathy in compassion fatigue and compassion satisfaction
Bibliographic record
Abstract
Figley’s (1995; 2002a) model of compassion stress/fatigue was used as a reference-point to re-examine the role of therapist/counsellor empathy in predicting therapist/counsellor compassion fatigue (CF) and compassion satisfaction (CS). The therapeutic alliance was also examined as a predictor of therapist/counsellor CF and CS. Participants included 146 female-identifying Canadian therapists/counsellors, aged 24-73 years. The Empathy Assessment Index (EAI), a social cognitive neuroscience-based empathy scale, gauged therapist/counsellor empathy; and the Working Alliance Inventory – Short therapist version (WAI-S) gauged therapist/counsellor perceptions of the strength of the therapeutic alliance. The Professional Quality of Life scale – Fifth edition (ProQOL-V) was the outcome measure for therapist/counsellor CF and CS. Contrary to Figley’s model, partial least squares path analyses determined that therapist/counsellor empathy was a significant inverse predictor of therapist/counsellor CF (R2 = .40 for total empathy-based CF model) and a significant positive predictor of therapist/counsellor CS (R2 = .16 for total empathy-based CS model). The therapeutic alliance likewise proved to be a significant inverse predictor of therapist/counsellor CF (R2 = .37 for total therapeutic alliance-based CF model) and a significant positive predictor of therapist/counsellor CS (R2 = .29 for total therapeutic alliance-based CS model). Personal Characteristics including age and years of clinical experience, and Workplace/Organizational factors including supervision and peer support, and percentage of non-distressing clients on therapist/counsellor caseloads, predicted less risk for therapist/counsellor CF and greater likelihood for therapist/counsellor CS. Additional analyses revealed that the therapeutic bond was equivalent to empathy in predicting therapist/counsellor CF, and stronger than empathy in predicting therapist/counsellor CS.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".