Personality Traits Associated with Genetic Counselor Compassion Fatigue: The Roles of Dispositional Optimism and Locus of Control
Bibliographic record
Abstract
Compassion fatigue (CMF) arises as a consequence of secondary exposure to distress and can be elevated in some health practitioners. Locus of control and dispositional optimism are aspects of personality known to influence coping style. To investigate whether these personality traits influence CMF risk, we surveyed 355 genetic counselors about their CMF, locus of control orientation, and degree of dispositional optimism. Approximately half of respondents reported they experience CMF; 26.6% had considered leaving their job due to CMF symptoms. Mixed-method analyses revealed that genetic counselors having an external locus of control and low optimism were at highest risk for CMF. Those at highest risk experienced moderate-to-high burnout, low-to-moderate compassion satisfaction, and tended to rely on religion/spirituality when coping with stress. CMF risk was not influenced by years in practice, number of genetic counselor colleagues in the workplace, or completion of graduate training in this area. Recommendations for practice and education are outlined.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".