Self-Compassion Interventions to Target Secondary Traumatic Stress in Healthcare Workers: A Systematic Review
Bibliographic record
Abstract
Healthcare professionals' wellbeing can be adversely affected by the intense demands of, and the secondary traumatic stress associated with, their job. Self-compassion is associated with positive wellbeing outcomes across a variety of workforce populations and is potentially an important skill for healthcare workers, as it offers a way of meeting one's own distress with kindness and understanding. This systematic review aimed to synthesise and evaluate the utility of self-compassion interventions in reducing secondary traumatic stress in a healthcare worker population. Eligible articles were identified from research databases, including ProQuest, PsycINFO, ScienceDirect, Google Scholar, and EBSCO. The quality of non-randomised and randomised trials was assessed using the Newcastle-Ottawa Scale. The literature search yielded 234 titles, from which 6 studies met the inclusion criteria. Four studies reported promising effects of self-compassion training for secondary traumatic stress in a healthcare population, although these did not use controls. The methodological quality of these studies was medium. This highlights a research gap in this area. Three of these four studies recruited workers from Western countries and one recruited from a non-Western country. The Professional Quality of Life Scale was used to evaluate secondary traumatic stress in all studies. The findings show preliminary evidence that self-compassion training may improve secondary traumatic stress in healthcare professional populations; however, there is a need for greater methodological quality in this field and controlled trials. The findings also show that the majority of research was conducted in Western countries. Future research should focus on a broader range of geographical locations to include non-Western countries.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".