Psychological pathway to emotional exhaustion among nurses and midwives who provide perinatal bereavement care in China: a path analysis
Bibliographic record
Abstract
BACKGROUND: A lack of confidence in perinatal bereavement care (PBC) and the psychological trauma experienced by nurses and midwives during bereavement care leads to their strong need for sufficient organisational support. The current study intended to test a hypothesised model of the specific impact paths among organisational support, confidence in PBC, secondary traumatic stress, and emotional exhaustion among nurses and midwives. METHODS: A descriptive, cross-sectional survey was conducted in sixteen maternity hospitals in Zhejiang Province, China, from August to October 2021. The sample (n = 779) consisted of obstetric nurses and midwives. A path analysis was used to test the relationships among study variables and assess model fit. RESULTS: Organisational support directly and positively predicted confidence in PBC and demonstrated a direct, negative, and significant association with secondary traumatic stress and emotional exhaustion. Confidence in PBC had a positive direct effect on secondary traumatic stress and a positive indirect effect on emotional exhaustion via secondary traumatic stress. Secondary traumatic stress exhibited a significant, direct effect on emotional exhaustion. CONCLUSIONS: This study shows that nurses' and midwives' confidence in PBC and mental health were leadingly influenced by organisational support in perinatal bereavement practice. It is worth noting that higher confidence in PBC may lead to more serious psychological trauma symptoms in nurses and midwives. Secondary traumatic stress plays an essential role in contributing to emotional exhaustion. The findings suggest that support from organisations and self-care interventions were required to improve confidence in PBC and reduce negative psychological outcomes among those providing PBC. The development of objective measures for assessing competence in PBC and organizational support are essential.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".