Spiritual care competence, moral distress and job satisfaction among Iranian oncology nurses
Bibliographic record
Abstract
BACKGROUND: Nurses have a crucial role in identifying spiritual needs and providing spiritual care to patients living with cancer. AIM: This study evaluated Iranian oncology nurses' spiritual care competence and its relationship with job satisfaction and moral distress. METHOD: This cross-sectional study was conducted on 280 Iranian oncology nurses in 2020 using four questionnaires: demographic questionnaires, the Spiritual Care Competence Questionnaire (SCCQ), the Minnesota Job Satisfaction Questionnaire (MSQ) and the nurses' Moral Distress Questionnaire (MDS-R). FINDINGS: The mean scores indicated a medium to high Spiritual Care Competence (SCC), mild to moderate moral distress and high job satisfaction. There was a positive correlation between SCC and external job satisfaction (r=184, p<0.05) and a negative correlation between SCC and moral distress (r=-0.356, p<0.05). CONCLUSIONS: SCC diminishes with decreasing external job satisfaction and increasing moral distress. To improve the SCC of nurses working with patients living with cancer, it is recommended that nursing managers and policymakers revise the organisational policies to tackle the obstacles and consider the related factors to provide an ethical climate, implement quality spiritual care and increase job satisfaction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".