Critical Care Nurses’ Experiences With Spiritual Care: The SPIRIT Study
Bibliographic record
Abstract
BACKGROUND: Little is known about the effect of chaplains on critical care nurses who are caring for critically ill patients and their families. OBJECTIVE: To understand nurses' experiences when they make a referral to the Spiritual Care Department for a patient or the family of a patient who is dying or deceased. Specific aims were to explore spiritual care's effect on nurses and how nurses understand the role of spiritual care in practice. METHODS: A qualitative descriptive study using in-person, semistructured interviews in a 21-bed medical-surgical intensive care unit in a teaching hospital. Purposeful sampling identified nurses who had at least 5 years of experience and had cared for at least 5 patients who died on their shift and at least 5 patients for whom they initiated a spiritual care referral. Interviews were digitally recorded and anonymized; conventional content analysis was used to analyze transcripts. Three investigators independently coded 5 transcripts and developed the preliminary coding list. As analysis proceeded, investigators organized codes into categories and themes. RESULTS: A total of 25 nurses were interviewed. The central theme that emerged was presence, described through 3 main categories: the value of having chaplains present in the intensive care unit and their role, nurses' experiences working with chaplains, and nurses' experiences providing spiritual care. CONCLUSION: Nurses considered spiritual care essential to holistic care and valued the support chaplains provide to patients, families, and staff in today's spiritually diverse society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".