The social relations of prayer in healthcare: Adding to nursing's equity‐oriented professional practice and disciplinary knowledge
Bibliographic record
Abstract
Although spiritual practices such as prayer are engaged by many to support well-being and coping, little research has addressed nurses and prayer, whether for themselves or facilitating patients' use of prayer. We conducted a qualitative study to explore how prayer (as a proxy for spirituality and religion) is manifest-whether embraced, tolerated, or resisted-in healthcare, and how institutional and social contexts shape how prayer is understood and enacted. This paper analyzes interviews with 21 nurses in Vancouver and London as a subset of the larger study. Findings show that nurses' kindness can buffer the loneliness and exclusion of ill health and in this way support the "spirit" of those in their care. Spiritual support for patients rarely incorporated prayer, in part because of ambiguities about permission and professional boundaries. Nurses' engagement with prayer and spiritual support could become a politicized site of religious accommodation, where imposition, religious illiteracy, and racism could derail person-centered care and consequently enact social exclusion. Spiritual support (including prayer) sustained nurses themselves. We propose that nursing's equity-oriented knowledge encompass spirituality and religion as sites of exclusion and inclusion. Nurses must be supported to move past religious illiteracy to provide culturally and spiritually sensitive care with clarity about professional boundaries and collaborative models of spiritual care.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
| grok | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
| opus | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.057 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.002 | 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, unvalidatedLabeled directly by 3 models reading the full record.
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".