Spiritual care training in healthcare: Does it really have an impact?
Bibliographic record
Abstract
OBJECTIVE: Spiritual care has formed an integral part of palliative care since its inception. People with advanced illnesses, however, frequently report that their spiritual needs are not attended to by their medical care team. The present study examines and describes the impact of a spiritual care training program on practice and cultural change in our Canadian hospice. METHOD: A qualitative case study approach was adopted to gather feedback from hospice staff and volunteers using purposive sampling. In-depth interviews were conducted, transcribed, and analyzed using thematic (semantic and latent) analysis. RESULT: Our data suggest that the program had a profound personal impact on attendees and contributed to a slight shift in practice patterns in our organization. Using a program not specifically tailored to our local and organizational cultural contexts resulted in some unanticipated challenges such as the range of tensions between personal and cultural boundaries. Although some people criticized parts of the program or questioned the program's value, a general agreement suggests that the program had a positive impact and meaningfully benefited our hospice. "What will happen next?" was the question most frequently voiced by interviewees. SIGNIFICANCE OF RESULTS: Although the program may not have been a perfect fit for our organization, its use instigated a process of cultural change that unfolds today. The present study suggests that a systematic approach to spiritual care training that includes the concepts of workplace spirituality and sensitive practice offer useful frameworks for the development and implementation of spiritual care training in other institutions.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".