Spiritual well-being of terminally ill patients and next-of-kin caregivers in hospice care: A quantitative and qualitative approach
Bibliographic record
Abstract
Abstract Background Terminal cancer patients often endure significant distress, impacting their quality of life. Spiritual well-being provides peace and meaning during this challenging period. Objectives. This study explored the spiritual well-being of terminally ill patients and their next-of-kin caregivers in hospice care, focusing on factors influencing their spiritual experiences. Methods This mixed-methods study included 30 terminally ill patients and 17 next-of-kin caregivers in hospice care. Spiritual well-being was assessed using the Functional Assessment of Chronic Illness Therapy – Spiritual Well-Being Scale (FACIT-Sp-12), and symptom distress with the Edmonton Symptom Assessment Scale. Qualitative data were collected through semi-structured interviews at baseline, 1 week, and 1 month. Data were analyzed using quantitative methods and thematic analysis. Results Patients showed a significant improvement in spiritual well-being over time, with FACIT-Sp-12 scores increasing from 28.6 at baseline to 31.3 at 1 month (p < .01). Symptoms such as shortness of breath (β = –1.19, p < .001), drowsiness (β = –1.27, p = .01), and anxiety (β = –0.60, p = .03) were negatively associated with spiritual well-being. Caregiver spiritual well-being positively influenced patient scores, especially with female caregivers (β = 0.26, p < .001). Qualitative findings supported these results, revealing themes of spiritual adjustment, the impact of physical symptoms on spiritual well-being, and the crucial role of caregivers in providing emotional and spiritual support. Significance of results Early palliative care facilitates spiritual adjustment in terminally ill patients. A holistic approach addressing physical symptoms and psychological distress is essential. Supporting caregivers, particularly female ones, positively impacts patient spiritual well-being. Tailored interventions considering the unique needs of patients and caregivers are recommended to enhance palliative care quality.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".