Are spiritual interventions beneficial to patients with cancer?
Bibliographic record
Abstract
BACKGROUND: In addition to the physical burden, the quality of life and survival in patients with cancer may also be reduced because of psychological distress, such as spiritual crisis, anxiety, and depression. Many studies have verified that spirituality could reduce anxiety and depression and improve quality of life and adjustment to cancer. However, there is uncertainty regarding the effectiveness of spiritual interventions in patients with cancer. The purpose of this meta-analysis is to use randomized controlled trials (RCTs) to evaluate the effects of spiritual interventions on spiritual and psychological outcomes and quality of life in patients with cancer. METHODS: All RCTs using spiritual interventions relevant to the outcomes of patients with cancer were retrieved from the following databases: Embase, PubMed, PsycINFO, Ovid, Springer Online Library, Wiley Online Library, Oxford Journals, the Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials. The reference lists of identified RCTs were also screened. The Cochrane risk of bias tool was used to evaluate the quality of the studies, RevMan (5.3) was used to analyze the data, and GRADE (3.6.1) was used to evaluate the evidence quality of the combined results. RESULTS: Ten RCTs involving 1239 patients were included. Spiritual interventions were compared with a control group receiving usual care or other psychosocial interventions. The weighted average effect size across studies was 0.46 (P = .003, I = 78%) for spiritual well-being, 0.19 (P = .005, I = 46%) for quality of life, -0.33 (P = .01, I = 50%) for depression, -0.58 (P = .03, I = 77%) for anxiety, and -0.38 (P = .008, I = 0%) for hopelessness. In subgroup analysis according to the type of cancer, only the weighted average effect size of spiritual well-being in patients with breast cancer had statistical significance (standardized mean difference 0.78, P = .01, I = 70%). CONCLUSION: Spiritual interventions may improve spiritual well-being and quality of life, and reduce depression, anxiety, and hopelessness for patients with cancer. However, due to the mixed study design and substantial heterogeneity, some evidence remains weak. More rigorously designed research is needed.
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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 | 0.019 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".