Sources of spiritual well-being in advanced cancer
Bibliographic record
Abstract
OBJECTIVE: To test a conceptual model of sources of spiritual well-being in patients facing life-limiting disease. DESIGN: Cross-sectional survey. SETTING: Princess Margaret Hospital, Toronto, Canada. PARTICIPANTS: 747 patients with stage IV gastrointestinal, breast, genitourinary or gynaecological cancer, or stage IIIA, IIIB or IV lung cancer, recruited from 2002 to 2008. MAIN OUTCOME MEASURE: Spiritual well-being as assessed by the FACIT-Sp-12. RESULTS: Using structural equation modelling, spiritual well-being was specified as being predicted by religiosity, self-esteem, social relatedness and the physical burden of disease. The model had a good fit, Comparative Fit Index=0.96, Non-normed Fit Index=0.94, Root Mean Square Error of Approximation=0.057. Standardised path coefficients relating each factor to spiritual well-being were as follows: religiosity 0.50, social relatedness 0.28, self-esteem 0.26 and physical burden -0.11. CONCLUSIONS: The authors confirmed our theoretical model in which spiritual well-being is positively associated with religiosity, self-esteem and social relatedness, and is negatively associated with physical suffering. Our findings support a multidimensional approach to spiritual well-being that addresses not only religious issues, but also pain and symptom control, and the potentially damaging effects of advanced disease on self-worth and close relationships. The spiritually informed clinical encounter may be one in which sufficient time and opportunity for reflection are afforded to consider illness trajectories and treatment decisions in the context of religious beliefs and personal values, self-worth, support systems and concerns about dependency.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".