Spiritual Well-Being and Correlated Factors in Subjects With Advanced COPD or Lung Cancer
Bibliographic record
Abstract
BACKGROUND: Spiritual care for patients with COPD has rarely been discussed, and thus much remains unknown about their needs. The aims of this study were to identify the factors associated with spiritual well-being and to compare the levels of spiritual well-being between subjects with advanced COPD and those with inoperable lung cancer. METHODS: A total of 96 subjects with COPD or lung cancer participated in this study, which was conducted between December 2014 and April 2016. Measures included the Japanese version of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being (FACIT-Sp-12) scale, the McGill Quality of Life Questionnaire (MQOL), the modified Medical Research Council (mMRC) dyspnea scale, and various other medico-social factors. RESULTS: No significant differences were found between subjects with COPD and those with lung cancer in median FACIT-Sp-12 scores (COPD, 27; lung cancer, 26; P = .81). However, significant differences were found in the 2 MQOL domains, suggesting that subjects with COPD had a better psychological state ( P = .01) and that subjects with lung cancer had a better support state ( P = .002). Multiple regression analysis revealed that mMRC was significantly associated with FACIT-Sp-12 scores in subjects with COPD. CONCLUSIONS: These results suggest that subjects with advanced COPD experience spiritual well-being similar to that of subjects with inoperable lung cancer.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".