How Spiritual Values and Worship Attendance Relate to Psychiatric Disorders in the Canadian Population
Bibliographic record
Abstract
OBJECTIVE: Research into risk and protective factors for psychiatric disorders may help reduce the burden of these conditions. Spirituality and religion are 2 such factors, but research remains limited. Using a representative national sample of respondents, this study examines the relation between worship frequency and the importance of spiritual values and DSM-IV psychiatric and substance use disorders. METHOD: In 2002, the Canadian Community Health Survey obtained data from about 37,000 individuals aged 15 years or older. While controlling for demographic characteristics, we determined odds ratios for lifetime, 1-year, and past psychiatric disorders, with worship frequency and spiritual values as predictors. RESULTS: Higher worship frequency was associated with lower odds of psychiatric disorders. In contrast, those who considered higher spiritual values important (in a search for meaning, in giving strength, and in understanding life's difficulties) had higher odds of most psychiatric disorders. CONCLUSION: This study confirms an association between higher worship frequency and lower odds of depression and it expands that finding to other psychiatric disorders. The association between spiritual values and mood, anxiety, and addictive disorders is complex and may reflect the use of spirituality to reframe life difficulties, including mental disorders.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".