Religion/spirituality, perceived need for care, and treatment-seeking behaviour in a sample of distressed Canadians
Bibliographic record
Abstract
BACKGROUND: Although religion/spirituality has been shown to play a potential role in the treatment of mental health problems, there is a growing body of evidence suggesting that it may be mis-conceptualized as a substitute for mental health and substance use treatment among those who are religious/spiritual. Therefore, this study aims to: 1) examine the association between religiousness/spirituality and perceived need for care, and, 2) determine whether there is an inverse relationship between religion/spirituality and treatment-seeking behaviour, among a distressed Canadian population. METHODS: Cross-sectional data from a subsample of 2307 distressed Canadians in the nationally representative 2022 Mental Health and Access to Care Survey was analyzed. Modified Poisson regression analysis was conducted, with perceived need for care and treatment-seeking behaviour (formal and informal) as the outcomes and religiousness/spirituality as the exposure. Effect modification by minority and immigrant status was examined, and associations were adjusted for age, gender, education, and income. RESULTS: Perceived need for care and treatment-seeking behaviour was lower among distressed individuals who were religious/spiritual compared to non-religious/non-spiritual individuals (p < 0.05). The likelihood of a perceived need for care and formal treatment-seeking behaviour was lowest among visible minorities (non-White) and non-immigrants, who were religious/spiritual compared to non-religious/non-spiritual counterparts. When stratifying by immigrant status, informal treatment-seeking behaviour was higher among immigrants who are religious/spiritual than among those who are non-religious/non-spiritual. CONCLUSIONS: Differences in the relationship between religiousness/spirituality and help-seeking among visible minorities and immigrants suggest that integration of religion/spirituality into de-stigmatizing treatment approaches may be warranted to better support at-risk individuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 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) | 0.002 | 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".