Suicidality and religiosity among patients with depressive and bipolar disorders: a cross-sectional North African study
Bibliographic record
Abstract
Introduction: From the beginning of suicide research by Durkheim (Citation1897); the relationship between religiosity and suicidal risk has been seen as a crucial issue. During the last decade, studies on this question have given variable results. However, such studies became a gateway to multiple questions, not only on the relationship between religion and suicide risk but more specifically among patients with depressive disorders, in particular. This study’s main objective is to assess the influence of religiosity on suicidal ideation; suicidal intentionality and on the severity of depressive symptoms in patients with depressive disorders diagnoses or bipolar depression episodes. We carried out an observational, descriptive, and analytical study of 324 patients with a current diagnosis of a major depressive disorder or a bipolar depressive episode. Patients were all Muslims and were interviewed using the Beck Depression Inventory; Suicide Intent Scale and Mini International neuropsychiatric interview Suicide Risk. The religiosity was assessed using the BIAC (Belief Into Action) adapted to Muslims in Morocco. We found that higher religiosity scores were associated with older age (>50 years), marriage, no negative impact of depression on work, presence of bipolar depression, and regularity of medical follow-up. Similarly, higher scores of religiosity were associated with lower scores of depression, suicidal intentionality, or suicidal risk. It will be useful to compare our results with other published results to appraise the positive impact of religiosity on reducing suicidal ideation and behavior among different populations, regardless of their religious affiliations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".