Bibliographic record
Abstract
The inner experience of spiritual and religious feelings is an integral part of the everyday lives of many individuals. For over 100 years the role of religion as a deterrent to suicidal behavior has been studied in various disciplines. We attempt to systematize the existing literature investigating the relationship between religion/spirituality and suicide in this paper. After an overview of the attitudes of the dominant religions (e.g., Catholicism, Islam, and Buddhism) toward suicide, the three main theories that have speculated regarding the link between religion and suicide are presented: "integration theory" (Durkheim, 1897/1997), "religious commitment theory" (Stack, 1983a; Stark, 1983), and "network theory" (Pescosolido & Georgianna, 1989). Subsequent to this theoretical introduction, we report on studies on religion/spirituality keeping the suicidal path as a reference: from suicidal ideation to nonlethal suicidal behavior to lethal suicidal behavior. Studies presenting indications of religious beliefs as a possible risk factor for suicidal behavior are also presented. The last section reviews possible intervention strategies for suicidal patients and suicide survivors. Indications for future research, such as more studies on nonreligious forms of spirituality and the use of qualitative methodology to achieve a better and deeper understanding of the spiritual dimension of suicidal behavior and treatment, are offered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".