Bibliographic record
Abstract
Following an introduction focusing on the role of religion in the treatment of psychosis, the first part of this paper describes an initial study in which the role of spirituality and religiosity was assessed in 115 patients with schizophrenia in Geneva (Switzerland) and 126 in Trois-Rivières (Quebec). These themes have been shown to be highly prevalent for these patients, though their clinicians are often unaware of this prevalence. The following part of the paper presents a second study where religious supervision was offered to clinicians in Geneva. Comparison between forty patients who received spiritual assessment and opportunities to work on religious topics with their clinicians was made with thirty patients without religious intervention. In the supervisory sessions, six different types of religious interventions were suggested. Outcomes at three months show that patients of the intervention group maintain their interest for help in religious matters while clinicians' interest in integrating religious topics in discussions with their patients has decreased. The third and main part of the paper is devoted to an analysis of the suggested interventions from the viewpoint of the study of religions. Five aspects of religion are distinguished, and explanations of the reasons some of them are easier to manage for clinicians are proposed. The paper concludes with proposals for the education of clinicians to help them to differentiate different kinds of religious coping and to recognize when it could be helpful to refer the patient to a pastoral counsellor.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.090 | 0.070 |
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".