Representations of Psychological Distress Among Canadian Muslims of South Asian Origin: A Qualitative Study using the Self-regulatory Model
Bibliographic record
Abstract
This study sought to gain insight into representations of distress among Canadian Muslims of South Asian origin. It sought to examine whether representations of distress among this population are influenced by Islamic, scientific, and Western representations, the extent to which they differ from those assumed in the prevailing literature on Islamic healing, counselling, psychotherapy, and psychiatry with Muslim populations, and whether individuals attempt to incorporate multiple influences into a single coherent representation, or they construct multiple representations simultaneously. The Self-Regulatory Model of Illness Representation (Leventhal, Brissette Leventhal, 2003) was utilized to understand how the participants made sense of, emotionally responded to, and coped with their experiences of distress. The findings of this study indicated that a common theme among the participants was the belief that their distress was a form of punishment from God due to lack of faith or piety, thereby suggesting a significant religious aspect to their representations of distress. Paradoxically, the participants attempted to cope with their distress through counselling and psychotherapy or pharmacotherapy, which implies an equally strong biomedical aspect to their representations of distress. Reasons for this dual and possibly contradictory nature of participants’ representations of distress are discussed along with the implications of the findings for counselling and psychotherapy.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".