Trust of patients and families in mental healthcare providers and institutions: A cross-cultural study in Chennai, India and Montreal, Canada
Bibliographic record
Abstract
Purpose: Cross-cultural psychosis research has typically focused on a limited number of outcomes (generally symptom-related). It is unknown if the purported superior outcomes for psychosis in some low- and middle-income countries extend to fundamental treatment processes like trust. Addressing this gap, we studied two similar first-episode psychosis programs in Montreal, Canada and Chennai, India. We hypothesized higher trust in healthcare institutions and providers among patients and families in Chennai at baseline and over follow-up. Methods: Upon treatment entry and at months 3, 12 and 24, trust in healthcare providers was measured using the Wake Forest Trust scale and trust in the healthcare and mental healthcare systems using two single items. Non-parametric tests were performed to compare trust levels across sites and mixed-effects linear regression models to investigate predictors of trust in healthcare providers. Results: The study included 333 patients (Montreal=165, Chennai=168) and 324 family members (Montreal=128, Chennai=168). Across all timepoints, Chennai patients and families had higher trust in healthcare providers and the healthcare and mental healthcare systems. The effect of site on trust in healthcare providers was significant after controlling for sociodemographic characteristics known to impact trust. Patients' trust in doctors increased over follow-up. Conclusion: This study uniquely focuses on trust as an outcome in psychosis, via a comparative longitudinal analysis of different trust dimensions and predictors, across two geographical settings. The consistent differences in trust levels between sites may be attributable to local cultural values and institutional structures and processes and underpin cross-cultural variations in treatment engagement and outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".