Patient-reported outcome measures in early psychosis: A cross-cultural, longitudinal examination of the self-reported health and self-reported mental health measures in Chennai, India and Montreal, Canada
Bibliographic record
Abstract
OBJECTIVE: Despite their acknowledged value, patient-reported outcome measures (PROMs) are infrequently used in psychosis, particularly in low-and middle-income countries. We compared ratings on two single-item PROMs, Self-Rated Health (SRH) and Self-Rated Mental Health (SRMH), of persons receiving similar early psychosis services in Chennai, India and Montreal, Canada. We hypothesized greater improvements in SRH and SRMH in the Chennai (compared to the Montreal) sample. METHODS: Participants (Chennai N = 159/168 who participated in the larger study; Montreal N = 74/165 who participated in the larger study) completed the SRH and SRMH during at least two out of three timepoints (entry, months 12 and 24). Repeated measures proportional odds logistic regressions examined the effects of time (baseline to month 24), site, and relevant baseline (e.g., gender) and time-varying covariates (i.e., symptoms) on SRH and SRMH scores. RESULTS: SRH (but not SRMH) scores significantly differed between the sites at baseline, with Chennai patients reporting poorer health (OR: 0.33; CI: 0.18, 0.63). While Chennai patients reported similar significant improvements in their SRH (OR: 7.03; CI: 3.13; 15.78) and SRMH (OR: 2.29, CI: 1.03, 5.11) over time, Montreal patients only reported significant improvements in their SRMH. Women in Chennai (but not Montreal) reported lower mental health than men. Higher anxiety and longer durations of untreated psychosis were associated with poorer SRH and SRMH, while negative symptoms were associated with SRH. CONCLUSIONS: As hypothesized, Chennai patients reported greater improvements in health and mental health. The marked differences between health and mental health in Montreal, in contrast to the overlap between the two in Chennai, aligns with previous findings of clearer distinctions between mind and body in Western societies. Cross-context (e.g., anxiety) and context-specific (e.g., gender) factors influence patients' health perceptions. Our results highlight the value of integrating simple PROMs in early psychosis.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".