Psychiatric hospitalization following psychosis onset: A retrospective cohort study using health administrative data
Bibliographic record
Abstract
AIM: There is limited evidence examining admissions in early psychosis. We sought to estimate the proportion of people with a psychiatric admission within 2 years of the first diagnosis of psychosis, and to identify associated risk factors. METHOD: We constructed a cohort of incident non-affective psychosis cases using health administrative data and identified the first psychiatric hospitalization after psychosis onset. We compared hospitalization rates across sociodemographic, clinical and service-use factors. RESULTS: One in three patients had an admission within 2 years of first diagnosis. Younger age, migrant status, diagnosis of psychosis not otherwise specified, and prior substance use were associated with increased hospitalization rates, whereas family physician involvement in diagnosis was protective. CONCLUSIONS: Adolescents, immigrants and people presenting with diagnostic instability or prior substance use issues may benefit from interventions aimed at reducing hospitalization risk. Increasing primary care access and utilization among youth with early psychosis may also reduce hospitalization rates.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".