Factors Associated with Timely Physician Follow-up after a First Diagnosis of Psychotic Disorder
Bibliographic record
Abstract
OBJECTIVE: Physician follow-up after a first diagnosis of psychotic disorder is crucial for improving treatment engagement. We examined the factors associated with physician follow-up within 30 days of a first diagnosis of schizophrenia. METHOD: We conducted a retrospective cohort study using linked health administrative data to identify incident cases of schizophrenia between 1999 and 2008 among people aged 14 to 35 years in Ontario. We estimated the proportion of patients who had physician follow-up within 30 days of the index diagnosis. We used multilevel logistic regression models to examine the factors associated with any physician follow-up and follow-up by a psychiatrist. RESULTS: We identified 20,096 people with a first diagnosis of schizophrenia. Approximately 40% of people did not receive any physician follow-up within 30 days, and nearly 60% did not receive follow-up by a psychiatrist. Males had lower odds of receiving any physician follow-up, and the odds of psychiatrist follow-up decreased with increasing age and were lower for those living in rural areas. Both prior contact with a general practitioner for a mental health reason and prior contact with a psychiatrist were strongly associated with higher odds of receiving both types of follow-up. CONCLUSIONS: Many people do not have any physician contact within 30 days of the first diagnosis of schizophrenia, and patients without prior engagement with mental health services are at highest risk. We need information on the reasons behind this lack of physician follow-up to inform strategies aimed at improving engagement with services during the early stages of psychosis.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".