Premorbid functional development and conversion to psychosis in clinical high-risk youths
Bibliographic record
Abstract
Deterioration in premorbid functioning is a common feature of schizophrenia, but sensitivity to psychosis conversion among clinical high-risk samples has not been examined. This study evaluates premorbid functioning as a predictor of psychosis conversion among a clinical high-risk sample, controlling for effects of prior developmental periods. Participants were 270 clinical high-risk individuals in the North American Prodrome Longitudinal Study-I, 78 of whom converted to psychosis over the next 2.5 years. Social, academic, and total maladjustment in childhood, early adolescence, and late adolescence were rated using the Cannon-Spoor Premorbid Adjustment Scale. Early adolescent social dysfunction significantly predicted conversion to psychosis (hazard ratio = 1.30, p = .014), independently of childhood social maladjustment and independently of severity of most baseline positive and negative prodromal symptoms. Baseline prodromal symptoms of disorganized communication, social anhedonia, suspiciousness, and diminished ideational richness mediated this association. Early adolescent social maladjustment and baseline suspiciousness together demonstrated moderate positive predictive power (59%) and high specificity (92.1%) in predicting conversion. Deterioration of academic and total functioning, although observed, did not predict conversion to psychosis. Results indicate early adolescent social dysfunction to be an important early predictor of conversion. As such, it may be a good candidate for inclusion in prediction algorithms and could represent an advantageous target for early intervention.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".