Predictors and Moderators of Long-Term Outcome of Persons at Clinical High Risk for Psychosis: Methods and Preliminary Data
Bibliographic record
Abstract
BACKGROUND AND HYPOTHESIS: Despite significant advances in our understanding of the clinical high risk (CHR) for psychosis state, the longer-term outcomes (5+ years) and the trajectory of diagnoses, symptoms, and psychosocial function have been seldom investigated. OBJECTIVE: Here we describe the methods for "Predictors and Moderators of Long-Term Outcome of Persons at Clinical High Risk for Psychosis," an ongoing study that is being conducted across North American Prodrome Longitudinal Studies sites that included n = 2184 past participants (1999-2018). STUDY DESIGN: The aims are to: (1) perform long-term assessments of individuals who previously met CHR criteria, (2) determine the 5+ year psychotic conversion rate and use previously collected longitudinal clinical, functional, neurocognitive, and biomarker data to predict longer term outcomes, and (3) investigate predictors of long-term clinical/functional outcome in CHR participants who did not convert to psychosis. STUDY RESULTS: Preliminary results from the first n = 504 participants demonstrate that 60% of those who previously met CHR criteria are still symptomatic. Eighteen percent of past participants converted to psychosis, half in the original studies and the remainder since last evaluated. Of those who converted to psychosis, the majority met criteria for an affective psychosis, consistent with the high rate of affective disorders (70%) in the non-converted group. An additional 7% of past participants died, substantially higher than the general population. CONCLUSIONS: These early data highlight the potential of how this dataset, when combined with baseline data, can be used to answer new questions about the life course of high-risk youth and how we might intervene early to improve their long-term outcome.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".