Trajectory and early predictors of apathy development in first-episode psychosis and healthy controls: a 10-year follow-up study
Bibliographic record
Abstract
Apathy is prevalent in first-episode psychosis (FEP) and associated with reduced global functioning. Investigations of the trajectory of apathy and its early predictors are needed to develop new treatment interventions. We here measured the levels of apathy over the first 10 years of treatment in FEP and in healthy controls (HC). We recruited 198 HC and 198 FEP participants. We measured apathy with the Apathy Evaluation Scale, self-report version, psychotic symptoms with the Positive and Negative Syndrome Scale, depression with the Calgary Depression Scale for Schizophrenia, functioning with the Global Assessment of Functioning Scale, and also estimated the duration of untreated psychosis (DUP). The longitudinal development of apathy and its predictors were explored using linear mixed models analyses. Associations to functioning at 10 years were investigated using multiple hierarchical linear regression analyses. In HC, mean apathy levels were low and stable. In FEP, apathy levels decreased significantly during the first year of treatment, followed by long-term stability. High individual levels of apathy at baseline were associated with higher apathy levels during the follow-up. Long DUP and high baseline levels of depression predicted higher apathy levels at follow-ups. The effect of DUP was persistent, while the effect of baseline depression decreased over time. At 10 years, apathy was statistically significantly associated with reduced functioning. The early phase of the disorder may be critical to the development of apathy in FEP.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".