Pathways to functional outcomes following a first episode of psychosis: The roles of premorbid adjustment, verbal memory and symptom remission
Bibliographic record
Abstract
OBJECTIVE: Most studies have investigated either the singular or relative contributions of premorbid adjustment, verbal memory and symptom remission to functional outcomes in first-episode psychosis. Fewer studies have examined the pathways of these factors in impacting functioning. Our study addresses this gap. The objective was to determine whether the relationship between premorbid adjustment and functional outcomes was mediated by verbal memory and symptom remission. METHOD: A total of 334 first-episode psychosis participants (aged 14-35 years) were assessed on premorbid adjustment, verbal memory upon entry, and positive and negative symptom remission and functioning at multiple time points over a 2-year follow-up. RESULTS: Mediation analyses showed that over the first year, the relationship between premorbid adjustment and functioning was mediated by verbal memory and positive symptom remission (β = -0.18; 95% confidence interval = [-0.51, -0.04]), as well as by verbal memory and negative symptom remission (β = -0.41; 95% confidence interval = [-1.11, -1.03]). Over 2 years, the relationship between premorbid adjustment and functioning was mediated by verbal memory and only negative symptom remission (β = -0.38; 95% confidence interval = [-1.46, -0.02]). CONCLUSION: Comparatively less malleable factors (premorbid adjustment and verbal memory) may contribute to functional outcomes through more malleable factors (symptoms). Promoting remission may be an important parsimonious means to achieving better functional outcomes.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".