Age at onset and cognition in schizophrenia: meta-analysis
Bibliographic record
Abstract
BACKGROUND: The relationship between cognition and age at onset of schizophrenia is largely unknown. AIMS: To compare cognitive deficits in individuals with youth-onset and late-onset schizophrenia with those in adults with first-episode schizophrenia. METHOD: Twenty-nine databases (including EMBASE, MEDLINE and PsycINFO) were searched from 1980 to 2008. Selected publications had to include healthy controls and analyse separately individuals diagnosed with schizophrenia or a related disorder and individuals with first-episode, youth-onset or late-onset schizophrenia. Descriptive and cognitive data were extracted and the latter aggregated into 22 cognitive measures. Cohen's effect size raw and weighted means of cognitive deficits were generated and compared in the three groups. RESULTS: Individuals with youth-onset and first-episode schizophrenia demonstrate large deficits (mean effect size >or=0.8) on almost all cognitive measures. Individuals with youth-onset schizophrenia demonstrate larger deficits than those with first-episode schizophrenia on arithmetic, executive function, IQ, psychomotor speed of processing and verbal memory. In contrast, those with late-onset schizophrenia demonstrate minimal deficits on arithmetic, digit symbol coding and vocabulary, but larger ones on attention, fluency, global cognition, IQ and visuospatial construction. CONCLUSIONS: Individuals with youth-onset schizophrenia have severe cognitive deficits, whereas those with late-onset schizophrenia have some relatively preserved cognitive functions. This finding supports the view that severity of the disease process is associated with different ages at onset. In addition, the cognitive pattern of people with late-onset schizophrenia suggests that their deficits are specific rather than solely as a result of ageing and related factors.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.037 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".