Cognitive function in early psychosis patients from a lower middle-income country
Bibliographic record
Abstract
OBJECTIVES: To establish evidence of cognitive changes in early psychosis (EP) patients compared to healthy controls (HC) in Pakistan. METHODS: Fifty-one participants with EP were recruited from psychiatric units in Karachi and Rawalpindi, Pakistan and matched with 51 HC. Neurocognitive domains were assessed using standardised neuropsychological tests [the Stroop test, block design, Matrix Reasoning, picture completion, object assembly, oral fluency, memory for design, Coughlan learning task (verbal and visual)]. RESULTS: EP patients had higher scores than controls for both Stroop tests (T1: EP = 122 HC = 65, p <.001; T2: EP = 190 HC = 153, p = .007) and memory for design test (EP = 10 HC = 3, p = .005). EP group had lower values for block design (EP = 4, HC = 11, p = .01), category fluency (EP = 18.9, HC = 26.1, p < .001), Coughlan verbal tasks (EP = 36.4 NC = 51.5, p < .001), matrix reasoning (EP = 4 NC = 10, p < .001), picture completion (EP = 4 NC = 6, p = .003) and object assembly (EP = 10.7, HC = 15.5, p = .002). There were limited significant associations between cognitive performance and PANSS scores. CONCLUSIONS: Reduced cognitive performance was found across multiple domains in Pakistani EP patients, which suggests that impaired cognitive performance is homogenous in patients with schizophrenia, regardless of ethnicity.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".