Memory impairment and the mediating role of task difficulty in patients with schizophrenia
Bibliographic record
Abstract
Using meta-analytic methods, we sought to synthesize the research literature on memory impairment in schizophrenia. Additionally, we compared performances across memory measures to determine if task difficulty (e.g., effortful encoding and retrieval vs non-effortful encoding and retrieval) could account for variance across studies. Our primary measures of interest included the California Verbal Learning Test, Wechsler Memory Scale, Rey Auditory Verbal Learning Test, Hopkins Verbal Learning Test, Rey-Osterrieth Complex Figure Test, and the Benton Visual Retention Test. We searched for all studies that met inclusion criteria using PubMed, PsycINFO, Scholars Portal Search, and Google Scholar. Studies were included if: (i) they were published after 1980; (ii) healthy controls were compared to patients with schizophrenia; (iii) at least one of the noted measures of interest was employed in the primary study; and (iv) the primary study included data that could be transformed to point estimate effect sizes (i.e., Cohen's d). Cohen's d was calculated between patients and healthy controls, along with overall 95% confidence intervals. A two-tailed independent samples t-test was conducted to assess if performance differed on various paired subtests of the same domain. Large effect sizes were found for all memory tests. No significant differences were found between subtests. In conclusion, patients with schizophrenia experience significant verbal and visual memory impairments, which are not explained by task difficulty. Patients were unable to learn or retrieve more reliably despite repetition and cuing strategies, suggesting that memory impairment in the illness is not a function of task difficulty.
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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 | 0.015 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.022 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".