A systematic review on improving cognition in schizophrenia: which is the more commonly used type of training, practice or strategy learning?
Bibliographic record
Abstract
BACKGROUND: The purpose of this article was to conduct a review of the types of training offered to people with schizophrenia in order to help them develop strategies to cope with or compensate for neurocognitive or sociocognitive deficits. METHODS: We conducted a search of the literature using keywords such as "schizophrenia", "training", and "cognition" with the most popular databases of peer-reviewed journals. RESULTS: We reviewed 99 controlled studies in total (though nine did not have a control condition). We found that drill and practice training is used more often to retrain neurocognitive deficits while drill and strategy training is used more frequently in the context of sociocognitive remediation. CONCLUSIONS: Hypotheses are suggested to better understand those results and future research is recommended to compare drill and strategy with drill and practice training for both social and neurocognitive deficits in schizophrenia.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".