The BEST Trials: Examining Brief Executive Skills Training for Schizophrenia-Spectrum Disorders
Bibliographic record
Abstract
Cognitive remediation is an efficacious treatment for schizophrenia that focuses on enhancing neurocognitive abilities and improving community functioning. However, there is currently no gold-standard cognitive remediation therapy and different approaches have produced varying results on cognitive and functional outcomes. One of the major barriers preventing cognitive remediation from being recommended in treatment guidelines has been limited generalization of cognitive improvement to functional improvement. Although results have been inconsistent, executive functioning may be more closely related to community functioning than other domains of neurocognition. The objective of the current dissertation was to examine the efficacy of cognitive training that specifically targets executive functioning for individuals with schizophrenia-spectrum disorders. In Chapter 2 data are presented from a randomized, double blind trial examining a brief two-week executive functioning intervention compared to a sham training condition. Compared to sham training, executive training significantly improved EEG alpha and theta band synchronization during working memory tasks, and neuropsychological measures of working memory and executive functioning. In Chapter 3 data are presented from a randomized, double-blind trial examining brief executive function training compared to training of perceptual abilities on measures of neurophysiology, neurocognition, and functioning. Perceptual training improved the EEG mismatch negativity more than executive training immediately post-treatment however, the effect did not persist 12-weeks post-treatment. At 12-week follow-up, executive training significantly improved EEG theta power, neurocognition, functional competence, and case manager rated community functioning to a greater extent than perceptual training. Executive training may be a more efficient cognitive enhancing treatment than other cognitive remediation techniques, and treatment effects generalize to community functioning better than alternative cognitive training approaches.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".