Successful computer-assisted cognitive remediation therapy in patients with unipolar depression: a proof of principle study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Despite increasing awareness of the extent and severity of cognitive deficits in major depressive disorder (MDD), trials of cognitive remediation have not been conducted. We conducted a 10-week course of cognitive remediation in patients with long-term MDD to probe whether deficits in four targeted cognitive domains, (i) memory, (ii) attention, (iii) executive functioning and (iv) psychomotor speed, could be improved by this intervention. METHOD: We administered a computerized cognitive retraining package (PSSCogReHab) with demonstrated efficacy to 12 stable patients with recurrent MDD. Twelve matched patients with MDD and a group of healthy control participants were included for comparison; neither comparator group received the intervention that involved stimulation of cognitive functions through targeted, repetitive exercises in each domain. RESULTS: Patients who received cognitive training improved on a range of neuropsychological tests targeting attention, verbal learning and memory, psychomotor speed and executive function. This improvement exceeded that observed over the same time period in a group of matched comparisons. There was no change in depressive symptom scores over the course of the trial, thus improvement in cognitive performance occurred independent of other illness variables. CONCLUSIONS: These results provide preliminary evidence that improvement of cognitive functions through targeted, repetitive exercises is a viable method of cognitive remediation in patients with recurrent MDD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it