Interval Versus Continuous Cognitive Training in Schizophrenia: Comparing Cognitive, Neurophysiological, and Subjective Outcomes
Bibliographic record
Abstract
Background: Therapies aimed at remediating cognitive deficits in schizophrenia vary widely in their approach and delivery of cognitive training. In healthy populations, rest breaks have been shown to improve attention, performance, and subjective experience of work or cognitive tasks. Neurophysiological research has demonstrated a relationship between on-task band power, performance, and working memory load. Objectives: The current study aimed to assess the effect of rest breaks during cognitive training in schizophrenia through examination of cognitive performance and improvement, mean theta and alpha power, and subjective measures focused on acceptability and intrinsic motivation. Methods: 24 participants with schizophrenia completed three working memory tasks to assess baseline functioning and were randomized into either interval or continuous cognitive training on the N-back task, each with a total of 10-minutes of on-task training. Immediately following training, subjects completed the three working memory tasks again to assess immediate change in performance, and again following a 30-minute period of respite to assess durable change. Continuous EEG was recorded throughout, and following completion participants’ subjective experience of training was assessed with a self-report questionnaire. Results: The interval training group performed significantly better than the continuous training group during the training period, however this did not lead to improvement differences at post-testing on the training task. For tasks not trained on, there was a trend for significantly greater improvement following interval training with medium effect size. No differences were observed in theta or alpha band power between groups during training, nor was band power found to be significantly correlated with task difficulty or performance. There were no significant differences between groups for subjective training experience. Discussion: Results suggest that incorporating rest intervals in cognitive training leads to greater performance during training and enhanced skills transfer to other domains of working memory. This observation could be due to memory retention benefits of the spacing effect in the interval condition. Alternatively, results could be due to mental fatigue and/or ego depletion in the continuous condition, leading to a reduced capacity for performance and improvement on non-trained tasks. Further research is needed to determine the underlying mechanism of improvement and transfer.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".