The Effect of Computer-Based Cognitive Rehabilitation on Improving Cognitive Function, Selective Attention, and Sustained Attention in Patients with Schizophrenia
Bibliographic record
Abstract
Introduction: Schizophrenia is a chronic psychiatric disorder characterized by severe distur� bances in thinking, perception, and behavior, significantly impacting cognitive functioning.Cognitive deficits in individuals with schizophrenia can adversely affect their everyday func� tioning and social abilities.The present study aimed to examine the effectiveness of comput� er�based cognitive rehabilitation in improving overall cognitive performance, selective at� Materials and Methods: This .tention,and sustained attention in patients with schizophrenia semi�experimental study employed a pretest�posttest�follow�up design with experimental and control groups.The statistical population consisted of individuals diagnosed with schizophre� nia who were hospitalized in psychiatric treatment and rehabilitation centers in Ardabil, Iran.A total of 30 participants were selected using purposive sampling and were randomly assigned to the experimental and control groups.The experimental group received twelve 45�minute sessions (three sessions per week) of computer�based cognitive rehabilitation using the Cap� tain's Log software.The control group received no intervention.To assess the study variables, the Montreal Cognitive Assessment, computerized versions of the Simple Stroop Test, and Continuous Performance Test were administered across three phases (pretest, posttest, and Results: The findings indicated that computer�based cognitive rehabilitation led .(follow�up to improvements in overall cognitive functioning and components of sustained attention in the experimental group compared to the control group.Changes were also observed in the pattern of selective attention between these groups, although these changes were less prominent com� Conclusion: The results suggest that computer�based .pared to those in sustained attention cognitive rehabilitation can serve as an effective complementary intervention for enhanc� ing cognitive performance and certain aspects of attention in patients with 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".