Comparing the Effect of Repetitive Transcranial Magnetic Stimulation Therapy and Aerobic Exercise as an Add-on Therapy on the Cognitive Function of Patients with Depression
Bibliographic record
Abstract
Background: Cognitive disturbances are a major cause of disability in depression. The antidepressant medication effectively improves cognitive function. However, its adverse effect limits its use, so add-on treatment is needed to support its effectiveness. Aim: This study aims to compare the efficacy of aerobic exercise and repetitive transcranial magnetic stimulation (rTMS) as an add-on treatment for improving cognitive function. Material and Methods: Twenty-seven patients with first episodes of moderate and severe depression were recruited from the outpatient psychiatry clinic to join this randomized controlled trial. Participants were allocated to three groups: antidepressant only, antidepressant with add-on aerobic exercise, and antidepressant with add-on rTMS therapy. All participants received 2 weeks of intervention. Cognitive functions were assessed using Montreal Cognitive Assessment (MOCA). Results: No differences were found in baseline characteristic data between groups. Total MOCA score increased after intervention in a group with no add-on treatment (p=0.007), with add-on aerobic exercise (p=0.011), and with add-on rTMS therapy (p=0.017). Hence, there was no between-group difference (p=0.222). The MOCA subtest analysis revealed between-group differences in changes in delayed recall subtest score (p=0.01). The group with add-on rTMS therapy improved better than the group with antidepressants only (p=0.005). Conclusion: The addition of rTMS therapy resulted in better improved delayed recall function than the addition of aerobic exercise or without any add-on treatment. This finding supports the application of rTMS therapy as an add-on treatment to improve the cognitive function of patients with depression.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".