Music-Based Cognitive Training for Adults with Major Depressive Disorder and Suicide Risk: A Pilot Study
Bibliographic record
Abstract
Background/Objectives: Cognitive challenges in attention and executive function worsen over time in individuals with major depressive disorder (MDD) and suicidal risk. These difficulties persist beyond acute episodes, with limited targeted treatments available. Neurologic music therapy (NMT) is effective for cognitive rehabilitation in brain injuries and developmental disabilities, suggesting potential benefits for adults with MDD and suicide risk. This pilot study evaluated the feasibility, acceptability, and preliminary effectiveness of short-term NMT on cognitive function in adults with MDD. Methods: Adults aged 18+ with MDD and suicidal ideations participated in an 8-week single-arm open label study with 45-min individual in-person NMT sessions using musical attention control training (MACT) and musical executive function training (MEFT). Participants provided feedback on feasibility and acceptability, and pre- and post-intervention assessments included neurocognitive tasks and questionnaires on suicidal ideation, depressive symptoms, and quality of life. Results: A total of 18 individuals enrolled, and 10 participants completed the study protocol. Of the participants, 100% were satisfied with their experience with NMT, with 100% noting improvements in attention and 80% in executive function. Participants experienced some improvements in short-term memory (Digit Span Forward Test), cognitive flexibility (Trail Making Test B), and inhibitory control (Stroop Task). Significant reduction in suicidal ideation intensity (Beck Suicidal Scale of Ideation) was observed, as well as significant improvements in quality of life. Conclusions: This is the first study using NMT to demonstrate feasibility, acceptability, and effectiveness with respect to cognitive function in adults with MDD and suicide risk, providing preliminary data for future randomized controlled trials.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".