Music’s Dual Role in Emotion Regulation: Network Analysis of Music Use, Emotion Regulation Self‐Efficacy, Alexithymia, Anxiety, and Depression
Bibliographic record
Abstract
Music serves as a prevalent emotional regulation tool among young people. However, the correlational and causal relationships between music use, emotion regulation ability, and emotional symptoms remain unclear. This study aimed to investigate the associations and causal relationships between healthy and unhealthy music use, emotion regulation ability, and emotional symptoms, including alexithymia, depression, and anxiety. This study included 16,588 college students nationwide in China. All participants were assessed online with the Healthy-Unhealthy Music Scale (HUMS), the Regulatory Emotional Self-Efficacy Scale (RESE), the Toronto Alexithymia Scale (TAS-20), and the 10-item Kessler Psychological Stress Scale (K10) using a cluster convenience sampling method. We applied a regularized partial correlation network (RPCN) and Bayesian network to analyze the network characteristics of the outcomes. In the RPCN analysis, healthy music use showed the second strongest expected influence (one-step) and correlated positively with emotion regulation self-efficacy while inversely correlating with externally oriented thinking of alexithymia and depression. The Bayesian network indicated that healthy music use was located downstream of the network, positively predicted by managing anger-irritation and expressing positive affect in emotion regulation self-efficacy. In contrast, unhealthy music use in the RPCN displayed the strongest bridge strength and bridge expected influence (one-step). It negatively correlated with expressing positive affect in emotion regulation self-efficacy and positively correlated with alexithymia, anxiety, and depression. The Bayesian network highlighted that unhealthy music use was positively affected by anxiety, depression, and difficulty identifying feelings. In addition, managing despondency-distress influences difficulty identifying feelings through depression, subsequently affecting unhealthy music use and, finally, influencing externally oriented thinking. This study provides a novel framework for understanding the role of emotion regulation self-efficacy and alexithymia in the relationship between music use and emotional symptoms. Emotion regulation and mental health may benefit from music-based interventions and therapies informed by the findings of this study.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.001 | 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 teacher head, 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".