Data · dataset · 2025
A Comprehensive Perspective on Gender Differences in Music Based Emotion Regulation Network
Listed in ScienceDB
Description
Background
Music plays a significant role in emotion regulation, exerting both positive and negative effects. The relationship between music-based emotion regulation, emotion regulation self-efficacy, and emotional symptoms is complex and influenced by gender.
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Methods
This study examined healthy and unhealthy music use, emotion regulation self-efficacy, and levels of depression, anxiety, and alexithymia among 16,588 Chinese university students (M_age = 19.82 years, SD = 1.78; 55% male, n = 9,128; 45% female, n = 7,460) through an online survey. Gender differences were investigated using a multi-step analytical framework combining independent-sample t-tests, regularized partial correlation network (RPCN) analysis, and network comparison tests (NCT).Results: Network comparison analyses revealed significant gender differences in both healthy and unhealthy music-use networks (all invariance tests, p < 0.05).
In the healthy-use network, males demonstrated greater node strength for Difficulty Identifying Feelings (DIF, p = 0.001) and Despondency-distress Efficacy (DES, p < 0.001), whereas females exhibited higher node strength for Depression (p = 0.022). A similar pattern of male predominance in DIF (p = 0.005) and DES (p < 0.001) was observed in the unhealthy-use network.Conclusions: These findings underscore the significance of gender in music-based emotion regulation and highlight the need for gender-sensitive strategies in targeted interventions.
The study contributes to a deeper understanding of the dynamic interrelations between music use and emotional processes, offering valuable implications for theory, clinical practice, and the development of music-related digital tools and emotion regulation programs.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.psych.00279 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Music 69%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.psych.00279 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3603 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (69%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |