基于SMOTEENN算法的音乐APP听歌习惯与大学生抑郁倾向的相关性研究

黄馨巧; 朱珲; 屈壕; 伍亚舟; 宋秋月

doi:10.16016/j.2097-0927.202312027

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基于SMOTEENN算法的音乐APP听歌习惯与大学生抑郁倾向的相关性研究

公共卫生与预防医学 | 更新时间：2026-01-09

- 基于SMOTEENN算法的音乐APP听歌习惯与大学生抑郁倾向的相关性研究
- Correlation between music APP listening habits and depression tendency in college students based on SMOTEENN algorithm
- 陆军军医大学学报 2024年46卷第23期页码：2670-2680
- 作者机构：
  
  400038 重庆，陆军军医大学(第三军医大学)军事预防医学系军队卫生统计学教研室
- 作者简介：
  
  [ 宋秋月，E-mali：sqy216@tmmu.edu.cnSONG Qiuyue, E-mail: sqy216@tmmu.edu.cn
- 基金信息：
  
  国家自然科学基金项目(82173621)
- DOI：10.16016/j.2097-0927.202312027
  中图分类号： G645.5;R195.1;R395.6
- 收稿：2023-12-06，
  
  修回：2024-09-13，
  
  纸质出版：2024-12-15
- 稿件说明：
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黄馨巧, 朱珲, 屈壕, 等. 基于SMOTEENN算法的音乐APP听歌习惯与大学生抑郁倾向的相关性研究[J]. 陆军军医大学学报, 2024,46(23):2670-2680.

Xinqiao HUANG, Hui ZHU, Hao QU, et al. Correlation between music APP listening habits and depression tendency in college students based on SMOTEENN algorithm[J]. Journal of Army Medical University, 2024, 46(23): 2670-2680.
黄馨巧, 朱珲, 屈壕, 等. 基于SMOTEENN算法的音乐APP听歌习惯与大学生抑郁倾向的相关性研究[J]. 陆军军医大学学报, 2024,46(23):2670-2680. DOI： 10.16016/j.2097-0927.202312027.

Xinqiao HUANG, Hui ZHU, Hao QU, et al. Correlation between music APP listening habits and depression tendency in college students based on SMOTEENN algorithm[J]. Journal of Army Medical University, 2024, 46(23): 2670-2680. DOI： 10.16016/j.2097-0927.202312027.

摘要

目的

探究基于音乐APP听歌习惯的大学生抑郁倾向影响因素，构建预测模型并进一步优化。

方法

2023年4~5月采用方便抽样对1 157份在校大学生进行问卷调查，利用单因素分析和Logistic回归分析筛选影响因素，在此基础上构建预测模型；采用SMOTEENN过抽样算法改进数据集，构建预测模型。

结果

Logistic回归分析发现性别: 女性(

=1.730，95%

：1.257~2.396)，年级：大四和研究生(

=2.649，95%

：1.198~7.506)、(

=2.041，95%

：1.231~3.885)，专业：理科(

=1.573，95%

：1.052~2.350)，每天听歌时长：0.5~2 h(

=1.661，95%

：1.011~2.695)，听歌曲风: “伤情”和“怀旧”(

=2.668，95%

：1.701~4.226)、(

=1.751

95%

: 1.086~2.837)，留言频率：“0~5%”的歌曲留言(

=2.938，95%

：1.018~8.417)是抑郁倾向的独立危险因素。开始听歌的年限：1~3年内(

=0.547，95%

：0.347~0.872)，听歌时间段：14：00~18：00和18：00~21：00(

=0.375，95%

：0.167~0.845)、(

=0.313，95%

：0.148~0.671)，“国风”类歌曲：喜欢(

=0.711，95%

：0.541~0.941)是抑郁倾向的独立保护因素。预测效果最优的模型为基于SMOTEENN算法的Logistic预警模型，AUC为0.923。

结论

构建Logistic回归模型得到大学生抑郁倾向的9个独立影响因素。基于SMOTEENN算法所构建的预警模型能更准确地预测大学生的抑郁倾向。

Abstract

Objective

To investigate the influencing factors for tendency towards depression in college students having music listening habits with music APP

and develop a prediction model and further optimize it.

Methods

A total of 1 157 college students were subjected with convenient sampling and surveyed with questionaires between April and May 2023. Univariate analysis and logistic regression analysis were employed to identify the influencing factors. Then a prediction model was constructed based on these factors. SMOTEENN over-sampling algorithm was utilized to enhance the dataset and construct the prediction model.

Results

Logistic regression analysis revealed that female (

=1.730

95%

: 1.257~2.396)

senior grade (

=2.649

95%

: 1.198~7.506)

postgraduate grade (

=2.041

95%

: 1.231~ 3.885)

major in Science(

=1.573

95%

: 1.052~2.350)

listening for a duration of 0.5~2 h (

=1.661

95%

: 1.011~2.695)

music style of melancholy (

=2.668

95%

: 1.701~4.226) and of nostalgia (

=1.751

95%

: 1.086~2.837)

and frequency of comments on 0~5% of songs (

=2.938

95%

: 1.018~8.417) were independent risk factors for depressive tendency. Time since listening to music for 1~3 years (

=0.547

95%

: 0.347~0.872)

listening to music from 14:00 to 18:00

(

= 0.375

95%

: 0.167~0.845) and 18:00 to 21:00 (

=0.313

95%

: 0.148~0.671)

and preference for Chinese style songs (

=0.711

95%

: 0.541~0.941) were independent protective factors. The logistic early warning model based on SMOTEENN algorithm demonstrated optimal predictive performance with an AUC value of 0.923.

Conclusion

Our constructed logistic regression model has identified 9 independent influencing factors associated with depression tendency among college students.The early warning model based on SMOTEENN algorithm can predict the depression tendency more accurately for college students.

关键词

Keywords

references

ZHONG S L, CHENG D M, SU J H, et al . A network analysis of depressive symptoms, psychosocial factors, and suicidal ideation in 8686 adolescents aged 12-20 years[J ] . Psychiatry Res, 2023, 329: 115517. DOI: 10.1016/j.psychres.2023.115517.

王艳, 卢静, 龙小花, 等. 基于高通量测序研究大学生抑郁人群肠道菌群的多样性[J]. 生物技术, 2023, 33(4): 458-465. DOI: 10.16519/j.cnki.1004-311x.2023.04.0069.

WANG Y, LU J, LONG X H, et al . Gut microbial profile analysis of depression in college students based on high-throughput sequencing technique[J ] . Biotechnology, 2023, 33(4): 458-465. DOI: 10.16519/j.cnki.1004-311x.2023.04.0069.

庞珍, 王炜. 当代大学生抑郁的影响因素及对策分析[J]. 太原城市职业技术学院学报, 2023(9): 182-184. DOI: 10.16227/j.cnki.tycs.2023.0542.

PANG Z, WANG W. Influencing factors and countermeasures of contemporary college students' depression[J]. J Taiyuan Urban Vocat Coll, 2023(9): 182-184. DOI: 10.16227/j.cnki.tycs.2023.0542.

STEWART J, GARRIDO S, HENSE C, et al . Music use for mood regulation: self-awareness and conscious listening choices in young people with tendencies to depression[J ] . Front Psychol, 2019, 10: 1199. DOI: 10.3389/fpsyg.2019.01199.

MCFERRAN K S, HENSE C, KOIKE A, et al . Intentional music use to reduce psychological distress in adolescents accessing primary mental health care[J ] . Clin Child Psychol Psychiatry, 2018, 23(4): 567-581. DOI: 10.1177/1359104518767231.

GARRIDO S, STEVENS C J, CHANG E, et al . Music and dementia: individual differences in response to personalized playlists[J ] . J Alzheimers Dis, 2018, 64(3): 933-941. DOI: 10.3233/JAD-180084.

GARRIDO S, SCHUBERT E. Music and people with tendencies to depression[J]. Music Percept, 2015, 32(4): 313-321. DOI: 10.1525/mp.2015.32.4.313.

丁雅婷, 伍麟. 音乐"网抑云": 青年圈群抑郁话语的符号表征和互动策略[J]. 当代青年研究, 2023(1): 98-111. DOI: 10.3969/j.issn.1006-1789.2023.01.012.

DING Y T, WU L. Music\\ "wangyiyun": the symbolic representation and interactive strategies of depression discourse in the youth circle[J]. Contemp Youth Res, 2023(1): 98-111. DOI: 10.3969/j.issn.1006-1789.2023.01.012.

WITTKAMPF K A, NAEIJE L, SCHENE A H, et al . Diagnostic accuracy of the mood module of the patient health questionnaire: a systematic review[J ] . Gen Hosp Psychiatry, 2007, 29(5): 388-395. DOI: 10.1016/j.genhosppsych.2007.06.004.

GILBODY S, RICHARDS D, BREALEY S, et al . Screening for depression in medical settings with the patient health questionnaire (PHQ): a diagnostic meta-analysis[J ] . J Gen Intern Med, 2007, 22(11): 1596-1602. DOI: 10.1007/s11606-007-0333-y.

KROENKE K, SPITZER R L, WILLIAMS J B. The PHQ-9: validity of a brief depression severity measure[J]. J Gen Intern Med, 2001, 16(9): 606-613. DOI: 10.1046/j.1525-1497.2001.016009606.x.

SPITZER R L, KROENKE K, WILLIAMS J B. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. primary care evaluation of mental disorders. patient health questionnaire[J]. JAMA, 1999, 282(18): 1737-1744. DOI: 10.1001/jama.282.18.1737.

LEVIS B, BENEDETTI A, THOMBS B D, et al . Accuracy of patient health questionnaire-9 (PHQ-9) for screening to detect major depression: individual participant data meta-analysis[J ] . BMJ, 2019, 365: l1476. DOI: 10.1136/bmj.l1476.

HE C, LEVIS B, RIEHM K E, et al . The accuracy of the patient health questionnaire-9 algorithm for screening to detect major depression: an individual participant data meta-analysis[J ] . Psychother Psychosom, 2020, 89(1): 25-37. DOI: 10.1159/000502294.

WANG Y, LIANG L J, SUN Z Y, et al . Factor structure of the patient health questionnaire-9 and measurement invariance across gender and age among Chinese university students[J ] . Medicine, 2023, 102(1): e32590. DOI: 10.1097/MD.0000000000032590.

张天翼, 丁立新. 一种基于SMOTE的不平衡数据集重采样方法[J]. 计算机应用与软件, 2021, 38(9): 273-279. DOI: 10.3969/j.issn.1000-386x.2021.09.043.

ZHANG T Y, DING L X. A new resampling method based on smote for imbalanced data set[J]. Comput Appl Softw, 2021, 38(9): 273-279. DOI: 10.3969/j.issn.1000-386x.2021.09.043.

YOON S, VERONA E, SCHLAUCH R, et al . Why do depressed people prefer sad music?[J ] . Emotion, 2020, 20(4): 613-624. DOI: 10.1037/emo0000573.

CARLSON E, SAARIKALLIO S, TOIVIAINEN P, et al . Maladaptive and adaptive emotion regulation through music: a behavioral and neuroimaging study of males and females[J ] . Front Hum Neurosci, 2015, 9: 466. DOI: 10.3389/fnhum.2015.00466.

张语熙, 郭炳亮. 当代流行音乐中的国风美学: 以《万疆》为例[J]. 黄河之声, 2022(13): 172-174. DOI: 10.19340/j.cnki.hhzs.2022.13.054.

ZHANG Y X,GUO B L. Aesthetics of national style in contemporary pop music—taking Wanjiang as an example[J]. Song Yellow River, 2022(13): 172-174. DOI: 10.19340/j.cnki.hhzs.2022.13.054.

KALMBACH D A, PILLAI V, DRAKE C L. Nocturnal insomnia symptoms and stress-induced cognitive intrusions in risk for depression: a 2-year prospective study[J]. PLoS One, 2018, 13(2): e0192088. DOI: 10.1371/journal.pone.0192088.

OBAYASHI K, SAEKI K, KURUMATANI N. Bedroom light exposure at night and the incidence of depressive symptoms: a longitudinal study of the HEIJO-KYO cohort[J]. Am J Epidemiol, 2018, 187(3): 427-434. DOI: 10.1093/aje/kwx290.

杨雪英. 青年"网抑云" 现象的心理成因与引导策略[J]. 新生代, 2021(3): 60-64.

YANG X Y. Psychological causes and guiding strategies of youth's phenomenon of "Internet suppressing clouds" [J]. New Gener, 2021(3): 60-64.

BAHHAWI T A, ALBASHEER O B, MAKEEN A M, et al . Depression, anxiety, and stress and their association with khat use: a cross-sectional study among jazan university students, Saudi Arabia[J ] . Neuropsychiatr Dis Treat, 2018, 14: 2755-2761. DOI: 10.2147/NDT.S182744.

HAMAIDEH S H, AL-MODALLAL H, TANASH M, et al . Depression, anxiety and stress among undergraduate students during COVID-19 outbreak and "home-quarantine"[J ] . Nurs Open, 2022, 9(2): 1423-1431. DOI: 10.1002/nop2.918.

ALBIKAWI Z F. Predictors of anxiety, depression, and stress among female university nursing students during the COVID-19 pandemic: a cross-sectional study in Saudi Arabia[J]. J Pers Med, 2022, 12(11): 1887. DOI: 10.3390/jpm12111887.

袁晓菲, 周娇娇, 齐涵, 等. 新型冠状病毒肺炎流行期间青少年女性情绪问题及影响因素[J]. 临床精神医学杂志, 2021, 31(5): 378-381. DOI: 10.3969/j.issn.1005-3220.2021.05.012.

YUAN X F, ZHOU J J, QI H, et al . Emotional problems and influencing factors of female adolescents during COVID-19 epidemic period[J ] . J Clin Psychiatry, 2021, 31(5): 378-381. DOI: 10.3969/j.issn.1005-3220.2021.05.012.

夏瑞婷. 疏肝固肾汤对女性更年期综合征患者雌激素及负面情绪的影响[J]. 中国民间疗法, 2019, 27(9): 46-47. DOI: 10.19621/j.cnki.11-3555/r.2019.0924.

XIA R T. Effect of Shugan Gushen Decoction on estrogen and negative emotion in women with climacteric syndrome[J]. China Naturopathy, 2019, 27(9): 46-47. DOI: 10.19621/j.cnki.11-3555/r.2019.0924.

张甲杰, 董雅莲, 冯青波. 围绝经期女性情绪障碍发生现状影响因素及综合保健措施干预效果分析[J]. 中国妇幼保健, 2022, 37(21): 4071-4075. DOI: 10.19829/j.zgfybj.issn.1001-4411.2022.21.051.

ZHANG J J, DONG Y L, FENG Q B. Analysis on the influencing factors of emotional disorder in perimenopausal women and the intervention effect of comprehensive health care measures[J]. Matern Child Health Care China, 2022, 37(21): 4071-4075. DOI: 10.19829/j.zgfybj.issn.1001-4411.2022.21.051.

ZHANG J Z, YIN J, SONG X D, et al . The effect of exogenous estrogen on depressive mood in women: a systematic review and meta-analysis of randomized controlled trials[J ] . J Psychiatr Res, 2023, 162: 21-29. DOI: 10.1016/j.jpsychires.2023.04.002.

杨雪龙. 求职被拒与未就业大学毕业生抑郁症状: 心理韧性和社会支持的调节作用[J]. 高校辅导员学刊, 2023, 15(5): 82-87, 100. DOI: 10.13585/j.cnki.gxfdyxk.2023.05.013.

YANG X L. Moderating effects of psychological resilience and social support on the relationship of unemployed college graduates' being rejected in job-seeking and depressive symptoms[J]. J Coll Advis, 2023, 15(5): 82-87, 100. DOI: 10.13585/j.cnki.gxfdyxk.2023.05.013.

王晓霞, 李雷孝, 林浩. SMOTE类算法研究综述[J]. 计算机科学与探索, 2024, 18(5): 1135-1159.

WANG X X, LI L X, LIN H. Survey of research on SMOTE type algorithms[J]. J Front Comput Sci Technol, 2024, 18(5): 1135-1159.

LIN M Y, ZHU X F, HUA T, et al . Detection of ionospheric scintillation based on XGBoost model improved by SMOTE-ENN technique[J ] . Remote Sens, 2021, 13(13): 2577. DOI: 10.3390/rs13132577.

LIU X Q, GUO Y X, ZHANG W J, et al . Influencing factors, prediction and prevention of depression in college students: a literature review[J ] . World J Psychiatry, 2022, 12(7): 860-873. DOI: 10.5498/wjp.v12.i7.860.

MCFERRAN K S, SAARIKALLIO S. Depending on music to feel better: being conscious of responsibility when appropriating the power of music[J]. Arts Psychother, 2014, 41(1): 89-97. DOI: 10.1016/j.aip.2013.11.007.

HENSE C, SILVERMAN M J, MCFERRAN K S. Using the healthy-unhealthy uses of music scale as a single-session music therapy intervention on an acute youth mental health inpatient unit[J]. Music Ther Perspect, 2018, 36(2): 267-276. DOI: 10.1093/mtp/miy013.

MCFERRAN K S, GARRIDO S, O'GRADY L, et al . Examining the relationship between self-reported mood management and music preferences of Australian teenagers[J ] . Nord J Music Ther, 2015, 24(3): 187-203. DOI: 10.1080/08098131.2014.908942.

PAPINCZAK Z E, DINGLE G A, STOYANOV S R, et al . Young people's uses of music for well-being[J ] . J Youth Stud, 2015, 18(9): 1119-1134. DOI: 10.1080/13676261.2015.1020935.

BIBB J, MCFERRAN K S. Musical recovery: the role of group singing in regaining healthy relationships with music to promote mental health recovery[J]. Nord J Music Ther, 2018, 27(3): 235-251. DOI: 10.1080/08098131.2018.1432676.

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