Journal of Shanghai Jiao Tong University (Medical Science) >
Study on factors influencing social network service addiction among junior college students based on problem behavior theory
Received date: 2023-01-13
Accepted date: 2023-04-03
Online published: 2023-08-28
Supported by
National Key R&D Program of China(2020YFC2006400);Yangtze River Delta Regional Leading Talents Research Project on Immunization(CSJP033);Key Young Talents Training Program for Shanghai Disease Control and Prevention(22QNGG16)
Objective ·To construct a structural equation model based on problem behavior theory to conduct a study on social network addiction among junior college students. Methods ·A cross-sectional questionnaire survey was conducted in a college in Shanghai. Logistic regression analysis was used to analyze the effects of gender, grade, study pressure, self-esteem, loneliness, depression, entrapment, defeat, interpersonal needs, perceived social support, smoking, alcohol, exercise, and academic achievement on social network service addiction. Based on the problem behavior theory, the structural equation model was used to construct a theoretical framework model of social network service addiction of junior college students. Results ·60.31% of the total 980 participants had social network service addiction. The univariate Logistic regression results showed that depression, self-esteem, loneliness, frustration, drowsiness, social support, interpersonal needs, exercise, and academic performance had a significant impact on social network addiction. The structural equation model fitted well [S-Bχ2/df=8.03, goodness-of-fit index (GFI)=0.924, comparative fit index (CFI)=0.909, Tucker-Lewis index (TLI)=0.872, root mean square error of approximation (RMSEA)=0.096, standardized root mean square residual (SRMR)=0.070], suggesting the mutual influence between the personality system and the perceived environment system, between the personality system and the behavioral system, and between the perceived environment system and the behavior system interact (β=1.018, P=0.000; β=0.218, P=0.003; β=0.268, P=0.000). The influence of personality system and behavior system on social network service addiction was not statistically significant, while the perceived environment system had a significant positive impact on social network service addiction (β=0.481, P=0.001). Conclusion ·Personality system and behavior system indirectly affect social network service addiction by influencing perceived environment system, and perceived environment system directly affects social network service addiction. For the problem of social network addiction among lower grade college students, it is necessary to fully respect the characteristics of college students, and work together from three levels of the system to reduce the risk of social network addiction among college students.
Suping WANG , Hua TANG , Dong ZHOU , Yong CAI , Ruijie GONG . Study on factors influencing social network service addiction among junior college students based on problem behavior theory[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2023 , 43(8) : 955 -962 . DOI: 10.3969/j.issn.1674-8115.2023.08.002
1 | ANDREASSEN C S, PALLESEN S. Social network site addiction: an overview[J]. Curr Pharm Des, 2014, 20(25): 4053-4061. |
2 | ANDREASSEN C S. Online social network site addiction: a comprehensive review[J]. Curr Addict Rep, 2015, 2(2): 175-184. |
3 | LA BARBERA D, LA PAGLIA F, VALSAVOIA R. Social network and addiction[J]. Stud Health Technol Inform, 2009, 144: 33-36. |
4 | KUSS D J, GRIFFITHS M D. Online social networking and addiction: a review of the psychological literature[J]. Int J Environ Res Public Health, 2011, 8(9): 3528-3552. |
5 | PANTIC I. Online social networking and mental health[J]. Cyberpsychol Behav Soc Netw, 2014, 17(10): 652-657. |
6 | JESSOR R. Risk behavior in adolescence: a psychosocial framework for understanding and action[J]. J Adolesc Health, 1991, 12(8): 597-605. |
7 | JESSOR R, DONOVAN J E, COSTA F M. Applying problem behavior theory to adolescent health behavior[M]//LEVESQUE R J R. Advancing responsible adolescent development. Cham: Springer International Publishing, 2017: 495-508. |
8 | YOON S, KLEINMAN M, MERTZ J, et al. Is social network site usage related to depression? A meta-analysis of Facebook-depression relations[J]. J Affect Disord, 2019, 248: 65-72. |
9 | WANG P C, LEI L, YU G L, et al. Social networking sites addiction and materialism among Chinese adolescents: a moderated mediation model involving depression and need to belong[J]. Front Psychol, 2020, 11: 581274. |
10 | 李亚杰, 李咸志, 余彬, 等. 成都市低年级大学生性知识现状及其影响因素调查[J]. 中国健康教育, 2021, 37(3): 244-247. |
10 | LI Y J, LI X Z, YU B, et al. Survey on sexual knowledge and its influencing factors among junior college students in Chengdu city[J]. Chinese Journal of Health Education, 2021, 37(3): 244-247. |
11 | 郑雨佳, 楼超华, 涂晓雯. 上海市3所高校低年级学生吸烟现状及其影响因素分析[J]. 中国健康教育, 2021, 37(7): 611-614, 619. |
11 | ZHENG Y J, LOU C H, TU X W. Current smoking prevalence and its influencing factors among lower grade students of 3 universities in Shanghai[J]. Chinese Journal of Health Education, 2021, 37(7): 611-614, 619. |
12 | 王甦平, 蔡泳, 朱睿, 等. 青少年社交网络成瘾评估量表初步编制和信效度检验[J]. 中华全科医学, 2022, 20(2): 324-326. |
12 | WANG S P, CAI Y, ZHU R, et al. Development of social network addiction tendency scale for adolescents and its reliability and validity[J]. Chinese Journal of General Practice, 2022, 20(2): 324-326. |
13 | 汪向东, 王希林, 马弘. 心理卫生评定量表手册[M]. 增订版. 北京: 中国心理卫生杂志社, 1999: 279. |
13 | WANG X D, WANG X L, MA H. Handbook of mental health assessment scales (updated edition) [M]. Beijing: Chinese Mental Health Journal, 1999: 279. |
14 | HAYS R D, DIMATTEO M R. A short-form measure of loneliness[J]. J Pers Assess, 1987, 51(1): 69-81. |
15 | MANEA L, GILBODY S, MCMILLAN D. A diagnostic meta-analysis of the Patient Health Questionnaire-9 (PHQ-9) algorithm scoring method as a screen for depression[J]. Gen Hosp Psychiatry, 2015, 37(1): 67-75. |
16 | ZIMET G D, DAHLEM N W, ZIMET S G, et al. The multidimensional scale of perceived social support[J]. J Pers Assess, 1988, 52(1): 30-41. |
17 | VAN ORDEN K A, CUKROWICZ K C, WITTE T K, et al. Thwarted belongingness and perceived burdensomeness: construct validity and psychometric properties of the Interpersonal Needs Questionnaire[J]. Psychol Assess, 2012, 24(1): 197-215. |
18 | 唐华, 王甦平, 龚睿婕, 等. 挫败感量表对医学生焦虑抑郁态的信效度评估[J]. 上海交通大学学报(医学版), 2019, 39(1): 84-88. |
18 | TANG H, WANG S P, GONG R J, et al. Reliability and validity of defeat scale on anxiety and depression in medical students[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2019, 39(1): 84-88. |
19 | 龚睿婕, 刘景壹, 王亦晨, 等. 困顿感量表中文版测评医学生的效度和信度[J]. 中国心理卫生杂志, 2019, 33(5): 393-397. |
19 | GONG R J, LIU J Y, WANG Y C, et al. Validity and reliability of the Chinese vision of the Entrapment Scale in medical students[J]. Chinese Mental Health Journal, 2019, 33(5): 393-397. |
20 | MACCALLUM R C, BROWNE M W, SUGAWARA H M. Power analysis and determination of sample size for covariance structure modeling[J]. Psychol Methods, 1996, 1(2): 130-149. |
21 | HU L T, BENTLER P M. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives[J]. Struct Equ Modeling, 1999, 6(1): 1-55. |
22 | BOLLEN K A, LONG J S. Testing structural equation models[M]. Thousand Oaks: SAGE Publications, 1993. |
23 | WANG S P, NI Y, GONG R J, et al. Psychosocial syndemic of suicidal ideation: a cross-sectional study among sexually transmitted infection patients in Shanghai, China[J]. BMC Public Health, 2020, 20(1): 1314. |
24 | 王昊. 大学生错失恐惧和社交网络成瘾倾向的关系及干预研究[D]. 昆明: 云南师范大学, 2021. |
24 | WANG H. Study on the relationship and intervention between fear of missing and social network addiction in college students[D]. Kunming: Yunnan Normal University, 2021. |
25 | 严慧兔. 大学生基本心理需要对社交网络成瘾的影响: 错失恐惧的中介作用[D]. 武汉: 武汉大学, 2020. |
25 | YAN H T. The influence of college students' basic psychological needs on social network addiction: the intermediary role of fear of missing out[D]. Wuhan: Wuhan University, 2020. |
26 | CHEN B F, LIU F, DING S S, et al. Gender differences in factors associated with smartphone addiction: a cross-sectional study among medical college students[J]. BMC Psychiatry, 2017, 17(1): 341. |
27 | XIE W J, KARAN K. Predicting Facebook addiction and state anxiety without Facebook by gender, trait anxiety, Facebook intensity, and different Facebook activities[J]. J Behav Addict, 2019, 8(1): 79-87. |
28 | KUSS D J, GRIFFITHS M D. Social networking sites and addiction: ten lessons learned[J]. Int J Environ Res Public Health, 2017, 14(3): E311. |
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