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Currently submitted to: Journal of Medical Internet Research

Date Submitted: Oct 8, 2020
Open Peer Review Period: Oct 8, 2020 - Dec 3, 2020
(currently open for review)

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

The bidirectional association between Internet addiction and depression: a large-sample longitudinal study among Chinese university students

  • Wan-Jun Guo; 
  • Xia Yang; 
  • Yu-Jie Tao; 
  • Ya-Jing Meng; 
  • Hui-Yao Wang; 
  • Xiao-Jing Li; 
  • Ya-Min Zhang; 
  • Jin-Kun Zeng; 
  • Wan-Jie Tang; 
  • Qiang Wang; 
  • Wei Deng; 
  • Lian-Sheng Zhao; 
  • Xiao-Hong Ma; 
  • Ming-Li Li; 
  • Jia-Jun Xu; 
  • Jing Li; 
  • Yan-Song Liu; 
  • Zhen Tang; 
  • Xiang-Dong Du; 
  • Wei Hao; 
  • Jeremy W. Coid; 
  • Sing Lee; 
  • Andrew J Greenshaw; 
  • Tao Li; 

ABSTRACT

Background:

Evidence indicates that Internet addiction (IA) is associated with depression, but longitudinal studies have rarely been reported, and no studies have yet investigated potential common vulnerability or a possible specific causal relationship between these disorders.

Objective:

To overcome these gaps, the present 12-month longitudinal study based on a large-sample employed a cross-lagged panel model (CLPM) approach to investigate the potential common vulnerability and specific cross-causal relationships between IA and CSD (or depression).

Methods:

IA and clinically-significant depression (CSD) among 12 043 undergraduates were surveyed at baseline (as freshmen) and in follow-up after 12 months (as sophomores). Application of CLPM revealed two well-fitted design between IA and CSD, and between severities of IA and depression, adjusting for demographics.

Results:

Rates of baseline IA and CSD were 5.47% and 3.85%, respectively; increasing to 9.47% and 5.58%, respectively at follow-up. Among those with baseline IA and CSD, 44.61% and 34.48% remained stable at the time of the follow-up survey, respectively. Rates of new-incidences of IA and CSD over 12 months were 7.43% and 4.47%, respectively. Application of a cross-lagged panel model approach (CLPM, a discrete time structural equation model used primarily to assess causal relationships in real-world settings) revealed two well-fitted design between IA and CSD, and between severities of IA and depression, adjusting for demographics. Models revealed that baseline CSD (or depression severity) had a significant net-predictive effect on follow-up IA (or IA severity), and baseline IA (or IA severity) had a significant net-predictive effect on follow-up CSD (or depression severity).

Conclusions:

These correlational patterns using a CLPM indicate that both common vulnerability and bidirectional specific cross-causal effects between them may contribute to the association between IA and depression. As the path coefficients of the net-cross-predictive effects were significantly smaller than those of baseline to follow-up cross-section associations, vulnerability may play a more significant role than bidirectional-causal effects. Clinical Trial: Ethics Committee of West China Hospital, Sichuan University (NO. 2016-171)


 Citation

Please cite as:

Guo W, Yang X, Tao Y, Meng Y, Wang H, Li X, Zhang Y, Zeng J, Tang W, Wang Q, Deng W, Zhao L, Ma X, Li M, Xu J, Li J, Liu Y, Tang Z, Du X, Hao W, Coid JW, Lee S, Greenshaw AJ, Li T

The bidirectional association between Internet addiction and depression: a large-sample longitudinal study among Chinese university students

JMIR Preprints. 08/10/2020:24874

DOI: 10.2196/preprints.24874

URL: https://preprints.jmir.org/preprint/24874

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