Personality Factors Predicting Smartphone Addiction Predisposition: Behavioral Inhibition and Activation Systems, Impulsivity, and Self-Control

被引:91
|
作者
Kim, Yejin [1 ]
Jeong, Jo-Eun [2 ]
Cho, Hyun [2 ]
Jung, Dong-Jin [2 ]
Kwak, Minjung [2 ]
Rho, Mi Jung [3 ]
Yu, Hwanjo [1 ]
Kim, Dai-Jin [2 ]
Choi, In Young [3 ]
机构
[1] Pohang Univ Sci & Technol, Dept Creat IT Engn, Pohang, South Korea
[2] Catholic Univ Korea, Seoul St Marys Hosp, Coll Med, Dept Psychiat, Seoul, South Korea
[3] Catholic Univ Korea, Coll Med, Dept Med Informat, Seoul, South Korea
来源
PLOS ONE | 2016年 / 11卷 / 08期
基金
新加坡国家研究基金会;
关键词
CELLULAR PHONE USE; COLLEGE-STUDENTS; INTERNET ADDICTION; SENSATION SEEKING; SOCIAL NETWORKING; YOUDEN INDEX; ASSOCIATION; BIS/BAS; BAS; DIMENSIONS;
D O I
10.1371/journal.pone.0159788
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The purpose of this study was to identify personality factor-associated predictors of smartphone addiction predisposition (SAP). Participants were 2,573 men and 2,281 women (n = 4,854) aged 20-49 years (Mean +/- SD: 33.47 +/- 7.52); participants completed the following questionnaires: the Korean Smartphone Addiction Proneness Scale (K-SAPS) for adults, the Behavioral Inhibition System/Behavioral Activation System questionnaire (BIS/BAS), the Dickman Dysfunctional Impulsivity Instrument (DDII), and the Brief Self-Control Scale (BSCS). In addition, participants reported their demographic information and smartphone usage pattern (weekday or weekend average usage hours and main use). We analyzed the data in three steps: (1) identifying predictors with logistic regression, (2) deriving causal relationships between SAP and its predictors using a Bayesian belief network (BN), and (3) computing optimal cut-off points for the identified predictors using the Youden index. Identified predictors of SAP were as follows: gender (female), weekend average usage hours, and scores on BAS-Drive, BAS-Reward Responsiveness, DDII, and BSCS. Female gender and scores on BAS-Drive and BSCS directly increased SAP. BAS-Reward Responsiveness and DDII indirectly increased SAP. We found that SAP was defined with maximal sensitivity as follows: weekend average usage hours > 4.45, BAS-Drive > 10.0, BAS-Reward Responsiveness > 13.8, DDII > 4.5, and BSCS > 37.4. This study raises the possibility that personality factors contribute to SAP. And, we calculated cut-off points for key predictors. These findings may assist clinicians screening for SAP using cut-off points, and further the understanding of SA risk factors.
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页数:15
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