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Cited 84 time in webofscience Cited 157 time in scopus
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dc.contributor.authorKim, Y-
dc.contributor.authorJeong, JE-
dc.contributor.authorCho, H-
dc.contributor.authorJung, DJ-
dc.contributor.authorKwak, M-
dc.contributor.authorRho, MJ-
dc.contributor.authorYu, H-
dc.contributor.authorKim, DJ-
dc.contributor.authorChoi, IY-
dc.date.accessioned2017-07-19T13:30:11Z-
dc.date.available2017-07-19T13:30:11Z-
dc.date.created2017-02-07-
dc.date.issued2016-08-17-
dc.identifier.issn1932-6203-
dc.identifier.urihttps://oasis.postech.ac.kr/handle/2014.oak/37109-
dc.description.abstractThe 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.-
dc.languageEnglish-
dc.publisherPublic Library of Science-
dc.relation.isPartOfPLoS ONE-
dc.titlePersonality Factors Predicting Smartphone Addiction Predisposition: Behavioral Inhibition and Activation Systems, Impulsivity, and Self-control-
dc.typeArticle-
dc.identifier.doi10.1371/JOURNAL.PONE.0159788-
dc.type.rimsART-
dc.identifier.bibliographicCitationPLoS ONE, v.11, no.8-
dc.identifier.wosid000381487600013-
dc.date.tcdate2019-02-01-
dc.citation.number8-
dc.citation.titlePLoS ONE-
dc.citation.volume11-
dc.contributor.affiliatedAuthorYu, H-
dc.identifier.scopusid2-s2.0-84984821879-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.wostc14-
dc.description.scptc13*
dc.date.scptcdate2018-05-121*
dc.description.isOpenAccessY-
dc.type.docTypeArticle-
dc.subject.keywordPlusCELLULAR PHONE USE-
dc.subject.keywordPlusCOLLEGE-STUDENTS-
dc.subject.keywordPlusINTERNET ADDICTION-
dc.subject.keywordPlusSENSATION SEEKING-
dc.subject.keywordPlusSOCIAL NETWORKING-
dc.subject.keywordPlusYOUDEN INDEX-
dc.subject.keywordPlusASSOCIATION-
dc.subject.keywordPlusBIS/BAS-
dc.subject.keywordPlusBAS-
dc.subject.keywordPlusDIMENSIONS-
dc.relation.journalWebOfScienceCategoryMultidisciplinary Sciences-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaScience & Technology - Other Topics-

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유환조YU, HWANJO
Dept of Computer Science & Enginrg
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