Personality Factors Predicting Smartphone Addiction Predisposition: Behavioral Inhibition and Activation Systems, Impulsivity, and Self-Control
Kim Y, Jeong JE, Cho H, Jung DJ, Kwak M, Rho MJ, Yu H, Kim DJ, Choi IY
PloS one · 109 citas
Cómo se estudió
- Diseño
- Estudio transversal (clasificado por nuestro filtro de IA)
- Estudiado en
- Personas
- Resultado principal
- Marcadores de salud y funcionamiento
Quién lo pagó
- Financiación
- Financiación independiente
- Gobierno
- National Research Foundation
- Universidad u hospital
- Catholic University of Korea
- Gobierno
- National Research Foundation of Korea
- Subvenciones
- National Research Foundation of Korea (NRF-2014M3C7A1062893); National Research Foundation of Korea (2014M3C7A1062893)
Según 3 financiadores declarados y la declaración de financiación del texto completo.
Publicación
- Publicado
- 2016-08-17 · PLoS One · vol. 11 · número 8 · pág. e0159788
- Editorial
- Public Library of Science
- Citado
- 235 citas · más que el 100% de estudios similares · 52.3× el promedio de su campo
- Impacto
- Entre el 10 % más citado de su campo
- Referencias
- 68 trabajos
- Acceso
- Acceso abierto (revista) · CC-BY
- Áreas de investigación
- Impact of Technology on Adolescents · Behavioral Health and Interventions · Digital Mental Health Interventions
- Palabras clave
- smartphone addiction, behavioral inhibition system, behavioral activation system, impulsivity, self-control, personality factors, gender differences, Bayesian networks
- MeSH
- humans, compulsive behavior, adult, middle aged, female, male, young adult, republic of korea, smartphone, surveys and questionnaires, self-control
9 autores
- Yejin Kim🇰🇷Pohang University of Science and Technology
- Jo-Eun Jeong🇰🇷The Catholic University of Korea Seoul St. Mary's Hospital; Catholic University of Korea
- Hyun Cho🇰🇷The Catholic University of Korea Seoul St. Mary's Hospital; Catholic University of Korea
- Dong-Jin Jung🇰🇷The Catholic University of Korea Seoul St. Mary's Hospital; Catholic University of Korea
- Minjung Kwak🇰🇷The Catholic University of Korea Seoul St. Mary's Hospital; Catholic University of Korea
- Mi Jung Rho🇰🇷Catholic University of Korea
- Hwanjo Yu🇰🇷Pohang University of Science and Technology
- Dai‐Jin Kim🇰🇷 · autor de correspondenciaThe Catholic University of Korea Seoul St. Mary's Hospital; Catholic University of Korea
- In Young Choi🇰🇷 · autor de correspondenciaCatholic University of Korea
Resumen
El texto original del estudio, en el idioma en que se publicó.
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.
Resumen vía Europe PMC. Los derechos de autor siguen siendo de los autores o la editorial (CC BY).
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