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Risk Factors for Smartphone Addiction in Korean Adolescents: Smartphone Use Patterns
Open accessAbstract
With widespread use of the smartphone, clinical evidence for smartphone addiction remains unclear. Against this background, we analyzed the effect of smartphone use patterns on smartphone addiction in Korean adolescents. A total of 370 middle school students participated. The severity of smartphone addiction was measured through clinical interviews and the Korean Smartphone Addiction Proneness Scale. As a result, 50 (13.5%) were in the smartphone addiction group and 320 (86.5%) were in the healthy group. To investigate the effect of smartphone use patterns on smartphone addiction, we performed self-report questionnaires that assessed the following items: smartphone functions mostly used, purpose of use, problematic use, and parental attitude regarding smartphone use. For smartphone functions mostly used, the addiction group showed significantly higher scores in "Online chat." For the purpose of use, the addiction group showed significantly higher "habitual use," "pleasure," "communication," "games," "stress relief," "ubiquitous trait," and "not to be left out." For problematic use, the addiction group showed significantly higher scores on "preoccupation," "tolerance," "lack of control," "withdrawal," "mood modification," "conflict," "lies," "excessive use," and "loss of interest." For parental attitude regarding children's smartphone use, the addiction group showed significantly higher scores in "parental punishment." Binary logistic regression analysis indicated that "female," "use for learning," "use for ubiquitous trait," "preoccupation," and "conflict" were significantly correlated with smartphone addiction. This study demonstrated that the risk factors for smartphone addiction were being female, preoccupation, conflict, and use for ubiquitous trait; the protective factor was use for learning. Future studies will be required to reveal the additional clinical evidence of the disease entity for smartphone addiction.
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“Smartphone addiction is associated with decreased cognitive function (Lee et al., 2017) and deficits in attention and executive function such as inhibition and working memory (Lin et al., 2015).”
From The impact of digital technology, social media, and artificial intelligence on cognitive functions: a review (2023) · cites this paper as Lee et al., 2017
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Metadata
- Authors
- Lee, H., Kim, J. W., & Choi, T. Y.
- Affiliations
- Republic of Korea Army (KR)
- Daegu Catholic University (KR)
- Corresponding author
- Choi, Tae Young
- Venue
- Journal of Korean Medical Science
- Publisher
- XMLink
- Published
- 2017
- Volume
- 32
- Issue
- 10
- Pages
- 1674
- ISSN
- 1011-8934 (ISSN-L)
- 1598-6357
- PMC
- PMC5592183
- OpenAlex
- W2752810496
- Cited by
- 200
- References
- 15
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 22 · 2023: 19 · 2022: 24 · 2021: 17 · 2020: 75 · 2019: 16 · 2018: 7 · 2017: 1
- FWCI
- 69.34
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Korean Medical Science (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Ministry of Health and Welfare (HM14C2238)
- Topics
- Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
- Social Sciences › Education › Child Development and Digital Technology
- Social Sciences › Psychology › Clinical Psychology › Sexuality, Behavior, and Technology
- Keywords
- smartphone addiction, adolescents, risk factors, parental attitudes, online chat, preoccupation, gender differences, junior high school students, Korean adolescents
- MeSH terms
- Smartphone, Adolescent, Female, Humans, Male, Surveys and Questionnaires, Risk Factors, Sex Factors, Logistic Models, Odds Ratio, Behavior, Addictive, Asian People, Republic of Korea, Self Report
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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