4.7 Article

Psychological distress and problematic smartphone use: Two faces of the same coin? Findings from a survey on young Italian adults

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COMPUTERS IN HUMAN BEHAVIOR
卷 132, 期 -, 页码 -

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chb.2022.107243

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Problematic smartphone use; Smartphone addiction; Internet addiction; Psychological distress; Factor analysis

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This study evaluated the factor structure of the Italian translation of the Smartphone Addiction Scale and investigated the role of psychological distress and other risk factors in problematic smartphone use among young Italian adults. The results led to the development of a shorter and reliable tool, as well as the identification of predictors that contribute to a potential risk profile.
Literature has shown that maladaptive smartphone use is more frequent in young adults and it is frequently associated with a condition of psychological distress. The Smartphone Addiction is an emerging phenomenon which has been shown to negatively affect individuals' well-being, productivity and health. It is considered a new form of Internet Addiction via mobile phone. The aim of the study was to evaluate the factor structure of the Italian translation of the Smartphone Addiction Scale -Short Version (SAS-SV) in a large sample of young Italian adults and to investigate the role of a psychological distress condition and other potential risk factors with respect to problematic smartphone use in this population. A sample of 2260 students (aged 18-25 years) filled in a web-based survey including the SAS-SV, the Internet Addiction Test, and the Matthey Generic Mood Questionnaire. An Exploratory Factor Analysis followed by Confirmatory Factor Analysis showed a reliable two-factor 8-items structure of SAS-SV. A multiple linear regression analysis showed that moderate-high perception of psychological distress, time spent using the smartphone overnight and, use of image-based social networks were independent predictors of problematic smartphone use. Results led to a shorter and reliable tool, the SAS-SV-8, and highlighted predictors that can account for a potential risk profile to be taken into consideration in prevention.

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