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. 2016 Mar;111(3):513-22.
doi: 10.1111/add.13192. Epub 2015 Nov 18.

Reframing video gaming and internet use addiction: empirical cross-national comparison of heavy use over time and addiction scales among young users

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Reframing video gaming and internet use addiction: empirical cross-national comparison of heavy use over time and addiction scales among young users

Stéphanie Baggio et al. Addiction. 2016 Mar.

Abstract

Background and aims: Evidence-based and reliable measures of addictive disorders are needed in general population-based assessments. One study suggested that heavy use over time (UOT) should be used instead of self-reported addiction scales (AS). This study compared UOT and AS regarding video gaming and internet use empirically, using associations with comorbid factors.

Design: Cross-sectional data from the 2011 French Survey on Health and Consumption on Call-up and Preparation for Defence-Day (ESCAPAD), cross-sectional data from the 2012 Swiss ado@internet.ch study and two waves of longitudinal data (2010-13) of the Swiss Longitudinal Cohort Study on Substance Use Risk Factors (C-SURF).

Setting: Three representative samples from the general population of French and Swiss adolescents and young Swiss men, aged approximately 17, 14 and 20 years, respectively.

Participants: ESCAPAD: n =22 945 (47.4% men); ado@internet.ch: n =3049 (50% men); C-SURF: n =4813 (baseline + follow-up, 100% men).

Measurements: We assessed video gaming/internet UOT ESCAPAD and ado@internet.ch: number of hours spent online per week, C-SURF: latent score of time spent gaming/using internet] and AS (ESCAPAD: Problematic Internet Use Questionnaire, ado@internet.ch: Internet Addiction Test, C-SURF: Gaming AS). Comorbidities were assessed with health outcomes (ESCAPAD: physical health evaluation with a single item, suicidal thoughts, and appointment with a psychiatrist; ado@internet.ch: WHO-5 and somatic health problems; C-SURF: Short Form 12 (SF-12 Health Survey) and Major Depression Inventory (MDI).

Findings: UOT and AS were correlated moderately (ESCAPAD: r = 0.40, ado@internet.ch: r = 0.53 and C-SURF: r = 0.51). Associations of AS with comorbidity factors were higher than those of UOT in cross-sectional (AS: .005 ≤ |b| ≤ 2.500, UOT: 0.001 ≤ |b| ≤ 1.000) and longitudinal analyses (AS: 0.093 ≤ |b| ≤ 1.079, UOT: 0.020 ≤ |b| ≤ 0.329). The results were similar across gender in ESCAPAD and ado@internet.ch (men: AS: 0.006 ≤ |b| ≤ 0.211, UOT: 0.001 ≤ |b| ≤ 0.061; women: AS: 0.004 ≤ |b| ≤ 0.155, UOT: 0.001 ≤ |b| ≤ 0.094).

Conclusions: The measurement of heavy use over time captures part of addictive video gaming/internet use without overlapping to a large extent with the results of measuring by self-reported addiction scales (AS). Measuring addictive video gaming/internet use via self-reported addiction scales relates more strongly to comorbidity factors than heavy use over time.

Keywords: Addiction; heavy use over time; internet use; measurement; population-based sample; video gaming.

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