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

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.

Disease profiles of detainees in the Canton of Vaud in Switzerland: gender and age differences in substance abuse, mental health and chronic health conditions.

BACKGROUND: Literature on the disease profile of prisoners that differentiates by age and gender remains sparse. This study aimed to describe the health of correctional inmates in terms of substance abuse problems and mental and somatic health conditions, and compare it by gender and age. METHODS: This study examined cross-sectional data from the Canton of Vaud in Switzerland on the health conditions of detainees who were in prison on January 1, 2011 or entered prison in 2011. Health conditions validated by physician examination were reported using the International Classification of Diseases (ICD) version 10. The analyses were descriptive by groups of prisoners: the entire sample (All), Men, Older adults and Women. RESULTS: A total of 1,664 individuals were included in the analysis. Men comprised 91.5 % of the sample and had a mean age of 33 years. The other 8.5 % were women and had an average age of 39. Older adults (i.e., age 50 and older) represented 7 % of the total sample. Overall, 80 % of inmates were non-Swiss citizens, but the proportion of Swiss prisoners was higher among the older adults (51 %) and women (29 %). Overall, 41 % of inmates self-reported substance abuse problems. Of those, 27 % were being treated by psychiatrists for behavioral disorders related to substance abuse. Chronic infectious diseases were found in 9 % of the prison population. In addition, 27 % of detainees suffered from serious mental health conditions. Gender and age had an influence on the disease profile of this sample: compared to the entire prison population, the older inmates were less likely to misuse illegal drugs and to suffer from communicable infections but exhibited more problems with alcohol and a higher burden of chronic health conditions. Female prisoners were more disposed to mental health problems (including drug abuse) and infectious diseases. In terms of chronic diseases, women suffered from the same conditions as men, but the diseases were more prevalent in women. CONCLUSION: It is important to understand the different disease profiles of prisoners by gender and age, as it helps identify the needs of different groups and tailor age-and gender-specific interventions.