This study aimed to examine associations between risk factors suggested in the pathway model proposed by Billieux et al., demographic and substance use variables, and problematic smartphone use (PSU).
The analytical sample consisted of 5,096 Swiss men (mean age = 25.5 years, SD = 1.26). Multiple linear regression analyses were conducted with PSU as dependent and the following as independent variables: (a) Billieux’s pathway model variables (depression, social anxiety, ADHD, aggression–hostility, and sensation seeking); (b) substance use variables [alcohol: at-risk risky single-occasion drinking (RSOD); at-risk volume drinking; tobacco use: daily smoking; illicit drug use: more than weekly cannabis use; having used at least one other illicit drug besides cannabis over the preceding 12 months]; and (c) sociodemographic variables (age, language region, and education).
All pathway-model variables except sensation seeking were significant predictors of PSU, especially symptoms of social anxiety (β = 0.196) and ADHD (β = 0.184). At-risk RSOD was positively (β = 0.071) associated with PSU, whereas both frequent cannabis use (β = −0.060) and daily cigarette smoking (β = −0.035) were negatively associated with PSU. Higher-achieved educational levels and being from the German-speaking part of Switzerland predicted PSU.
Discussion and conclusions
The findings of this study can be used to develop tailored interventional programs that address the co-occurrence of certain risky behaviors (e.g., at-risk RSOD and PSU) and target individuals who might be particularly prone to PSU. Such interventions would need to ensure that addressing one problem (e.g., decreasing PSU) does not lead to some other compensatory behavior (e.g., frequent cigarette smoking).
Internet Use Disorders (IUDs) are emerging as a societal challenge. Evidence-based treatment options are scarce. Digital health interventions may be promising to deliver psychological treatment to individuals with IUDs directly in their online setting. The aim of this study was to evaluate the efficacy of a digital health intervention for IUDs compared to a waitlist control group (WCG).
In a two-armed randomized controlled trial, N = 130 individuals showing IUDs (Internet Addiction Test; IAT ≥49) were randomly allocated to the intervention group (IG; n = 65) or WCG (n = 65). The intervention consisted of 7 sessions based on cognitive behavioral therapy. The primary outcome was IUD symptom severity measured via the IAT at post treatment 7 weeks after randomization. Secondary outcomes included IUD symptoms (Compulsive Internet Use Scale; CIUS), quality of life, depressive and anxiety symptoms, and other psychosocial variables associated with IUDs.
Participants were on average 28.45 years old (SD = 10.59) and 50% identified as women, 49% as men, and 1% as non-binary. The IG (n = 65) showed significantly less IUD symptom severity (IAT) (d = 0.54, 95% CI 0.19–0.89) and symptoms (d = 0.57, 95% CI 0.22–0.92) than the WCG (n = 65) at post-treatment. Study attrition was 20%. Effects on all other secondary outcomes were not significant. On average, participants completed 67.5% of the intervention.
Discussion and Conclusions
A digital health intervention could be a promising first step to reduce IUD symptom severity.