(PS6-D92) Differential Predictors of Problematic Smartphone Use and Problematic Gaming: Contributions of Age, Sex, and Use Expectantcies

The Interaction of Person, Affect, Cognition, and Environment (I-PACE) model has been used as a theoretical framework for investigating problematic technology use. Psychopathology variables such as depression and anxiety have been shown to be related to severity of problematic technology use; however, there is evidence to suggest that response variables (such as use expectancies) may be better predictors of problematic technology use. Our study sought to examine relative contributions of use expectancies to problematic smartphone use (PSU) and problematic gaming (PG).

Data were collected from 462 college undergraduates at a large Midwestern university using a web-based survey. Bivariate correlations conducted using R software indicated strong relationships (p < .01) between PSU (measured via the Smartphone Addiction Scale-Short Version) and the variables of interest including depression and anxiety symptoms (measured via the Depression Anxiety Stress Scales-21) and smartphone use expectancies (measured via the Smartphone Use Expectancies Scale). Bivariate correlations also indicated strong relationships (p < .01) between problematic gaming (PG; measured via the Internet Gaming Disorder Test) and the variables of interest including depression and anxiety symptoms, and gaming expectancies (measured via the Video Game Use Expectancies Scale [adapted]).

Sequential regression analyses were conducted to test two regression models with PSU severity and PG severity as the dependent variables. The first models for PSU and PG (with age, sex, depression and anxiety symptoms entered as predictors) were statistically significant, PSU model 1: R² = 0.11, F(4,462) = 14.85, p < .001; PG model 1: R² = 0.21, F(4,462) = 31.11, p < .001. The second models for PSU and PG (adding smartphone and gaming use expectances as predictors) were also statistically significant, PSU model 2: ∆R² = .22, F-change(6,460) = 39.49, p < .001; PG model 2: : ∆R² = .25, F-change(6,460) = 66.23, p < .001. Both using a smartphone to experience positive emotions (β = .301, p < .01) and to relieve negative emotions (β = .735, p < .001) demonstrated significant contributions to PSU. Younger age (p < .05) was also a predictor of PSU. Whereas, playing games to relieve negative emotions (β = .733, p < .001) and male sex (p < .001) demonstrated significant contributions to PG. Results indicate that use expectancies provide unique and differential contributions to PSU and PG severity.