Smart youth: sociodemographic factors, usage patterns, and self-reported vs. actual smartphone addiction among secondary school students

Abstract Background Smartphone addiction is a growing social problem especially in young mobile users. This study investigated indicators of smartphone use, smartphone addiction, and their associations with demographic and behavior-related variables in young people. Methods 460 participants were secondary school students (M age = 17,10, SD age = 0.92, 51.1% males, 52.4% high school students), took part in an anonymous questionnaire consisting of the following elements: the Mobile Phone Addiction Assessment Questionnaire (KBUTK), original questions regarding problematic smartphones usage, along with a subjective assessment of the use of such devices. Logistic regression model using forward stepwise method was used to characterize a typical smartphone user. Smartphone addiction was measured using KBUTK. Multiple logistic regression analysis was performed to determine factors associated with smartphone addiction. Results A total of 460 participants admitted to using a smartphone. Gender, age, type of school, place of living influenced the ways respondents used their smartphones. Being female (OR = 5.80; p < 0.0001), sixteen-year-old (OR = 0,41; p = 0.0456), and student of technical school (OR = 2.66; p = 0.0025) turned out to be the characteristics of a typical smartphone user. 21.7% of adolescents considered themselves addicted to smartphones, 22.2% admitted that they had problems with face-to-face relationships and girls significantly more often than boys (61.8% vs. 51.5%) neglected home or school duties as a result of using a smartphone. The overall rate of smartphone addiction was significantly higher ( p < 0.0001) among girls (2.31 pts) than boys (2.03 pts), and correlated positively with the perception of being a smartphone addict ( rho = 0.223; p < 0.0001). Addiction to smartphones was also significantly more common among students of technical schools, and respondents living in blocks of flats. Conclusions The way adolescents used smartphones differed depending on gender, age and type of school. Interventions for reducing the negative effects of smartphone use should take into account these context, as well as education both adolescents and their parents.