Factors associated with smartphone addiction prevalence and its predictive capacity for health-related quality of life among Filipino adolescents

Abstract

ObjectivesThe prevalence of smartphone addiction among adolescents is currently on the rise. Earlier studies focused on the impact of smartphone addiction on various aspects of life, but little is known about its capacity to predict an individual’s quality of life. This study aimed to determine the prevalence of smartphone addiction among Filipino adolescents and to investigate the relationship between smartphone addiction and health-related quality of life (HRQoL). Furthermore, this study explored the differences between the smartphone addiction and non-smartphone addiction groups in terms of demographic profile, family environment, smartphone usage patterns, and HRQoL, and examined the predictive capacity of smartphone addiction on HRQoL above and beyond demographic profile, family environment, and smartphone usage patterns. MethodsThis cross-sectional study employed descriptive and hierarchical linear multiple regression analyses for the data obtained from 1,447 Filipino junior and senior high school students (males, n = 580; females, n = 867) through a Google forms online survey. ResultsWe found that the prevalence rate of smartphone addiction among Filipino high school students was 62.6% (males = 66.2%; females = 60.2%). A significant negative correlation between smartphone addiction and total HRQoL (r = −0.090; p < .01) was found in this study as well as with its subdomains: physical well-being (r = −0.106; p < .01), psychological well-being (r = −0.169; p < .01), and school environment (r = −0.072; p < .01), but not with the autonomy and parents (r = −0.001; p > .05) or peers and social support (r = 0.011; p > .05). Furthermore, significant differences were found between the smartphone addiction and non-smartphone addiction groups in terms of gender, hours spent on smartphones on weekdays and weekends, and frequency of smartphone use on weekends as well as total HRQoL and its subdomains: Physical well-being, psychological well-being, and school environment. Hierarchical multiple regression analysis reported that after entering smartphone addition in Model 4, it accounted for 3% of the variance in HRQoL (F(1, 1429) = 2.557, p < .05), which indicates that smartphone addiction significantly predicts HRQoL after accounting for demographic profile, family environment, and smartphone usage patterns. ConclusionsThis study clearly shows that the prevalence rate of smartphone addiction among Filipino adolescents is high. This calls for full awareness among parents as well as community educators and counselors regarding this issue and for the development of both community-based and school-based intervention programs to lessen the risk of smartphone addiction and its impact on the HRQoL of students.