https://ogma.newcastle.edu.au/vital/access/ /manager/Index en-au 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41153 Thu 28 Jul 2022 09:20:25 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:46476 n = 951), while confirmatory factor analysis (CFA) was used to assess the goodness-of-fit of EFA models for the remaining half (n = 951). Spearman correlations were used to assess the convergent validity of the SAS-SV, taking account of time spent by subjects on phones per day, the Smart Device Addiction Screening Tool (SDAST), the Pittsburgh Sleep Quality Index (PSQI), the Multidimensional Scale of Perceived Social Support (MSPSS), and the Center for Epidemiological Studies Depression Scale for Children (CES-DC). EFA generated a three-factor model (with factors labeled “dependency,” the incidence of a “problem,” and “time spent”). CFA confirmed this model yielded an acceptable goodness-of-fit (Comparative Fit Index = 0.96, Tucker Lewis Index = 0.95, and root-mean-square error of approximation = 0.06). SAS-SV was positively correlated with SDAST (ρ = 0.59), PSQI (ρ = 0.29), and CES-D (ρ = 0.35), and negatively correlated with MSPSS (ρ = −0.10). A linear regression model showed that female adolescents, those with highly educated caregivers and those who spent more time using smartphones on their holidays, had on average higher SAS-SV scores, meaning they showed greater vulnerability to becoming addicted. The study found that SAS-SV is a valid scale for estimating excessive smartphone use among Hong Kong children and adolescents.]]> Thu 24 Nov 2022 08:29:24 AEDT ]]>