

SPSS for Screen (ver. 21.0; SPSS Inc., Chi town, IL, USA) was applied to own analytical investigation. Market qualities was said just like the frequency and you can percentage. Chi-square attempt was utilized examine habits and you will regular teams on the properties out of sex, socio-financial standing, friends design, despair, nervousness, ADHD, smoking, and you can alcoholic drinks use. Pearson correlation data is actually performed to determine the correlation between mobile dependency scores or other parameters interesting. Ultimately, multivariate binary logistic regression research was performed to assess the latest dictate out-of gender, despair, nervousness, ADHD, puffing, and you can liquor use on mobile addiction. The research are done having fun with backwards approach, having addiction group and you can regular group as the created details and you may females sex, depression class, stress class, ADHD group, smoking classification, and you can alcoholic beverages communities as the separate parameters. A p value of lower than 0.05 are thought to indicate analytical value.
Among 5051 students employed on investigation, 539 have been excluded on account of partial responses. Therefore, a maximum of 4512 children (45.1% male, n = 2034; 54.9% female, n = 2478) was indeed one of them analysis. The brand new mean ages of the new victims was (SD = 1.62). The newest sociodemographic attributes of your own sufferers is summarized inside Dining table 1. To have source, 4060 students (87.8%) was in fact mobile phone customers (84.2% away from men, letter = 1718 regarding 2041; 90.6% out-of lady, n = 2342 out-of 2584) among 4625 college students whom taken care of immediately issue off cellular phone ownership (426 failed to work).
Table 2 shows clinical characteristics between smartphone addiction and normal groups. Of the 4512 participants, 338 (7.5%) were categorized to the addiction group, while 4174 belonged to the normal group. The mean age in the addiction group and normal group was ± 1.63 and ± 1.44, respectively, with no statistical difference between the groups (t = 0.744, p = 0.458). Furthermore, socio-economic status and family structure had no statistical difference between the groups (? 2 = 3.912, p = 0.141; ? 2 = 0.685, p = 0.710). Apart from age, socio-economic status, and family structure, all other variables showed statistically significant differences between the addiction group and the normal group. These include: female sex (OR 1.75, 95% CI 1.38–2.21), depression (OR 4.15, 95% CI 3.26–5.28), anxiety (OR 4.41, 95% CI 3.43–5.64), cigarette smoking (OR 2.06, 95% CI 1.44–2.96), and alcohol use (OR 1.62, 95% CI 1.22–2.16). The largest difference among all variables was noted with ADHD symptomspared to 26.0% of addiction group also belonging to the ADHD group, only 3.4% in the normal group were in the ADHD group. The odds ratio for smartphone addiction https://datingranking.net/ios-hookup-apps/ in ADHD group compared to non-ADHD was (? 2 = , p < 0.001).
Table 3 shows the Pearson correlation coefficients of smartphone addiction with other variables. Total smartphone addiction score showed greatest correlation with total CASS score (r = 0.427, p < 0.001). The total SAS score was also associated with total BDI score, total BAI score, female sex, smoking group, and alcohol use group in a statistically significant manner.
To identify the variables associated with smartphone addiction, multivariate logistic regression analyses were performed. All variables showing statistically significant difference between addiction group and normal group were entered and analyzed using backward method. In the goodness-of-fit test of the regression analysis model, the ? 2 log likelihood was and statistically significant (p < 0.001). In the first model tested, alcohol use had no statistically significant effect on smartphone addiction (B = 0.161, OR = 1.174 p = 0.375, 95% CI 0.823–1.675) and was, thus, removed from the final model. Table 4 shows the final model of the analysis; the odds ratio for smartphone addiction of female sex to males was 2.01 (95% CI 1.54–2.61). Odds ratio of ADHD group compared to non-ADHD group for song all variables (95% CI 4.60–9.00).
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