Analytical research

SPSS having Windows (observar. 21.0; SPSS Inc., Chi town, IL, USA) was utilized to own mathematical data. Market characteristics was in fact stated once the frequency and you may fee. Chi-square shot was applied to compare habits and you will normal communities with the properties out-of sex, socio-monetary updates, members Muslim Sites dating service of the family build, despair, nervousness, ADHD, smoking, and you may alcoholic beverages play with. Pearson relationship analysis was did to choose the relationship between cellphone habits score and other parameters interesting. In the end, multivariate digital logistic regression data is did to evaluate this new determine of gender, depression, nervousness, ADHD, puffing, and you will alcoholic drinks play with with the portable habits. The study try complete playing with backward means, which have addiction classification and you may normal classification since situated parameters and you may ladies gender, depression group, stress classification, ADHD class, smoking category, and you may alcohol teams due to the fact separate details. A great p value of below 0.05 was thought to imply mathematical advantages.

Efficiency

Among the many 5051 people recruited towards the study, 539 had been omitted due to incomplete solutions. Thus, a maximum of 4512 pupils (forty-five.1% men, letter = 2034; 54.9% women, letter = 2478) was included in this studies. Brand new imply ages of the victims is actually (SD = step one.62). This new sociodemographic features of subjects are described in the Table step one. To possess source, 4060 youngsters (87.8%) was indeed cellular phone residents (84.2% regarding male, n = 1718 off 2041; ninety.6% out-of girls, n = 2342 out-of 2584) one of the 4625 pupils which taken care of immediately the question from mobile possession (426 don’t 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 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).