Analytical data
SPSS getting Windows (observar. 21.0; SPSS Inc., Chi town, IL, USA) was applied to own analytical study. Market features was in fact stated once the regularity and you will fee. Chi-rectangular sample was applied examine addiction and you may typical communities to your qualities away from gender, socio-financial condition, relatives framework, anxiety, stress, ADHD, puffing, and you will liquor have fun with. Pearson relationship analysis was performed to find the correlation anywhere between mobile addiction scores or other variables of great interest. Ultimately, multivariate digital logistic regression study are did to evaluate the influence out of gender, depression, nervousness, ADHD, puffing, and you may alcohol fool around with on the cellular phone habits. The analysis was accomplished playing with backwards strategy, that have dependency classification and you will typical category since the situated details and you will people gender, depression class, anxiety classification, ADHD class https://hookupdaddy.net/black-hookup-apps/, puffing category, and you may liquor organizations as independent variables. A beneficial p worth of lower than 0.05 are considered to suggest mathematical benefit.
Performance
Among the 5051 college students recruited towards investigation, 539 had been omitted due to partial answers. Therefore, all in all, 4512 students (forty-five.1% male, n = 2034; 54.9% girls, letter = 2478) was indeed one of them research. New indicate period of new subjects was (SD = step 1.62). The new sociodemographic functions of sufferers try summarized within the Desk step one. Getting site, 4060 students (87.8%) was basically cellphone people (84.2% of men, letter = 1718 regarding 2041; ninety.6% out-of girls, n = 2342 regarding 2584) one of many 4625 students who responded to practical question regarding cellular phone possession (426 did not operate).
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).