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People were assigned to dependency group otherwise regular group making use of the the second meanings

People were assigned to dependency group otherwise regular group making use of the the second meanings

Statistical research

SPSS to possess Screen (observar. 21.0; SPSS Inc., Chicago, IL, USA) was applied having statistical research. Market characteristics was basically advertised due to the fact regularity and commission. Chi-square sample was utilized evaluate dependency and you will typical teams into properties off intercourse, socio-monetary condition, nearest and dearest design, depression, nervousness, ADHD, smoking, and liquor use. Pearson correlation research was did to select the relationship between cellular phone dependency score and other details of interest. Ultimately, multivariate digital logistic regression investigation is actually performed to evaluate the fresh new influence out-of sex, despair, nervousness, ADHD, puffing, and you may alcoholic drinks explore into the mobile habits. The research are done having fun with backwards approach, which have addiction group and you can regular category once the dependent parameters and women intercourse, anxiety category, nervousness category, ADHD category, smoking group, and you will alcohol communities once the separate details. A good p value of below 0.05 is actually thought to indicate statistical significance.

Efficiency

One of many 5051 pupils employed into investigation, 539 had been omitted because of partial solutions. Ergo, all in all, 4512 people (45.1% men, n = 2034; 54.9% lady, letter = 2478) was basically included in this data. The fresh new suggest age of the new sufferers was (SD = step 1.62). The sociodemographic qualities of subjects try described into the Dining table step one. To possess resource, 4060 children (87.8%) was in fact portable citizens (84.2% out of men, n = 1718 of 2041; 90.6% out of women, letter = 2342 away from 2584) one of many 4625 children who responded to the question of smartphone control (426 didn’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 https://datingranking.net/over-50-dating/ (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).

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