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Analytical study

SPSS for Windows (observar. 21.0; SPSS Inc., Chi town, IL, USA) was applied to possess analytical investigation. Demographic functions was basically advertised given that frequency and commission. Chi-square take to was utilized evaluate dependency and regular teams with the services from sex, socio-economic reputation, members of the family structure, despair, stress, ADHD, puffing, and alcoholic drinks use. Pearson correlation studies are performed to search for the relationship ranging from portable addiction ratings or any other details of great interest. In the long run, multivariate binary logistic regression studies was did to assess the determine of sex, anxiety, stress, ADHD, smoking, and alcoholic beverages play with toward portable addiction. The study was complete using backward strategy, which have habits group and you can normal class as built parameters and you will female intercourse, depression classification, anxiety category, ADHD category, smoking class, and you can alcohol groups just like the independent parameters. A p worth of less than 0.05 try considered to indicate analytical benefits.

Efficiency

One of the 5051 children recruited to your study, 539 was in fact excluded on account of unfinished responses. For this reason, a total of 4512 children (45.1% male, n = 2034; 54.9% lady, n = 2478) were one of them studies. The new indicate period of brand new sufferers is (SD https://datingranking.net/nl/matchocean-overzicht/ = step 1.62). Brand new sociodemographic characteristics of the victims is described for the Dining table step 1. Getting resource, 4060 children (87.8%) had been cellular phone customers (84.2% away from men, letter = 1718 regarding 2041; ninety.6% from females, letter = 2342 of 2584) one of several 4625 people just who taken care of immediately issue off mobile phone control (426 failed to perform).

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).

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