Exploring obesity, physical activity, and digital game addiction levels among adolescents: A study on machine learning-based prediction of digital game addiction

Primary study aim was defining prevalence of obesity, physical activity levels, digital game addiction level in adolescents, to investigate gender differences, relationships between outcomes. Second aim was predicting game addiction based on anthropometric measurements, physical activity levels. Cross-sectional study design was implemented. Participants aged 9-14 living in Kirikkale were part of the study. The sample of the study consists of 405 adolescents, 231 girls (57%) and 174 boys (43%). Self-reported data were collected by questionnaire method from a random sample of 405 adolescent participants. To determine the physical activity levels of children, the Physical Activity Questionnaire for Older Children (PAQ-C). Digital Game addiction was evaluated with the digital game addiction (DGA) scale. Additionally, body mass index (BMI) status was calculated by measuring the height and body mass of the participants. Data analysis were performed using Python 3.9 software and SPSS 28.0 (IBM Corp., Armonk, NY, United States) package program. According to our findings, it was determined that digital game addiction has a negative relationship with physical activity level. It was determined that physical activity level had a negative relationship with BMI. In addition, increased physical activity level was found to reduce obesity and DGA. Game addiction levels of girl participants were significantly higher than boy participants, and game addiction was higher in those with obesity. With the prediction model obtained, it was determined that age, being girls, BMI and total physical activity (TPA) scores were predictors of game addiction. The results revealed that the increase in age and BMI increased the risk of DGA, and we found that women had a 2.59 times greater risk of DGA compared to men. More importantly, the findings of this study showed that physical activity was an important factor reducing DGA 1.51-fold. Our prediction model Logit (P) = 1/(1 + exp(-(-3.384 + Age*0.124 + Gender-boys*(-0.953) + BMI*0.145 + TPA*(-0.410)))). Regular physical activity should be encouraged, digital gaming hours can be limited to maintain ideal weight. Furthermore, adolescents should be encouraged to engage in physical activity to reduce digital game addiction level. As a contribution to the field, the findings of this study presented important results that may help in the prevention of adolescent game addiction

Exploring obesity, physical activity, and digital game addiction levels among adolescents: A study on machine learning-based prediction of digital game addiction

Primary study aim was defining prevalence of obesity, physical activity levels, digital game addiction level in adolescents, to investigate gender differences, relationships between outcomes. Second aim was predicting game addiction based on anthropometric measurements, physical activity levels. Cross-sectional study design was implemented. Participants aged 9-14 living in Kirikkale were part of the study. The sample of the study consists of 405 adolescents, 231 girls (57%) and 174 boys (43%). Self-reported data were collected by questionnaire method from a random sample of 405 adolescent participants. To determine the physical activity levels of children, the Physical Activity Questionnaire for Older Children (PAQ-C). Digital Game addiction was evaluated with the digital game addiction (DGA) scale. Additionally, body mass index (BMI) status was calculated by measuring the height and body mass of the participants. Data analysis were performed using Python 3.9 software and SPSS 28.0 (IBM Corp., Armonk, NY, United States) package program. According to our findings, it was determined that digital game addiction has a negative relationship with physical activity level. It was determined that physical activity level had a negative relationship with BMI. In addition, increased physical activity level was found to reduce obesity and DGA. Game addiction levels of girl participants were significantly higher than boy participants, and game addiction was higher in those with obesity. With the prediction model obtained, it was determined that age, being girls, BMI and total physical activity (TPA) scores were predictors of game addiction. The results revealed that the increase in age and BMI increased the risk of DGA, and we found that women had a 2.59 times greater risk of DGA compared to men. More importantly, the findings of this study showed that physical activity was an important factor reducing DGA 1.51-fold. Our prediction model Logit (P) = 1/(1 + exp(-(-3.384 + Age*0.124 + Gender-boys*(-0.953) + BMI*0.145 + TPA*(-0.410)))). Regular physical activity should be encouraged, digital gaming hours can be limited to maintain ideal weight. Furthermore, adolescents should be encouraged to engage in physical activity to reduce digital game addiction level. As a contribution to the field, the findings of this study presented important results that may help in the prevention of adolescent game addiction

The Effects of Screen Time on Children

With the development of technology continuing to grow at a fast-paced pace in society, children are now becoming exposed to such technology at a younger age. The introduction of smartphones and tablets, which is defined as screen time in this paper, are being introduced to children as young as 6 months of age. Instead of children playing with toys recommended for their age, they use screen time for their play needs and entertainment. Some parents use screen time as a distraction and/or relief for their own needs when the child is upset or they’re unable to tend to the child. This can lead to a decrease in parent-child interaction which may impair the child’s ability to socialize with others, as well as affect their language development, which is associated with the communication that can help developing brains. My research question is: How does screen time affect children’s behaviors/coping, health, and language development? In my literature review, I searched various databases for primary articles related to the topic and organized the articles I found into categories, including behavioral effects on children, health problems that can occur in children, and how the use of screens impact a child’s language development. Based on the research in the literature review, I propose a study to survey parents in the San Francisco Bay Area, California. This study aims to add to the limited research regarding the effects of screen time on a child’s behavior, overall health, and language development

Adölesanlarda Beslenme, Egzersiz Davranışları ile İnternet Bağımlılığı Arasındaki İlişkinin İncelenmesi

Objective: This study aims to determine the relationship between adolescents' nutritionexercise behaviors and internet addiction, as well as identify the factors affecting their eating-exercise behaviors and internet addiction. Material and Method: This cross-sectional descriptive correlational study was performed in Fethiye. The sample of the study consisted of 421 students attending 11 secondary schools. Data were collected using a descriptive data form, the Internet Addiction Scale and the Nutrition Exercise Behavior Scale. The data were collected by the researcher after obtaining ethical committee and institutional permissions. Results: The students' psychological/addictive eating behavior subscale mean score was 38.9±8.8, their healthy eating/exercise subscale mean score was 47.6±9.4, the unhealthy eating/exercise behavior subscale mean score was 49.0±7.0, and the meal pattern subscale mean score was 23.4±4.5. The internet addiction scale mean score was 19.6±7.5. The regression analysis showed that variables pertaining to the students’ psychological/ addictive eating behavior, meal patterns, unhealthy nutrition/exercise behavior, their use of the internet for social media and other purposes, their class, and their consciousness of eating during the COVID-19 pandemic explained 35.8% of internet addiction, meaning that the model was statistically significant. An inverse correlation was found between the variables of psychological/addictive eating, meal patterns, unhealthy nutrition/exercise and being conscious of what one was eating during the COVID-19 pandemic, while a positive correlation was found between the variables of using the internet for social media and class. Conclusion: Pediatric nurses play an important role in supporting the healthy development of adolescents by creating programs to instill healthy lifestyle habits

Association of sleep quality and internet addiction among the medical students

Background: The side effects of Internet overuse have been emerging progressively causing the emergence of a problem that is defined as internet addiction or problematic internet use. It also disrupts the sleep wake cycle so adversely affecting quality of sleep. This study is a preliminary step toward understanding the effect of internet addiction on sleep quality among medical college students in India.Methods: This was an observational, cross-sectional, single-centred, and self-assessable. Questionnaire based study administrated among 525 consenting medical students. The participants were assessed by proforma containing demographic details, variables related with internet use, questionnaires of IAT (Internet Addiction Test for Internet Use) and PSQI (Pittsburgh Sleep Quality Index for Sleep quality. Statistical data were analysed by Graph Pad InStat version 3.06 using Chi–square test and Mann-Whitney test.Results: There were 9.3% of all participants were considered problematic internet users with frequency of internet addiction 0.9%. Participants with problematic internet use are likely to have poor sleep quality (p<0.0001). 23.8% of all participants had poor sleep quality and 76.2% of the students had good quality of sleep. Participants with poor quality of sleep were having high IAT scores in comparison to participants with good quality of sleep. Severity of poor sleep quality is positively correlated with internet addiction (r2=0.233, p<0.0001).Conclusions: Participants with problematic internet use were more likely to have poor quality of sleep and vice a versa

Internet gaming disorder and online gambling disorder: Clinical and personality correlates

Background and aims: The recent growth of Internet use has led to an increase of potentially problematic behaviors that can be engaged online, such as online gambling or Internet gaming. The aim of this study is to better conceptualize Internet gaming disorder (IGD) by comparing it with gambling disorder (GD) patients who only gamble online (online GD). Methods: A total of 288 adult patients (261 online GD and 27 IGD) completed self-reported questionnaires for exploring psychopathological symptoms, food addiction (FA), and personality traits. Results: Both clinical groups presented higher psychopathological scores and less functional personality traits when compared with a normative Spanish population. However, when comparing IGD to online GD, some singularities emerged. First, patients with IGD were younger, more likely single and unemployed, and they also presented lower age of disorder onset. In addition, they displayed lower somatization and depressive scores together with lower prevalence of tobacco use but higher FA scores and higher mean body mass index. Finally, they presented lower novelty seeking and persistence traits. Discussion: GD is fully recognized as a behavioral addiction, but IGD has been included in the Appendix of DSM-5 as a behavioral addiction that needs further study. Our findings suggest that IGD and online GD patients share some emotional distress and personality traits, but patients with IGD also display some differential characteristics, namely younger age, lower novelty seeking scores and higher BMI, and FA scores. Conclusions: IGD presents some characteristics that are not extensive to online GD. These specificities have potential clinical implications and they need to be further studied

Türkiye’de üniversite öğrencilerinde psikolojik iyi oluş ile sosyal medya kullanımı, öz-kontrol ve uykusuzluk arasındaki ilişkinin incelenmesi

This study aims to examine the relationship students’ social media use, insomnia, and self-control have with their psychological well-being. A total of 404 students (305 females and 99 males) participated in the research. The data have been collected using the Turkish versions of the Social Media Disorder Scale, Psychological Well-Being Scale, Brief Self-Control Scale, and Insomnia Severity Index. The relationship between variables were examined by Path Analysis. According to the results, the model shows that self-control significantly and directly increases psychological well-being, social media disorder increases insomnia, and insomnia decreases self-control. Social media disorder and insomnia significantly and indirectly predict psychological well-being through the mediation of self-control. The findings show psychological well-being to be affected by self-control, social media disorder, and insomnia.Bu çalışmada üniversite öğrencilerinin psikolojik iyi oluşları ile sosyal medya kullanımları, uykusuzluk ve özkontrolleri arasındaki ilişkileri incelemek amaçlanmıştır. Araştırmaya 404 öğrenci katılmıştır (305 Kadın ve 99 erkek). Verilerin toplanmasında, Psikolojik İyi Oluş Ölçeği, Sosyal Medya Bozukluğu Ölçeği, Uykusuzluk Şiddeti İndeksi ve Kısa Öz-Kontrol Ölçeğinden yararlanılmıştır. Değişkenler arasındaki ilişkiler Yol Analizi ile incelenmiştir. Sonuçlara göre, oluşturulan model öz kontrolün psikolojik iyi oluşu anlamlı ölçüde ve doğrudan artırdığını, sosyal medya bozukluğunun uykusuzluğu artırdığını ve uykusuzluğun öz kontrolü azalttığını göstermiştir. Sosyal medya bozukluğu ve uykusuzluk psikolojik iyi oluşu öz kontrol aracılığı ile dolaylı ve anlamlı olarak yordamıştır. Bulgular, psikolojik iyi oluşun öz kontrol, sosyal medya bozukluğu ve uykusuzluktan etkilendiğini göstermiştir

Problematic Internet Use as a Predictor of Eating Disorders in Students: A Systematic Review and Meta-Analysis Study

Problematic Internet use (PIU) has begun to be linked to the development of certain eating disorders. This uncontrolled use of the Internet is mainly found in the student population. The purposes of this paper were to determine PIU-related eating disorders in students from a systematic review of the literature and to analyze the incidence of PIU in eating disorders through a meta-analysis of the literature. We used two electronic databases (Web of Science and Scopus) from inception to June 2019. The systematic literature review was based on fixed inclusion and exclusion criteria. A total of 12 studies were identified (systematic review) and 10 studies for meta-analysis, which included 16,520 students. Di erent eating disorders were associated with PIU: anorexia nervosa, bulimia nervosa, binge-eating disorder, food preoccupation, loss of control eating, and dieting. Furthermore, meta-analysis confirmed that PIU is a predictor of eating disorders in students. The groups of students with PIU presented a higher rate in the presence of eating disorders, these di erences being significant. Finally, this study showed empirical evidence on the link between PIU and eating disorders. The need for prevention in childhood and adolescence is highlighted

Problematic usage of the internet and eating disorder and related psychopathology: a multifaceted, systematic review and meta-analysis

© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)Eating disorders are widespread illnesses with significant impact. There is growing concern about how those at risk of eating disorders overuse online resources to their detriment. We conducted a pre-registered systematic review and meta-analysis of studies examining Problematic Usage of the Internet (PUI) and eating disorder and related psychopathology. The meta-analysis comprised n = 32,295 participants, in which PUI was correlated with significant eating disorder general psychopathology Pearson r = 0.22 (s.e. = 0.04, p < 0.001), body dissatisfaction r = 0.16 (s.e. = 0.02, p < 0.001), drive-for-thinness r = 0.16 (s.e. = 0.04, p < 0.001) and dietary restraint r = 0.18 (s.e. = 0.03). Effects were not moderated by gender, PUI facet or study quality. Results are in support of PUI impacting on eating disorder symptoms; males may be equally vulnerable to these potential effects. Prospective and experimental studies in the field suggest that small but significant effects exist and may have accumulative influence over time and across all age groups. Those findings are important to expand our understanding of PUI as a multifaceted concept and its impact on multiple levels of ascertainment of eating disorder and related psychopathology.Peer reviewe