The Relationship Between Emotional Eating Behavior and Internet Addiction in Junior High School Students: A Cross-Sectional Study.

This research was conducted determine the mediating role of eating habits in the effect of internet and smartphone addiction on body mass index. The study group consisted of 604 individuals aged between 18 and 45 years (Mean(Age) = 21.07, SD = 3.00). Data were collected using Young Internet Addiction Scale, Smartphone Addiction Scale Short Form and Three-Factor Eating Questionnaire. Findings show positive correlations between internet addiction and smartphone addiction with uncontrolled eating, cognitive restraint and emotional eating behavior. Internet and smartphone addiction were determined to positively predict emotional eating behavior, uncontrolled eating behavior and cognitive restraint. The direct effect and total effect of internet addiction on body mass index were insignificant. However results show that both smartphone and internet use by individuals affect body mass index mediated by eating behavior. This is the first study showing that smartphone and internet use both affected body mass index mediated by eating behavior. Research results emphasise the threat of addiction on physical health and suggest that educational and cognitive dietary interventions can contribute to healthy eating habits. Additionally, considering the internet may be used as an emotion regulation strategy, intervention programs may focus on developing emotion regulation skills aiming to develop coping ability for negative emotions to reduce emotional or uncontrolled eating.

Introduction: Internet addiction is one of the major issues among university students which affected not only their academic performance but also their sleep quality and eating behaviours. Thus, this study aims to investigate the association between internet addiction and eating behavior, with sleep quality among undergraduate students at Universiti Sains Malaysia (USM). Method: A cross-sectional study was conducted among 107 university students to obtain data regarding their internet addiction, eating behaviour, and sleep quality through a series of validated questionnaires. The Chi-square test, Mann-Whitney, and Kruskal-Wallis test had been used for the univariate analysis while binary logistic regression was the multivariate analysis. Significance was set as a p-value less than 0.05. Results: A total of 54.2% of the participants showed mild internet addiction and 59.8% of them had poor sleep quality. Severe internet addiction was significantly associated with highest scores in all the eating behaviour. Individuals who were overweight had the highest score for emotional eating. Furthermore, no association was found between internet addiction and eating behavior with sleep quality in both the univariate and multivariate analysis. Conclusion: Internet addiction may affect an individual`s eating behaviour and may potentially lead to several health complications in the future. Those who were overweight tend to be emotional eaters. Although, no significant factors were associated with sleep quality, future research should be done involving other parameters such as physical activity level, biochemical data and comorbidities.

BackgroundEvidence on the burden of depression, internet addiction and poor sleep quality in undergraduate students from Nepal is virtually non-existent. While the interaction between sleep quality, internet addiction and depressive symptoms is frequently assessed in studies, it is not well explored if sleep quality or internet addiction statistically mediates the association between the other two variables.MethodsWe enrolled 984 students from 27 undergraduate campuses of Chitwan and Kathmandu, Nepal. We assessed sleep quality, internet addiction and depressive symptoms in these students using Pittsburgh Sleep Quality Index, Young’s Internet Addiction Test and Patient Health Questionnaire-9 respectively. We included responses from 937 students in the data analysis after removing questionnaires with five percent or more fields missing. Via bootstrap approach, we assessed the mediating role of internet addiction in the association between sleep quality and depressive symptoms, and that of sleep quality in the association between internet addiction and depressive symptoms.ResultsOverall, 35.4%, 35.4% and 21.2% of students scored above validated cutoff scores for poor sleep quality, internet addiction and depression respectively. Poorer sleep quality was associated with having lower age, not being alcohol user, being a Hindu, being sexually active and having failed in previous year’s board examination. Higher internet addiction was associated with having lower age, being sexually inactive and having failed in previous year’s board examination. Depressive symptoms were higher for students having higher age, being sexually inactive, having failed in previous year’s board examination and lower years of study. Internet addiction statistically mediated 16.5% of the indirect effect of sleep quality on depressive symptoms. Sleep quality, on the other hand, statistically mediated 30.9% of the indirect effect of internet addiction on depressive symptoms.ConclusionsIn the current study, a great proportion of students met criteria for poor sleep quality, internet addiction and depression. Internet addiction and sleep quality both mediated a significant proportion of the indirect effect on depressive symptoms. However, the cross-sectional nature of this study limits causal interpretation of the findings. Future longitudinal study, where the measurement of internet addiction or sleep quality precedes that of depressive symptoms, are necessary to build upon our understanding of the development of depressive symptoms in students.

In this study, we aimed to evaluate the relationships between Internet addiction, smartphone addiction, sleep quality, and academic success. In this cross-sectional study, high-school students were surveyed to evaluate sleep quality, Internet addiction, and smartphone addiction. Students were queried about their demographics, and grade averages from the previous term were taken as an indicator of academic success. A total of 1,959 students were enrolled in this study, with 1,034 (52.8%) girls and 925 (47.2%) boys, and the median age of the participants was 16 (13-21) years. Multivariate analyses found that poor sleep quality in students who did not have breakfast before going to school was 1.58 times higher than those who did (p<0.001). Students who stayed in a dormitory had 1.79 times more poor sleep quality than those who stayed with their family, and a one-unit increase in the total score of the Young's Internet Addiction Test short form resulted in a 1.08-fold increase (both, p<0.001). Our study has shown that students' sleep quality was predicted to be lower if they stayed in a dormitory and skipped breakfast. In addition, Internet and smartphone addictions have a negative effect on sleep quality and academic performance.

The aim of this study was to investigate the relationship among sleep quality, impulsivity, anxiety, and depression in individuals with emotional eating behavior. The study was designed as a cross-sectional study. The study included 92 individuals (age 31.29 ± 9.17; female, 67.4% [ n = 62]; male, 32.6% [ n = 30]) with symptoms of emotional eating but no previous psychiatric diagnosis or treatment. Participants were administered a Structured Clinical Interview for DSM-5 Disorders interview form, a sociodemographic data form, the Emotional Eating Scale, the Beck Depression Scale, the Barratt Impulsivity Scale, the Beck Anxiety Scale, and the Pittsburgh Sleep Quality Index Scale. Emotional eating is positively correlated with anxiety ( r = 0.377, p = 0.001), depression ( r = 0.375, p = 0.001), impulsivity ( r = 0.250, p = 0.016), and poor sleep quality ( r = 0.478, p = 0.001). Obese individuals (defined as having a body mass index of 30 or higher) showed higher emotional eating ( z = -2.552, p = 0.016) and poorer sleep quality ( z = -2.089, p = 0.044) than nonobese individuals, and women showed higher emotional eating ( t = 2116, p = 0.037) and poorer sleep quality ( z = -2537, p = 0.010) than men. Poor sleep quality was associated with emotional eating. In this relationship, poor sleep quality influenced emotional eating through all mediators, including anxiety and depression ( B = 3.491; standardized effect, 0.485; p = 0.001). Poor sleep quality directly influenced emotional eating ( B = 2.806; standardized effect, 0.390; p = 0.001). The findings of the study suggest that emotional eating is associated with higher levels of anxiety, depression, impulsivity, and sleep problems, especially in women. It suggests that the interrelationships of psychological factors associated with emotional eating should be investigated.

BackgroundExcessive use of the internet among adolescents often led to later bedtimes and poor sleep quality. This study assessed the relationship between internet addiction and sleep quality among adolescents in a peri-urban setting in Nepal.MethodThis cross-sectional study employed a questionnaire survey among 390 adolescent students recruited from two schools in Kirtipur Municipality in Nepal. The Internet Addiction Test and the Pittsburgh Sleep Quality Index were used to assess internet addiction and poor sleep quality respectively. The association between internet addiction and sleep quality was analysed by logistic regression.ResultsOne-fifth (21.5%) of the participants were identified with borderline internet addiction and 13.3% with possible internet addiction. Poor sleep quality was found among 31% of the participants. Internet addiction was significantly associated with poor sleep quality (OR = 1.85, p = 0.022 for borderline, and OR = 3.98, p = <0.001 for possible internet addiction compared to no internet addiction).ConclusionAdolescents with internet addiction were more vulnerable to suffer from poor sleep quality. It is recommended that municipalities and schools should aware the adolescent students on the adverse effects of excessive internet use including poor sleep quality. The findings have implications for adolescents, parents, school authorities and researchers.

Background: Sleep quality plays a principal role in the protection of health. There is an increasing number of studies in the literature demonstrating that internet addiction and smartphone addiction impair sleep quality. However, the number of studies on Turkish adolescents is very limited. Therefore, this study examined the effects of internet addiction and smartphone addiction on sleep quality among Turkish adolescents.Methods: Participants in this cross-sectional study were 910 adolescents aged 13–18 years. Data were collected with the Short Internet Addiction Test, Smartphone Addiction Scale, and Pittsburgh Sleep Quality Index. In addition, a questionnaire was used to gather information about the demographic, socioeconomic, and health-related characteristics. Pearson’s Chi-square test, Chi-square test for trend, Mann–Whitney U test, logistic regression analysis, and Spearman’s correlation analysis were used in the analysis.Results: The sleep quality of 58.7% of the adolescents was poor. Additionally, girls and adolescents ≥16 years old had poor sleep quality. Sleep quality deteriorated as perceived health status and perceived economic status of family deteriorated. Compared to participants with normal internet addiction scores, poor sleep quality was 1.83 (95% CI [1.22–2.74]) times higher in those with problematic internet addiction and 1.99 (95% CI [1.23–3.87]) times higher in those with pathological internet addiction. One point increase in Smartphone Addiction Scale total score increased poor sleep quality 1.01 (95% CI [1.00–1.02]) times. Sleep quality scale were positively correlated with the smartphone addiction and internet addiction. However, there was no positive correlation between habitual sleep efficiency subcomponent of sleep quality and smartphone addiction and internet addiction.Conclusions: Internet addiction and smartphone addiction were associated with poor sleep quality in adolescents. Older adolescents (≥16 years), gender (female), poor health perception, and perception of moderate economic status of the family were other factors associated with poor sleep quality.

Problematic Internet use (PIU) is the inability of individuals to control their Internet use, resulting in marked distress and/or functional impairment in daily life. We assessed the frequency of PIU and predictors of PIU, including social anxiety disorder (SAD), quality of sleep, quality of life and Internet-related demographic variables among school going adolescents. This was an observational, single-centered, cross-sectional, questionnaire-based study of 1,312 school going adolescents studying in Grades 10, 11 and 12 in Bhavnagar, India. Every participant was assessed by a pro forma containing demographic details, questionnaires of Internet Addiction Test (IAT), Social Phobia Inventory (SPIN), Pittsburgh Sleep Quality Index (PSQI) and Satisfaction With Life Scale (SWLS) for PIU severity, SAD severity, Quality of Sleep assessment and Quality of Life assessment, respectively. The statistical analysis was done with SPSS Version 23 (IBM Corporation) using chi-square test, Student's t test and Pearson's correlation. Multiple linear regression analysis was applied to find the predictors of PIU. We found frequency of PIUs as 16.7% and Internet addiction as 3.0% among school going adolescents. Participants with PIU are more likely to experience SAD ( p < .0001), poor quality of sleep ( p < .0001) and poor quality of life ( p < .0001). There is positive correlation between severity of PIU and SAD ( r = .411, p < .0001). Linear regression analysis shows PIU can be predicted by SAD, sleep quality, quality of life, English medium, male gender, total duration of Internet use, monthly cost of Internet use, education, social networking, gaming, online shopping and entertainment as purpose of Internet use. Participants with PIU are more likely to experience SAD, poor quality of sleep and poor quality of life.

Facteurs associés à la cyberaddiction chez les adolescents Tunisiens

Poor sleep quality and internet addiction are significant issues affecting adolescents globally, and Nepal is no exception. Several studies have independently assessed the prevalence and associated factors of poor sleep quality and internet addiction among Nepali adolescents and youth, but the relationship between sleep-related attributes and internet addiction remains unexplored. This study aimed to explore the prevalence and contributing factors of poor sleep quality and internet addiction along with the relationship between sleep quality-related attributes and internet addiction. A cross-sectional study was conducted among 243 adolescents of Dakshinkali Municipality, Nepal. Pittsburgh Sleep Quality Index and Young's Internet Addiction Test scale were used to measure sleep quality and internet addiction. Pearson's chi-square test and binary logistic regression were performed at a 5% level of significance to examine the associated factors. The prevalence of poor sleep quality was 27.6% (95% CI: 22.6-33.7) while potential internet addiction was 49.4% (95% CI: 42.0-56.7). Poor sleep quality was associated with internet addiction (aOR: 1.845; 95% CI: 1.344-3.608), poor perceived relation with teachers (aOR: 2.274; 95% CI: 1.149-4.497), and presence of family conflict (aOR: 2.355; 95% CI: 1.040-5.329). Bad subjective sleep quality (aOR: 5.613; 95% CI: 2.007-15.701), sleep disturbance (aOR: 1.781; 95% CI: 1.251-4.872), frequent daytime dysfunction (aOR: 1.902; 95% CI: 1.083-4.638), and poor perceived relation with teachers (aOR: 2.298; 95% CI: 1.233-4.285), and presence of family conflict (aOR: 1.606; 95% CI: 1.202-3.675) were associated with internet addiction. Almost a quarter of adolescents' experience poor sleep quality, while nearly half screened positive for potential internet addiction. Established interrelations between sleep quality and internet usage underscore the importance of integrated intervention approaches combining lifestyle modification and family/school support to protect and promote the mental health and well-being of Nepalese adolescents.

Internet addiction has been a major behavioral disorder over the past decade. There remains a paucity of research to find the relationship between internet addictions and sleep quality in low- and middle-income countries such as Bangladesh. The aim of this study is to find the association between internet addiction and sleep quality among the medical college students. We conducted an analytical cross-sectional study in two medical colleges with 390 students in Dhaka, from December 2017 to May 2018. Pittsburg Sleep Quality Index was used to determine the quality of sleep and Orman’s Internet Addiction Test was used to classify the severity of internet addiction. It appears that the prevalence of poor sleep quality is 69.5% among the students and 68.4% of the students are having moderate to severe internet addiction. The results of multivariate logistic regression model indicated that the students with moderate and severe internet addiction are 75% and 95% less likely to have good sleep quality, respectively (OR = 0.25, CI 0.141–0.407; OR = 0.05, CI 0.013–0.118; reference: no internet addiction). Besides, the students who live with family during the class (OR = 1.74, CI 1.02–3.11), with smoking habit (OR = 0.236, CI 0.093–0.551, reference: non-smoker), not brushing teeth before sleep (OR = 1.705, CI 0.932–3.189), and housewife mother (OR = 0.576, CI 0.313–1.056; reference: working mother) are significantly associated with the good sleep quality among the medical college students. This study indicates that a significant proportion of students are having a poor sleep quality; there exists a positive correlation between internet addiction and poor sleep quality among the students. Thus, a necessity for developing interventions and education strategies to reduce internet addiction to improve the sleep quality in students is indispensable.

ABSTRACTExcessive internet use causes addiction leading to obsessive-compulsive behavior, depression, anxiety, juvenile delinquency, and sleep disorders. Poor sleep quality will reduce the ability to think, increase the risk of accidents, hormonal metabolism disorders during puberty and menstruation, excessive fatigue during the day, and impaired activities in work, school, and social functions. Internet addiction therapy is often carried out after complaints of severe symptoms such as social isolation, depression, and the risk of suicide. Patients must be hospitalized, which takes a long time and cost. Thus, developments are carried out to overcome the problem of internet addiction by preventing, screening, and intervening in internet addiction in a practical, effective, safe, and economical way using mobile applications. This study aimed to identify the effectiveness of internet-addiction mobile applications on internet-addicted students' sleep quality. A quasi-experimental using non-equivalent control group design with pre-test and post-test. The research instrument used was the Internet Addiction Test (IAT) and the Pittsburgh Sleep Quality Index (PSQI). This study used a consecutive sampling of 46 people for the intervention and control groups. Data were analyzed using the McNemar test. Internet-Addiction Mobile Application significantly improved sleep quality for students who experienced internet addiction (60,9%) experienced good sleep quality. Furthermore, Internet-Addiction Mobile Application can significantly reduce internet addiction (p-value = 0.04). Internet-Addiction Mobile Application effectively improves students' sleep quality who experience internet addiction. This information can be used as data to prevent and intervene in sleep quality problems in people with internet addiction.

Internet addiction is an emerging public health concern among adults, potentially affecting psychological well-being and sleep quality. Although a substantial body of research has focused on adolescents and younger adults, less is known about middle-aged and older adult populations. This study investigated the relationships between Internet addiction, sleep quality, and psychological well-being in 629 adults (aged 30-60 years) and examined the socio-demographic predictors of Internet addiction. Participants completed online questionnaires assessing Internet addiction, psychological well-being, and sleep quality (Pittsburgh Sleep Quality Index). The final sample had a mean age of 39.4 (SD = 7.8), with 53.4% female participants. Most were employed (77.9%), and nearly half held an undergraduate degree (49.1%). The mean Internet addiction score was 38.1 ± 13.6. Poor sleep quality was prevalent (67.2%), and Internet addiction was positively correlated with total PSQI scores (r = 0.593; p < 0.001). Higher psychological well-being was inversely associated with both Internet addiction (r = -0.417; p < 0.001) and poor sleep quality (r = -0.490; p < 0.001). Younger age, female gender, regular employment, and higher income predicted greater Internet addiction, whereas having an undergraduate degree was associated with lower scores. Taken together, the findings of this study emphasize the importance of addressing sleep quality and psychological well-being to mitigate excessive Internet use in mid-life and older populations, particularly among those at higher risk.

Background: At present, the cell-phone is not only a talking tool but also a virtual network connection in the individual’s daily life as people can connect easily in one click of finger through internet. Use mobile for more time may enhance the chance to several health risk and psychiatric disorders, such as anxiety disorders and depression. Aims and Objectives: The aim of this study is to access sleep quality and internet addiction in these students using Pittsburgh sleep quality index (PSQI) and internet addiction scale, respectively. Materials and Methods: The study was designed as a cross-sectional and questionnaire-based study. This study has been conducted among 300 college students in India through online, emails, and social media. Data analysis has been done on PSQI score and Internet addition score among the subjects. Results: The results of this study demonstrated significant associations of Internet addiction and poorer quality of sleep in those who have moderate and severe internet addiction than normal internet users. Conclusion: In the present study, more percentage of students met the criteria for poor sleep quality and internet addiction as well as have positive association with the different degrees of internet addiction.

IntroductionFood intake behavior is implicated in many chronic health issues, including obesity. Thus, understanding the underlying factors that affect food intake is important. Several studies have associated sleep restriction to increased dietary intake and poor food choices, which can be driven by hedonic mechanisms, specially food palatability. Given that people eat for different reasons other than stress, including boredom, anxiety, sadness or joy, our aim was to study the potential association between sleep quality and the cognitive-behavioral nature of food intake (eating behaviors, EB), as well as their impact on body mass index in a population of young adults.Materials and MethodsOne thousand twenty eight young adults (78% females; 21.4 ± 4.1years) were included in a cross-sectional study. The following questionnaires were used: Pittsburg Sleep Quality Index to assess sleep quality (scores &gt; 5 indicate poor sleep quality), the Three Factor Eating Questionnaire to assess the three dimensions of EB (emotional, uncontrolled and restraint eating) (Higher scores indicate higher EB). Additionally, height, weight, body mass index (BMI) and the level of physical activity were evaluated. Statistical analysis were performed using SPSS v24, and adjusted for confounding variables.ResultsSixty one percent of the studied population had a poor sleep quality, whereas no significant associations were found between poor sleep quality, gender or age. Poor sleep quality was associated with uncontrolled (p &lt; 0.001) and emotional (p &lt; 0.001) eating, as well as with BMI (p &lt; 0.001). In addition, emotional eating was associated to BMI (p &lt; 0.001). Finally, linear regression model showed that BMI is associated with poor sleep quality (p &lt; 0.01) and emotional eating (p &lt; 0.001).DiscussionOur findings suggest that poor sleep quality is frequent among young adults. Furthermore, poor sleep quality is associated with higher emotional and uncontrolled eating, showing that poor sleep might be associated with a higher tendency to over eat when coping to emotionally negative emotions (sadness, anger, depression, anxiety), and a high tendency to lose control over food intake itself. Finally, the association between poor sleep quality and high emotional eating can have a negative impact over BMI, even in young adults. Hence, interventions designed to improve weight status would benefit from focusing on sleep quality in order to reduce emotional and uncontrolled eating.