ABSTRACT
Objective: To determine whether psychiatric and gaming pattern variables are associated with gaming disorder in a school-based sample. Methods: We analyzed data from the Brazilian High-Risk Cohort for Psychiatric Disorders, a community sample aged 10 to 18, using questionnaires on gaming use patterns. We applied the Gaming Addiction Scale to diagnose gaming disorder and the Development and Well-Being Behavior Assessment for other diagnoses. Results: Out of 407 subjects, 83 (20.4%) fulfilled the criteria for gaming disorder. More role-playing game players were diagnosed with gaming disorder that any other genre. Gaming disorder rates increased proportionally to the number of genres played. Playing online, being diagnosed with a mental disorder, and more hours of non-stop gaming were associated with higher rates of gaming disorder. When all variables (including age and gender) were considered in a logistic regression model, the number of genres played, the number of non-stop hours, the proportion of online games, and having a diagnosed mental disorder emerged as significant predictors of gaming disorder. Conclusion: Each variable seems to add further risk of gaming disorder among children and adolescents. Monitoring the length of gaming sessions, the number and type of genres played, time spent gaming online, and behavior changes may help parents or guardians identify unhealthy patterns of gaming behavior.
Subject(s)
Humans , Child , Adolescent , Behavior, Addictive/diagnosis , Behavior, Addictive/epidemiology , Video Games , Disruptive, Impulse Control, and Conduct Disorders , Schools , Brazil/epidemiology , InternetABSTRACT
OBJECTIVE: To determine whether psychiatric and gaming pattern variables are associated with gaming disorder in a school-based sample. METHODS: We analyzed data from the Brazilian High-Risk Cohort for Psychiatric Disorders, a community sample aged 10 to 18, using questionnaires on gaming use patterns. We applied the Gaming Addiction Scale to diagnose gaming disorder and the Development and Well-Being Behavior Assessment for other diagnoses. RESULTS: Out of 407 subjects, 83 (20.4%) fulfilled the criteria for gaming disorder. More role-playing game players were diagnosed with gaming disorder that any other genre. Gaming disorder rates increased proportionally to the number of genres played. Playing online, being diagnosed with a mental disorder, and more hours of non-stop gaming were associated with higher rates of gaming disorder. When all variables (including age and gender) were considered in a logistic regression model, the number of genres played, the number of non-stop hours, the proportion of online games, and having a diagnosed mental disorder emerged as significant predictors of gaming disorder. CONCLUSION: Each variable seems to add further risk of gaming disorder among children and adolescents. Monitoring the length of gaming sessions, the number and type of genres played, time spent gaming online, and behavior changes may help parents or guardians identify unhealthy patterns of gaming behavior.
Subject(s)
Behavior, Addictive , Disruptive, Impulse Control, and Conduct Disorders , Video Games , Adolescent , Behavior, Addictive/diagnosis , Behavior, Addictive/epidemiology , Brazil/epidemiology , Child , Humans , Internet , SchoolsABSTRACT
INTRODUCTION: Restless legs syndrome (RLS) is a highly prevalent sleep movement disorder usually accompanied by periodic limb movements of sleep (PLMS). The incidence of RLS and PLMS in patients with end-stage renal disease (ESRD) on dialysis is much higher. Clinically, RLS and PLMS can co-occur. We hypothesized that patients with ESRD on dialysis would have a distinct presentation of RLS, with a higher prevalence of PLMS. METHODS: We examined clinical, demographic, biochemical, and polysomnographic characteristics of RLS in patients on dialysis matched to control subjects with normal renal function based on age, sex, body mass index, and frequency of apneas and hypopneas per hour of sleep, defined by the apnea and hypopnea index (AHI), in a proportion of 3:1. Patients with ESRD were on hemodialysis three times per week. Polysomnography was performed overnight in the sleep laboratory. FINDINGS: Patients on dialysis compared to control subjects had a lower amount of N3 sleep (77.6 ± 39.9 minutes vs. 94.8 ± 33.7 minutes, p = 0.037) and REM sleep (55.6 ± 27.5 minutes vs. 74.1 ± 28.4 minutes, p = 0.006), regardless of the presence of RLS. Among the patients on dialysis, those with RLS had higher PLMS. In the control group, patients with RLS had a lower ferritin level, which was not observed in the dialysis group. There was a significant interaction between PLMS and ESRD (p = 0.001), with a higher prevalence of PLMS in patients with ESRD on dialysis in a model adjusted for AHI, sex, arousals, and age. Factors that were associated with PLMS were RLS (p = 0.003), ESRD (p = 0.0001), and AHI (p = 0.041), with an adjusted R2 of 0.321. CONCLUSION: RLS in patients with ESRD on dialysis is independently associated with PLMS, regardless of the severity of sleep apnea, arousals, and age.
