Evaluation of Anxiety Levels in Children and Their Mothers and Appearance of Sleep Bruxism in Turkish Children and Associated Risk Factors: A Cross-Sectional Study.

AIMS: To evaluate the anxiety of children and their mothers in relation to sleep bruxism (SB) and associated risk factors. METHODS: A total of 96 children (48 with and 48 without bruxism) and their mothers participated in this study. A form with comprehensive history and oral and parafunctional habits associated with SB was used. Screen for Child Anxiety and Related Disorders (SCARED) was used to measure anxiety in children. The anxiety levels of the mothers were evaluated with the State-Trait Anxiety Inventory (STAI). SPSS version 21.0 was used for the analyses. Chi-square test was used to compare categorical data. Student t test or Mann-Whitney U test was used for the comparison of continuous data, and multiple logistic regression model was applied to detect the real factors associated with SB. RESULTS: The comparisons of SCARED total (P = .005), factor 3 (separation anxiety; P = .015), factor 4 (social anxiety; P = .011) and factor 5 (school fear; P = .005) showed significant differences between groups. State anxiety scores of the mothers were significantly higher in the bruxism group (P < .001). Statistically significant differences were seen for learning/behavioral/anger problems, mouth breathing, snoring, bad breath, parasitic infections, sleep difficulty, chewing a pen or pencil, and sleeping in their own room (P < .05). The real risk factors associated with SB were learning/behavioral/anger problems, an experience causing stress, snoring, and increased anxiety levels of mothers and children. CONCLUSION: Elevated anxiety levels of mother or children, learning/behavioral/anger problems, experience causing stress, and snoring increased the risk of having SB in children.

Technological addictions in attention deficit hyperactivity disorder: Are they associated with emotional intelligence?

BACKGROUND: The impaired regulation of emotional responses has significant social consequences for patients with attention deficit hyperactivity disorder (ADHD) and can be thought to increase the risk for technological addictions. AIM: Ditto objective of the present research is to investigate the relationship between technological addictions and trait emotional intelligence (EI) in adolescents with ADHD. METHODS: This cross-sectional study was conducted in 150 treatment-naïve adolescents with ADHD, aged 12-18 years. The sociodemographic information form, the Emotional Quotient-Inventory: Youth Version (EQ-i: YV), Internet Addiction Test, Smartphone Addiction Scale, and Conners' Parent Rating Scales were used for data collection. RESULTS: The findings revealed that ADHD-C and female patients have lower mean stress management scores on EQ-i: YV. Patients who have smartphone addiction (SA)/problematic internet usage have lower total EI and stress management scores. The oppositional, hyperactivity, and DSM-total scores were negatively correlated with stress management scores. Intrapersonal and stress management scores were negatively correlated to SA symptoms. CONCLUSION: The stress management dimension was the strongest factor related to ADHD and technological addictions. In adolescents with ADHD, stress management may be the key factor to cope with daily problems. Therefore, the interventions to develop EI can be a therapeutic option in ADHD and technological addictions.

Mannose-Binding Lectin 2 Gene Polymorphism in PANDAS Patients.

INTRODUCTION: Pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections (PANDAS), a subgroup of obsessive-compulsive disorder (OCD), has received much attention even though the specific underlying mechanisms remain unknown. Mannose-binding lectin (MBL) is a key factor in the innate immune response. The aim of this study was to investigate the role of MBL2 gene polymorphisms in pediatric OCD patients diagnosed as PANDAS, PANDAS-Variant and non-PANDAS. METHODS: The study included 102 pediatric OCD patients (59 [57.8% ] PANDAS, 20 [19.6% ] non-PANDAS, and 23 [22.5% ] PANDAS-Variant) and 60 healthy controls. Polymorphisms at codon 52, 54 and 57 of the MBL2 gene were investigated. RESULTS: Codon 54 polymorphism and any variant of MBL2 gene were significantly more frequent in the OCD group than in the control group (OR=2.97, 95% CI: 1.26-6.97; and OR=2.66, 95% CI: 1.32-5.38, respectively). According to regression analysis, the presence of any variant of MBL2 gene was found in 14.50-fold increased frequency in the PANDAS subgroup compared with the non-PANDAS subgroup (95% CI: 2.49-84.19). CONCLUSIONS: Our findings support an association between MBL2 genotypes and pediatric OCD, particularly PANDAS-OCD.