Background and Objectives: There is evidence that eating meals or snacks while watching TV is an obesogenic factor. Moreover, the patterns of TV and other screen use during meals begin early and persist. However, there are only a few studies to date which address the prevalence and predictors of young children’s exposure to screen during mealtimes. Thus, the present study aimed to investigate the prevalence and the associated factors of screen use during meals in early childhood. Materials and Methods: A cross sectional survey was conducted in Lithuania. Data of 847 children aged 2 to 5 years old (51.5% boys) were analyzed in this study. Parents completed the Child Behavior Checklist (CBCL/1½-5) and reported their children’s daily screen time, exposure to background TV, screen use during child’s meals, child and parental height and weight, and sociodemographic data. Results: More than half of children were exposed to screen during meals: 33.7% occasionally, several times per week or per month, and 22%—daily or during every meal. Overall daily screen time, background TV, consumption of junk food, child age, and emotional and behavioral problems were related to mealtime screen use (all associations significant at p < 0.01). Longer daily screen time (OR 1.01; 95% CI 1.00–1.01), more background TV (OR 1.26; 95% CI 1.10–1.45), and elder child age (OR 1.02; 95% CI 1.00–1.03) were significant predictors of occasional use of screen during meals. Also, longer daily screen time (OR 0.99; 95% CI 0.98–0.99), background TV (OR 0.78; 95% CI 0.66–0.91) together with no siblings’ status of a child (OR 0.42; 95% CI 0.25–0.69) increased the probability that children were fed in front of screens daily. Conclusions: This study confirmed the unfavorable associations among screen use during meals, daily screen time and junk food consumption in early childhood. In addition, first-time parents should get particular health providers’ attention as they are more likely to use screens during child’s mealtime.

Background/Objectives: Excessive screen time has been linked to poorer developmental outcomes in preschool years, with the impact depending on context. Parents of emotionally reactive children, in particular, may use screens to manage their child’s emotions, especially when experiencing distress themselves. This reliance on screens can hinder the development of self-regulation, leading to behavioral difficulties. Our study aimed to explore how emotional reactivity, parental distress, screen time, and media-related coping interact while contributing to externalizing (behavioral) problems in preschool-aged children. Methods: The study included 754 children (49.1% girls), aged 2–5 years (M = 44.6 months, SD = 13.7). Parents reported children’s emotional reactivity and externalizing problems using the Child Behavior Checklist and provided data on daily screen time and media-related coping behaviors. Bivariate correlations, group comparisons, and structural equation modeling were employed to analyze the data. Results: Children averaged 111.86 min of daily screen time (SD = 83.94), with 35.2% of parents using screens as a coping strategy. Emotional reactivity was the strongest predictor of externalizing problems, while the role of screen time was weak, yet significant. Parental distress was positively associated with child emotional reactivity and screen time. Structural equation modeling showed that child emotional reactivity related to behavioral problems both directly and indirectly via parental distress, media-related coping, and increased screen time. Conclusions: The findings highlight emotional reactivity as a key factor in child behavioral problems, emphasizing the cumulative risks posed by parental distress and screen use. The results suggest interventions promoting healthier screen habits and supporting parental well-being.

Lithuania was one of the countries that applied quarantine during the rise of COVID-19 pandemic in spring 2020, the duration of which was three months (from March 16th, 2020 to June 16th, 2020). Despite emerging literature showing negative effects of quarantine on children’s mental health, insight into specific risk factors is lacking due to limited longitudinal data. The aim of the present study was to analyse changes in Lithuanian pre-schoolers’ emotional and behavioural problems during the first quarantine due to COVID-19 pandemic and their relations to the potential risk factors such as parental distress and increase in daily screen time. Parents of 78 children aged 4 to 6 (31% girls and 69% boys, mean age at the first measurement 66.1 months (SD = 10.33)) completed Child Behaviour Checklist (CBCL/1½-5), questions on children’s screen time and physical activity and reported their distress before the quarantine (November 2019–February 2020) and at the end of it (May–June 2020). Results showed that children had more behavioral problems, spent more time on screens and were less physically active during the quarantine, and their parents were experiencing more distress than before. However, parental distress emerged as the only variable that predicted preschoolers’ emotional and behavioral problems during the quarantine after a child’s previous problems were taken into account. This highlights the importance of targeting support towards families raising children with behavioral problems, as the challenges they were already facing increase during quarantine and their parents may be more susceptible to less desirable practices such as providing children with more screen time as a way to cope with this situation.

Background/Objectives: Excessive screen time has been linked to poorer developmental outcomes in preschool years, with the impact depending on context. Parents of emotionally reactive children, in particular, may use screens to manage their child's emotions, especially when experiencing distress themselves. This reliance on screens can hinder the development of self-regulation, leading to behavioral difficulties. Our study aimed to explore how emotional reactivity, parental distress, screen time, and media-related coping interact while contributing to externalizing (behavioral) problems in preschool-aged children. Methods: The study included 754 children (49.1% girls), aged 2–5 years (M = 44.6 months, SD = 13.7). Parents reported children’s emotional reactivity and externalizing problems using the Child Behavior Checklist and provided data on daily screen time and media-related coping behaviors. Bivariate correlations, group comparisons, and structural equation modeling were employed to analyze the data. Results: Children averaged 111.86 minutes of daily screen time (SD = 83.94), with 35.2% of parents using screens as a coping strategy. Emotional reactivity was the strongest predictor of externalizing problems, while the role of screen time was weak, yet significant. Parental distress was positively associated with child emotional reactivity and screen time. Structural equation modeling showed that child emotional reactivity related to behavioral problems both directly and indirectly via parental distress, media-related coping, and increased screen time. Conclusions: The findings highlight emotional reactivity as a key factor in child behavioral problems, emphasizing the cumulative risks posed by parental distress and screen use. The results suggest interventions promoting healthier screen habits and supporting parental well-being.

Working memory (WM) is crucial for learning and academic success, emphasizing the need for effective theory- and practice-informed interventions supporting children with poor WM. Given limited transferable effects, recent research stresses the importance of context, focusing on malleable environmental factors like teacher–student interaction. This study uses a microtrial approach to explore the effects of teacher-provided instructional support on children’s observable WM-related problematic behavior. The experimental group (n = 35, 42.9% girls, Mage = 8.37, SDage = 1.66) received targeted instructional support, while the control group (n = 32, 40.6% girls, Mage = 8.67, SDage = 2.03) received teaching as usual. Pre- and post-intervention comparisons examined changes in students’ WM behavior. The four-week intervention included five strategies derived from a systematic review and a qualitative study, building on teachers’ existing practices. Findings revealed a significant time × condition interaction, with reduced WM-related problematic behavior in the experimental group, showing medium to large effect sizes (η_p² = 0.08–0.20). Improvements were noted in classroom behavior and the home environment, as reported by parents blinded to the condition. This study contributes to the causal evidence base indicating that targeted instructional support can reduce WM-related challenges and highlights the potential of brief, teacher-provided classroom interventions.

The concept of cost, defined as the perceived negative consequences of engaging in a task, is an important yet understudied component of the expectancy–value theory of student motivation. In this study, we examined the multidimensional cost structure in mathematics learning, focusing on four facets proposed in recent research: effort, opportunity, emotional, and ego costs. Participants consisted of 1483 ninth-grade students from 24 public schools in Lithuania (56.04% girls; M = 14.88 years). Students completed a questionnaire developed to assess the four cost dimensions, along with measures of their intentions to pursue mathematics, procrastination, and negative classroom emotions; academic achievement data were obtained from school records. Using a split-sample design, we used exploratory and confirmatory factor analyses to test alternative structural representations of cost. A comparison of correlated-factor, higher-order, and bifactor models indicated that the correlated-factor ESEM model best fitted the data, supporting the specificity of the four distinct cost dimensions. Specific associations of each cost dimension with study outcomes further supported this differentiation, with ego cost most notably diverging from the other three cost dimensions. The results confirm the distinct nature of the four cost dimensions and underscore the importance of examining their separate roles in students’ mathematics learning, contributing to the existing evidence from a comparatively understudied cultural context.