Objective: Mobile-based cognitive training programs can be a viable alternative to in-person interventions, but their efficacies have not been established yet. In this study, we examined the efficacy of DoBrain, a mobile-based cognitive training program designed for children with developmental disabilities (DDs), in comparison with general educational apps named Junior Naver and Kakao Kids. Methods: Children aged 34 to 77 months were recruited and randomized at a 1:1 ratio to use DoBrain or general educational apps. Each group used the assigned app on a daily basis at home for 30 minutes for 24 weeks. Parents were instructed to help the children with the app usage. A total of 166 children completed the post-test visit (DoBrain group, n=85, 55.4±8.7 months old; general educational app group, n=81, 53.7±9.9 months old). The primary outcome was cognitive development measured by Psychoeducational Profile-Revised (PEP-R), administered at baseline and at post-test. Results: DoBrain had no superior effect over general educational apps on the PEP-R Developmental Quotient. When the changes before and after app usage were compared, the DoBrain group and the general educational app group both showed declines in imitation (adjusted p=0.049 and 0.022), perception (adjusted p=0.004 and <0.001), and gross motor (adjusted p=0.003 and 0.002) domains of the PEP-R. Among the DoBrain group, children with DD showed a significantly greater gain in the eye-hand coordination domain of PEP-R compared with those without DD (adjusted p=0.047). Conclusion DoBrain did not show a superior effect over general educational apps on overall cognitive development in preschool children, regardless of the presence of DD. Careful monitoring of the negative effect of mobile-based cognitive training programs is necessary.

Objective: The current study aimed to investigate the differences in sleep reactivity and sleep effort differs among late night shift workers (LSWs) and non-late night shift workers (non-LSWs), and non-shift workers (non-SWs). Methods: In total, 6,023 participants (1,613 non-SWs, 3,339 LSWs, and 1,071 non-LSWs) were recruited. Non-SWs was defined as those who works at fixed schedules during standard daylight. LSWs was defined as who work late night hours (10 PM–6 AM), while non-LSWs was SWs who did not work during late night. All completed the Ford Insomnia Response to Stress Test (FIRST), the Glasgow Sleep Effort Scale (GSES), the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), the Insomnia Severity Index (ISI), and the short-term Center for Epidemiologic Studies-Depression scale (CES-D) through online survey. Results: LSWs and non-LSWs reported higher FIRST, GSES scores than non-SWs. In addition, LSWs reported higher FIRST, GSES scores than non-LSWs. FIRST scores were correlated with CES-D, PSQI, ISI, and ESS for LSWs, non-LSWs, and non-SWs alike. GSES scores were also correlated with CES-D, PSQI, ISI, and ESS for LSWs, non-LSWs, and non-SWs alike. Conclusion SWs showed higher sleep reactivity and sleep effort than non-SWs. LSWs had higher sleep reactivity and sleep effort than non-LSWs, and these variables are associated with insomnia, daytime sleepiness, and depressive symptoms. Our findings suggests that late night schedule, may increase sleep reactivity and sleep effort, which are associated with sleep and mood disturbances.

Objective: This study compared parenting stress in preschool children with developmental disabilities (DD) or typical development (TD). We also investigated children’s factors that affect parenting stress. Methods: A total of 196 preschool children participated in the study (aged 54.8±9.2 months). There were 79 children with DD (59 with autism spectrum disorder, 61 with intellectual disability, 12 with language disorder) and 117 with TD. The high parenting stress and the low parenting stress groups were divided based on the Total Stress of Korean Parenting Stress Index Fourth Edition (K-PSI-4) with an 85-percentile cutoff score. Pearson’s correlation analysis was conducted to calculate the correlation between K-PSI-4 and the children’s or parents’ measures. Results: The difference in parenting stress between DD and TD was significant in the Total Stress of K-PSI-4 (p<0.001). The Total Stress scale of K-PSI-4 represented a modest to strong correlation with cognitive development, adaptive functioning, social communication, and behavioral problems in children with DD. Our results showed that caregivers of children with DD reported higher parenting stress than those with TD. Parenting stress was strongly associated with cognitive development, adaptive functioning, social communication, and behavioral problems in children with DD. Among the children’s factors, especially social communication, attention problems, and aggressive behavior had association with caregivers’ higher parenting stress. Conclusion These findings suggest the need for early intervention for parenting stress in caregivers by assessing child characteristics, including social cognition, awareness, communication, and inattention and hyperactivity, in the evaluation of children with DD.

Objective: Early detection and intervention of developmental disabilities (DDs) are critical to improving the long-term outcomes of afflicted children. In this study, our objective was to utilize facial landmark features from mobile application to distinguish between children with DDs and typically developing (TD) children. Methods: The present study recruited 89 children, including 33 diagnosed with DD, and 56 TD children. The aim was to examine the effectiveness of a deep learning classification model using facial video collected from children through mobile-based application. The study participants underwent comprehensive developmental assessments, which included the child completion of the Korean Psychoeducational Profile-Revised and caregiver completing the Korean versions of Vineland Adaptive Behavior Scale, Korean version of the Childhood Autism Rating Scale, Social Responsiveness Scale, and Child Behavior Checklist. We extracted facial landmarks from recorded videos using mobile application and performed DDs classification using long short-term memory with stratified 5-fold cross-validation. Results: The classification model shows an average accuracy of 0.88 (range: 0.78–1.00), an average precision of 0.91 (range: 0.75–1.00), and an average F1-score of 0.80 (range: 0.60–1.00). Upon interpreting prediction results using SHapley Additive exPlanations (SHAP), we verified that the most crucial variable was the nodding head angle variable, with a median SHAP score of 2.6. All the top 10 contributing variables exhibited significant differences in distribution between children with DD and TD (p<0.05). Conclusion The results of this study provide evidence that facial landmarks, utilizing readily available mobile-based video data, can be used to detect DD at an early stage.

OBJECTIVES: The present study investigated current practices of insomnia treatment among Korean doctors in clinical settings. METHODS: A total of 100 doctors participated in the present study and filled out a series of survey questions regarding their treatment of insomnia patients. RESULTS: The results revealed that the primary type of insomnia treatment was pharmacological and that the most popular medication was zolpidem. The majority of doctors reported that they also utilized non-pharmacological treatments such as sleep hygiene education and cognitive-behavioral therapy. However, these treatments tended to result in low satisfaction. In addition, the doctors perceived that patients largely preferred pharmacological treatments to non-pharmacological ones and did not have sufficient knowledge of non-pharmacological treatments. CONCLUSION: Many doctors believed that non-pharmacological treatments for insomnia were important, but reported that they were difficult to implement in practice. The results of this study suggest that improved medical conditions for non-pharmacological treatments and education of physicians are necessary to appropriately treat insomnia.
Education ; Humans ; Hygiene ; Sleep Initiation and Maintenance Disorders*