Background: Elucidating developmental changes in the symptoms of autism spectrum disorder (ASD) is important to support individuals with ASD. However, no report has clarified the developmental changes in attention to social information for a broad age range. The aim of this study was to investigate the developmental changes in attention to social information from early childhood to adolescence in individuals with ASD and typically developed (TD) children. Methods: We recruited children with ASD (n = 83) and TD participants (n = 307) between 2 and 18 years of age. Using the all-in-one-eye-tracking system, Gazefinder, we measured the percentage fixation time allocated to areas of interest (AoIs) depicted in movies (the eyes and mouth in movies of a human face with/without mouth motion, upright and inverted biological motion in movies showing these stimuli simultaneously, people and geometry in preference paradigm movies showing these stimuli simultaneously, and objects with/without finger-pointing in a movie showing a woman pointing toward an object). We conducted a three-way analysis of variance, 2 (diagnosis: ASD and TD) by 2 (sex: male and female) by 3 (age group: 0–5, 6–11, and 12–18 years) and locally weighted the scatterplot smoothing (LOESS) regression curve on each AoI. Results: In the face stimuli, the percentage fixation time to the eye region for the TD group increased with age, whereas the one for the ASD group did not. In the ASD group, the LOESS curves of the gaze ratios at the eye region increased up to approximately 10 years of age and thereafter tended to decrease. For the percentage fixation time to the people region in the preference paradigm, the ASD group gazed more briefly at people than did the TD group. Limitations: It is possible that due to the cross-sectional design, the degree of severity and of social interest might have differed according to the subjects’ age. Conclusions: There may be qualitative differences in abnormal eye contact in ASD between individuals in early childhood and those older than 10 years.

Background: Heterogeneous mental health outcomes during the COVID-19 pandemic are documented in the general population. Such heterogeneity has not been systematically assessed in youth with autism spectrum disorder (ASD) and related neurodevelopmental disorders (NDD). To identify distinct patterns of the pandemic impact and their predictors in ASD/NDD youth, we focused on pandemic-related changes in symptoms and access to services. Methods: Using a naturalistic observational design, we assessed parent responses on the Coronavirus Health and Impact Survey Initiative (CRISIS) Adapted For Autism and Related neurodevelopmental conditions (AFAR). Cross-sectional AFAR data were aggregated across 14 European and North American sites yielding a clinically well-characterized sample of N = 1275 individuals with ASD/NDD (age = 11.0 ± 3.6 years; n females = 277). To identify subgroups with differential outcomes, we applied hierarchical clustering across eleven variables measuring changes in symptoms and access to services. Then, random forest classification assessed the importance of socio-demographics, pre-pandemic service rates, clinical severity of ASD-associated symptoms, and COVID-19 pandemic experiences/environments in predicting the outcome subgroups. Results: Clustering revealed four subgroups. One subgroup—broad symptom worsening only (20%)—included youth with worsening across a range of symptoms but with service disruptions similar to the average of the aggregate sample. The other three subgroups were, relatively, clinically stable but differed in service access: primarily modified services (23%), primarily lost services (6%), and average services/symptom changes (53%). Distinct combinations of a set of pre-pandemic services, pandemic environment (e.g., COVID-19 new cases, restrictions), experiences (e.g., COVID-19 Worries), and age predicted each outcome subgroup. Limitations: Notable limitations of the study are its cross-sectional nature and focus on the first six months of the pandemic. Conclusions: Concomitantly assessing variation in changes of symptoms and service access during the first phase of the pandemic revealed differential outcome profiles in ASD/NDD youth. Subgroups were characterized by distinct prediction patterns across a set of pre- and pandemic-related experiences/contexts. Results may inform recovery efforts and preparedness in future crises; they also underscore the critical value of international data-sharing and collaborations to address the needs of those most vulnerable in times of crisis.

Background: High prevalence of sleep problems in not only children with neurodevelopmental disorders (NDS) but also non NDS has been established. However, there are few studies that have looked into population-based and age-specific prevalence of sleep problems of children. Moreover, there are even fewer studies that have investigated the correlation of demographic and lifestyle-related factors affecting sleep problems in children. Considering these, the purpose of this study is to assess the correlation of the prevalence of sleep problems and selected socio-demographic and lifestyle-related factors in 5-year-old Japanese children in population-based study.Methods: Study children (SC) were recruited from two cohorts of the Hirosaki City 5-Year-Old Child Developmental Health Checkup Study. The first cohort consisted of 281 (162 males, 119 females) children recruited from 2014 to 2015, and the second cohort consisted of 2055 (1,068 males, 987 females) children from 2018 to 2019. In total there were 2,336 SC participants (1,230 males and 1,106 females). To determine the prevalence of sleep problems the Japanese Sleep Questionnaire for Preschoolers (JSQ-P) was utilized, and sleep problems are defined by a total score of ≥86. To determine socio-demographic and lifestyle-related factors affecting sleep, 10 factors (NDS diagnosis, birth month, childcare place, income, number of siblings, bedtime, waking time, sleeping hours, sleep onset delay, and screen time) were selected. Finally, to determine the correlation between prevalence of sleep problems and the selected demographic and lifestyle-related factors, data was analyzed using chi-square test.Results: The prevalence rate of sleep problems in 5-year-olds was 18% (369/2,055). Further, the prevalence of sleep problems was high in participants with ASD (50.4%), ADHD (39.8%), 22:00 of bedtime (30.7%), >7:30 of waking time (30.7%), 30 min of sleep onset delay (35.3%), and ≥2 h of screen time (21.1%).Conclusion: The findings report 18% prevalence rate of sleep problems in 5-year-old children. Further, the findings establish a significant correlation of sleep problems and NDS, specific socio-demographic, and lifestyle-related factors. In considering the identified modifiable lifestyle-related factors contributing to sleep problems among the participants (i.e., bed/waking times and screen times), sleep programs to address these concerns are suggested.

This study explores the challenge of differentiating autism spectrum (AS) from non-AS conditions in adolescents and adults, particularly considering the heterogeneity of AS and the limitations of diagnostic tools like the ADOS-2. In response, we advocate a multidimensional approach and highlight lexicogrammatical analysis as a key component to improve diagnostic accuracy. From a corpus of spoken language we developed, interviews and story-recounting texts were extracted for 64 individuals diagnosed with AS and 71 non-AS individuals, all aged 14 and above. Utilizing machine learning techniques, we analyzed the lexicogrammatical choices in both interviews and story-recounting tasks. Our approach led to the formulation of two diagnostic models: the first based on annotated linguistic tags, and the second combining these tags with textual analysis. The combined model demonstrated high diagnostic effectiveness, achieving an accuracy of 80%, precision of 82%, sensitivity of 73%, and specificity of 87%. Notably, our analysis revealed that interview-based texts were more diagnostically effective than story-recounting texts. This underscores the altered social language use in individuals with AS, a crucial aspect in distinguishing AS from non-AS conditions. Our findings demonstrate that lexicogrammatical analysis is a promising addition to traditional AS diagnostic methods. This approach suggests the possibility of using natural language processing to detect distinctive linguistic patterns in AS, aiming to enhance diagnostic accuracy for differentiating AS from non-AS in adolescents and adults.

In recent years, it has been reported that the prevalence of autism spectrum disorder (ASD) is increasing, but there are few research reports in Asia equivalent to those in Europe and the United States. Since large-scale epidemiological studies of neurodevelopmental disorders (NDDs) have not been conducted in Japan, the delay in early detection is conspicuous compared to other countries. Therefore, we started epidemiological studies in a medium-sized city (Hirosaki City) in northern Japan from 2013 to elucidate the prevalence of ASD and have been conducting a 9-year community cohort survey. In 2020, we published an adjusted prevalence of ASD of 3.2% at the age of 5 years, no change in 4-year incidence, and comorbidity of ASD. Since then, we have focused on sleep problems at the age of 5 years and have been studying the estimation of the prevalence of sleep disorders and the relationship with neurological development disorders. In this chapter, in addition to our research results since 2013, we will introduce the screening and support system in the community in Japan.