Abstract

Background

Neurodevelopmental delay precedes attention‐deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) diagnoses. However, exactly when this emerges in association with these outcomes remains unclear. We investigated (1) the earliest representations of neurodevelopmental variation and (2) what neurodevelopmental variations at an early age (10 months to 3 years) are specifically associated with the emergence of parentally reported behavioral traits of ADHD, ASD, and related disorders at age 9.

Methods

Children from the Hamamatsu Birth Cohort of Mothers and Children (HBC Study) born between December 2007 and March 2012 were enrolled and followed from birth to age 9. Standardized scores of neurodevelopment across five domains (gross motor, visual reception, fine motor, receptive language, and expressive language) were calculated using the Mullen Scales of Early Learning at ages 10, 14, 18, 24, 32, and 40 months. ADHD and ASD traits were ascertained as Z‐scores using the ADHD‐Rating Scale and Social Responsiveness Scale‐2 at age 9. To explore the earliest recognition of neurodevelopmental variation with credibility, structural equation modeling (SEM) was used to estimate the total effects of the linear associations between exposures and outcomes.

Results

836 children (405 females, 48%) were enrolled in the analysis. The ADHD trait was associated with visual reception score before age 1 and was concurrent with both fine motor and receptive language scores between ages 1–2. The ASD trait was associated with gross motor score before age 1 and expressive language score between ages 1.5 and 3.

Conclusion

Suboptimal visual‐motor coordination can be a prototype of the ADHD trait, while a cascading pattern of suboptimalities from gross motor to language domains can be a prototype of the ASD trait. The distinct neurodevelopmental variations related to ADHD and ASD traits running in the general population can be found before age 1.

Introduction

This study aimed to investigate whether there is a significant association between teachers’ and students’ perceptions of school climate, and if not, whether teacher factors are associated with the respective perceptions.

Methods

The participants included 1,831 students and 59 homeroom teachers from 11 public elementary and junior high schools in Japan. Multilevel models were used to examine the association between students’ and teachers’ perceptions of school climate.

Results

Of the three teacher-rated school climate scales, only teacher-perceived disciplinary climate was associated with students’ perceptions of school climate. Teachers’ working conditions, such as self-efficacy and stress, were associated with teachers’ perceptions but not students’ perceptions of school climate. Disciplinary climate was associated with students’ perceptions of school climate, even after accounting for the teachers’ working conditions.

Discussion

Items questioning specific student behaviors, such as those included in the disciplinary climate scale, may be effective in avoiding incongruence with student evaluations. Moreover, maintaining disciplinary climate itself is important for students’ positive perceptions of the school climate. A disciplinary climate in which teachers and students share responsibility for learning and classroom organization, and strategies that support positive student behavior are preferable to exclusionary discipline strategies. Incorporating feedback data gathered through classroom observations or student perceptions is also important in resolving the incongruence between teachers’ and students’ perceptions of the school climate.

OBJECTIVE: The implementation of school-based mental health screening offers promise for early detection of mental health issues in children; however, various barriers hinder its widespread adoption. This study aimed to investigate the predictive value of digital data obtained from an established daily health observation scheme in Japanese schools to identify later mental health issues in children. METHODS: Data for the analysis were obtained from 2,433 students enrolled in five public schools. The data acquisition period spanned 76 school days, from September 1, 2022, to December 23, 2022, and student absences were recorded during this period. Depressive and anxiety symptoms were assessed in January 2023. The students' daily physical and emotional health status was recorded as "daily health issue" scores and group-based trajectory modeling was employed to classify the long-term trends in these scores. Additionally, rolling z-scores were utilized to capture variability in daily health issue scores, with z-scores above +1 considered unusual responses. RESULTS: After 4 months of daily health observations, students' response trends were classified into five trajectory groups. The group experiencing the highest number of daily health issues (Group 5; 5.4% of the sample) exhibited more subsequent depressive and anxiety symptoms compared to the group with fewer issues (Group 1; 47.5%) (incident rate ratio [IRR] = 5.17; 95% confidence interval [CI]: 3.82, 6.99). Group 5 also demonstrated significantly more days of absence than Group 1 (IRR = 2.14, 95% CI: 1.19, 3.85). The average daily health issue scores for the entire period were associated with both depressive/anxiety symptoms and the number of days absent from school (IRR = 1.59, 95% CI: 1.45, 1.73; IRR = 1.18, 95% CI: 1.04, 1.35, respectively). Furthermore, a higher number of unusual responses during the entire period was also associated with more depressive/anxiety symptoms (IRR = 1.10, 95% CI: 1.07, 1.12). CONCLUSION: The current study is the first to demonstrate the predictive capability of a traditional daily health observation scheme to identify mental health issues in children. This study highlights the scheme's potential to screen and safeguard children's mental health, emphasizing the importance of digitalization and collaboration with various stakeholders.