Early Detection of Autism Spectrum Disorder Among Preschoolers: The Case of Early Child Educators in Greater Accra Region, Ghana.

Abstract

Background: In this modern era, children as young as six months old are increasingly spending significant amounts of time in school, largely due to the demanding schedules of working mothers. Consequently, preschool teachers are expected to have extensive expertise in child development and the ability to identify deviations from the norm. The objective of this research is to delve into the insights and encounters of early childhood educators regarding the timely recognition of autism spectrum disorder in the capital city of Ghana. Furthermore, the study investigates the origins of the knowledge held by preschool teachers and the influence of various aspects of health literacy in this context. Methodology: The data for this study was collected through in-depth interviews with 21 randomly and purposively selected preschools in the Greater Accra region, Ghana with a focus on their experience in working with children with autism. It was a qualitative study analyzed thematically using Dedoose software. Findings: The findings showed that preschool teachers possess greater practical familiarity with ASD than theoretical understanding. They demonstrate proficiency in recognizing ASD's clinical signs. The study highlighted individual health literacy, primarily reliant on the internet for autism information. However, challenges arise from information overload and complex medical terms. Conclusion: The results show that participants have a strong grasp of clinical aspects of ASD beyond its causes and definition, enabling them to recognize autism effectively. However, parental denial delays intervention. They primarily rely on the internet for autism-related information. In light of these findings, we recommend GES to revise the curriculum for teachers, accompanied by in-service training and professional development initiatives. Future research could delve deeper into autism, potentially using mixed methods.