Search results

In this study, the research question posed was: What are the defining characteristics, limitations, and potential opportunities in the research on heterogeneity within ASD?

This scoping review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses methodology to address the research question: “What are the defining characteristics, limitations, and potential opportunities in the research on heterogeneity within ASD?” A comprehensive literature search was conducted across databases including MEDLINE/PubMed, SciVerse Scopus and Springer Link, with keywords such as autism, autism spectrum disorder (ASD), heterogeneity and neurodevelopment. Inclusion criteria covered original research, reviews and protocols published since 1990, while irrelevant or out-of-date works were excluded. Thematic analysis was applied to collected data to identify common patterns, trends and key characteristics, leading to a narrative synthesis. Ethical review board approval was not required due to the nature of the review.

The scoping review underscored the multifaceted nature of ASD, emphasizing its clinical, methodological and investigational complexities. ASD’s diverse behavioral, social and biological characteristics challenged its classification as a uniform entity. To address this, the review examined strategies like stricter clinical criteria, categorization into functional subgroups, and larger, diverse sample sizes. Moreover, it highlighted the transformative role of Big Data and machine learning in advancing the comprehension of ASD’s manifold manifestations. This research contributed valuable insights and innovative approaches for addressing the intrinsic heterogeneity of ASD, reshaping the understanding of this complex condition.

One limitation of this scoping review is that it primarily relied on existing literature and did not involve primary data collection. While the review synthesized and analyzed a substantial body of research, the absence of original data collection may limit the depth of insights into specific aspects of ASD heterogeneity. Future research could benefit from incorporating primary data collection methods, such as surveys or interviews with individuals with ASD and their families, to gain more nuanced perspectives on the condition’s heterogeneity.

The reliance on existing literature in this scoping review highlights the need for further empirical studies exploring ASD’s heterogeneity. Researchers should consider conducting primary data collection to capture real-world experiences and variations within the ASD population. This approach could provide more comprehensive and context-specific insights, ultimately informing the development of tailored interventions and support strategies for individuals with ASD and their families.

This paper offers a fresh perspective on understanding ASD by examining its clinical, methodological and investigational implications in light of its inherent heterogeneity. Rather than viewing ASD as a uniform condition, this study explores strategies such as stricter clinical criteria, subcategorization based on functionality and diverse sample sizes to address its complexity. In addition, this study highlights the innovative use of Big Data and machine learning to gain deeper insights into ASD’s diverse manifestations. This approach contributes new insights and promising directions for future research, challenging the conventional understanding of ASD as a singular entity.