Browsing by Author "Gandhi, Siddhi N."

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    Evaluating Autism Knowledge Through Pre- and Post-Training Surveys: A Psychometric and Statistical Approach
    (2023) Gandhi, Siddhi N.; Neal, Tiffany; Swiezy, Naomi
    This project focused on analyzing the psychometric properties and training impact of the Autism Knowledge Survey (AKS) across over 18 datasets. Tasks included data cleaning, merging pre- and post-training survey responses, and conducting statistical analyses in REDCap, Excel, and R Studio. Psychometric evaluation revealed high internal consistency (Cronbach’s alpha = 0.836) and identified five key factors via Principal Component Analysis: diagnosis, genetics, autism across the lifespan, social challenges, and interventions. Ordinal regression showed that experience had no significant effect on knowledge in three areas, while paired t-tests revealed limited improvement in five specific topics post-training. These insights underscore the need for targeted training content in areas such as early intervention, autism genetics, and social relatedness. Results support the refinement of training curricula and demonstrate how statistical modeling can inform future ASD education strategies.
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    Exploring Autism Knowledge and Provider Experience: Implications for Diagnosis, Treatment, and Training
    (2023-03-27) Swiezy , Naomi B.; Neal, Tiffany J.; Somasundaram, Manasi; Gandhi, Siddhi N.; Uppalapati, Yashaswini; Gottipati, Mounika
    The Autism Knowledge survey allows for the assessment of knowledge disparities arising from diverse backgrounds, identifying barriers to mutual understanding, and highlighting groups that require specialized training in autism spectrum disorder (ASD) related areas. By assessing knowledge across subdomains such as diagnosis, etiology, and intervention, the AKS aims to enhance people's understanding of ASD. The research emphasizes the significance of accurate ASD knowledge in care provision and could promise to transform diagnosis, treatment, and training within the ASD field. Through rigorous psychometric validation and statistical analyses, this study offers insights that contribute to improving the quality of life for individuals with ASD.