Browsing by Author "Somasundaram, Manasi"

Now showing 1 - 4 of 4
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    A global perspective: Quantitative changes in training participants’ knowledge of autism across selected settings within the United States and Singapore
    (2023-11) Neal, Tiffany; Nazarloo, Shawn; Deodhar, Aditi; Somasundaram, Manasi; Gandhi, Siddhi; Swiezy, Naomi
    The present study aimed to assess and compare the effectiveness of the HANDS in Autism™ Model training curriculum, framework and process specific to changes in autism knowledge via the Autism Knowledge Survey-Revised (AKS-R; HANDS in Autism®, 2005). Additional exploration using the AKS-R, sought to explore differences in the global, Singapore training cohorts specific to their participation in either single-week or multi-week training formats. Results from this preliminary exploration demonstrated statistically significant improvement in autism knowledge across both countries. These findings provide initial evidence as to both the effectiveness and transportability of the HANDS in Autism® Model across participants and countries. While findings are specific to improved autism knowledge, the emerging potential of the Hands in Autism® Model as a comprehensive treatment model will be further discussed.
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    Evaluation of accessibility of open-source EHRs for visually impaired users
    (AMIA, 2024-01) Moncy, Megha M.; Pilli, Manya; Somasundaram, Manasi; Purkayastha, Saptarshi; Fulton, Cathy R.; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    This study investigates the accessibility of open-source electronic health record (EHR) systems for individuals who are visually impaired or blind. Ensuring the accessibility of EHRs to visually impaired users is critical for the diversity, equity, and inclusion of all users. The study used a combination of automated and manual accessibility testing with screen readers to evaluate the accessibility of three widely used open-source EHR systems. We used three popular screen readers - JAWS (Windows), NVDA (Windows), and Apple VoiceOver (OSX) to evaluate accessibility. The evaluation revealed that although each of the three EHR systems was partially accessible, there is room for improvement, particularly regarding keyboard navigation and screen reader compatibility. The study concludes with recommendations for making EHR systems more inclusive for all users and more accessible.
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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.
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    Psychometric Validation of Autism Knowledge Surveys to Identify Training Gaps in Autism Care
    (2023-08-04) Somasundaram, Manasi; Neal, Tiffany; Swiezy, Naomi
    This practicum, conducted at HANDS in Autism® Interdisciplinary Training and Resource Center, focused on validating the Autism Knowledge Survey (AKS) through psychometric analysis. The AKS is designed to assess disparities in autism-related knowledge across diverse stakeholder groups, identify barriers to mutual understanding, and inform the development of targeted training interventions. The student’s responsibilities included reviewing the AKS manuscript, exploring AKS2 datasets, and performing statistical validation procedures using REDCap, R Studio, Excel, and EndNote. Through integration of psychometric data and evaluation of survey reliability, this project advanced the validation process for AKS2 and provided insights into how such instruments can support evidence-based practices in ASD care. Practicum outcomes included improved skills in statistical reasoning, data management, research writing, and project coordination—highlighting the critical role of data-informed approaches in enhancing autism education and healthcare outcomes.