Analyzing Participant Feedback on various training components to enhance future HANDS Intensive trainings (2006-2025)

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Vignitha_Poster presentation_spring 2025.pdf (582.62 KB)
Date
2025-05-09
Authors
Maddipatla, Vignitha
Neal, Tiffany
Gottipati, Mounika
Swiezy, Naomi
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American English
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Abstract

This project analyzed nearly two decades of participant feedback from HANDS in Autism® Intensive Trainings conducted between 2006 and 2025. The goal was to identify satisfaction trends and improvement opportunities in training logistics, content, communication, and participant engagement. Using REDCap datasets, the data was cleaned, standardized, and analyzed using Python, Power BI, and Excel. Results revealed consistently high satisfaction scores (averaging 4.8/5), with increased engagement over the course of each training week. Top-rated components included speaker knowledge and small group activities, while lecture engagement showed room for improvement. The project demonstrated the value of health informatics in translating large-scale feedback into actionable insights and highlighted the importance of data-driven strategies to enhance the delivery of autism-focused professional training programs.

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Autism, Autism Spectrum Disorder (ASD), Evidence-based practices (EBP), Psychiatry, Individuals with ASD, Behavioral Outcome Analysis, Feedback Analysis, Training Evaluation, Data Visualization, Longitudinal Data Analysis, Survey Trend Analysis
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Maddipatla, V., Neal, T., Gottipati. M., & Swiezy, N. (2025). Analyzing Participant Feedback on various training components to enhance future HANDS Intensive trainings (2006-2025). Presented at the Spring 2025 Poster Session, Luddy School of Informatics, Computing, and Engineering, Department of Biomedical Engineering and Informatics, Indiana University Indianapolis.
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https://hdl.handle.net/1805/49253
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HANDS in Autism