Browsing by Author "Deodhar, Aditi"

Now showing 1 - 10 of 23
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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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    Analyzing Autism Spectrum Disorder Behaviors Through Evidence-Based Educational Models in School Support Settings
    (2022-05) Boligorla, Srinivasulu; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    Autism Spectrum Disorder (ASD) often presents with challenging behaviors that require structured, evidence-based educational strategies. This practicum focused on implementing and evaluating the HANDS in Autism® model across three collaborative school sites (Warsaw, Lakeview, and Gateway) to monitor and improve the use of evidence-based practices (EBPs) for managing problem behaviors among students with ASD. Data were collected using REDCap, cleaned and analyzed in R and Excel, and visualized to compare the proportion of students exhibiting problem behaviors across schools and visits. Results suggested variation in behavioral trends across school sites, with Warsaw showing higher proportions of students demonstrating problem behaviors during observed visits. The findings support the value of systematic monitoring and data-driven implementation of EBPs in improving behavioral outcomes and reducing the use of exclusionary discipline in autism support classrooms.
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    Analyzing Behavioral Patterns in Acute Inpatient Psychiatric Settings for Individuals with Autism Spectrum Disorder
    (2023) Bodempudi, Sai Tejaswi; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    This project focused on analyzing behavioral patterns in patients at the Indiana NeuroDiagnostic Institute (NDI) over a three-year period (2021–2023). Using data from Cerner and REDCap, the study examined the frequency and types of physical and verbal aggression among 100 patients. The analysis identified “Other/Unspecified” as the most commonly reported category for both physical and verbal aggression, suggesting the need for improved classification methods. “Hitting,” “kicking,” “verbal threats,” and “screaming” were also frequent behaviors. Year-to-year variation in certain behaviors, such as an increase in “punching” in 2023, points to changing trends in patient aggression. Recommendations include refining behavior categorization, improving data extraction from Cerner, and developing more targeted intervention strategies to support patient care and staff safety. The project also emphasized the value of ethical research practices, collaborative teamwork, and data accuracy through recurring tasks such as scoring, entry, and validation.
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    Assessing Behavioral Outcomes in Youth with Autism Following Evidence-Based Interventions
    (2022-12) Navudu, Sai Pooja; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    This practicum, completed at HANDS in Autism® in collaboration with the Indiana NeuroDiagnostic Institute (NDI), focused on evaluating the behavioral outcomes of individuals with Autism Spectrum Disorder (ASD) receiving psychiatric services. The project involved systematic data collection from the Cerner patient portal, followed by data harmonization in Microsoft Excel and coding using REDCap. Psychiatric and behavioral factors were coded to identify patterns and changes in behavior across treatment episodes. The goal was to assess the effectiveness of autism-related services and interventions provided within the inpatient setting. Results from this exploratory analysis will inform potential modifications to HANDS training modules and curricula to better align with client needs and improve long-term care outcomes for individuals with ASD. The practicum also provided practical training in data analysis, coding, and interpretation of real-world clinical data.
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    Assessing Clinical Global Impressions Severity Scores in Adults with Autism Across Counties: A Coordinated Care Study from Preadmission to Post-Discharge
    (2023-08-04) Enugu, Hari Priya Reddy; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    This practicum, conducted at HANDS in Autism® in collaboration with the Indiana NeuroDiagnostic Institute (NDI), aimed to examine changes in behavioral severity among adults with Autism Spectrum Disorder (ASD) using the Clinical Global Impressions (CGI) Severity Scale. Data were collected from REDCap across multiple stages of care, including preadmission, 7-day, 1-month, 3-month, 6-month, 9-month, and 12-month post-discharge intervals. Severity scores were categorized by county and visualized using Excel, Python, and Tableau to assess behavioral change trends. Results showed a clear reduction in severity from preadmission (primarily scores of 6–7) to post-discharge (with most scores at 5 or below), suggesting improved outcomes following inpatient intervention. This analysis supports the value of longitudinal tracking using standardized tools like CGI to inform treatment planning and promote recovery monitoring in adults with ASD.
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    Assessing Clinical Global Impressions Severity Scores in an adolescent ASD and DD population across counties
    (2023-09) Reddy, Enugu Hari Priya; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    The Indiana NeuroDiagnostic Institute (NDI) embodies comprehensive care, stabilization, and transition support for teenagers with autism, across the stages like waitlist, preadmission, admission, discharge, and follow-up, focusing on sustainable community integration and preventing re-admission. The project employs the Clinical Global Impressions (CGI; adapted from Guy, 1976), gauging illness severity and patient progress on a scale of 1 (Normal) to 7 (Extremely ill), assessed preadmission and post-discharge. Most counties initially had high severity scores (7 and 6) but showed a marked shift towards level 5 after leaving the care facility. This positive trend persisted at 1 month, 9 months, and 12 months post-discharge, though data samples were limited. The findings emphasize the enduring benefits of interventions. Factors like individual response variations and external support may have influenced outcomes, warranting further investigation. Overall, the study underscores the effectiveness of tailored interventions for individuals with autism, with potential for broader validation in larger, diverse samples.
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    Assessing Outcomes of Evidence-Based Practices Through Violence Risk Assessment and Clinical Global Impression (CGI) Analysis in Children with Autism Spectrum Disorder
    (2023-04-28) Darsanapu, Archana; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    This practicum at HANDS in Autism®, in collaboration with the Indiana NeuroDiagnostic Institute (NDI), aimed to evaluate the effectiveness of an evidence-based coordinated care approach for youth with Autism Spectrum Disorder (ASD) receiving inpatient psychiatric services. The study compared pre-admission data collected via Cerner and post-discharge data collected through REDCap for 42 individuals. Using the Clinical Global Impression (CGI) scale and Violence Risk Assessment (VRA), the project measured behavioral outcomes following treatment. Data were coded, analyzed using Python and Excel, and visualized to assess changes in severity and improvement scores. Results showed that 31 of 42 patients demonstrated measurable improvement. The findings support the use of integrated data systems and standardized behavioral tools to monitor treatment impact and reduce risks associated with behavioral health crises. This project contributes to ongoing evaluation of treatment interventions and development of comprehensive, individualized care plans for youth with ASD.
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    Assessing Patient Characteristics and Improving Data Accessibility in Autism Spectrum Disorder Inpatient Programs.
    (2023-12) Darsanapu, Archana; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    This project focused on enhancing healthcare data visualization and accessibility for individuals with Autism Spectrum Disorder (ASD) receiving inpatient psychiatric services. Data review and quality assurance were conducted using REDCap, with a focus on accuracy and completeness of patient demographic and service data. An interactive Power BI dashboard was developed using REDCap-exported datasets to visualize trends in service characteristics, patient profiles, and healthcare utilization. Although dynamic integration through API was not available, the dashboard was built with scalable design features to support future real-time functionality. Additional responsibilities included coordinating evaluations, supporting subgroup communication, and organizing timelines to ensure consistent data workflows across projects. The effort demonstrates the practical value of integrating informatics tools in ASD clinical settings to support data-driven care, team collaboration, and strategic decision-making.
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    Data-Driven Insights into Autism Client Denials in Acute Inpatient Psychiatric Settings
    (2023) Kaur, Charanjit; Neal, Tiffany; Deodhar, Aditi; Swiezy, Naomi
    This project analyzed denial client data from 2021–2023 to identify key patterns, trends, and barriers affecting service eligibility for individuals with Autism Spectrum Disorder (ASD) and related conditions. Tasks included data cleaning, preprocessing, and exploratory data analysis using REDCap, Cerner, Python, and Excel. Customized REDCap forms were developed to streamline data entry. Analysis revealed that IQ-related criteria, followed by age and diagnosis, were leading causes of denial. A notable gender disparity was identified, with males being denied at higher rates. Additional findings indicated that medical conditions unrelated to ASD, administrative burdens, and lack of parent engagement were significant contributing factors. These insights highlight the need for streamlined administrative processes and improved parent communication systems to reduce unnecessary denials and enhance access to care.
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    Enhancing evidence-based practices in educational settings serving students with autism spectrum disorder: A collaborative study of the HANDS in Autism® Model in community classroom settings.
    (2023-11) Pittala, Venkataramana; Neal, Tiffany; Deodhar, Aditi; Thumu, Mrudhula; Swiezy, Naomi
    The collaborative initiative between HANDS in Autism® and school districts focuses on elevating evidence-based practices (EBPs) in educational settings supporting students with autism spectrum disorder (ASD). Training within sites is informed by the HANDS in Autism® Model, a comprehensive module-based training curriculum, framework, and process covering areas such as Environmental Control, Assessment, Goal Setting, Teaching, and Generalization. Module advancement hinges on demonstrating mastery of prior content. This project aims to successively enhance educational team members' application and understanding of evidence-based practices (EBPs) and refine precision of EBP implementation. Ongoing data is collected via Module-Based Rubrics (MBRs), appraising EBP implementation through observed behaviors aligned with each module. A Likert-style rating is used for scoring with a range from 0 (Not Present) to 4 (Fully Present). Preliminary subsample results indicate, that in the initial academic year, a rural Midwest-based middle school location displayed the highest average scores whereas a comparable high school setting consistently demonstrated superior strategy implementation across modules over the 3-year period when contrasted with other educational settings. Furthermore, in subsequent years, both settings surpassed a comparison group (i.e., a rural elementary school) across modules. The project showcases the potential for effective EBP implementation over years using the systematic approach hallmark to the HANDS in Autism® Model. Future plans encompass integration of data analysis to compare school years and sites for comprehensive insights on the influence of implementation on student outcomes. Subsequent steps involve validating trends to inform individual approaches to maximize implementation outcomes based on site characteristics.