Browsing by Subject "Autism"
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Item 143 Training & Sustaining: Training and learning collaborative outcomes across a statewide network for early diagnosis of children with autism(Cambridge University Press, 2024-04-03) McNally Keehn, Rebecca; Paxton, Angela; Delaney, Mary; Ciccarelli, Mary; Pediatrics, School of MedicineOBJECTIVES/GOALS: Community-based primary care autism diagnostic models are one promising solution to delays in autism diagnosis. Our objective is to describe the development and report on outcomes related to primary care professional (PCP) training and sustained engagement in a longitudinal learning collaborative across a statewide network for autism diagnosis. METHODS/STUDY POPULATION: We developed ADAPT (i.e., Accelerating the Diagnosis of Autism with Primary care Training), a training program to prepare PCPs to develop independent competency in evaluation of autism in children ages 14-48 months. ADAPT includes didactic and case-based modules and expert practice-based coaching delivered by a diagnostic specialist; following training PCPs participate in a longitudinal learning collaborative. Aligned with competency-based medical education standards, measures of autism evaluation knowledge and diagnostic competency are collected. RESULTS/ANTICIPATED RESULTS: To date, 13 PCPs have completed ADAPT didactic and practicum training reaching competency in independent autism evaluation. Clinicians demonstrated significant improvement in total autism knowledge following didactic training (p=.02). There was an overall trend toward increased scoring agreement on an autism observational assessment over case observations and practicum evaluations. Similarly, PCPs demonstrated improved evaluation competence, moving on average from Advanced Beginner to Competent Performer as rated by expert trainers. Following training, PCPs attended 57% of monthly learning collaborative sessions. DISCUSSION/SIGNIFICANCE: Training PCPs to deliver autism evaluations as part of community-based models of care is a promising solution to address access and waitlist challenges. ADAPT is an intensive, standard PCP training model which results in achievement of independent competency and sustained engagement in in autism evaluation.Item A Literature Review of Similarities Between and Among Patients With Autism Spectrum Disorder and Epilepsy(Springer Nature, 2023-01-18) Assuah, Freda B.; Emanuel, Bryce; Lacasse, Brianna M.; Beggs, John; Lou, Jennie; Motta, Francis C.; Nemzer, Louis R.; Worth, Robert; Cravens, Gary D.; Mathematical Sciences, School of ScienceAutism spectrum disorder (ASD) has been shown to be associated with various other conditions, and most commonly, ASD has been demonstrated to be linked to epilepsy. ASD and epilepsy have been observed to exhibit high rates of comorbidity, even when compared to the co-occurrence of other disorders with similar pathologies. At present, nearly one-half of the individuals diagnosed with ASD also have been diagnosed with comorbid epilepsy. Research suggests that both conditions likely share similarities in their underlying disease pathophysiology, possibly associated with disturbances in the central nervous system (CNS), and may be linked to an imbalance between excitation and inhibition in the brain. Meanwhile, it remains unclear whether one condition is the consequence of the other, as the pathologies of both disorders are commonly linked to many different underlying signal transduction mechanisms. In this review, we aim to investigate the co-occurrence of ASD and epilepsy, with the intent of gaining insights into the similarities in pathophysiology that both conditions present with. Elucidating the underlying disease pathophysiology as a result of both disorders could lead to a better understanding of the underlying mechanism of disease activity that drives co-occurrence, as well as provide insight into the underlying mechanisms of each condition individually.Item Analysis of Parent, Teacher, and Consultant Speech Exchanges and Educational Outcomes of Students With Autism During COMPASS Consultation(Taylor & Francis, 2011) Ruble, Lisa; Birdwhistell, Jessie; Toland, Michael D.; McGrew, John H.; Psychology, School of ScienceThe significant increase in the numbers of students with autism combined with the need for better trained teachers (National Research Council, 2001) call for research on the effectiveness of alternative methods, such as consultation, that have the potential to improve service delivery. Data from 2 randomized controlled single-blind trials indicate that an autism-specific consultation planning framework known as the collaborative model for promoting competence and success (COMPASS) is effective in increasing child Individual Education Programs (IEP) outcomes (Ruble, Dal-rymple, & McGrew, 2010; Ruble, McGrew, & Toland, 2011). In this study, we describe the verbal interactions, defined as speech acts and speech act exchanges that take place during COMPASS consultation, and examine the associations between speech exchanges and child outcomes. We applied the Psychosocial Processes Coding Scheme (Leaper, 1991) to code speech acts. Speech act exchanges were overwhelmingly affiliative, failed to show statistically significant relationships with child IEP outcomes and teacher adherence, but did correlate positively with IEP quality.Item Analyzing Autism Spectrum Disorder Behaviors Through Evidence-Based Educational Models in School Support Settings(2022-05) Boligorla, Srinivasulu; Neal, Tiffany; Deodhar, Aditi; Swiezy, NaomiAutism 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.Item Analyzing Behavioral Patterns in Acute Inpatient Psychiatric Settings for Individuals with Autism Spectrum Disorder(2023) Bodempudi, Sai Tejaswi; Neal, Tiffany; Deodhar, Aditi; Swiezy, NaomiThis 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.Item Analyzing client denial trends in the NDI dataset: Patterns and predictive insights(2024-05) Samala, Vishwasree; Neal, Tiffany; Deodhar, A; Devarapalli, Baby Amulya; Swiezy, NaomiThis project analyzed denial patterns among clients in the HANDS in Autism® NDI Exploratory dataset. Using REDCap and Cerner data, a structured coding scheme was implemented for consistent data entry and scoring. Python was used to quantitatively analyze denial reasons across 2021–2023. The most frequent denial factors included unmet family/parent criteria and issues unrelated to autism. Statistical testing, including Chi-Square and Fisher’s exact tests, revealed no significant relationship between gender and denial reasons. The project also produced a user guide for REDCap data entry and proposed future directions, including expanding the dataset and improving data completeness through enhanced data collection practices.Item Analyzing Participant Feedback on various training components to enhance future HANDS Intensive trainings (2006-2025)(2025-05-09) Maddipatla, Vignitha; Neal, Tiffany; Gottipati, Mounika; Swiezy, NaomiThis 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.Item Analyzing self-injurious behaviors (SIB) in individuals with autism spectrum disorder: Trends, interventions, and treatment outcomes(2024-08) Viswanath, Adarsh; Neal, Tiffany; Devarapalli, Baby Amulya; Swiezy, NaomiThis project explored self-injurious behaviors (SIB) in individuals with Autism Spectrum Disorder (ASD) using the NDI Exploratory dataset comprising progress notes for 110 patients. Data was managed via REDCap, analyzed using Python, and visualized through Power BI. The study examined how SIB trends varied over five weeks and their association with gender and age. Findings revealed a significant reduction in behaviors such as hitting oneself, hitting the body against objects, and cutting. Males exhibited higher SIB frequencies overall, with early adolescence, particularly around ages 12 to 16, showing peak incidences. The consistent improvement in weekly recovery scores indicates that tailored interventions are effective. Recommendations include age- and gender-specific strategies, continuous treatment monitoring, and increased caregiver support to enhance outcomes and reduce long-term SIB risk.Item Analyzing Team Engagement and Participation Patterns Through Dashboard-Driven Behavioral Profiling in Autism Support Settings(2025-05-09) Aluru, Sai Srilekha; Neal, Tiffany; Devarapalli, Baby Amulya; Swiezy, NaomiThis project involved developing interactive data visualizations and analyzing team participation metrics in autism support classrooms as part of an internship at HANDS in Autism® Interdisciplinary Training and Resource Center. The work focused on REDCap data entry, survey tracking, and Power BI dashboard development for the Team Participation and Observation Profile (TPOP). These dashboards enabled site-specific filtering and scoring analysis across key behavioral dimensions such as engagement, participation, and cultural competence. Findings revealed strengths in staff engagement and roles clarity, with areas of improvement noted in cultural responsiveness and inclusive practices. This project enhanced technical fluency in Power BI, strengthened skills in structured data collection and analysis, and supported data-informed planning for school teams. The intern’s contributions directly advanced the organization’s goal of using behavioral insights to improve team performance and educational outcomes for students with ASD.Item Analyzing the Trend in Engagement of IIACC Delegates in IIACC Quarterly meetings from June 2023 to June 2024(2024-05) Sanjeev, Samantha; Neal, Tiffany; Ogunmola, Botiwuoluwa; Swiezy, NaomiThe Indiana Interagency Autism Coordinating Council (IIACC) is a collective stakeholder work group with primary mission to “facilitate the efficient and effective exchange of information on autism- related activities among the member agencies, and to leverage resources and experiences to address common issues and outcomes, and to fill identified gaps” (INformation Network, 2022). Established in 2005, the IIACC's work is guided by ongoing evaluations of statewide and regional needs through gap analyses, community input, and national data, with a 27% increase in 2022 compared to the previous period. Trend in IIACC engagement of IIACC meetings of 250 stakeholders were analyzed. Community Providers formed the largest group at 58.4% (146 individuals), followed by Family Members/Caregivers at 18.4% (46), Medical Providers at 11.2% (28), School Personnel at 6.4% (16), and Others at 5.6% (14). While June 2023, December 2023, and June 2024 saw relatively consistent attendance with 24, 22, and 19 participants respectively, March 2024 experienced a dramatic surge with 185 attendees. The analysis of IIACC meeting participation from June 2023 to June 2024 reveals consistent engagement which underscore the importance of the INformation Network in disseminating relevant information and engaging stakeholders. These insights can inform future strategies to enhance engagement and ensure the council's activities effectively meet the needs of its diverse stakeholders.