A Discussion of Positive Behavior Support and Applied Behavior Analysis in the Context of Autism Spectrum Disorder in the UK and Ireland

Mental and Behavioral Health, and Crisis Services for People with Intellectual and Developmental Disabilities in Medicaid Home- and Community-Based Services

People with intellectual and developmental disabilities (IDD) often have higher rates of comorbid mental health conditions compared to the general population. Yet, many people with IDD also have unmet needs for mental and behavioral health services. The aim of this study was to examine how states provided mental and behavior health, and crisis services to people with IDD in their Home- and Community-Based Services (HCBS) programs, the largest funding mechanism for Long-Term Services and Supports (LTSS) for people with IDD in the United States. We analyzed fiscal year (2021) Medicaid HCBS waivers for people with IDD from across the United States to examine if and how they provided mental and behavior health, and crisis services. States projected spending $968.9 million for mental and behavior health, and crisis services for 190,299 people with IDD. Applied behavior analysis services were provided at greater rates than positive behavior supports and other forms of behavior interventions. While most states provided mental and behavior health, and crisis services in their waivers, there were vast inconsistencies in how they did so, across states, waivers, and services. HCBS are a crucial safety net to ensure people with IDD, especially those who also have mental health disabilities, can live and thrive in their communities.

A Non-parametric Analysis of Gender Differences With the Impacts of Applied Behavior Analysis on Autistic Individuals

Introduction Considering the scarcity of research that directly investigates the differences between genders in their response to applied behavior analysis (ABA) therapy for individuals diagnosed with autism spectrum disorder (ASD), the objective of this study is twofold. First, it aims to reinforce the male-to-female ratio reported in existing scientific literature, thereby contributing to a broader understanding of gender distribution in ABA therapy for ASD. Second, it seeks to identify gender-based differences in aggregate target behaviors at various time intervals using three distinct datasets. The goal is to determine if gender influences the effectiveness of ABA therapy for ASD, which could inform future therapeutic strategies. Ultimately, this study strives to enhance our understanding of gender disparities in ABA therapy response among ASD individuals and hopes to improve therapeutic outcomes for all, regardless of gender. Materials and methods Three to five behavioral technicians per child collected daily general target mastery data for 263 individuals with autism. This data was gathered using a large N design through retrospective chart reviews within the "Catalyst" tracking software (DataFinch Technologies, Atlanta, USA). Three separate datasets were collected from June 7, 2023 to January 7, 2024. Behavior analysts employed a mixed model of discrete trial training, mass trials, and naturalistic environment treatment over seven months. General target mastery data was assembled for 259 children and four adults, with seven data instances missing. Descriptive statistics encompassed central tendency and dispersion measures, including the data distribution's mean, standard deviation, median, and range. Non-parametric inferential analysis was performed with the Mann-Whitney U test. Results Mann-Whitney U computations resulted in non-significant gender differences on all gender comparisons for the three datasets covering the seven-month timeframe. Dataset #1: Time 1-(U=727.5, p=0.846, ή2=0.0002, Time 2-(U=736, p=0.910, ή2=0.00005), Time 3-(U=687.5, p=0.569, ή2=0.001) Dataset #2: Time 1-(U=781, p=0.383, ή2=0.003), Time 2-(U=819.5, p=0.585, ή2=0.001), Time 3-(U=825, p=0.618, ή2=0.001) Dataset #3: Time 1-(U=395, p=0.198, ή2=0.007), Time 2-(U=373.5, p=0.365, ή2 =0.003), Time 3-(U=363, p=0.471, ή2=0.002), Time 4-(U=366.5, p=0.436, ή2 =0.003), Time 5-(U=371, p=0.391, ή2=0.003), Time 6-(U=394, p=0.208, ή2=0.007), Time 7-(U=373, p=0.373, ή2=0.003), Time 8-(U=371.5, p=0.387, ή2=0.003), Time 9-(U=464.5, p=0.512, ή2=0.002), Time 10-(U=356.5, p=0.546, ή2=0.002), Time 11-(U=357.5, p=0.535, ή2=0.002), Time 12-(U=350.5, p=0.346, ή2=0.004) Conclusions This study suggests no significant gender differences in response to ABA therapy among individuals with autism, indicating its potential effectiveness for both genders. However, these findings should be interpreted cautiously due to statistical uncertainties reflected in the broad confidence intervals as they hint at possible substantial gender differences. Further research, including an extension study, must confirm these results and understand potential gender nuances in ABA therapy response. This could help tailor more effective, personalized therapeutic strategies for individuals with autism.

Comparative Effects of Applied Behavior Analysis on Male and Female Individuals With Autism Spectrum Disorder

Introduction Current evidence-based treatments for autism spectrum disorder (ASD) are based on applied behavior analysis (ABA). However, research on gender differences in ABA therapy response is limited. This study seeks to (1) confirm the 4:1 male-to-female ratio reported in the literature and (2) identify any possible gender differences in target behaviors over seven timepoints measured every two weeks. Materials and methods  For three months, from March 19, 2023, to June 11, 2023, a team of 3-5 behavioral technicians per individual collected daily data on general target mastery for 100 individuals with ASD treated with ABA. Data was collected at seven timepoints every two weeks. Descriptive demographics were computed. Two independent sample t-tests were performed to determine significant or nonsignificant gender differences with the seven timepoint variables.  Results Nonstatistically significant gender differences (p > .05) were found on all seven cumulative target behavior timepoints measured at two-week intervals. For targets mastered Time 1, baseline between males and females, there was no significant difference in the means for males (M = 1.0571, SD = 1.9196) and females (M = 2.0455, SD = 3.9457) (t(90) = -1.591, p = 0.115, confidence interval (CI) = -2.2223, 0.2456, d = -0.389). For targets mastered Time 2, two weeks between males and females, there was no significant difference in the means for males (M = 3.7132; SD = 4.5065) and females (M = 4.0682, SD = 5.1508) (t(88) = -0.310, p = 0.757, CI = -2.6305, 1.92056, d = -0.076). For targets mastered Time 3, four weeks between males and females, there was no significant difference in the means for males (M = 7.0956; SD = 8.7781) and females (M = 8.6136; SD = 11.2799) (t(88) = -0.656, p = 0.514, CI = -6.1173, 3.0811, d = -0.161). For targets mastered Time 4, six weeks between males and females, there was no significant difference in the means for males (M = 13.1728, SD = 16.2003) and females (M = 13.0682, SD = 16.9272) (t(88) = 0.026, p = 0.979, CI = -7.8779, 8.0871, d = 0.006). For targets mastered Time 5, eight weeks between males and females, there was no significant difference in the means for males (M = 17.2096; SD = 18.8546) and females (M = 17.4286, SD = 22.1683) (t(87) = -0.045, p = 0.965, CI = -9.9773, 9.5393, d = -0.011). For targets mastered Time 6, 10 weeks between males and females, there was no significant difference in the means for males (M = 21.0074, SD = 21.3329) and females (M = 20.6818, SD = 26.1231) (t(88) = 0.059, p = 0.953, CI = -10.6752, 11.3262, d = 0.014). For targets mastered Time 7, 12 weeks between males and females, there was no significant difference in the means for males (M = 26.1196, SD = 24.2235) and females (M = 29.6364, SD = 33.7406) (t(89) = -0.536, p = 0.593, CI = -16.5431, 9.5094, d = -0.131). Conclusions The study indicates that ABA treatments may be equally beneficial for both genders with ASD, showing no significant gender differences. However, the broad CIs in this study imply a level of statistical uncertainty, indicating potential gender differences, suggesting the results may not be uniform across genders. These findings challenge assumptions on gender-specific treatment responses, implying that ABA treatments shouldn't be recommended based on gender. Instead, individual needs should guide treatment recommendations. Future research could consider other response moderators like age, ASD severity, or coexisting mental health conditions.