Understanding the experiences of self-injurious behavior in autism spectrum disorder: Implications for monitoring technology design

Abstract

Objective Monitoring technology may assist in managing self-injurious behavior (SIB), a pervasive concern in autism spectrum disorder (ASD). Affiliated stakeholder perspectives should be considered to design effective and accepted SIB monitoring methods. We examined caregiver experiences to generate design guidance for SIB monitoring technology. Materials and Methods Twenty-three educators and 16 parents of individuals with ASD and SIB completed interviews or focus groups to discuss needs related to monitoring SIB and associated technology use. Results Qualitative content analysis of participant responses revealed 7 main themes associated with SIB and technology: triggers, emotional responses, SIB characteristics, management approaches, caregiver impact, child/student impact, and sensory/technology preferences. Discussion The derived themes indicated areas of emphasis for design at the intersection of monitoring and SIB. Systems design at this intersection should consider the range of manifestations of and management approaches for SIB. It should also attend to interactions among children with SIB, their caregivers, and the technology. Design should prioritize the transferability of physical technology and behavioral data as well as the safety, durability, and sensory implications of technology. Conclusions The collected stakeholder perspectives provide preliminary groundwork for an SIB monitoring system responsive to needs as articulated by caregivers. Technology design based on this groundwork should follow an iterative process that meaningfully engages caregivers and individuals with SIB in naturalistic settings.

Development and validation of a system for the prediction of challenging behaviors of people with autism spectrum disorder based on a smart wearable shirt: A mixed-methods design

“…However, reflections are anticipated about the individual sensory preferences of each person that may compromise the use of SWS in some people with ASD. Themes similar to this one emerged from a previous focus group related to the design of wearable technologies for people with ASD (Cantin-Garside et al, 2021). Furthermore, concerns can arise related to the hottest times of the year, when wearing a tank top under the shirt may be inappropriate.…”

“…Moreover, higher prediction performance was reported for the SVM + PCA model than for the LR model. Consistently, Cantin-Garside et al (2021) reported higher accuracy of SVM and k-nearest neighbor (kNN) algorithm in classifying self-injurious behavior in children with ASD compared to other methods [discriminant analysis (DA), decision trees (DT), Naïve Bayes (NB), and neural networks (NN)]. Furthermore, Zheng et al (2021) proposed a multimodal data analysis to predict precursors of CBs of children with ASD through various ML algorithms.…”

A Systematic Survey of Technology Driven Diagnosis for ASD

“…The objective of 90% of the research paper [11-14, 18, 20, 21, 49, 79, 95-97] is to detect ASD by ML and IoT. Only 9% researchers [29,94,98,99] focused on the study and analysis of self-Injurious Behavior of Autistic children. The rest of the paper [100,101] focuses on detecting and monitoring the child's hyperactivity .…”

“…On the other hand, Garside et al [99] recruited 11 ASD children with their caretakers for the SIB database. They used a multilevel logistic regression model for group-level SIB classification.…”

Mapping the time course of overt emotion dysregulation, self‐injurious behavior, and aggression in psychiatrically hospitalized autistic youth: A naturalistic study

“…There is some evidence for a positive association (Samson et al, 2014) between SIB and emotion dysregulation, while other work reports a negative relationship between SIB and anxiety severity (Williams et al, 2015). A recent qualitative study interviewing caregivers of autistic individuals about their children's SIB found that emotional responses-most often consisting of feeling upset, stressed, frustrated, or angry-emerged as a prominent theme in discussing caregivers' perceptions of direct causes of SIB (Cantin-Garside et al, 2021).…”