Supporting emotion regulation in children on the autism spectrum: co-developing a digital mental health application for school-based settings with community partners.

OBJECTIVE: KeepCalm is a digital mental health application, co-designed with community partners, that incorporates wearable biosensing with support for teams to address challenging behaviors and emotion dysregulation in children on the autism spectrum. METHODS: We followed a user-centered design framework. Before app development, we conducted design workshops, needs assessment interviews, a systematic review, and created an Expert Advisory Board. Once we had a working prototype, we recruited 73 participants to test and help improve the app across five testing cycles. RESULTS: Participants rated the app across testing cycles as highly acceptable, appropriate, feasible, and with good usability. Qualitative data indicated that KeepCalm helped teachers (a) be aware of students' previously unrealized triggers, especially for nonspeaking students; (b) prevent behavioral episodes; (c) communicate with parents about behaviors/strategies; and (d) equipped parents with knowledge of strategies to use at home. We learned that in order to make the app acceptable and appropriate we needed to make the app enjoyable/easy to use and to focus development on novel features that augment teachers' skills (e.g., behavioral pattern and stress detection). We also learned about the importance of maximizing feasibility, through in-person app training/support especially regarding the wearable devices, and the importance of having aides involved. CONCLUSION: Our findings have informed plans for wider-scale feasibility testing so that we may examine the determinants of implementation to inform adaptations and refinement, and gather preliminary efficacy data on KeepCalm's impact on reducing challenging behaviors and supporting emotion regulation in students on the autism spectrum.

Can peripheral psychophysiological markers predict response to exposure-based cognitive behavioral therapy in youth with severely impairing irritability? A study protocol.

BACKGROUND: Irritability, an increased proneness to anger, is a primary reason youth present for psychiatric care. While initial evidence supports the efficacy of exposure-based cognitive behavioral therapy (CBT) for youth with clinically impairing irritability, treatment mechanisms remain unclear. Here, we propose to measure peripheral psychophysiological indicators of arousal-heart rate (HR)/electrodermal activity (EDA)-and regulation-heart rate variability (HRV)-during exposures to anger-inducing stimuli as potential predictors of treatment efficacy. The objective of this study is to evaluate whether in-situ biosensing data provides peripheral physiological indicators of in-session response to exposures. METHODS: Blood volume pulse (BVP; from which HR and HRV canl be derived) and EDA will be collected ambulatorily using the Empatica EmbracePlus from 40 youth (all genders; ages 8-17) undergoing six in-person exposure treatment sessions, as part of a multiple-baseline trial of exposure-based CBT for clinically impairing irritability. Clinical ratings of irritability will be conducted at baseline, weekly throughout treatment, and at 3-month and 6-month follow-ups via the Clinical Global Impressions Scale (CGI) and the Affective Reactivity Index (ARI; clinician-, parent-, and child-report). Multilevel modeling will be used to assess within- and between-person changes in physiological arousal and regulation throughout exposure-based CBT and to determine whether individual differences are predictive of treatment response. DISCUSSION: This study protocol leverages a wearable biosensor (Empatica) to continuously record HR/HRV (derived from BVP) and EDA during in-person exposure sessions for youth with clinically impairing irritability. Here, the goal is to identify changes in physiological arousal (EDA, HR) and regulation (HRV) over the course of treatment in tandem with changes in clinical symptoms. TRIAL REGISTRATION: The participants in this study come from an overarching clinical trial (trial registration numbers: NCT02531893 first registered on 8/25/2015; last updated on 8/25/2023). The research project and all related materials were submitted and approved by the appropriate Institutional Review Board of the National Institute of Mental Health (NIMH).

Systematic review: emotion dysregulation and challenging behavior interventions for children and adolescents on the autism spectrum with graded key evidence-based strategy recommendations.

Challenging behavior, such as aggression, is highly prevalent in children and adolescents on the autism spectrum and can have a devastating impact. Previous reviews of challenging behavior interventions did not include interventions targeting emotion dysregulation, a common cause of challenging behavior. We reviewed emotion dysregulation and challenging behavior interventions for preschoolers to adolescents to determine which evidence-based strategies have the most empirical support for reducing/preventing emotion dysregulation/challenging behavior. We reviewed 95 studies, including 29 group and 66 single case designs. We excluded non-behavioral/psychosocial interventions and those targeting internalizing symptoms only. We applied a coding system to identify discrete strategies based on autism practice guidelines with the addition of strategies common in childhood mental health disorders, and an evidence grading system. Strategies with the highest quality evidence (multiple randomized controlled trials with low bias risk) were Parent-Implemented Intervention, Emotion Regulation Training, Reinforcement, Visual Supports, Cognitive Behavioral/Instructional Strategies and Antecedent-Based Interventions. Regarding outcomes, most studies included challenging behavior measures, while few included emotion dysregulation measures. This review highlights the importance of teaching emotion regulation skills explicitly, positively reinforcing replacement/alternative behaviors, using visuals and metacognition, addressing stressors proactively, and involving parents. It also calls for more rigorously designed studies and for including emotion dysregulation as an outcome/mediator in future trials.

A Tribute to the Mind, Methodology and Mentoring of Wayne Velicer.

Wayne Velicer is remembered for a mind where mathematical concepts and calculations intrigued him, behavioral science beckoned him, and people fascinated him. Born in Green Bay, Wisconsin on March 4, 1944, he was raised on a farm, although early influences extended far beyond that beginning. His Mathematics BS and Psychology minor at Wisconsin State University in Oshkosh, and his PhD in Quantitative Psychology from Purdue led him to a fruitful and far-reaching career. He was honored several times as a high-impact author, was a renowned scholar in quantitative and health psychology, and had more than 300 scholarly publications and 54,000+ citations of his work, advancing the arenas of quantitative methodology and behavioral health. In his methodological work, Velicer sought out ways to measure, synthesize, categorize, and assess people and constructs across behaviors and time, largely through principal components analysis, time series, and cluster analysis. Further, he and several colleagues developed a method called Testing Theory-based Quantitative Predictions, successfully applied to predicting outcomes and effect sizes in smoking cessation, diet behavior, and sun protection, with the potential for wider applications. With $60,000,000 in external funding, Velicer also helped engage a large cadre of students and other colleagues to study methodological models for a myriad of health behaviors in a widely applied Transtheoretical Model of Change. Unwittingly, he has engendered indelible memories and gratitude to all who crossed his path. Although Wayne Velicer left this world on October 15, 2017 after battling an aggressive cancer, he is still very present among us.

Framework for selecting and benchmarking mobile devices in psychophysiological research.

Commercially available consumer electronics in (smartwatches and wearable biosensors) are increasingly enabling acquisition of peripheral physiological and physical activity data inside and outside of laboratory settings. However, there is scant literature available for selecting and assessing the suitability of these novel devices for scientific use. To overcome this limitation, the current paper offers a framework to aid researchers in choosing and evaluating wearable technologies for use in empirical research. Our seven-step framework includes: (1) identifying signals of interest; (2) characterizing intended use cases; (3) identifying study-specific pragmatic needs; (4) selecting devices for evaluation; (5) establishing an assessment procedure; (6) performing qualitative and quantitative analyses on resulting data; and, if desired, (7) conducting power analyses to determine sample size needed to more rigorously compare performance across devices. We illustrate the application of the framework by comparing electrodermal, cardiovascular, and accelerometry data from a variety of commercial wireless sensors (Affectiva Q, Empatica E3, Empatica E4, Actiwave Cardio, Shimmer) relative to a well-validated, wired MindWare laboratory system. Our evaluations are performed in two studies (N = 10, N = 11) involving psychometrically sound, standardized tasks that include physical activity and affect induction. After applying our framework to this data, we conclude that only some commercially available consumer devices for physiological measurement are capable of wirelessly measuring peripheral physiological and physical activity data of sufficient quality for scientific use cases. Thus, the framework appears to be beneficial at suggesting steps for conducting more systematic, transparent, and rigorous evaluations of mobile physiological devices prior to deployment in studies.

Cardiovascular Reactivity During Marital Conflict in Laboratory and Naturalistic Settings: Differential Associations with Relationship and Individual Functioning Across Contexts.

Cardiovascular reactivity during spousal conflict is considered to be one of the main pathways for relationship distress to impact physical, mental, and relationship health. However, the magnitude of association between cardiovascular reactivity during laboratory marital conflict and relationship functioning is small and inconsistent given the scope of its importance in theoretical models of intimate relationships. This study tests the possibility that cardiovascular data collected in laboratory settings downwardly bias the magnitude of these associations when compared to measures obtained in naturalistic settings. Ambulatory cardiovascular reactivity data were collected from 20 couples during two relationship conflicts in a research laboratory, two planned relationship conflicts at couples' homes, and two spontaneous relationship conflicts during couples' daily lives. Associations between self-report measures of relationship functioning, individual functioning, and cardiovascular reactivity across settings are tested using multilevel models. Cardiovascular reactivity was significantly larger during planned and spontaneous relationship conflicts in naturalistic settings than during planned relationship conflicts in the laboratory. Similarly, associations with relationship and individual functioning variables were statistically significantly larger for cardiovascular data collected in naturalistic settings than the same data collected in the laboratory. Our findings suggest that cardiovascular reactivity during spousal conflict in naturalistic settings is statistically significantly different from that elicited in laboratory settings both in magnitude and in the pattern of associations with a wide range of inter- and intrapersonal variables. These differences in findings across laboratory and naturalistic physiological responses highlight the value of testing physiological phenomena across interaction contexts in romantic relationships.

Dense home-based recordings reveal typical and atypical development of tense/aspect in a child with delayed language development.

Studies investigating the development of tense/aspect in children with developmental disorders have focused on production frequency and/or relied on short spontaneous speech samples. How children with developmental disorders use future forms/constructions is also unknown. The current study expands this literature by examining frequency, consistency, and productivity of past, present, and future usage, using the Speechome Recorder, which enables collection of dense, longitudinal audio-video recordings of children's speech. Samples were collected longitudinally in a child who was previously diagnosed with autism spectrum disorder, but at the time of the study exhibited only language delay [Audrey], and a typically developing child [Cleo]. While Audrey was comparable to Cleo in frequency and productivity of tense/aspect use, she was atypical in her consistency and production of an unattested future form. Examining additional measures of densely collected speech samples may reveal subtle atypicalities that are missed when relying on only few typical measures of acquisition.

Interpersonal Autonomic Physiology: A Systematic Review of the Literature.

Interpersonal autonomic physiology is defined as the relationship between people's physiological dynamics, as indexed by continuous measures of the autonomic nervous system. Findings from this field of study indicate that physiological activity between two or more people can become associated or interdependent, often referred to as physiological synchrony. Physiological synchrony has been found in both new and established relationships across a range of contexts, and it correlates with a number of psychosocial constructs. Given these findings, interpersonal physiological interactions are theorized to be ubiquitous social processes that co-occur with observable behavior. However, this scientific literature is fragmented, making it difficult to evaluate consistency across reports. In an effort to facilitate more standardized scholarly approaches, this systematic review provides a description of existing work in the area and highlights theoretical, methodological, and statistical issues to be addressed in future interpersonal autonomic physiology research.

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion.

BACKGROUND: Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum disorder (ASD) instrument algorithms in an attempt to improve upon widely used ASD screening and diagnostic tools. METHODS: The data consisted of Autism Diagnostic Interview-Revised (ADI-R) and Social Responsiveness Scale (SRS) scores for 1,264 verbal individuals with ASD and 462 verbal individuals with non-ASD developmental or psychiatric disorders, split at age 10. Algorithms were created via a robust ML classifier, support vector machine, while targeting best-estimate clinical diagnosis of ASD versus non-ASD. Parameter settings were tuned in multiple levels of cross-validation. RESULTS: The created algorithms were more effective (higher performing) than the current algorithms, were tunable (sensitivity and specificity can be differentially weighted), and were more efficient (achieving near-peak performance with five or fewer codes). Results from ML-based fusion of ADI-R and SRS are reported. We present a screener algorithm for below (above) age 10 that reached 89.2% (86.7%) sensitivity and 59.0% (53.4%) specificity with only five behavioral codes. CONCLUSIONS: ML is useful for creating robust, customizable instrument algorithms. In a unique dataset comprised of controls with other difficulties, our findings highlight the limitations of current caregiver-report instruments and indicate possible avenues for improving ASD screening and diagnostic tools.

Adaptive thresholding increases sensitivity to detect changes in the rate of skin conductance responses to psychologically arousing stimuli in both laboratory and ambulatory settings.

Psychophysiologists recording electrodermal activity (EDA) often derive measures of slow, tonic activity-skin conductance level (SCL)-and faster, more punctate changes-skin conductance responses (SCRs). A SCR is conventionally considered to have occurred when the local amplitude of the EDA signal exceeds a researcher-determined threshold (e.g., 0.05 µS), typically fixed across study participants and conditions. However, fixed SCR thresholds can preferentially exclude data from individuals with low SCL because their SCRs are smaller on average, thereby reducing statistical power for group-level analyses. Thus, we developed a fixed plus adaptive (FA) thresholding method that adjusts identification of SCRs based on an individual's SC at the onset of the SCR to increase statistical power and include data from more participants. We assess the utility of applying FA thresholding across two independent samples and explore age and race-related associations with EDA outcomes. Study 1 uses wired EDA measurements from 254 healthy adults responding to evocative images and sounds in a laboratory setting. Study 2 uses wireless EDA measurements from 20 children with autism in a clinical environment while they completed behavioral tasks. Compared to a 0.01, 0.03, and 0.05 µS fixed threshold, FA thresholding at 1.9% modestly increases statistical power to detect a difference in SCR rate between tasks with higher vs. lower subjective arousal and reduces exclusion of participants by up to 5% across both samples. This novel method expands the EDA analytical toolbox and may be useful in populations with highly variable basal SCL or when comparing groups with different basal SCL. Future research should test for reproducibility and generalizability in other tasks, samples, and contexts. IMPACT STATEMENTS: This article is important because it introduces a novel method to enhance sensitivity and statistical power in analyses of skin conductance responses from electrodermal data.

Examining the feasibility and utility of heart rate variability on intervention outcomes targeting emotion regulation in autism: a brief report.

Autistic youth experience several behavioral and emotional characteristics that can predispose them to emotion dysregulation (ED). Current literature examining ED in autism spectrum disorder (ASD) is limited to parent- and self-reported measures, indicating a need for biological or physiological methods to better assess emotion regulation in ASD. Utilizing the autonomic nervous system, specifically heart rate variability (HRV), may be a promising method to objectively measure ED in ASD, given it is one of the body's primary means of regulating physiological arousal. Our pilot study is one of the first to examine the feasibility, utility, and construct validity of HRV along with clinical measures within an intervention targeting ED-specific symptoms in ASD. Participants included 30 autistic youth ages 8-17 years who participated in the pilot study of Regulating Together, a group-based intervention targeting emotion regulation. We demonstrate HRV is feasible, demonstrates adequate test-retest reliability, and is complimentary to clinician- and parent-reported measures. Our preliminary findings also point to certain HRV profiles being indicative of long-term outcomes after receiving treatment. HRV may be a useful, objective tool in determining differential needs of long-term follow-up care for treatment maintenance at screening or baseline stages.

Wearable Biosensing to Predict Imminent Aggressive Behavior in Psychiatric Inpatient Youths With Autism.

Importance: Aggressive behavior is a prevalent and challenging issue in individuals with autism. Objective: To investigate whether changes in peripheral physiology recorded by a wearable biosensor and machine learning can be used to predict imminent aggressive behavior before it occurs in inpatient youths with autism. Design, Setting, and Participants: This noninterventional prognostic study used data collected from March 2019 to March 2020 from 4 primary care psychiatric inpatient hospitals. Enrolled participants were 86 psychiatric inpatients with confirmed diagnoses of autism exhibiting operationally defined self-injurious behavior, emotion dysregulation, or aggression toward others; 16 individuals were not included (18.6%) because they would not wear the biosensor (8 individuals) or were discharged before an observation could be made (8 individuals). Data were analyzed from March 2020 through October 2023. Main Outcomes and Measures: Research staff performed live behavioral coding of aggressive behavior while inpatient study participants wore a commercially available biosensor that recorded peripheral physiological signals (cardiovascular activity, electrodermal activity, and motion). Logistic regression, support vector machines, neural networks, and domain adaptation were used to analyze time-series features extracted from biosensor data. Area under the receiver operating characteristic curve (AUROC) values were used to evaluate the performance of population- and person-dependent models. Results: There were 70 study participants (mean [range; SD] age, 11.9 [5-19; 3.5] years; 62 males [88.6%]; 1 Asian [1.4%], 5 Black [7.1%], 1 Native Hawaiian or Other Pacific Islander [1.4%], and 63 White [90.0%]; 5 Hispanic [7.5%] and 62 non-Hispanic [92.5%] among 67 individuals with ethnicity data). Nearly half of the population (32 individuals [45.7%]) was minimally verbal, and 30 individuals (42.8%) had an intellectual disability. Participant length of inpatient hospital stay ranged from 8 to 201 days, and the mean (SD) length was 37.28 (33.95) days. A total of 429 naturalistic observational coding sessions were recorded, totaling 497 hours, wherein 6665 aggressive behaviors were documented, including self-injury (3983 behaviors [59.8%]), emotion dysregulation (2063 behaviors [31.0%]), and aggression toward others (619 behaviors [9.3%]). Logistic regression was the best-performing overall classifier across all experiments; for example, it predicted aggressive behavior 3 minutes before onset with a mean AUROC of 0.80 (95% CI, 0.79-0.81). Conclusions and Relevance: This study replicated and extended previous findings suggesting that machine learning analyses of preceding changes in peripheral physiology may be used to predict imminent aggressive behaviors before they occur in inpatient youths with autism. Further research will explore clinical implications and the potential for personalized interventions.

Regulating Together: Emotion Dysregulation Group Treatment for ASD Youth and Their Caregivers.

Individuals with autism spectrum disorder (ASD) experience behavioral and emotional symptoms hypothesized to arise from emotion dysregulation (ED), difficulty modulating emotional experience, expression, and intensity in an acceptable and contextually appropriate manner. We developed Regulating Together (RT)-an intensive-outpatient, caregiver-assisted group program to meet the ASD + ED intervention critical need. A within-subjects trial was conducted (5-week-control lead-in period, 5-week-treatment, and 5-and 10-weeks-post-treatment follow-ups). Forty-four youth with ASD + ED (25 8-12, 19 13-18 yr-olds, 88% male, mean FSIQ of 96) participated. Improvements were found in reactivity, emotion regulation knowledge, and flexibility post-treatment and 10-weeks post-treatment. A reduction in inpatient hospitalization rates by 16% from the 12 months pre-RT to 12 months post-RT was observed. RT shows promise to reduce ED in ASD.

Systematic Review: Emotion Dysregulation and Challenging Behavior Interventions for Children andAdolescents with Autism with Graded Key Evidence-Based Strategy Recommendations.

Challenging behavior, such as aggression, is highly prevalent in children and adolescents with autism and can have a devastating impact. Previous reviews of challenging behavior interventions did not include interventions targeting emotion dysregulation, a common cause of challenging behavior. We reviewed emotion dysregulation and challenging behavior interventions for preschoolers to adolescents to determine which evidence-based strategies have the most empirical support for reducing/preventing emotion dysregulation/challenging behavior. We reviewed 95 studies, including 29 group and 66 single-case designs. We excluded non-behavioral/psychosocial interventions and those targeting internalizing symptoms only. We applied a coding system to identify discrete strategies based on autism practice guidelines with the addition of strategies common in childhood mental health disorders, and an evidence grading system. Strategies with the highest quality evidence (multiple randomized controlled trials with low bias risk) were Parent-Implemented Intervention, Emotion Regulation Training, Reinforcement, Visual Supports, Cognitive Behavioral/Instructional Strategies and Antecedent-Based Interventions. Regarding outcomes, most studies included challenging behaviors measures while few included emotion dysregulation measures. This review highlights the importance of teaching emotion-regulation skills explicitly, positively reinforcing replacement/alternative behaviors, using visuals and metacognition, addressing stressors proactively, and involving parents. It also calls for more rigorously-designed studies and for including emotion dysregulation as an outcome/mediator in future trials.

A Digital Mental Health App Incorporating Wearable Biosensing for Teachers of Children on the Autism Spectrum to Support Emotion Regulation: Protocol for a Pilot Randomized Controlled Trial.

BACKGROUND: As much as 80% of children on the autism spectrum exhibit challenging behaviors (ie, behaviors dangerous to the self or others, behaviors that interfere with learning and development, and behaviors that interfere with socialization) that can have a devastating impact on personal and family well-being, contribute to teacher burnout, and even require hospitalization. Evidence-based practices to reduce these behaviors emphasize identifying triggers (events or antecedents that lead to challenging behaviors); however, parents and teachers often report that challenging behaviors surface with little warning. Exciting recent advances in biometric sensing and mobile computing technology allow the measurement of momentary emotion dysregulation using physiological indexes. OBJECTIVE: We present the framework and protocol for a pilot trial that will test a mobile digital mental health app, the KeepCalm app. School-based approaches to managing challenging behaviors in children on the autism spectrum are limited by 3 key factors: children on the autism spectrum often have difficulties in communicating their emotions; it is challenging to implement evidence-based, personalized strategies for individual children in group settings; and it is difficult for teachers to track which strategies are successful for each child. KeepCalm aims to address those barriers by communicating children's stress to their teachers using physiological signaling (emotion dysregulation detection), supporting the implementation of emotion regulation strategies via smartphone pop-up notifications of top strategies for each child according to their behavior (emotion regulation strategy implementation), and easing the task of tracking outcomes by providing the child's educational team with a tool to track the most effective emotion regulation strategies for that child based on physiological stress reduction data (emotion regulation strategy evaluation). METHODS: We will test KeepCalm with 20 educational teams of students on the autism spectrum with challenging behaviors (no exclusion based on IQ or speaking ability) in a pilot randomized waitlist-controlled field trial over a 3-month period. We will examine the usability, acceptability, feasibility, and appropriateness of KeepCalm as primary outcomes. Secondary preliminary efficacy outcomes include clinical decision support success, false positives or false negatives of stress alerts, and the reduction of challenging behaviors and emotion dysregulation. We will also examine technical outcomes, including the number of artifacts and the proportion of time children are engaged in high physical movement based on accelerometry data; test the feasibility of our recruitment strategies; and test the response rate and sensitivity to change of our measures, in preparation for a future fully powered large-scale randomized controlled trial. RESULTS: The pilot trial will begin by September 2023. CONCLUSIONS: Results will provide key data about important aspects of implementing KeepCalm in preschools and elementary schools and will provide preliminary data about its efficacy to reduce challenging behaviors and support emotion regulation in children on the autism spectrum. TRIAL REGISTRATION: ClinicalTrials.gov NCT05277194; https://www.clinicaltrials.gov/ct2/show/NCT05277194. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/45852.

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

Challenges with emotion dysregulation, self-injurious behavior (SIB), and aggression are common in autistic individuals. Prior research on the relationships between these behaviors is limited mainly to cross-sectional correlations of parent-report data. Understanding how emotion dysregulation, SIB, and aggression present and relate to one another in real-time could add to our understanding of the context and function of these behaviors. The present study examined the real-time occurrence and temporal relationships between these behaviors in 53 psychiatrically hospitalized autistic youth. Over 500 hours of behavioral observation occurred during everyday activities in the hospital. Start and stop times for instances of overt emotion dysregulation, SIB, and aggression were coded live using a custom mobile phone app. Results indicated large individual variability in the frequency and duration of these behaviors and their co-occurrence. Both SIB and aggression co-occurred with overt emotion dysregulation at above-chance levels, suggesting a role for emotional distress in the occurrence of these behaviors. However, there was substantial variability within and between individuals in co-occurrence, and SIB and aggression often (and for some individuals, almost always) occurred without overt emotion dysregulation. Relatedly, cross-recurrence quantitative analysis revealed that SIB and aggression preceded emotion dysregulation more often than emotion dysregulation preceded SIB and aggression. Future research, perhaps using ambulatory psychophysiological measures, is needed to understand whether emotion dysregulation may sometimes be present but not easily observed during SIB and aggression. LAY SUMMARY: This study provides insight into how overt emotion dysregulation (i.e., visible distress), aggression, and self-injury unfold in real-time for autistic individuals. Participants were 53 autistic youth staying in a psychiatric hospital. Research staff observed participants in everyday activities on the hospital unit and noted instances of aggression, self-injurious behavior, and emotion dysregulation. Results suggest that aggression and self-injury sometimes occur with visible signs of distress but also often occur without visible distress. In addition, observable distress was more common in the moments after these behaviors than in the moments before.

Evaluating commercially available wireless cardiovascular monitors for measuring and transmitting real-time physiological responses in children with autism.

Commercially available wearable biosensors have the potential to enhance psychophysiology research and digital health technologies for autism by enabling stress or arousal monitoring in naturalistic settings. However, such monitors may not be comfortable for children with autism due to sensory sensitivities. To determine the feasibility of wearable technology in children with autism age 8-12 years, we first selected six consumer-grade wireless cardiovascular monitors and tested them during rest and movement conditions in 23 typically developing adults. Subsequently, the best performing monitors (based on data quality robustness statistics), Polar and Mio Fuse, were evaluated in 32 children with autism and 23 typically developing children during a 2-h session, including rest and mild stress-inducing tasks. Cardiovascular data were recorded simultaneously across monitors using custom software. We administered the Comfort Rating Scales to children. Although the Polar monitor was less comfortable for children with autism than typically developing children, absolute scores demonstrated that, on average, all children found each monitor comfortable. For most children, data from the Mio Fuse (96%-100%) and Polar (83%-96%) passed quality thresholds of data robustness. Moreover, in the stress relative to rest condition, heart rate increased for the Polar, F(1,53) = 135.70, p < 0.001, ηp2  = 0.78, and Mio Fuse, F(1,53) = 71.98, p < 0.001, ηp2  = 0.61, respectively, and heart rate variability decreased for the Polar, F(1,53) = 13.41, p = 0.001, ηp2  = 0.26, and Mio Fuse, F(1,53) = 8.89, p = 0.005, ηp2  = 0.16, respectively. This feasibility study suggests that select consumer-grade wearable cardiovascular monitors can be used with children with autism and may be a promising means for tracking physiological stress or arousal responses in community settings. LAY SUMMARY: Commercially available heart rate trackers have the potential to advance stress research with individuals with autism. Due to sensory sensitivities common in autism, their comfort wearing such trackers is vital to gathering robust and valid data. After assessing six trackers with typically developing adults, we tested the best trackers (based on data quality) in typically developing children and children with autism and found that two of them met criteria for comfort, robustness, and validity.

Cardiovascular reactivity as a measure of irritability in a transdiagnostic sample of youth: Preliminary associations.

OBJECTIVES: Irritability is a transdiagnostic symptom in developmental psychopathology, conceptualized as a low threshold for frustration and increased proneness to anger. While central to emotion regulation, there is a vital need for empirical studies to explore the relationship between irritability and underlying physiological mechanisms of cardiovascular arousal. METHODS: We examined the relationship between irritability and cardiovascular arousal (i.e., heart rate [HR] and heart rate variability [HRV]) in a transdiagnostic sample of 51 youth (M = 12.63 years, SD = 2.25; 62.7% male). Data was collected using the Empatica E4 during a laboratory stop-signal task. In addition, the impact of motion activity, age, medication, and sleep on cardiovascular responses was explored. RESULTS: Main findings showed that irritability was associated with increased HR and decreased HRV during task performance. CONCLUSIONS: Findings support the role of peripheral physiological dysregulation in youth with emotion regulation problems and suggest the potential use of available wearable consumer electronics as an objective measure of irritability and physiological arousal in a transdiagnostic sample of youth.

Visual Preference for Biological Motion in Children and Adults with Autism Spectrum Disorder: An Eye-Tracking Study.

Participants with autism spectrum disorder (ASD) (n = 121, mean [SD] age: 14.6 [8.0] years) and typically developing (TD) controls (n = 40, 16.4 [13.3] years) were presented with a series of videos representing biological motion on one side of a computer monitor screen and non-biological motion on the other, while their eye movements were recorded. As predicted, participants with ASD spent less overall time looking at presented stimuli than TD participants (P < 10-3) and showed less preference for biological motion (P < 10-5). Participants with ASD also had greater average latencies than TD participants of the first fixation on both biological (P < 0.01) and non-biological motion (P < 0.02). Findings suggest that individuals with ASD differ from TD individuals on multiple properties of eye movements and biological motion preference.