The emotion dysregulation inventory: Psychometric properties and item response theory calibration in an autism spectrum disorder sample

Mazefsky, Carla; Yu, Lan; White, Susan W.; Siegel, Matthew; Pilkonis, Paul A.

doi:10.1002/aur.1947

Cited by 101 publications

(61 citation statements)

References 57 publications

(69 reference statements)

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“…These findings share some overlap with the factor structure of the Emotion Dysregulation Inventory (EDI), a caregiver report measure for children with ASD designed to assess emotion dysregulation, which refers more narrowly to difficulty regulating mood and behavior versus mood, behavior, and cognition. The EDI is comprised of two distinct factors, “dysphoria which is characterized by anhedonia, sadness, and nervousness” and “reactivity which refers to intense, rapidly escalating, sustained, and poorly regulated negative emotional reactions.” Unlike our findings, however, the EDI does not have a general dysregulation factor subsuming the two [Mazefsky et al, ].…”

Section: Discussioncontrasting

confidence: 99%

“…The EDI is comprised of two distinct factors, "dysphoria which is characterized by anhedonia, sadness, and nervousness" and "reactivity which refers to intense, rapidly escalating, sustained, and poorly regulated negative emotional reactions." Unlike our findings, however, the EDI does not have a general dysregulation factor subsuming the two [Mazefsky et al, 2018].…”

Section: Discussioncontrasting

confidence: 99%

“…Impairments in self‐regulation are characterized by deficits in one's ability to modulate affect, behavior, and cognition [Mick et al, ]. Dysregulation is a prominent feature in many children with ASD and has been associated with many negative outcomes including increased risk for psychiatric disorders and impairments in adaptive functioning [Mazefsky, Yu, White, Siegel, & Pilkonis, ; Meyer et al, ; Uljarevic et al, ; Weiss, Riosa, Mazefsky, & Beaumont, ]. Hence, dysregulation is an important transdiagnostic treatment target that may improve mental health outcomes in individuals with ASD [Uljarevic et al, ].…”

Section: Introductionmentioning

confidence: 99%

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Investigating the factor structure of the child behavior checklist dysregulation profile in children and adolescents with autism spectrum disorder

et al. 2019

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Dysregulation has been identified as an important risk factor for the development of psychiatric disorders in individuals with autism spectrum disorder (ASD). Therefore, it is necessary to empirically characterize dysregulation and identify psychometrically sound and readily available assessment methods in the ASD population. We sought to evaluate the factor structure of the Child Behavior Checklist‐Dysregulation Profile (CBCL‐DP), an established dysregulation measure in neurotypical children that is derived from the CBCL, in a large, clinically referred sample of children, ages 6–18 years, with ASD (n = 727). Confirmatory factor analysis was used to characterize dysregulation and assess the validity of the CBCL‐DP in children with ASD. Our findings support a bi‐factor model of dysregulation in which dysregulation is a broad and distinct syndrome that is associated with the three subdomains of the CBCL‐DP, anxiety/depression (AD), attention problems (AP), and aggressive behavior (AGG). Dysregulation was associated with most items in the AD and AGG domains and few items in the AP domain. This association with AD and AGG indicates that dysregulation in ASD may be conceptualized as the combined experience of internalized, negative mood states and externalized, reactive behaviors. These findings provide support as well as important caveats for the use of the CBCL‐DP as a measure of dysregulation in the ASD population. Autism Res 2020, 13: 436–443. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. Lay Summary Dysregulation is a risk factor for psychiatric disorders in ASD. This study examined if the CBCL‐DP, an established measure of dysregulation in neurotypical children, can be used to assess dysregulation in children with ASD. Findings provide evidence that in ASD, dysregulation is a broad construct that exists alongside anxiety/depression, attention problems, and aggression. These findings indicate that the CBCL‐DP can be considered a valid measure of dysregulation in the ASD population and could be used in clinical settings.

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Section: Discussioncontrasting

confidence: 99%

Section: Discussioncontrasting

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Investigating the factor structure of the child behavior checklist dysregulation profile in children and adolescents with autism spectrum disorder

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“…Emotion dysregulation, or difficulty altering one’s emotions in adaptive or goal-directed ways, has been shown to be impaired in many psychiatric disorders, including anxiety and depression, in people without [85] and with ASD [86]. There have been recent strides made in the valid assessment of emotion dysregulation in people with ASD [84]; as such, emotional reactivity/emotion dysregulation are prime candidates for further exploration in treatment research. In a recent two-site open trial of a therapy developed to improve emotion regulation in adolescents with ASD, of 17 treatment completers, all showed meaningful improvement on at least one index of emotion regulation and most (94%) had meaningful reduction in depression, anxiety, or problem behaviors [30].…”

Section: Identifying and Engaging Common Factorsmentioning

confidence: 99%

Psychosocial Treatments Targeting Anxiety and Depression in Adolescents and Adults on the Autism Spectrum: Review of the Latest Research and Recommended Future Directions

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Simmons

Gotham

et al. 2018

Curr Psychiatry Rep

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There is considerable evidence for the efficacy of cognitive-behavioral therapy (CBT) to treat co-occurring problems with anxiety, but there has been relatively little research on treatment of co-occurring depression. Multiple mechanisms of treatment effect have been proposed, but there has been little demonstration of target engagement via experimental therapeutics. Comorbidity between ASD and anxiety and/or mood problems is common. Although there is evidence for the use of CBT for anxiety, little work has addressed how to effectively treat depression. There is emerging support for alternative treatment approaches, such as mindfulness-based interventions. We encourage rigorous, collaborative approaches to identify and manipulate putative mechanisms of change.

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“…Exclusion criteria included not having a parent available who was proficient in English or the individual with ASD having prisoner status. Within 10 days of admission, a primary caregiver of the participant completed the Aberrant Behavior Checklist (ABC) [Aman, Singh, Stewart, & Field, ], Child Behavior Checklist (CBCL) [Achenbach, ], Vineland Adaptive Behavior Scales‐2 (VABS‐2) [Sparrow, Balla, & Cicchetti, ], and Emotion Dysregulation Inventory (EDI) [Mazefsky, Yu, White, Siegel, & Pilkonis, ]. Participants were also administered the Leiter‐3 test of nonverbal intelligence [Roid & Koch, ].…”

Section: Methodsmentioning

confidence: 99%

Predicting aggression to others in youth with autism using a wearable biosensor

et al. 2019

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Unpredictable and potentially dangerous aggressive behavior by youth with Autism Spectrum Disorder (ASD) can isolate them from foundational educational, social, and familial activities, thereby markedly exacerbating morbidity and costs associated with ASD. This study investigates whether preceding physiological and motion data measured by a wrist-worn biosensor can predict aggression to others by youth with ASD. We recorded peripheral physiological (cardiovascular and electrodermal activity) and motion (accelerometry) signals from a biosensor worn by 20 youth with ASD (ages 6-17 years, 75% male, 85% minimally verbal) during 69 independent naturalistic observation sessions with concurrent behavioral coding in a specialized inpatient psychiatry unit. We developed prediction models based on ridge-regularized logistic regression. Our results suggest that aggression to others can be predicted 1 min before it occurs using 3 min of prior biosensor data with an average area under the curve of 0.71 for a global model and 0.84 for person-dependent models. The biosensor was well tolerated, we obtained useable data in all cases, and no users withdrew from the study. Relatively high predictive accuracy was achieved using antecedent physiological and motion data. Larger trials are needed to further establish an ideal ratio of measurement density to predictive accuracy and reliability. These findings lay the groundwork for the future development of precursor behavior analysis and just-in-time adaptive intervention systems to prevent or mitigate the emergence, occurrence, and impact of aggression in ASD.Lay Summary: Unpredictable aggression can create a barrier to accessing community, therapeutic, medical, and educational services. The present study evaluated whether data from a wearable biosensor can be used to predict aggression to others by youth with autism spectrum disorder (ASD). Results demonstrate that aggression to others can be predicted 1 min before it occurs with high accuracy, laying the groundwork for the future development of preemptive behavioral interventions and just-in-time adaptive intervention systems to prevent or mitigate the emergence, occurrence, and impact of aggression to others in ASD.

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The emotion dysregulation inventory: Psychometric properties and item response theory calibration in an autism spectrum disorder sample

Cited by 101 publications

References 57 publications

Investigating the factor structure of the child behavior checklist dysregulation profile in children and adolescents with autism spectrum disorder

Investigating the factor structure of the child behavior checklist dysregulation profile in children and adolescents with autism spectrum disorder

Psychosocial Treatments Targeting Anxiety and Depression in Adolescents and Adults on the Autism Spectrum: Review of the Latest Research and Recommended Future Directions

Predicting aggression to others in youth with autism using a wearable biosensor

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