Evidence map›Paper›PMID 31225952›Full record

ArticleAutism research : official journal of the International Society for Autism Research2019

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

Matthew S Goodwin, Carla A Mazefsky, Stratis Ioannidis, Deniz Erdogmus, Matthew Siegel

2 registry-linked trialsOpen access · greenAbstract read
In one paragraph

Article in Autism research : official journal of the International Society for Autism Research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 63 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 3 pooled it
5.8field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05340608 completednot on this mapstarted 2022, after this paper: background citation

Development and Validation of a System for the Anticipation of Challenging Behaviors of People With Autism Spectrum Disorder Based on a Smart Shirt: a Mixed-method Design

TypeobservationalSponsorAriel UniversityRan2022 to 2022Enrolled51ConditionsAutism Spectrum DisorderArmsSmart, non-invasive shirt - Physiological parameters, Smart, non-invasive shirt - Relation with challenging behaviors, Smart, non-invasive shirt - Proof of Concept
NCT07504224 nacompletednot on this mapstarted 2024, after this paper: background citation

Feasibility of Wearable Devices as a Source of Data to Support HealthAI in Autism Spectrum Disorder Populations

TypeinterventionalSponsorRady Pediatric Genomics & Systems Medicine InstituteRan2024 to 2026Enrolled40ConditionsAutism Spectrum Disorder, Wearable DevicesArms14-Day Device Monitoring
3 · Its place in the literature

Who cites it

63 citing papers in PubMed, 3 syntheses or guidelines pooled it, 111 citations in OpenAlex.

  1. Artificial Intelligence Methods in Early Detection of Autism Spectrum Disorder: A DSM-5 Criterion-Based Systematic Review.Autism research : official journal of the International Society for Autism Research · 2026
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  3. Momentary physiological indices related to eating disorders: A systematic and methodological review.European eating disorders review : the journal of the Eating Disorders Association · 2024
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  7. Beyond the Outburst: Charting a New Frontier for Understanding and Treating Irritability in Autistic Adults.Autism research : official journal of the International Society for Autism Research · 2026
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3 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Matthew S GoodwinDepartment of Health Sciences, Northeastern University, Boston, Massachusetts.ORCID 0000-0002-4237-601X
Carla A MazefskyDepartment of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.ORCID 0000-0001-7467-0902
Stratis IoannidisDepartment of Electrical and Computer Engineering, Northeastern University, Boston, Massachusetts.
Deniz ErdogmusDepartment of Electrical and Computer Engineering, Northeastern University, Boston, Massachusetts.
Matthew SiegelMaine Medical Center Research Institute, Portland, Maine.
Northeastern University · USMaine Medical Center Research Institute · USUniversity of Pittsburgh · US

Funding

Testing the efficacy of a novel intervention for minimally verbal children with P50DC013027 · NIDCD · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI SHINN-CUNNINGHAM, BARBARA · 2012 to 2016
$9.4M
Change-sensitive Measurement of Emotion Dysregulation in ASDR01HD079512 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Carla A Mazefsky · 2014 to 2026
$6.3M
Nancy Lurie Marks Family FoundationNational Science Foundation IIS-1118061National Science Foundation SCH-1622536NICHD NIH HHS R01 HD079512NIDCD NIH HHS P50 DC013027Simons Foundation 296318Simons Foundation 618037U.S. Department of Defense 12507232U.S. Department of Defense 12507733
6 · The paper itself

Abstract

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. Autism Res 2019, 12: 1286-1296. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. 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.

Indexed as

Wearable Electronic DevicesAdolescentAggressionAutism Spectrum DisorderBiosensing TechniquesChildFemaleHumansMaleReproducibility of Resultsaggressionautism spectrum disorderautonomic nervous systembiosensing techniquesinpatients

Identifiers

PMID31225952
PMCPMC6988899
OpenAlexW2952797450

What OpenQuestion holds

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Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.