Evidence map›Paper›PMID 40162513›Full record

ArticlePsychological medicine2025

Using machine learning to identify features associated with different types of self-injurious behaviors in autistic youth.

Ligia Antezana, Caitlin M Conner, Safaa Eldeeb, Samuel Turecki, Matthew Siegel, Helmet T Karim, Carla A Mazefsky

Abstract read
In one paragraph

Article in Psychological medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ligia AntezanaDepartment of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.ORCID 0000-0003-0603-9371
Caitlin M ConnerDepartment of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Safaa EldeebDepartment of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Samuel TureckiDivision of Child and Adolescent Psychiatry, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Matthew SiegelDepartments of Psychiatry and Pediatrics, Tufts University School of Medicine, Medford, MA, USA.
Helmet T KarimDepartment of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Carla A MazefskyDepartment of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.

Funding

Change-sensitive Measurement of Emotion Dysregulation in ASDR01HD079512 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Carla A Mazefsky · 2014 to 2026
$6.3M
Eunice Kennedy Shriver National Institute of Child Health and Human Development R01HD079512Nancy Lurie Marks Family Foundation #296318NICHD NIH HHS R01 HD079512
6 · The paper itself

Abstract

backgroundSelf-injurious behaviors (SIB) are common in autistic people. SIB is mainly studied as a broad category, rather than by specific SIB types. We aimed to determine associations of distinct SIB types with common psychiatric, emotional, medical, and socio-demographic factors.

methodsParticipants included 323 autistic youth (~50% non-/minimally-speaking) with high-confidence autism diagnoses ages 4-21 years. Data were collected by the Autism Inpatient Collection during admission to a specialized psychiatric inpatient unit (www.sfari.org/resource/autism-inpatient-collection/). Caregivers completed questionnaires about their child, including SIB type and severity. The youth completed assessments with clinicians. Elastic net regressions identified associations between SIB types and factors.

resultsNo single factor relates to all SIB types. SIB types have unique sets of associations. Consistent with previous work, more repetitive motor movements and lower adaptive skills are associated with most types of SIB; female sex is associated with hair/skin pulling and self-rubbing/scratching. More attention-deficit/hyperactivity disorder symptoms are associated with self-rubbing/scratching, skin picking, hair/skin pulling, and inserts finger/object. Inserts finger/object has the most medical condition associations. Self-hitting against surface/object has the most emotion dysregulation associations.

conclusionsSpecific SIB types have unique sets of associations. Future work can develop clinical likelihood scores for specific SIB types in inpatient settings, which can be tested with large community samples. Current approaches for SIB focus on the behavior functions, but there is an opportunity to further develop interventions by considering the specific SIB type in assessment and treatment. Identifying factors associated with specific SIB types may aid with screening, prevention, and treatment of these often-impairing behaviors.

Indexed as

Autism Spectrum DisorderAutistic DisorderMachine LearningSelf-Injurious BehaviorAdolescentChildChild, PreschoolFemaleHumansMaleYoung Adultadaptive behaviorADHDautismautism inpatient collectionelastic net regressionemotion dysregulationheadachesinpatientmachine learningmedical problemspicapsychiatric symptomsrepetitive behaviorself-injurious behaviorsleep

Identifiers

PMID40162513
PMCPMC12094640

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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.