Evidence map›Paper›PMID 42656572›Full record

ArticleFrontiers in psychiatry2026

Transdiagnostic clinical correlates for behaviors of concern in pediatric neurodevelopmental disorders: a retrospective chart review and machine learning analysis.

Myka Estes, Margaret Ryan, Sara Early, Kimberly Amador, Noah Bloom, Amani Ahmed, Anza Momin, Tina R Ram, Nils D Forkert, Sarah J MacEachern

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Myka EstesDepartment of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Margaret RyanDepartment of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Sara EarlyAlberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Kimberly AmadorAlberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Noah BloomDepartment of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Amani AhmedDepartment of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Anza MominDepartment of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Tina R RamAlberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Nils D ForkertAlberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Sarah J MacEachernDepartment of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Behaviors of concern, such as aggression and self-injury, are common in children with neurodevelopmental disorders and contribute substantially to caregiver stress and health system burden. However, most evidence on behaviors is drawn from diagnostically homogeneous samples, limiting relevance to real-world presentations encountered in tertiary care. Our aim was to characterize the diagnostic and behavioral complexity of children referred to tertiary clinics and use machine learning to identify transdiagnostic features associated with behaviors across diverse neurodevelopmental presentations. Method: This retrospective chart review and analysis examined all children aged 2 to 17 years undergoing first-time assessment at a tertiary developmental pediatrics clinic between May 2022-2023. Unstructured physician notes and supporting documentation were transformed into structured data and supervised machine learning models identified factors associated with behaviors of concern. Results: Among 600 children, 83% exhibited at least one behavior of concern (mean, 3.15 [SD 2.98]). Most had multiple neurodevelopmental diagnoses (73%) and frequent co-occurrence of physical (80%) and mental health conditions (21%). Emotional dysregulation and non-cooperation were the most common behaviors, while aggression and self-injury were frequently moderate to severe. Machine learning models identified sleep difficulties, speech and language delay, restricted and repetitive behaviors (B symptoms) of autism, gastrointestinal issues, and service use as top-ranked associated factors across multiple behavioral types. Factors associated with any behaviors included ADHD, sensory impairments, and genetic contributors to autism. Discussion: Transdiagnostic factors highlight key domains often under-assessed in routine care. These findings support integrated assessment models that address modifiable clinical correlates for behaviors of concern across diagnostic boundaries to improve outcomes for high-need neurodevelopmental populations.

Indexed as

behaviors of concernchart reviewclinical outcomesmachine learningmedical complexityneurodevelopmental disorderspediatricstransdiagnostic

Identifiers

PMID42656572
PMCPMC13506917

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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.