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Toby Constable

As seen in: Nature, Wiley Online Library, BioRxiv
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Articles by Toby Constable

Commentary: Strengths remain underweighted in dimensional and transdiagnostic models of child and youth mental health: Commentary on Altschuler et al. (2026)

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By Toby Constable, Beth Johnson, Vander Weele
| Wiley Online Library Verified
INTRODUCTION This commentary considers the advances of a recent article by Altschuler et al. (2026), published in the 2026 Special Issue of JCPP Advances. This paper presents the case for inclusion of transdiagnostic assessment of strengths, including domains such as biopsychosocial factors, caregiver resources and needs, cultural factors and broad strengths, when evaluating child and youth mental health.
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The cross-site reproducibility of MRI morphometric phenotypes in psychiatric disorders

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By Trang Cao, James C. Pang, Mehul Gajwani, Ashlea Segal, Alexander Holmes, Joshua F. Wiley, Sidhant Chopra, Juan Zhou, Christopher Chen, Fang Ji, Ben Harrison, Christopher G Davey, Toby Constable, Jeggan Tiego, Jessica Kwee, Mark A. Bellgrove, Bree Hartshorn
| Nature Verified
Abstract Decades of structural magnetic resonance imaging (MRI) studies have documented alterations of gray matter morphometry in psychiatric disorders, but the field has failed to identify any consensus disease phenotypes.
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Assessing the Psychometric Properties of the Child Behaviour Checklist in the ABCD Study

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By Kane Pavlovich, Toby Constable
| Wiley Online Library Verified
Alex Fornito and Jeggan Tiego are joint last authors. K., T.Constable, A.Fornito, and J.Tiego. 2026. “Assessing the Psychometric Properties of the Child Behaviour Checklist in the ABCD Study.” Developmental Science29, no. 4: e70216. Pavlovich, https://doi.org/10.1111/desc.70216 Conflicts of Interest None of the authors have a conflict of interest to disclose. Data Availability Statement The data used in this study were obtained from the ABCD Study, release 5.1, under the terms of a data use agreement.
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The efficacy of resting-state fMRI denoising pipelines for motion correction and behavioural prediction.

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By James C. Pang, Alexander Holmes, Kane Pavlovich, Toby Constable
| BioRxiv
Abstract Resting state functional magnetic resonance imaging (rsfMRI) is a pivotal tool for mapping the functional organization of the brain and its relation to individual differences in behaviour. One challenge for the field is that rsfMRI signals are contaminated by multiple sources of noise that can contaminate these rsfMRI signals, affecting the reliability and validity of any derivative phenotypes and attenuating their correlations with behaviour.
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