Journal article
Longitudinal Dynamics and Pluripotentiality of Polysymptomatic Clustering in Adolescent Mental Health
Mental Illness, Vol.2025, pp.1-13
2025
Abstract
Background: Adolescence represents a sensitive developmental period characterised by an increased incidence of emerging mental health symptoms and formal diagnostic onset. These conditions can remain a significant burden throughout life. The Longitudinal Adolescent Brain Study (LABS) commenced in 2018 to track the onset and trajectory of mental health symptoms among participants aged 12–17 years. This research is aimed at identifying the clusters of emerging symptoms transdiagnostically in adolescents and examining how these clusters vary by age and change over time, providing insights into the pluripotentiality of disorder development.
Methods: LABS participants (12–17 years, n = 166) completed the Mini International Neuropsychiatric Interview (MINI Kid) approximately every 4 months, up to 15 timepoints. The high dimensional dataset underwent a dimensionality reduction step (uniform manifold approximation and projection [UMAP]), followed by Bayesian model averaging of k-means, Gaussian mixture model and hierarchical clustering to identify distinct symptom clusters. Symptom clusters were described in terms of the original neuropsychiatric interview responses using separate XGBoost classifier models. Symptom cluster dynamics were analysed using Markov chain transition probability matrices and longitudinal analysis. To explore the relationship between symptom clusters and psychological distress and well-being, correlational analyses were conducted using scores from the Kessler Psychological Distress Scale (K10) and the COMPAS-W Wellbeing Scale.
Results: Six symptom-based clusters (states) were identified: attention, anxiety, depression, manic episode—heritability, anhedonia, and well. Depression and anxiety clusters had the greatest pluripotentiality. Analysis of psychological distress and well-being scores demonstrated an inverse relationship between the states: those with greater psychological distress had more symptoms; conversely, those with greater well-being had fewer symptoms.
Conclusions: Mapping clusters of mental health symptoms and their pluripotential and transitory trajectories in adolescents enables more effective targeting of preventive interventions. This approach moves beyond categorical classifications, addressing comorbidity of emerging symptoms to mitigate the progression of early symptoms into enduring psychiatric disorders.
Details
- Title
- Longitudinal Dynamics and Pluripotentiality of Polysymptomatic Clustering in Adolescent Mental Health
- Authors
- Michelle F. Kennedy (Corresponding Author) - University of the Sunshine Coast, Queensland, Thompson InstitutePaul E. Schwenn - University of the Sunshine Coast, Queensland, Thompson InstituteAmanda Boyes - University of the Sunshine Coast, Queensland, Thompson InstituteLia Mills - University of the Sunshine Coast, Queensland, Thompson InstituteTaliah Prince - University of the Sunshine Coast, Queensland, Thompson InstituteMarcella J. Parker - University of the Sunshine Coast, Queensland, Thompson InstituteDaniel F. Hermens - University of the Sunshine Coast, Queensland, Thompson Institute
- Publication details
- Mental Illness, Vol.2025, pp.1-13
- Publisher
- John Wiley & Sons, Inc.
- Date published
- 2025
- DOI
- 10.1155/mij/4875116
- ISSN
- 2036-7465
- Copyright note
- Copyright © 2025 Michelle F. Kennedy et al. Mental Illness published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
- Data Availability
- The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
- Grant note
- This study was supported by the Australian Government (Australian Commonwealth Government’s “Prioritising Mental Health Initiative” [2018–2025]).
- Organisation Unit
- Centre for Human Factors and Systems Science; Thompson Institute
- Language
- English
- Record Identifier
- 991152475502621
- Output Type
- Journal article
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- Web Of Science research areas
- Psychiatry