Association Between Hair Cortisol and Psychopathology in Children With a Chronic Physical Illness
Bibliographic record
Abstract
Children with a chronic physical illness (CPI) experience significant stress and are at a greater risk of psychopathology. However, little is known about chronic stress and its relationship with psychopathology in this population. Over the last decade, hair cortisol concentration (HCC) has emerged as a viable biomarker of chronic stress. This study identified trajectories of HCC in children with a CPI and examined their associations with psychopathology. The study included data from 244 children enroled in the Multimorbidity in Children and Youth across the Life-course (MY LIFE) study. MY LIFE is a prospective study of children aged 2-16 years with a CPI recruited from outpatient clinics at a Canadian paediatric hospital and followed for 48 months. Children provided 3-cm hair samples for cortisol assay and parents reported psychopathology symptoms using the Emotional Behavioural Scales. We identified three HCC trajectories: (1) Hypersecretion (n = 166, 68.03%); (2) Hyposecretion (n = 21, 8.61%); and (3) Hyper-to-Hypo (n = 57, 23.36%). When adjusting for sociodemographic and clinical characteristics, children in the Hyper-to-Hypo class had lower internalising (β = -3.17, p = 0.005) and externalising (β = -2.27, p = 0.007) psychopathology symptoms compared to the Hypersecretion class. This study provides evidence that children with a CPI follow distinct HCC trajectories. Children who followed a decreasing trajectory exhibited lower psychopathology symptoms compared to children who followed a consistently elevated trajectory, indicating that chronically high cortisol levels may contribute to the development of psychopathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".