Hair Cortisol and Health-Related Quality of Life in Children with Mental Disorder
Bibliographic record
Abstract
INTRODUCTION: Children living with mental disorder are at risk for lower health-related quality of life (HRQoL) compared to their peers. While evidence suggests that cortisol dysregulation is implicated in the onset of mental disorder, the extent to which cortisol is associated with HRQoL is largely unknown. Further, it remains unknown how comorbid physical illness may alter this relationship. This study examined whether the presence of a comorbid physical illness moderated the association between hair cortisol concentration (HCC) and HRQoL among children with mental disorder. METHODS: One-hundred children (4-17 years) receiving care from a pediatric hospital were recruited. The Mini International Neuropsychiatric Interview was used to measure mental disorder and the KIDSCREEN-27 to assess HRQoL. Cortisol extracted from children's hair was assayed using high-sensitivity ELISA. Multiple regression analyses tested the association between HCC and HRQoL. RESULTS: Presence of a physical illness was found to moderate the relationship between HCC and HRQoL in the domain of peers and social support [comorbidity: β = -0.57 (-0.97, -0.17); no comorbidity: β = 0.22 (-0.11, 0.55)]. CONCLUSION: The association between HCC and HRQoL in children with mental disorder is moderated by the presence of a physical illness, such that in children with comorbid physical and mental disorder, elevated HCC is associated with lower HRQoL. Approaches that reduce stress in these children may help promote optimal well-being. More research investigating physiological stress and psychosocial outcomes in children with mental disorder, particularly those with comorbid physical illness, is needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".