It’s all in the hair: Association between changes in hair cortisol concentrations in reaction to the COVID-19 pandemic and post-traumatic stress symptoms in children over time
Bibliographic record
Abstract
After exposure to a stressful/traumatic event, some individuals will develop post-traumatic stress symptoms (PTSS). In adults, low cortisol levels appear to be a risk factor for the development of PTSS. Indeed, both lower pre-trauma cortisol levels and low cortisol levels in the aftermath of a traumatic event have been associated with greater PTSS. In contrast, studies conducted in children showed that elevated cortisol levels shortly after trauma exposure are associated with more severe post-traumatic stress symptomatology. The few studies that have examined how pre-trauma cortisol levels predict PTSS in children have found no effect. Given that a pandemic can induce PTSS in certain individuals, we investigated whether cortisol secretion prior to and in the early stages of the COVID-19 pandemic in Quebec (Canada) predicted PTSS in children. In June 2020, we collected a hair sample from 71 children (8-15 y/o, M = 11.65; 54.93% girls) without a history of psychopathology or exposure to previous traumatic events. Hair samples allowed us to derive cumulative measures of cortisol levels for the months prior to (from mid-December 2019 to mid-March 2020) and at the beginning of the pandemic (from mid-March 2020 to mid-June 2020). PTSS were assessed every 3 months between June 2020 (T1) and March 2021 (T4). The results showed that a greater increase in hair cortisol at the beginning of the pandemic predicted less PTSS at T1, with an increase in these symptoms over time. This study highlights the utility of using hair cortisol during future chronic stressful events to better understand its association with the evolution of distress.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".