Adversity and Risk of Adolescent Mental Health Admission During COVID‐19
Bibliographic record
Abstract
Adolescent mental health was a major problem during the COVID-19 pandemic. We determined the extent to which adolescents with a history of adversity were at risk of mental health hospitalization during the pandemic. We conducted a longitudinal cohort study of 303,378 adolescents from Quebec, Canada, who were age 10-14 years at the start of the pandemic. The main exposure was early life adversity, which included childhood adversity as well as maternal history of adversity or mental illness. The main outcome was hospitalization for a psychiatric disorder, substance use disorder, or suicide attempt between March 2020 and March 2023. We used Cox regression models to compute adjusted hazard ratios (HR) and 95% confidence intervals (CI) for the association of adversity with risk of mental health admission during the pandemic. Adolescents with a history of childhood adversity were 6-9 times more likely to be admitted for a psychiatric disorder (HR 5.79, 95% CI 4.82-6.95), substance use disorder (HR 8.89, 95% CI 6.36-12.43), or suicide attempt (HR 6.93, 95% CI 4.85-9.90) during the pandemic, compared with other adolescents. Adolescents whose mothers experienced adversity or whose mothers had mental illness were 2-6 times more likely to be admitted for mental disorders. Associations were present for both sexes, although adversity was particularly associated with substance use disorders among males. Having a history of childhood or maternal adversity was a strong risk factor for mental health hospitalization among adolescents during the pandemic.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".