Adverse Childhood Experiences and COVID-19 Stress on Changes in Mental Health among Young Adults
Bibliographic record
Abstract
The COVID-19 pandemic has been linked to poor mental health outcomes and may be particularly damaging for young adults who may be more affected by governmental pandemic responses such as mandatory school and work closures, online schooling, and social isolation. Exposure to Adverse Childhood Experiences (ACEs) has also been shown to have a significant impact on mental health among young adults. This prospective study examined whether young adults with higher ACE profiles were more vulnerable to COVID-19 stressors. Using pre-COVID-19 data from the Niagara Longitudinal Heart Study and a follow-up online survey during COVID-19, we examined 171 young adults and found that high COVID-19-related stress, especially emotional and relationship stress, led to a greater reduction in mental health among young adults with higher levels of ACEs. Findings indicate that young adults with high ACE profiles may benefit from resources and intervention programs directed at mental health in times of crisis, such as the COVID-19 pandemic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".