Stressors and symptoms associated with a history of adverse childhood experiences among older adolescents and young adults during the COVID-19 pandemic in Manitoba, Canada
Bibliographic record
Abstract
INTRODUCTION: The COVID-19 pandemic has had major economic, social and psychological consequences for adolescents and young adults. It is unclear whether those with a history of adverse childhood experiences (ACEs) were particularly vulnerable. We examined whether a history of ACEs was associated with financial difficulties, lack of emotional support, feeling stressed/anxious, feeling down/depressed, increased alcohol and/or cannabis use and increased conflict with parents, siblings and/or intimate partners among 16- to 21-year-olds during the pandemic. METHODS: Data were collected in November and December 2020 from respondents aged 16 to 21 years (n = 664) participating in the longitudinal and intergenerational Well-being and Experiences Study (Wave 3) conducted in Manitoba, Canada. Age-stratified associations between ACEs and pandemic-related stressors/symptoms were examined with binary and multinomial logistic regression. RESULTS: A history of ACEs was associated with pandemic-related financial difficulties (adjusted relative risk ratio [aRRR] range: 2.44-7.55); lack of emotional support (aRRR range: 2.13-26.77); higher levels of feeling stressed/anxious and down/depressed (adjusted odds ratio [aOR] range: 1.78-5.05); increased alcohol and cannabis use (aOR range: 1.99-8.02); and increased relationship conflict (aOR range: 1.98-22.59). Fewer associations emerged for older adolescents and these were not to the same degree as for young adults. CONCLUSION: Adolescents and young adults with a history of ACEs reported increased odds of pandemic-related stressors and symptoms, and may need more resources and greater support compared to peers without an ACE history. Differences in results for adolescents and young adults suggest that interventions should be tailored to the needs of each age group.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".