COVID-19-Related Posttraumatic Stress in U.S. and Canadian Youth in the First Year of the Pandemic
Bibliographic record
Abstract
Objective Disasters and public health emergencies raise child/adolescent risk for posttraumatic stress (PTS). This study examined prospective predictors of COVID-related PTS in a large sample of U.S. and Canadian youth. Demographics, pre-pandemic contextual factors, baseline clinical factors, and pandemic experiences were examined. We hypothesized pandemic proximity/exposure and pandemic-related financial hardship in the first seven months, as well as baseline resource insecurity, internalizing symptoms, and female gender, would predict subsequent COVID-related PTS.Method A prospective two-wave study of English- or Spanish-speaking youth ages 5–17 years (N = 1,413; 46.2% female; 33.4% racial/ethnic minority youth), and their caregivers, was conducted. The sample was recruited via crowdsourcing methods (e.g. existing community samples, advertisements, online recruitment). Data were collected via online caregiver-report surveys. Recruitment began 3/20/2020 (<10 days after pandemic declaration); follow-up assessments were collected M = 6.56 months later (7 months into pandemic).Results Maximum likelihood estimation linear regression indicated baseline internalizing problems, pre-pandemic food insecurity, and COVID-19-related financial hardship predicted youth PTS at follow-up, whereas COVID-19 proximity/exposure and youth gender, age, and race/ethnicity did not. Youth with baseline internalizing problems had eight times the odds of developing probable PTSD than youth without baseline internalizing problems. The effect of COVID-19-related financial hardship on PTS was particularly high among youth who went into the pandemic with food insecurity.Conclusion The financial toll the pandemic took on a child’s family and whether there were pre-pandemic mental health or resource-related vulnerabilities may have been more determinant of individual youth PTS than the child’s degree of direct COVID-19 proximity or family exposure.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 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".