Changes in Canadian Adolescent Well-Being since the COVID-19 Pandemic: The Role of Prior Child Maltreatment
Bibliographic record
Abstract
Adolescents may be particularly vulnerable to the negative impact of the coronavirus disease 2019 (COVID-19) pandemic, given their increased socialization needs during this developmental period. This prospective study examined the potential changes in adolescents’ well-being from before to during the pandemic, and the moderating role of a history of child maltreatment (CM), COVID-19-related distress, and gender among 1,802 adolescents (55.5% participants identified as boy, 42.2% as girl, and 1.5% as nonbinary; Mage 14.74 years). Another aim was to determine whether COVID-19-related distress mediated the relationship between CM and well-being. Results revealed that COVID-19-related distress was associated with lower well-being (i.e., higher levels of internalized and externalized behaviors, and lower levels of self-esteem and life satisfaction). Boys experienced a greater decrease in life satisfaction and self-esteem than girls. A history of CM had a moderation effect, with the pandemic having a lesser impact on the outcomes of adolescents with such a history. However, it was also associated with more COVID-19-related distress, which in turn was associated with lower levels of internalized and externalized behaviors, self-esteem, and life satisfaction. These unexpected results with regard to CM might indicate that the social restrictions during the pandemic could have had a relieving effect on adolescents with particular challenges associated with CM.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".