Changes in Student Mental Health and Adaptive Functioning During the COVID-19 Pandemic: Does Age Matter
Bibliographic record
Abstract
The impact of the COVID-19 pandemic on the lives of individuals across the globe has been significant. One segment of the Canadian population that may be particularly vulnerable to the impact of the pandemic are adolescents. Due to the developmental tasks and formational experiences that characterize the adolescent period, a growing number of studies have set out to investigate the potential effect that the pandemic may be having on youth, particularly as the pandemic effects pertain to their mental health. Almost a year and a half later, there are questions that still remain unanswered. As such, the current study sought to better understand adolescent mental health and adaptive functioning during this time and to determine whether there are age differences both cross-sectionally and across time. The current study followed a sample of adolescents from four metropolitan school divisions at two time points: September 2020 (N=2397) and December 2020 (N=1689). Participants completed the Behavior Intervention Monitoring Assessment System (BIMAS-2) measure, a 34-item universal screening measure of conduct problems, negative affect, and cognitive/attention difficulties as well as social and academic functioning. To better understand adolescents’ pandemic-related concerns, participants also completed an 11-item COVID-concern scale. Results indicated that, although mental health and COVID-related concerns are increasing and adaptive functioning is decreasing during the first four months of the school year, that adolescents’ experience during COVID-19 differs depending on their age. Older adolescents reported higher negative affect and cognition/attention difficulties while younger adolescents reported higher conduct and academic functioning. Moving forward, these results can help to inform development of programs and strategies for adolescents as they continue to navigate new experiences within the context of COVID-19.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".