Canadian adolescents’ mental health and substance use during the COVID-19 pandemic: Associations with COVID-19 stressors.
Bibliographic record
Abstract
Objective: There have been significant concerns regarding the mental health impact of coronavirus disease 2019 , due to isolation, anxiety around the pandemic, and increased conflict in the home.The purpose of this study was to examine the rates of mental health problems and substance use, and to assess which COVID-19 related stressors were predictors of mental health and substance use in a large Canadian sample of adolescents, with comparisons across genders.Method: Participants (N = 809, Mage = 15.67,SD = 1.37) identified as a girl (56.2%), boy (38.7%), or trans/non-binary individual (TNBI; 5.1%) and were recruited via social media to complete an online survey.Results: A high proportion of adolescents met clinical cut-offs for depression (51%), anxiety (39%), and post-traumatic stress disorder (45%).Other mental health problems ranged from 9%-20%.Adolescents were mainly concerned with the health of family members and vulnerable populations, as well as the increased family stress at home during COVID-19.Rates of substance use were higher than expected, with over 50% of youth engaging in some form of substance use in the past 90 days, and almost 20% engaging in substance use at least once a week.TNBI and girls reported higher rates of mental health problems compared to boys.Family stress due to confinement and violence at home predicted higher rates of mental health, but not substance use problems.Conclusions: Increased rates of mental health problems and substance use necessitate targeted supports that encourage positive coping amidst the additional stresses of COVID-19.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".