Gender-Based Susceptibility to Mental Health Issues in Adolescents During the COVID-19 Pandemic: Descriptive Study
Bibliographic record
Abstract
Background: Adolescence, the transitional phase between childhood and adulthood, is a stressful, fragile, and critical period. While the COVID-19 pandemic introduced numerous stressors affecting the mental health of all age groups, adolescents are particularly vulnerable. However, there is limited research focusing on the impact of COVID-19 on this population. Objective: This study aimed to explore the impact of COVID-19, coping strategies, depression, anxiety, and post-traumatic stress disorder (PTSD) in adolescents during the pandemic. Methods: This web-based cross-sectional survey study included 217 adolescents in Southern California, USA, between 2020 and 2021. Self-report measures include demographic questionnaires, COVID-19 impact, types of coping strategies used during COVID-19, depression, anxiety, and PTSD analyses. The χ2 tests were used for depression and anxiety, and ANOVA was used for PTSD analysis. Results: Female gender was identified as a risk factor for depression, anxiety, and PTSD. Approximately 24.2% (52/217) of participants had a family member or someone close who was infected with COVID-19 during the pandemic, which was a significant factor for both anxiety and PTSD (P<.05). More than half of all the participants (56.8%, 109/217) were Asian Americans, but there was no significant difference in depression, anxiety and PTSD among different racial or ethnic groups (P>.05). About a quarter of the participants reported experiencing depression (49/217, 25.5%) or anxiety (46/217, 24.0%). The mean (SD) score for PTSD was 8.08 (5.70). Social media and the internet were the most frequently used coping strategies, with 67.3% of participants using each. Conclusions: Considering our findings, prevention programs focusing on mental health, including routine screening, should be implemented at community level for adolescents. School programs fostering healthy social interactions and education on coping strategies should also be implemented for both families and adolescents.
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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 | 0.001 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".