The Impact of the COVID-19 Pandemic on Mental Health of Teens
Bibliographic record
Abstract
The stress, fear, and uncertainty created by the COVID-19 pandemic can wear anyone down, but teens may have an especially tough time coping emotionally. In this study, we aim to highlight the impact of this pandemic on the mental health of teens, who account for almost 50% of the population in Pakistan. We conducted a descriptive cross-sectional study in Islamabad, Pakistan. Due to the COVID-19 lockdown in Pakistan, we collected data through a validated online questionnaire from the students at private schools enrolled only in Cambridge Assessment International Examination (CAIE) system. The study included a total of 289 students, comprised of 116 males and 173 females within the age range of 13–19 years. Our study showed that the prevalence of signs of mental illness was quite high amongst teenagers, with slightly higher prevalence in female respondents. These signs included feeling socially disconnected, frequent mood swings, constant worry, self-dissatisfaction, change in eating habits, and change in sleep cycle. Since there is evidence that significant burden of mental illnesses originates at a young age, we assert that close attention to mental health of young people in quarantine is warranted to avoid any long-term consequences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".