Supporting young people through the COVID-19 pandemic and beyond: a multi-site qualitative longitudinal study
Bibliographic record
Abstract
Abstract Background Throughout the COVID-19 pandemic, youth have experienced substantial stress due to abrupt changes in education, finances, and social life, compounding pre-existing stressors. With youth (ages 15–26) often at critical points in development, they are vulnerable to long-term mental health challenges brought on by pandemic trauma. Methods To identify youth experiences throughout the pandemic and examine changes over time, we conducted semi-structured interviews among n = 141 youth in two Canadian provinces (Ontario and British Columbia) and across the country of Ireland at three time points over the course of more than one year (August 2020-October 2021). We conducted a qualitative longitudinal analysis using an inductive content approach. Results Categories identified were (1) coping with hardship; (2) opportunities for growth; (3) adapting to new ways of accessing services; (4) mixed views on the pandemic: attitudes, behaviour, and perception of policy response; (5) navigating COVID-19 information; (6) transitioning to life after the pandemic; and (7) youth-led recommendations for government and service response. The findings also reveal trends in health and wellness in accordance with prolonged periods of lockdown, changes in weather, and return to normalcy after the availability of COVID-19 vaccines. Key recommendations from youth include incorporating youth voice into decision making, communicating public health information effectively to youth, enhancing service delivery post-pandemic, and planning for future pandemics. Conclusions These results provide insights into the extensive longitudinal impacts of the COVID-19 pandemic on young people across three geographical locations. Actively involving youth in decision making roles for future pandemics or public health emergencies is critical.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".