Impact of the COVID-19 pandemic on the experience and mental health of university students studying in Canada and the UK: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVES: To explore the impact of the COVID-19 pandemic on the experiences and mental health of university students. DESIGN: A cross-sectional study consisting of an electronic survey about students' experiences and concerns during the pandemic and the associated impact. In addition to the quantitative analysis, free-text responses were extracted and analysed using a framework technique. SETTING: Queen's University in Canada and the University of Oxford in the UK. PARTICIPANTS: Undergraduate students at Queen's University and first-year undergraduate students at the University of Oxford were invited to complete the COVID-19 supplement survey. This study included data from 3013 Queen's students as the primary focus and 339 Oxford students as a secondary comparison. RESULTS: p<0.01) than males. A similar trend was seen among Oxford students. Students' concerns were wide ranging including those related to their learning experience, finances and future academic and career prospects. 78.9% of Queen's students and 50.4% of first-year Oxford students reported worries about the long-term impact on their academic and job prospects. A sizeable proportion of students also reported that the pandemic negatively impacted their plans to continue at university (29.4% of Queen's, 14.2% of Oxford) and disrupted activities important to their mental well-being. Key themes identified in the qualitative component included the negative impacts of social isolation, challenging academic changes and disruption to support services and means of coping. CONCLUSIONS: Overall, findings underscore the importance of addressing areas of student concern and the aspects of student life negatively impacted by the pandemic in order to maintain student well-being and support a successful university experience.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".