The inequitable psychological impacts of the COVID-19 pandemic on post-secondary students with preexisting health conditions: A longitudinal study
Bibliographic record
Abstract
Objective: Evidence suggests young adults in post-secondary school experienced increased distress during the COVID-19 pandemic, but students’ experiences likely varied. Effects may have also changed over time as students adapted. This study examined the mental health of students with and without preexisting health conditions at two points during the pandemic (winter 2020/2021 and spring/summer 2021). Methods: Participants (N = 1465) completed a baseline and follow-up questionnaire assessing their health history, depressive symptoms, anxiety symptoms, stress, and COVID-19-related worry and perceived vulnerability of severe infection. Results: At both time points, students with preexisting health conditions reported greater distress than those without preexisting health conditions. Stress increased from time 1 to time 2 for all students, and participants with preexisting health conditions significantly increased in their COVID-19 perceived vulnerability of severe infection over time. Conclusions: Findings highlight the need for additional and ongoing mental health supports for vulnerable students throughout the pandemic.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".