Do resilience and social support buffer Vietnamese college students’ mental health during the COVID-19 pandemic? A pilot study
Bibliographic record
Abstract
This pilot study aimed to investigate college students’ mental health during the peak of COVID-19 pandemic in Vietnam and its associated factors, such as resilience and perceived social support. A total of 101 college students completed an online survey on Qualtrics in the last quarter of 2021, when Vietnam was under social distancing measures. The results show that, at the peak of the pandemic, more than 80% of college students in the study reported at least mild depression, with very high prevalence of mild and moderate depression (39.44% and 30.99% respectively). Resilience and perceived social support were associated with each other, and both were found to buffer students’ mental health, yet resilience became an insignificant predictor when other covariates were added to the linear regression model. This pilot study prepares for the development of the larger study to develop resilience training programme for college students to cope with emergency situations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".