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Record W4387503164 · doi:10.1080/02185385.2023.2269125

Do resilience and social support buffer Vietnamese college students’ mental health during the COVID-19 pandemic? A pilot study

2023· article· en· W4387503164 on OpenAlexaboutno aff
Trang Nguyen

Bibliographic record

VenueAsia Pacific Journal of Social Work and Development · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthVietnamesePsychological resilienceBachelorPsychologySocial supportPandemicMedical educationCoronavirus disease 2019 (COVID-19)Social distanceSocial workSocial isolationQuarter (Canadian coin)GerontologyMedicinePolitical scienceSocial psychologyPsychiatryGeography

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.082
GPT teacher head0.414
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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