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Record W4414006200 · doi:10.2196/74370

Changing Trends in Suicidal Ideation and Its Influencing Factors During the Transition From Quarantine to Post-Quarantine Among Chinese University Students During the COVID-19 Surge: Six-Wave Panel Study

2025· article· en· W4414006200 on OpenAlexvenueno aff
Lijing Li, Tingzhong Yang, Sihui Peng, Randall R. Cottrell

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
FundersBasic and Applied Basic Research Foundation of Guangdong ProvinceZhejiang UniversityJinan University
KeywordsQuarantineCoronavirus disease 2019 (COVID-19)Suicidal ideation2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PsychologyMedicineVirologyMedical emergencySuicide preventionPoison controlInternal medicineOutbreak

Abstract

fetched live from OpenAlex

Background: To mitigate the rapid spread of COVID-19, numerous countries have adopted lockdowns and quarantine measures. Despite their public health benefits, the effects of these measures on suicidal ideation have not been well documented. Objective: This study aims to examine the relationship among COVID-19 infection, perceived beliefs, uncertainty stress, and suicidal ideation during the transition from quarantine to post-quarantine periods amid China's COVID-19 surge. Methods: A prospective longitudinal observational design was used. Changing trends across the 6 time points were assessed using the Mann-Kendall test and the Cochran-Armitage test. A generalized estimating equation was used to analyze the associations between independent variables and suicidal ideation. Results: A total of 221 (96.5%) participants completed all 6 observation waves. The prevalence of suicidal ideation during the quarantine period was 16.7% (n=37), 14.5% (n=32), and 14.5% (n=32), while during the post-quarantine period, it was 13.8% (n=30), 10.9% (n=24), and 10.0% (n=22), respectively. A significant downward trend in suicidal ideation was observed. In contrast, perceived risk, perceived severity, and the number of new infections exhibited significant upward trends (z scores of 9.56, 7.13, and 3.69, respectively; P<.001, P<.001 and P=.002, respectively). However, uncertainty stress remained stable over time (z=0.71; P=.48). The generalized estimating equation indicated that perceived risk (β=0.5482; P<.001), perceived severity (β=0.0817; P=.007), and uncertainty stress (β=0.1776; P<.001) were positively associated with suicidal ideation. The number of new infections (β=0.0041; P=.49) was not significantly associated with suicidal ideation. Conclusions: This study found that suicidal ideation gradually declined following the lifting of quarantine measures. Perceived risk, perceived severity, and uncertainty stress, rather than numbers of infected cases, were significantly associated with suicidal ideation. These findings highlight the importance of addressing individuals' perceptions with real-world context when developing effective strategies to manage COVID-19 and future infectious disease outbreaks.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.081
GPT teacher head0.455
Teacher spread0.374 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes1
Has abstractyes

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