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Record W6891806845 · doi:10.48336/vs0r-4z04

COVID-19 vaccine willingness and long COVID predictors among Chinese residents in Canada

2025· article· en· W6891806845 on OpenAlexaffabout

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2025
Typearticle
Languageen
FieldEngineering
TopicAutonomous Vehicle Technology and Safety
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVaccinationPandemicLogistic regressionPublic healthCoronavirus disease 2019 (COVID-19)China

Abstract

fetched live from OpenAlex

Purpose This thesis investigated two critical aspects of the COVID-19 pandemic among Chinese residents in Canada: vaccine willingness and long COVID prevalence. Vaccination has been identified as a critical approach to controlling the COVID-19 pandemic. Long COVID, characterized by persistent COVID-19 symptoms beyond the initial infection, emerged as a public health concern worldwide. This study aimed to assess the COVID-19 vaccine willingness and the associated factors among Chinese residents in Canada during the early stage of the pandemic. Moreover, this study investigated the frequency, main symptoms, and the associated risk factors of long COVID among Chinese residents in Canada. Methods Two surveys were conducted: the first one, at the time of the initial distribution of the COVID-19 vaccine in Canada in early 2021, examined diverse aspects of COVID-19 vaccine willingness such as sociodemographic information, beliefs, perceptions, experiences, and emotions; the second survey, done in early 2023, focused on long COVID, defined as symptoms persisting beyond 12 weeks’ post-infection, to explore related experiences, sociodemographic factors, psychological resilience, clinical status, and vaccination history. Both surveys were cross-sectional and were administered among Chinese residents aged over 16 in Canada and who have lived in Canada for at least six months. Utilizing SAS software version 9.4, multiple variable logistic regression iii analyses were employed to investigate the determinants influencing vaccine willingness and examine the risk factors associated with long COVID, considering P-value<0.05. Results Among the 970 eligible respondents of the former study, about 40% expressed reluctance or uncertainty about COVID-19 vaccination, citing safety concerns. Men exhibited twice the willingness compared to women (OR 2.09, 95% CI 1.43-3.04, p=0.0001). A high level of education also influenced acceptance (OR 1.85, 95% CI 1.33-2.59, P=0.0003). Healthcare workers were about three times more likely to accept vaccination (OR 2.94, 95% CI 1.42-6.07, p=0.0035). Also, Blood group B individuals were more willing to receive the COVID-19 vaccine than those with other blood types (OR 2.25, 95% CI 1.23-4.13, p=0.0086). Those believing in vaccine efficacy (OR 3.43, 95% CI 1.57-7.47, p=0.0019) and who received influenza vaccination since October 2020 (OR 2.79, 95% CI 2.01-3.89, p<0.0001) were more inclined to accept COVID-19 vaccination. In the later study of 488 eligible participants for long COVID, 24.1% reported symptoms. Fatigue (46.3%), memory problems (42.9%), and anxiety/depression (30.2%) were common. More than 70% had underlying diseases, with allergies most prevalent (31.8%). 96.7% were fully vaccinated. Women were 2.24 times more likely to report long COVID (95% CI: 1.09-4.57; P=0.026). Worsening health status pre-COVID-19 increased the odds of long COVID (OR= 4.29; 95% CI: 2.05-6.92; P=0.008). Long COVID was more likely in those with reported vaccine side effects (OR=2.17; 95% CI: 1.14-4.11; P=0.017). Conclusions Findings from this research highlighted the critical influence of factors such as vaccine safety concerns, trust in health authorities, and beliefs regarding vaccine efficacy on COVID-19 vaccine willingness. These insights emphasized the necessity for tailored public health messaging and interventions to address the specific concerns of diverse communities and enhance vaccine uptake. Enhancing vaccine uptake requires providing adequate information and tailored public health interventions to address safety concerns. Additionally, this study revealed a notable prevalence of long COVID among Chinese Canadians, particularly affecting women and those with poor health. This underscored the heightened healthcare needs of these groups to effectively prevent long COVID. Further research into the relationship between long COVID and previous vaccine side effects is necessary to effectively inform future public health strategies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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