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Record W3205138787 · doi:10.2196/31707

Multilevel Determinants of COVID-19 Vaccine Uptake Among South Asian Ethnic Minorities in Hong Kong: Cross-sectional Web-Based Survey

2021· article· en· W3205138787 on OpenAlexvenueno aff
Akansha Singh, Angel Hor Yan Lai, Jingxuan Wang, Saba Asim, Paul Chan, Zixin Wang, Eng‐Kiong Yeoh

Bibliographic record

VenueJMIR Public Health and Surveillance · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicVaccine Coverage and Hesitancy
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupCross-sectional studyNepaliVaccinationMedicineDemographyLogistic regressionPandemicGeographyCoronavirus disease 2019 (COVID-19)DiseasePolitical scienceSociologyInfectious disease (medical specialty)Immunology

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic continues to have a disproportionate effect on ethnic minorities. Across countries, greater vaccine hesitancy has been observed among ethnic minorities. After excluding foreign domestic helpers, South Asians make up the largest proportion of ethnic minorities in Hong Kong. It is necessary to plan for COVID-19 vaccination promotional strategies that cater to the unique needs of South Asians in Hong Kong. OBJECTIVE: This study investigated the prevalence of COVID-19 vaccine uptake among a sample of South Asians in Hong Kong. We examined the effects of sociodemographic data and factors at individual level (perceptions), interpersonal level (information exposure on social media), and sociostructural level (cultural) based on the socioecological model. METHODS: A cross-sectional web-based survey was conducted on May 1-31, 2021. Participants were South Asian people aged 18 years or older living in Hong Kong; able to comprehend English, Hindi, Nepali, or Urdu; and having access to a smartphone. Three community-based organizations providing services to South Asians in Hong Kong facilitated the data collection. The staff of the community-based organizations posted the study information in WhatsApp groups involving South Asian clients and invited them to participate in a web-based survey. Logistic regression models were fit for data analysis. RESULTS: Among 245 participants, 81 (33.1%) had taken at least one dose of the COVID-19 vaccine (one dose, 62/245, 25.2%; and both doses, 19/245, 7.9%). After adjusting for significant background characteristics, cultural and religious reasons for COVID-19 vaccine hesitancy were associated with lower COVID-19 vaccine uptake (adjusted odds ratio [AOR] 0.83, 95% CI 0.71-0.97; P=.02). At the individual level, having more positive attitudes toward COVID-19 vaccination (AOR 1.31, 95% CI 1.10-1.55; P=.002), perceived support from significant others (AOR 1.29, 95% CI 1.03-1.60; P=.03), and perceived higher behavioral control to receive COVID-19 vaccination (AOR 2.63, 95% CI 1.65-4.19; P<.001) were associated with higher COVID-19 vaccine uptake, while a negative association was found between negative attitudes and the dependent variable (AOR 0.73, 95% CI 0.62-0.85; P<.001). Knowing more peers who had taken the COVID-19 vaccine was also associated with higher uptake (AOR 1.39, 95% CI 1.11-1.74; P=.01). At the interpersonal level, higher exposure to information about deaths and other serious conditions caused by COVID-19 vaccination was associated with lower uptake (AOR 0.54, 95% CI 0.33-0.86; P=.01). CONCLUSIONS: In this study, one-third (81/245) of our participants received at least one dose of the COVID-19 vaccine. Cultural or religious reasons, perceptions, information exposure on social media, and influence of peers were found to be the determinants of COVID-19 vaccine uptake among South Asians. Future programs should engage community groups, champions, and faith leaders, and develop culturally competent interventions.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.302
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.097
GPT teacher head0.391
Teacher spread0.294 · 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.

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

Citations43
Published2021
Admission routes1
Has abstractyes

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