Evidence map›Paper›PMID 42056256›Full record

ArticleCommunications medicine2026

Institutional trust and vaccination delay as key metrics for vaccination rollout success.

Cyrus Lap Kwan Leung, Kin-Kit Li, Arthur Tang, Wilson Wai San Tam, Samuel Yeung Shan Wong, Wan In Wei, Kin On Kwok

Abstract read
In one paragraph

Article in Communications medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Cyrus Lap Kwan LeungJC School of Public Health and Primary Care, The Chinese University of Hong Kong, New Territories, Hong Kong.ORCID http://orcid.org/0000-0003-1998-5316
Kin-Kit LiDepartment of Social and Behavioural Sciences, City University of Hong Kong, Kowloon, Hong Kong.
Arthur TangSchool of Science, Engineering and Technology, RMIT University, Ho Chi Minh City, Vietnam.
Wilson Wai San TamAlice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Samuel Yeung Shan WongJC School of Public Health and Primary Care, The Chinese University of Hong Kong, New Territories, Hong Kong.
Wan In WeiJC School of Public Health and Primary Care, The Chinese University of Hong Kong, New Territories, Hong Kong. vivian1628@cuhk.edu.hk.ORCID http://orcid.org/0000-0001-8083-3528
Kin On KwokJC School of Public Health and Primary Care, The Chinese University of Hong Kong, New Territories, Hong Kong. kkokwok@cuhk.edu.hk.ORCID http://orcid.org/0000-0002-2804-5433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTimely vaccination effectively reduced COVID-19 hospitalizations and mortality, yet vaccination hesitancy undermined this benefit. Understanding the factors contributing to hesitancy is critical for improving future pandemic control by identifying barriers to timely vaccination. This paper operationalizes hesitancy in terms of vaccine delay-a key public health metric that reflects changing vaccination policies and infection status, factors that can alter individuals' eligibility, and real-world complexities like infections.

methodUsing longitudinal data from the earliest stage of the pandemic in Hong Kong, we examined how institutional trust and the 5C constructs (confidence, complacency, constraints, calculation, and collective responsibility) influenced both vaccination intention and timing.

resultsOur results show that only 34.89% and 42.97% of vaccinated participants received their first and third doses within 100 days of eligibility, respectively, despite rising uptake prior to government mandates. Confidence and vaccination intention are key predictors of delay, and higher institutional trust boosts both confidence and collective responsibility, thereby enhancing intention and reducing delays.

conclusionsThese findings underscore the importance of building institutional trust and public confidence to minimize vaccine delay, particularly among vulnerable populations. Ultimately, incorporating vaccine delay as a key metric into public health strategies can guide more effective interventions and strengthen pandemic preparedness.

Identifiers

PMID42056256
PMCPMC13333957

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.