Evidence map›Paper›PMID 35214672›Full record

ArticleVaccines2022

Behavioural Determinants of COVID-19-Vaccine Acceptance in Rural Areas of Six Lower- and Middle-Income Countries.

Thomas P Davis, Adugna Kebede Yimam, Md Abul Kalam, Asrat Dibaba Tolossa, Robert Kanwagi, Sarah Bauler, Loria Kulathungam, Heidi Larson

Abstract read
In one paragraph

Article in Vaccines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Who cites it

33 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

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

8 authors.

Thomas P DavisWorld Vision International, 1202 Geneva, Switzerland.ORCID 0000-0002-2567-3549
Adugna Kebede YimamWorld Vision International, 1202 Geneva, Switzerland.
Md Abul KalamBangladesh Country Office, Helen Keller International, Dhaka 1212, Bangladesh.ORCID 0000-0003-4236-8519
Asrat Dibaba TolossaWorld Vision Canada, Mississauga, ON L5T 2Y4, Canada.
Robert KanwagiWorld Vision International, 1202 Geneva, Switzerland.
Sarah BaulerWorld Vision International, 1202 Geneva, Switzerland.
Loria KulathungamWorld Vision International, 1202 Geneva, Switzerland.
Heidi LarsonVaccine Confidence Project, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.ORCID 0000-0002-8477-7583

Funding

Government of Canada CA-3-D00209900
6 · The paper itself

Abstract

Delayed acceptance or refusal of COVID-19 vaccines may increase and prolong the threat to global public health and the economy. Identifying behavioural determinants is considered a critical step in explaining and addressing the barriers of vaccine refusal. This study aimed to identify the behavioural determinants of COVID-19-vaccine acceptance and provide recommendations to design actionable interventions to increase uptake of the COVID-19 vaccine in six lower- and middle-income countries. Taking into consideration the health belief model and the theory of reasoned action, a barrier analysis approach was employed to examine twelve potential behavioural determinants of vaccine acceptance in Bangladesh, India, Myanmar, Kenya, the Democratic Republic of the Congo (DRC), and Tanzania. In all six countries, at least 45 interviews with those who intended to get the vaccine ("Acceptors") and another 45 or more interviews with those who did not ("Non-acceptors") were conducted, totalling 542 interviews. Data analysis was performed to find statistically significant (

Indexed as

acceptancebehaviourCOVID-19determinantshesitancyvaccine

Identifiers

PMID35214672
PMCPMC8875839

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.