Evidence map›Paper›PMID 39300382›Full record

ArticleBMC public health2024

Connect, collaborate and tailor: a model of community engagement through infographic design during the COVID-19 pandemic.

Elizabeth Vernon-Wilson, Moses Tetui, Mathew DeMarco, Kelly Grindrod, Nancy M Waite

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

5 authors.

Elizabeth Vernon-WilsonSchool of Pharmacy, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L3G1, Canada.
Moses TetuiSchool of Pharmacy, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L3G1, Canada.
Mathew DeMarcoSchool of Pharmacy, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L3G1, Canada.
Kelly GrindrodSchool of Pharmacy, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L3G1, Canada.
Nancy M WaiteSchool of Pharmacy, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L3G1, Canada. nancy.waite@uwaterloo.ca.

Funding

Public Health Agency of Canada 2122-HQ-000330
6 · The paper itself

Abstract

backgroundAcross the globe, racial and ethnic minorities have been disproportionately affected by COVID-19 with increased risk of infection and burden from disease. Vaccine hesitancy has contributed to variation in vaccine uptake and compromised population-based vaccination programs in many countries. Connect, Collaborate and Tailor (CCT) is a Public Health Agency of Canada funded project to make new connections between public health, healthcare professionals and underserved communities in order to create culturally adapted communication about COVID-19 vaccines. This paper describes the CCT process and outcomes as a community engagement model that identified information gaps and created tailored tools to address misinformation and improve vaccine acceptance.

methodsSemi-structured interviews with CCT participants were undertaken to evaluate the effectiveness of CCT in identifying and addressing topics of concern to underserved and ethnic minority communities. Interviews also explored CCT participants' experiences of collaboration through the development of new partnerships between ethnic minority communities, public health and academic researchers, and the evolution of co-operation sharing ideas and creating infographics. Thematic analysis was used to produce representative themes. The activities described were aligned with the levels of public engagement described in the IAP2 spectrum (International Association for Public Participation).

resultsAnalysis of interviews (n = 14) revealed that shared purpose and urgency in responding to the COVID-19 pandemic motivated co-operation among CCT participants. Acknowledgement of past harm, present health, and impact of social inequities on public service access was an essential first step in establishing trust. Creating safe spaces for open dialogue led to successful, iterative cycles of consultation and feedback between participants; a process that not only helped create tailored infographics but also deepened engagement and collaboration. Over time, the infographic material development was increasingly directed by community representatives' commentary on their groups' real-time needs and communication preferences. This feedback noticeably guided the choice, style, and presentation of infographic content while also directing dissemination strategies and vaccine confidence building activities.

conclusionsThe CCT process to create COVID-19 vaccine communication materials led to evolving co-operation between groups who had not routinely worked together before; strong community engagement was a key driver of change. Ensuring a respectful environment for open dialogue and visibly using feedback to create information products provided a foundation for building relationships. Finally, our data indicate participants sought reinforcement of close cooperative ties and continued investment in shared responsibility for community partnership-based public health.

Indexed as

COVID-19COVID-19 VaccinesCanadaCommunity ParticipationEthnic and Racial MinoritiesFemaleHumansInterviews as TopicMalePandemicsPublic HealthSARS-CoV-2Vaccination HesitancyCOVID-19 VaccinesCommunity engagementCOVID-19 pandemicPublic health communicationVaccinationVaccine confidenceVaccine hesitancyVaccine inequity

Identifiers

PMID39300382
PMCPMC11411729

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.