Evidence map›Paper›PMID 40017953›Full record

ArticleBMJ public health2025

Applying a diffusion of innovations framework to characterise diffusion groups and more effectively reach late adopters: a cross-sectional study on COVID-19 vaccinations in Canada in late 2021.

Ally Memedovich, Brian Steele, Taylor Orr, Aidan Hollis, Charleen Salmon, Jia Hu, Kate Zinszer, Tyler Williamson, Reed Beall

Abstract read
In one paragraph

Article in BMJ public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

9 authors.

Ally MemedovichCommunity Health Sciences, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada.ORCID 0000-0003-3193-8088
Brian SteeleCommunity Health Sciences, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada.
Taylor OrrCommunity Health Sciences, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada.
Aidan HollisDepartment of Economics, University of Calgary, Calgary, Alberta, Canada.
Charleen SalmonCommunity Health Sciences, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada.
Jia HuCommunity Health Sciences, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada.
Kate ZinszerDepartment of Social and Preventive Medicine, Universite de Montreal Institut de recherche en sante publique, Montreal, Quebec, Canada.
Tyler WilliamsonCommunity Health Sciences, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada.
Reed BeallCommunity Health Sciences, University of Calgary Cumming School of Medicine, Calgary, Alberta, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Rogers' diffusion of innovation theory suggests innovations are adopted in stages by different groups (innovators/early adopters, early majority, late majority and late adopters). In healthcare, this could mean that there is the potential to worsen health disparities as later groups tend to also face more social and structural barriers. Determining the unique sociodemographic characteristics, beliefs and attitudes of those in each diffusion category could be useful for theorising how to reach later groups more effectively. Methods: Using a cross-sectional survey among Canadian adults in late 2021, we assigned respondents to diffusion groups based on when they received their first dose, relative to others within their age group in accordance with Rogers' model (ie, cut points: 16%, 50%, 84% with 100% being all those vaccinated within the age group). Participants answered questions about their COVID-19 vaccinations and questions related to their motivations, beliefs, values and attitudes towards COVID-19. A multinomial logistic regression model assessed the likelihood of participants being associated with each diffusion category (with the significance level set at p<0.05). Results: The final sample included 2131 respondents. Late adopters were significantly more likely to identify as non-white, live in rural locations and receive vaccinations at pharmacies. Innovators and early adopters were significantly more likely to get vaccinated in settings other than pharmacies or community centres. Conclusion: A diffusion group-based analysis brought insight into how vaccination strategies could be tailored to reach each diffusion group sooner, particularly late adopters who encounter more barriers.

Indexed as

Communicable Disease ControlCOVID-19Public Health

Identifiers

PMID40017953
PMCPMC11812860

What OpenQuestion holds

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LicenceCC BY-NC
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.