Factors Associated with COVID-19 Vaccine Hesitancy among Visible Minority Groups from a Global Context: A Scoping Review
2. Materials and Methods
- We identified key concepts underlying our research question.
- We identified search terms related to each key concept.
- With the help of a public health librarian, we
- identified databases (Medline, CINAHL, and PubMed) from which to select literature; and
- created and implemented a search strategy for each database to generate a list of possible literature for review.
- Two authors independently implemented the search strategies and identified literature from the three databases. They identified additional search terms from the literature and re-ran the searches. This was repeated until no new search terms were added to the search strategy.
- These two authors independently implemented the final search strategy for each database to generate a list of possible articles for review. They then applied the filters: journal articles, full-text availability, papers published in 2020 and onwards, English language, and human participants, to create a reduced list of articles from each database.
- A single reviewer transferred the reduced lists obtained in Step 5 to Zotero and compiled one list of articles for review while removing any duplicate articles.
- Our scoping review process deviated from the Arksey and O’Malley strategy at this point because we hypothesized that findings regarding visible minorities and their respective reasons for vaccine hesitancy may not be found within the titles or abstracts of research papers. Therefore, to ensure that all relevant articles were included in our final list, we skipped title and abstract screening, and two reviewers performed full-text reviews applying the inclusion/exclusion criteria independently (Table 1) to create a final list of articles for data extraction. During this full-text review process, two reviewers discussed and resolved any disagreement that arose in terms of whether to include an article for data extraction. For when the two reviewers disagreed on whether or not to include an article, a third reviewer reviewed the article and decided on whether or not to include it. The final list of articles for data extraction was collated. The levels of agreement between both reviewers were calculated using the Cohen’s Kappa statistic.
- While performing full-text reviews, the reviewers extracted themes of vaccine hesitancy in visible minority populations and stored them in an excel spreadsheet. Figure 1 depicts the steps taken to arrive at the final list of relevant articles for our scoping review.
- ADJ3: is a syntax used in a proximity search used in the Medline database—it is also known as (ADJ = adjacency). ADJ3 is the same as searching by having up to three words next to each other in any order. One needs to separate their search terms with ADJ3 in between when using this adjacency operator.
- N3: is a syntax used in the CINAHL database, (N = near). N3 specifies there are three words between each search term while searching in no particular order.
- AND, OR, NOT: are Boolean operators used in the PubMed database to retrieve all search terms results, retrieve results with at least search term or exclude search terms retrieved from the search.
- Thematic qualitative analysis: Two reviewers independently grouped the extracted themes from the final list of articles that arose in step 8, into overarching factors. The level of agreement between both reviewers was calculated using the Cohen’s Kappa statistic.
- Principal component analysis (PCA): Using the themes identified by both reviewers in step 8, a PCA with Promax oblique rotation was used to group the themes into overarching factors influencing COVID-19 vaccine hesitancy. A parallel analysis (with 1000 Monte Carlo simulation repetitions) was used to select the initial list of overarching factors. Themes that had a correlation of 0.6 or more or −0.6 or less with a factor were used to determine the name of the factor. An author different from the two who did the qualitative thematic analysis named the factors identified through the PCA.
- Word cloud: To qualitatively complement the themes extracted during data extraction, a word cloud was created for 100 of the most frequently occurring words in the titles and abstracts of the final set of articles.
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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|Peer-reviewed journal articles||Non-peer reviewed articles/grey literature|
|Articles related to COVID-19 and visible minorities||Articles studying diseases other than COVID-19 and non-visible minorities|
|Papers written in English language||Papers written in languages other than English language|
|Papers published in 2020 and onwards||Papers published prior to 2020|
|Papers involving human participants||Papers involving non-human participants|
|Articles discussing reasons for COVID-19 vaccine hesitancy||Articles not discussing reasons but rather stating statistics related to COVID-19 vaccine hesitancy|
|Articles studying COVID-19 vaccine hesitancy in clinical/vaccine trial participation|
|Concept 1 (Vaccine): (Combine Terms below with OR)||ADJ3 *||Concept 2 (Hesitancy): (Combine Terms below with OR)||AND||Concept 3 (Visible Minority): (Combine Terms below with OR)||AND||Concept 4 (COVID-19): (Combine Terms below with OR)|
|Vaccin * Inoculat * Immuniz *|
|Visible minorit *|
(Race OR racial OR ethnic) ADJ3 (disparit * OR inequality * OR inequit * OR segregate * OR minorit *)
(Vulnerab * ADJ3 population *)
(South ADJ3 Asian *)
(Black OR Blacks OR African ADJ3 American *)
(Latin American * OR Latino * OR Hispanic *)
(Southeast ADJ3 Asian *)
(West ADJ3 Asian *)
Indigenous Native *
First Nation *
SARS CoV 2
Coronavirus disease 2019
Novel corona virus
2019 novel CoV
SARS coronavirus 2
Sars coronavirus 2
SARS like coronavirus
Severe Acute Respiratory Syndrome Coronavirus 2
Severe acture respiratory syndrome coronavirus 2
wuhan OR hubei OR huanan OR china OR chinese) AND (severe acute respiratory OR pneumonia *) AND outbreak *)
|Safety and effectiveness of vaccine||88|
|Frequency of Injections/Fear of Needles||4|
|Lack of Trust||39|
|Underrepresentation in Medical/Clinical Research||10|
|Short duration of Vaccine Development||14|
|Cost of Vaccine||12|
|Place of Manufacturing||8|
|Novelty of Vaccine||7|
|Duration of Immunity||4|
|Type of media Information||17|
|Knowledge and acceptance||18|
|General Vaccine Beliefs||7|
|Past Vaccine Compliance||3|
|Perceived risk of COVID-19||17|
|Perceived risk of acquiring COVID-19||13|
|Opinion of HCP||4|
|Number of people Vaccinated||1|
|Factor (Eigenvalue)||Themes (Loading)|
|Perceived benefit (4.584)||Occupation (0.688)|
|Collective benefit (0.916)|
|Personal benefit (0.916)|
|Safety and effectiveness of vaccine (3.532)||Side effects (0.714)|
|Socioeconomic characteristics (2.863)||Income (0.834)|
|Having children (0.767)|
|Convenience associated with getting the vaccine (2.525)||Frequency of injections/schedule (0.656)|
|Number of people vaccinated (0.855)|
|Knowledge and acceptance of vaccine (2.099)||Education (0.622)|
|Past vaccine compliance (0.699)|
|General vaccine beliefs (0.665)|
|Mistrust (2.002)||Lack of trust (0.787)|
|Source of information about vaccine (1.855)||Type of media information|
|External factors (1.706)||Duration of immunity (0.623)|
|Opinion of HCP (0.643)|
|Pre-existing medical conditions (0.619)|
|Vaccine coverage (0.794)|
|Factors from Thematic Qualitative Analysis||Factors from Principal Component Analysis||Factors in Agreement|
|Perceived benefit||Perceived benefit||Perceived benefit|
|Safety and effectiveness of vaccine||Safety and effectiveness of vaccine||Safety and effectiveness of vaccine|
|Socioeconomic characteristics||Socioeconomic characteristics||Socioeconomic characteristics|
|Information circulation||Source of information about vaccine||Source of information about vaccine|
|Knowledge and acceptance||Knowledge and acceptance of vaccine||Knowledge and acceptance of vaccine|
|Vaccine development||Convenience associated with getting the vaccine|
|Perceived risk of COVID-19||External factors|
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Ochieng, C.; Anand, S.; Mutwiri, G.; Szafron, M.; Alphonsus, K. Factors Associated with COVID-19 Vaccine Hesitancy among Visible Minority Groups from a Global Context: A Scoping Review. Vaccines 2021, 9, 1445. https://doi.org/10.3390/vaccines9121445
Ochieng C, Anand S, Mutwiri G, Szafron M, Alphonsus K. Factors Associated with COVID-19 Vaccine Hesitancy among Visible Minority Groups from a Global Context: A Scoping Review. Vaccines. 2021; 9(12):1445. https://doi.org/10.3390/vaccines9121445Chicago/Turabian Style
Ochieng, Candy, Sabrita Anand, George Mutwiri, Michael Szafron, and Khrisha Alphonsus. 2021. "Factors Associated with COVID-19 Vaccine Hesitancy among Visible Minority Groups from a Global Context: A Scoping Review" Vaccines 9, no. 12: 1445. https://doi.org/10.3390/vaccines9121445