| Literature DB >> 36171961 |
Hyunjin Seo1, Yuchen Liu2, Muhammad Ittefaq3, Fatemeh Shayesteh1, Ursula Kamanga4, Annalise Baines1.
Abstract
Objective: This study examines how those who were born outside the United States and migrated to the country in the past decade used social media and other online sites to deal with uncertainties around the coronavirus disease 2019 pandemic. In particular, we examine how they used digital communication technologies to tap into online resources and social connections both in the United States and their origin country and how various aspects of online information management were associated with their willingness to get vaccinated against the virus. Method: We conducted an online survey and in-depth interviews with international migrants aged 18-64 years who moved to the United States in 2011 or later and were living in two neighboring states in the US Midwest as of spring 2021. Since this research involves understanding how these international migrants dealt with uncertainties related to coronavirus disease 2019 vaccinations, we collected the survey and interview data when each state had a vaccination rate of less than 10% and very limited vaccination eligibility for those aged 64 years and below.Entities:
Keywords: Coronavirus disease 2019 vaccination; digital health; international migrants; mixed-methods; online health literacy; social media
Year: 2022 PMID: 36171961 PMCID: PMC9511311 DOI: 10.1177/20552076221125972
Source DB: PubMed Journal: Digit Health ISSN: 2055-2076
Figure 1.Hypothesized model.
Demographic characteristics of survey participants.
| Variable | Value | Count | Percent |
|---|---|---|---|
| Age | 18–29 | 81 | 43.3 |
| 30–39 | 67 | 35.8 | |
| 40–49 | 26 | 13.9 | |
| 50–64 | 13 | 7.0 | |
| Total | 187 | 100 | |
| Region | East Asia | 58 | 31 |
| South or Southeast Asia | 37 | 19.8 | |
| Middle East and North Africa | 29 | 15.5 | |
| Sub-Saharan Africa | 29 | 15.5 | |
| South or Central America | 18 | 9.6 | |
| Europe | 16 | 8.6 | |
| Total | 187 | 100 | |
| Gender | Male | 103 | 55.1 |
| Female | 84 | 44.9 | |
| Total | 187 | 100 | |
| Education | High school completed | 31 | 16.6 |
| Bachelor's degree | 71 | 37.9 | |
| Master's degree | 70 | 37.5 | |
| PhD | 15 | 8 | |
| Total | 187 | 100 |
Demographic characteristics of interview participants.
| Variable | Value | Count | Percent |
|---|---|---|---|
| Age | 18–29 | 13 | 33.3 |
| 30–39 | 12 | 30.8 | |
| 40–49 | 8 | 20.5 | |
| 50–59 | 5 | 12.8 | |
| 60–64 | 1 | 2.6 | |
| Total | 39 | 100 | |
| Region | East Asia | 9 | 23.1 |
| South or Southeast Asia | 9 | 23.1 | |
| Middle East and North Africa | 7 | 17.9 | |
| Sub-Saharan Africa | 7 | 17.9 | |
| South or Central America | 7 | 17.9 | |
| Total | 39 | 100 | |
| Gender | Female | 20 | 51.3 |
| Male | 19 | 48.7 | |
| Total | 39 | 100 | |
| Education | High school completed | 12 | 30.8 |
| Bachelor's degree | 13 | 33.3 | |
| Master's degree | 13 | 33.3 | |
| PhD | 1 | 2.6 | |
| Total | 39 | 100 |
Figure 2.Path analysis results.