Cargando…

Examining the Public’s Most Frequently Asked Questions Regarding COVID-19 Vaccines Using Search Engine Analytics in the United States: Observational Study

BACKGROUND: The emergency authorization of COVID-19 vaccines has offered the first means of long-term protection against COVID-19–related illness since the pandemic began. It is important for health care professionals to understand commonly held COVID-19 vaccine concerns and to be equipped with qual...

Descripción completa

Detalles Bibliográficos
Autores principales: Sajjadi, Nicholas B, Shepard, Samuel, Ottwell, Ryan, Murray, Kelly, Chronister, Justin, Hartwell, Micah, Vassar, Matt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8341336/
https://www.ncbi.nlm.nih.gov/pubmed/34458683
http://dx.doi.org/10.2196/28740
_version_ 1783733908455555072
author Sajjadi, Nicholas B
Shepard, Samuel
Ottwell, Ryan
Murray, Kelly
Chronister, Justin
Hartwell, Micah
Vassar, Matt
author_facet Sajjadi, Nicholas B
Shepard, Samuel
Ottwell, Ryan
Murray, Kelly
Chronister, Justin
Hartwell, Micah
Vassar, Matt
author_sort Sajjadi, Nicholas B
collection PubMed
description BACKGROUND: The emergency authorization of COVID-19 vaccines has offered the first means of long-term protection against COVID-19–related illness since the pandemic began. It is important for health care professionals to understand commonly held COVID-19 vaccine concerns and to be equipped with quality information that can be used to assist in medical decision-making. OBJECTIVE: Using Google’s RankBrain machine learning algorithm, we sought to characterize the content of the most frequently asked questions (FAQs) about COVID-19 vaccines evidenced by internet searches. Secondarily, we sought to examine the information transparency and quality of sources used by Google to answer FAQs on COVID-19 vaccines. METHODS: We searched COVID-19 vaccine terms on Google and used the “People also ask” box to obtain FAQs generated by Google’s machine learning algorithms. FAQs are assigned an “answer” source by Google. We extracted FAQs and answer sources related to COVID-19 vaccines. We used the Rothwell Classification of Questions to categorize questions on the basis of content. We classified answer sources as either academic, commercial, government, media outlet, or medical practice. We used the Journal of the American Medical Association’s (JAMA’s) benchmark criteria to assess information transparency and Brief DISCERN to assess information quality for answer sources. FAQ and answer source type frequencies were calculated. Chi-square tests were used to determine associations between information transparency by source type. One-way analysis of variance was used to assess differences in mean Brief DISCERN scores by source type. RESULTS: Our search yielded 28 unique FAQs about COVID-19 vaccines. Most COVID-19 vaccine–related FAQs were seeking factual information (22/28, 78.6%), specifically about safety and efficacy (9/22, 40.9%). The most common source type was media outlets (12/28, 42.9%), followed by government sources (11/28, 39.3%). Nineteen sources met 3 or more JAMA benchmark criteria with government sources as the majority (10/19, 52.6%). JAMA benchmark criteria performance did not significantly differ among source types (χ(2)(4)=7.40; P=.12). One-way analysis of variance revealed a significant difference in mean Brief DISCERN scores by source type (F(4,23)=10.27; P<.001). CONCLUSIONS: The most frequently asked COVID-19 vaccine–related questions pertained to vaccine safety and efficacy. We found that government sources provided the most transparent and highest-quality web-based COVID-19 vaccine–related information. Recognizing common questions and concerns about COVID-19 vaccines may assist in improving vaccination efforts.
format Online
Article
Text
id pubmed-8341336
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-83413362021-08-25 Examining the Public’s Most Frequently Asked Questions Regarding COVID-19 Vaccines Using Search Engine Analytics in the United States: Observational Study Sajjadi, Nicholas B Shepard, Samuel Ottwell, Ryan Murray, Kelly Chronister, Justin Hartwell, Micah Vassar, Matt JMIR Infodemiology Original Paper BACKGROUND: The emergency authorization of COVID-19 vaccines has offered the first means of long-term protection against COVID-19–related illness since the pandemic began. It is important for health care professionals to understand commonly held COVID-19 vaccine concerns and to be equipped with quality information that can be used to assist in medical decision-making. OBJECTIVE: Using Google’s RankBrain machine learning algorithm, we sought to characterize the content of the most frequently asked questions (FAQs) about COVID-19 vaccines evidenced by internet searches. Secondarily, we sought to examine the information transparency and quality of sources used by Google to answer FAQs on COVID-19 vaccines. METHODS: We searched COVID-19 vaccine terms on Google and used the “People also ask” box to obtain FAQs generated by Google’s machine learning algorithms. FAQs are assigned an “answer” source by Google. We extracted FAQs and answer sources related to COVID-19 vaccines. We used the Rothwell Classification of Questions to categorize questions on the basis of content. We classified answer sources as either academic, commercial, government, media outlet, or medical practice. We used the Journal of the American Medical Association’s (JAMA’s) benchmark criteria to assess information transparency and Brief DISCERN to assess information quality for answer sources. FAQ and answer source type frequencies were calculated. Chi-square tests were used to determine associations between information transparency by source type. One-way analysis of variance was used to assess differences in mean Brief DISCERN scores by source type. RESULTS: Our search yielded 28 unique FAQs about COVID-19 vaccines. Most COVID-19 vaccine–related FAQs were seeking factual information (22/28, 78.6%), specifically about safety and efficacy (9/22, 40.9%). The most common source type was media outlets (12/28, 42.9%), followed by government sources (11/28, 39.3%). Nineteen sources met 3 or more JAMA benchmark criteria with government sources as the majority (10/19, 52.6%). JAMA benchmark criteria performance did not significantly differ among source types (χ(2)(4)=7.40; P=.12). One-way analysis of variance revealed a significant difference in mean Brief DISCERN scores by source type (F(4,23)=10.27; P<.001). CONCLUSIONS: The most frequently asked COVID-19 vaccine–related questions pertained to vaccine safety and efficacy. We found that government sources provided the most transparent and highest-quality web-based COVID-19 vaccine–related information. Recognizing common questions and concerns about COVID-19 vaccines may assist in improving vaccination efforts. JMIR Publications 2021-08-04 /pmc/articles/PMC8341336/ /pubmed/34458683 http://dx.doi.org/10.2196/28740 Text en ©Nicholas B Sajjadi, Samuel Shepard, Ryan Ottwell, Kelly Murray, Justin Chronister, Micah Hartwell, Matt Vassar. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 04.08.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Infodemiology, is properly cited. The complete bibliographic information, a link to the original publication on https://infodemiology.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Sajjadi, Nicholas B
Shepard, Samuel
Ottwell, Ryan
Murray, Kelly
Chronister, Justin
Hartwell, Micah
Vassar, Matt
Examining the Public’s Most Frequently Asked Questions Regarding COVID-19 Vaccines Using Search Engine Analytics in the United States: Observational Study
title Examining the Public’s Most Frequently Asked Questions Regarding COVID-19 Vaccines Using Search Engine Analytics in the United States: Observational Study
title_full Examining the Public’s Most Frequently Asked Questions Regarding COVID-19 Vaccines Using Search Engine Analytics in the United States: Observational Study
title_fullStr Examining the Public’s Most Frequently Asked Questions Regarding COVID-19 Vaccines Using Search Engine Analytics in the United States: Observational Study
title_full_unstemmed Examining the Public’s Most Frequently Asked Questions Regarding COVID-19 Vaccines Using Search Engine Analytics in the United States: Observational Study
title_short Examining the Public’s Most Frequently Asked Questions Regarding COVID-19 Vaccines Using Search Engine Analytics in the United States: Observational Study
title_sort examining the public’s most frequently asked questions regarding covid-19 vaccines using search engine analytics in the united states: observational study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8341336/
https://www.ncbi.nlm.nih.gov/pubmed/34458683
http://dx.doi.org/10.2196/28740
work_keys_str_mv AT sajjadinicholasb examiningthepublicsmostfrequentlyaskedquestionsregardingcovid19vaccinesusingsearchengineanalyticsintheunitedstatesobservationalstudy
AT shepardsamuel examiningthepublicsmostfrequentlyaskedquestionsregardingcovid19vaccinesusingsearchengineanalyticsintheunitedstatesobservationalstudy
AT ottwellryan examiningthepublicsmostfrequentlyaskedquestionsregardingcovid19vaccinesusingsearchengineanalyticsintheunitedstatesobservationalstudy
AT murraykelly examiningthepublicsmostfrequentlyaskedquestionsregardingcovid19vaccinesusingsearchengineanalyticsintheunitedstatesobservationalstudy
AT chronisterjustin examiningthepublicsmostfrequentlyaskedquestionsregardingcovid19vaccinesusingsearchengineanalyticsintheunitedstatesobservationalstudy
AT hartwellmicah examiningthepublicsmostfrequentlyaskedquestionsregardingcovid19vaccinesusingsearchengineanalyticsintheunitedstatesobservationalstudy
AT vassarmatt examiningthepublicsmostfrequentlyaskedquestionsregardingcovid19vaccinesusingsearchengineanalyticsintheunitedstatesobservationalstudy