A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 176

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016

File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

"Alexa, Am I pregnant?": A content analysis of a virtual assistant's responses to prenatal health questions during the COVID-19 pandemic. | LitMetric

"Alexa, Am I pregnant?": A content analysis of a virtual assistant's responses to prenatal health questions during the COVID-19 pandemic.

Patient Educ Couns

Egan School of Nursing and Health Studies, Fairfield University, 1073 North Benson Road, Fairfield, CT, 06824-5195, USA. Electronic address:

Published: March 2021

Objective: To elucidate whether Amazon's virtual assistant, Alexa, provides evidence-based support as a supplement to provider-facilitated prenatal care, during the COVID-19 pandemic.

Methods: Using a conceptual content analysis approach, a query of 40 questions, relating to all phases of pregnancy, was collected from Alexa by two independent investigators, using two unique devices, over a one-week period between May 20, 2020 and May 27, 2020. Alexa's responses were matched to the evidence-based content from the American College of Obstetricians and Gynecologists (ACOG) and reviewed by a Certified Nurse Midwife for completeness and currency.

Results: Of the 40 questions asked of Alexa, it was unable to answer 14 questions (35%). A total of 21 out of the 40 responses (52%) were not evidence-based and three COVID-specific questions (about 1%) were answered incorrectly or insufficiently. Four questions (10%) were answered accurately.

Conclusion: Alexa was largely unable to provide evidence-based answers to commonly asked pregnancy questions and, in many cases, supplied inaccurate, incomplete, or completely unrelated answers that could further confuse health consumers.

Practice Implications: Ensuring that mobile health (mhealth) tools, such as Amazon Alexa, are evidence-based and credible in answering common prenatal questions has important implications for this pandemic and future consumer needs.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771908PMC
http://dx.doi.org/10.1016/j.pec.2020.12.026DOI Listing

Publication Analysis

Top Keywords

content analysis
8
questions
8
alexa evidence-based
8
alexa unable
8
alexa
5
evidence-based
5
"alexa pregnant?"
4
pregnant?" content
4
analysis virtual
4
virtual assistant's
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!