Voice Assistants and Cancer Screening: A Comparison of Alexa, Siri, Google Assistant, and Cortana

Hong, Grace; Folcarelli, Albino; Less, Jacob; Wang, Claire; Erbasi, Neslihan; Lin, Steven

doi:10.1370/afm.2713

Cited by 22 publications

(11 citation statements)

References 3 publications

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“…However, interactive voice response systems remain relatively unexplored. A previous study has evaluated the quality of health information dissemination on cancer screening provided by voice assistants, such as Siri, Alexa, and Cortana, but did not evaluate these devices’ ability to screen for cancer [ 18 ]. One study evaluated the quality of speech intelligibility of Amazon Alexa and Google Home by providing individuals with intellectual disabilities with smart speaker devices [ 19 ].…”

Section: Discussionmentioning

confidence: 99%

Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular Clinics (VOICE-COVID-19-II): Protocol for a Randomized Controlled Trial

Oulousian¹,

Chung²,

Ganni³

et al. 2023

JMIR Res Protoc

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Background The COVID-19 pandemic has disrupted the health care system, limiting health care resources such as the availability of health care professionals, patient monitoring, contact tracing, and continuous surveillance. As a result of this significant burden, digital tools have become an important asset in increasing the efficiency of patient care delivery. Digital tools can help support health care institutions by tracking transmission of the virus, aiding in the screening process, and providing telemedicine support. However, digital health tools face challenges associated with barriers to accessibility, efficiency, and privacy-related ethical issues. Objective This paper describes the study design of an open-label, noninterventional, crossover, randomized controlled trial aimed at assessing whether interactive voice response systems can screen for SARS-CoV-2 in patients as accurately as standard screening done by people. The study aims to assess the concordance and interrater reliability of symptom screening done by Amazon Alexa compared to manual screening done by research coordinators. The perceived level of comfort of patients when interacting with voice response systems and their personal experience will also be evaluated. Methods A total of 52 patients visiting the heart failure clinic at the Royal Victoria Hospital of the McGill University Health Center, in Montreal, Quebec, will be recruited. Patients will be randomly assigned to first be screened for symptoms of SARS-CoV-2 either digitally, by Amazon Alexa, or manually, by the research coordinator. Participants will subsequently be crossed over and screened either digitally or manually. The clinical setup includes an Amazon Echo Show, a tablet, and an uninterrupted power supply mounted on a mobile cart. The primary end point will be the interrater reliability on the accuracy of randomized screening data performed by Amazon Alexa versus research coordinators. The secondary end point will be the perceived level of comfort and app engagement of patients as assessed using 5-point Likert scales and binary mode responses. Results Data collection started in May 2021 and is expected to be completed in fall 2022. Data analysis is expected to be completed in early 2023. Conclusions The use of voice-based assistants could improve the provision of health services and reduce the burden on health care personnel. Demonstrating a high interrater reliability between Amazon Alexa and health care coordinators may serve future digital tools to streamline the screening and delivery of care in the context of other conditions and clinical settings. The COVID-19 pandemic occurs during the first digital era using digital tools such as Amazon Alexa for disease screening, and it represents an opportunity to implement such technology in health care institutions in the long term. Trial Registration ClinicalTrials.gov NCT04508972; https://clinicaltrials.gov/ct2/show/NCT04508972 International Registered Report Identifier (IRRID) DERR1-10.2196/41209

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Section: Discussionmentioning

confidence: 99%

Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular Clinics (VOICE-COVID-19-II): Protocol for a Randomized Controlled Trial

Oulousian¹,

Chung²,

Ganni³

et al. 2023

JMIR Res Protoc

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“…Previous studies have highlighted pitfalls associated with the use of VAs as sources of health information, which often offer counsel that is inaccurate or incongruous with official recommendations [ 6 - 14 ]. Our study adds to this body of work by examining the responses of VAs to questions about the COVID-19 vaccine.…”

Section: Discussionmentioning

confidence: 99%

“…Given the increasing use of VAs by individuals and health care institutions to obtain and provide health information [2,3], VAs represent a tool that could, in theory, support the dissemination of evidence-based vaccine information. However, the literature assessing the reliability of health information provided by VAs is limited, and recent studies have found VAs provide users with health information that are inaccurate or incongruous with official recommendations [6][7][8][9][10][11][12][13][14]. For example, a content analysis of Amazon Alexa's responses to common pregnancy questions during the pandemic revealed that the majority (52%) of Alexa's responses were not evidence based [8].…”

Section: Introductionmentioning

confidence: 99%

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Voice Assistants’ Responses to Questions About the COVID-19 Vaccine: National Cross-sectional Study

Sossenheimer¹,

Hong²,

Devon-Sand³

et al. 2023

JMIR Form Res

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Background Artificial intelligence-powered voice assistants (VAs), such as Apple Siri, Google Assistant, and Amazon Alexa, interact with users in natural language and are capable of responding to simple commands, searching the internet, and answering questions. Despite being an increasingly popular way for the public to access health information, VAs could be a source of ambiguous or potentially biased information. Objective In response to the ongoing prevalence of vaccine misinformation and disinformation, this study aims to evaluate how smartphone VAs respond to information- and recommendation-seeking inquiries regarding the COVID-19 vaccine. Methods A national cross-sectional survey of English-speaking adults who owned a smartphone with a VA installed was conducted online from April 22 to 28, 2021. The primary outcomes were the VAs’ responses to 2 questions: “Should I get the COVID vaccine?” and “Is the COVID vaccine safe?” Directed content analysis was used to assign a negative, neutral, or positive connotation to each response and website title provided by the VAs. Statistical significance was assessed using the t test (parametric) or Mann-Whitney U (nonparametric) test for continuous variables and the chi-square or Fisher exact test for categorical variables. Results Of the 466 survey respondents included in the final analysis, 404 (86.7%) used Apple Siri, 53 (11.4%) used Google Assistant, and 9 (1.9%) used Amazon Alexa. In response to the question “Is the COVID vaccine safe?” 419 (89.9%) users received a direct response, of which 408 (97.3%) had a positive connotation encouraging users to get vaccinated. Of the websites presented, only 5.3% (11/207) had a positive connotation and 94.7% (196/207) had a neutral connotation. In response to the question “Should I get the COVID vaccine?” 93.1% (434/466) of users received a list of websites, of which 91.5% (1155/1262) had a neutral connotation. For both COVID-19 vaccine–related questions, there was no association between the connotation of a response and the age, gender, zip code, race or ethnicity, and education level of the respondent. Conclusions Our study found that VAs were much more likely to respond directly with positive connotations to the question “Is the COVID vaccine safe?” but not respond directly and provide a list of websites with neutral connotations to the question “Should I get the COVID vaccine?” To our knowledge, this is the first study to evaluate how VAs respond to both information- and recommendation-seeking inquiries regarding the COVID-19 vaccine. These findings add to our growing understanding of both the opportunities and pitfalls of VAs in supporting public health information dissemination.

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“…CAs have been variously used and studied in health care for supporting behavioral health and healthy living [3,4]; health information seeking [5][6][7][8][9]; appointment, medication, symptom tracking and chronic condition management [10][11][12]; and facilitating COVID-19 screening and information sharing [13,14]. Mobile phone ownership enables and increases the potential applications, availability, and access to CAs in practice.…”

Section: Introductionmentioning

confidence: 99%

Design and Evaluation Challenges of Conversational Agents in Health Care and Well-being: Selective Review Study

Kocaballı¹,

Sezgın²,

Clark³

et al. 2022

J Med Internet Res

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Background Health care and well-being are 2 main interconnected application areas of conversational agents (CAs). There is a significant increase in research, development, and commercial implementations in this area. In parallel to the increasing interest, new challenges in designing and evaluating CAs have emerged. Objective This study aims to identify key design, development, and evaluation challenges of CAs in health care and well-being research. The focus is on the very recent projects with their emerging challenges. Methods A review study was conducted with 17 invited studies, most of which were presented at the ACM (Association for Computing Machinery) CHI 2020 conference workshop on CAs for health and well-being. Eligibility criteria required the studies to involve a CA applied to a health or well-being project (ongoing or recently finished). The participating studies were asked to report on their projects’ design and evaluation challenges. We used thematic analysis to review the studies. Results The findings include a range of topics from primary care to caring for older adults to health coaching. We identified 4 major themes: (1) Domain Information and Integration, (2) User-System Interaction and Partnership, (3) Evaluation, and (4) Conversational Competence. Conclusions CAs proved their worth during the pandemic as health screening tools, and are expected to stay to further support various health care domains, especially personal health care. Growth in investment in CAs also shows the value as a personal assistant. Our study shows that while some challenges are shared with other CA application areas, safety and privacy remain the major challenges in the health care and well-being domains. An increased level of collaboration across different institutions and entities may be a promising direction to address some of the major challenges that otherwise would be too complex to be addressed by the projects with their limited scope and budget.

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Voice Assistants and Cancer Screening: A Comparison of Alexa, Siri, Google Assistant, and Cortana

Cited by 22 publications

References 3 publications

Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular Clinics (VOICE-COVID-19-II): Protocol for a Randomized Controlled Trial

Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular Clinics (VOICE-COVID-19-II): Protocol for a Randomized Controlled Trial

Voice Assistants’ Responses to Questions About the COVID-19 Vaccine: National Cross-sectional Study

Design and Evaluation Challenges of Conversational Agents in Health Care and Well-being: Selective Review Study

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