Voice Assistants and Cancer Screening: A Comparison of Alexa, Siri, Google Assistant, and Cortana.
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ABSTRACT:
SUBMITTER: Hong G
PROVIDER: S-EPMC8437561 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundA voice assistant (VA) is inanimate audio-interfaced software augmented with artificial intelligence, capable of 2-way dialogue, and increasingly used to access health care advice. Postpartum depression (PPD) is a common perinatal mood disorder with an annual estimated cost of $14.2 billion. Only a small percentage of PPD patients seek care due to lack of screening and insufficient knowledge of the disease, and this is, therefore, a prime candidate for a VA-based digital health intervention.ObjectiveIn order to understand the capability of VAs, our aim was to assess VA responses to PPD questions in terms of accuracy, verbal response, and clinically appropriate advice given.MethodsThis cross-sectional study examined four VAs (Apple Siri, Amazon Alexa, Google Assistant, and Microsoft Cortana) installed on two mobile devices in early 2020. We posed 14 questions to each VA that were retrieved from the American College of Obstetricians and Gynecologists (ACOG) patient-focused Frequently Asked Questions (FAQ) on PPD. We scored the VA responses according to accuracy of speech recognition, presence of a verbal response, and clinically appropriate advice in accordance with ACOG FAQ, which were assessed by two board-certified physicians.ResultsAccurate recognition of the query ranged from 79% to 100%. Verbal response ranged from 36% to 79%. If no verbal response was given, queries were treated like a web search between 33% and 89% of the time. Clinically appropriate advice given by VA ranged from 14% to 29%. We compared the category proportions using the Fisher exact test. No single VA statistically outperformed other VAs in the three performance categories. Additional observations showed that two VAs (Google Assistant and Microsoft Cortana) included advertisements in their responses.ConclusionsWhile the best performing VA gave clinically appropriate advice to 29% of the PPD questions, all four VAs taken together achieved 64% clinically appropriate advice. All four VAs performed well in accurately recognizing a PPD query, but no VA achieved even a 30% threshold for providing clinically appropriate PPD information. Technology companies and clinical organizations should partner to improve guidance, screen patients for mental health disorders, and educate patients on potential treatment.
| S-EPMC7834933 | biostudies-literature
Project description:We investigated how intelligent virtual assistants (IVA), including Amazon's Alexa, Apple's Siri, Google Assistant, Microsoft's Cortana, and Samsung's Bixby, responded to addiction help-seeking queries. We recorded if IVAs provided a singular response and if so, did they link users to treatment or treatment referral services. Only 4 of the 70 help-seeking queries presented to the five IVAs returned singular responses, with the remainder prompting confusion (e.g., "did I say something wrong?"). When asked "help me quit drugs" Alexa responded with a definition for the word drugs. "Help me quit…smoking" or "tobacco" on Google Assistant returned Dr. QuitNow (a cessation app), while on Siri "help me quit pot" promoted a marijuana retailer. IVAs should be revised to promote free, remote, federally sponsored addiction services, such as SAMSHA's 1-800-662-HELP helpline. This would benefit millions of IVA users now and more to come as IVAs displace existing information-seeking engines.
| S-EPMC6989668 | biostudies-literature
Project description:To compare voice-activated internet searches by smartphone (two digital assistants) with laptop ones for information and advice related to smoking cessation.Responses to 80 questions on a range of topics related to smoking cessation (including the FAQ from a NHS website), compared for quality.Smartphone and internet searches as performed in New Zealand.Ranked responses to the questions.Google laptop internet searches came first (or first equal) for best quality smoking cessation advice for 83% (66/80) of the responses. Voiced questions to Google Assistant ("OK Google") came first/first equal 76% of the time vs Siri (Apple) at 28%. Google and Google Assistant were statistically significantly better than Siri searches (odds ratio 12.4 and 8.5 respectively, p<0.0001 in each comparison). When asked FAQs from the National Health Service website, or to find information the Centers for Disease Control has made videos on, the best search results used expert sources 59% (31/52) of the time, "some expertise" (eg, Wikipedia) 18% of the time, but also magazines and other low quality sources 19% of the time. Using all three methods failed to find relevant information 8% (6/80) of the time, with Siri having the most failed responses (53% of the time).Google internet searches and Google Assistant were found to be significantly superior to the Siri digital assistant for smoking cessation information. While expert content was returned over half the time, there is still substantial room for improvement in how these software systems deliver smoking cessation advice.
| S-EPMC5874038 | biostudies-literature
Project description:BackgroundPatients with multiple myeloma (MM) have high information needs due to the complexity of the disease and variety of treatments. Digital voice assistants provide support in daily life and can be a convenient tool that even older patients can use to access health information. Voice assistants may therefore be useful in providing digital health services to meet the information needs of patients with MM.ObjectiveWe aim to describe and report on the development, content, and functionality of the first Amazon Alexa voice assistant skill for patients with MM in Germany with the goal of empowering and educating patients. Further, we share data on skill usage and first learnings.MethodsIn a cocreation workshop with MM patient organizations and MM medical experts in Germany, Takeda Oncology discussed the development and content of the Alexa skill Multiple Myeloma. Patient information on MM disease, diagnostics, and therapy was presented in a question-and-answer format, reviewed by experts, and programmed into the skill. Additionally, a search function for finding patient support groups within a perimeter of 200 km around the users and a myeloma quiz functionality with multiple-choice questions were integrated into the skill. Aggregated retrospective data on the total number of skill installations and skill usage were retrieved from an Amazon Alexa developer account, and a web-based patient survey was conducted on the Takeda Oncology website.ResultsThe Alexa skill Multiple Myeloma was launched in September 2019. It was available free of charge on the German Amazon Alexa skill store between September 2019 and March 2022 and could be used with devices featuring the Amazon Alexa voice assistant. Since the launch in September 2019 and up to July 2021, a total of 141 users have installed the skill. Between July 2020 and July 2021, a total of 189 skill sessions with 797 utterances were analyzed. The most popular inquiries were searches for patient support groups near the users (58/797, 7.3%), followed by inquiries about information on MM disease (53/797, 6.6%) and the quiz (43/797, 5.4%). The web-based survey on voice assistant usage and the feedback on the Alexa skill Multiple Myeloma were collected from 24 participants and showed that 46% (11/24) of participants would recommend the Alexa skill. Nonusers of voice assistants (11/24, 46%) stated that data protection concerns (7/11, 64%) and a lack of need (6/11, 55%) were the most important factors of not using voice assistants.ConclusionsThe Alexa skill Multiple Myeloma offers patient-friendly and expert-reviewed answers and explanations for medical terms related to MM disease, diagnostics, and therapy, as well as connections to patient support groups and a quiz functionality. In the future, the skill can be extended with new content and functionalities, such as medication adherence support.
| S-EPMC9227649 | biostudies-literature
Project description:The acceptability of artificially intelligent interactive voice response (AI-IVR) systems in cardiovascular research settings is unclear. As a result, we evaluated peoples' attitudes regarding the Amazon Echo Show 8 device when used for electronic data capture in cardiovascular clinics. Participants were recruited following the Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular clinics study. Overall, 215 people enrolled and underwent screening (mean age 46.1; 55% females) in the VOICE-COVID study and 58 people consented to participate in a post-screening survey. Following thematic analysis, four key themes affecting AI-IVR acceptability were identified. These were difficulties with communication (44.8%), limitations with available interaction modalities (41.4%), barriers with the development of therapeutic relationships (25.9%), and concerns with universality and accessibility (8.6%). While there are potential concerns with the use of AI-IVR technologies, these systems appeared to be well accepted in cardiovascular clinics. Increased development of these technologies could significantly improve healthcare access and efficiency.
| S-EPMC9904249 | biostudies-literature
Project description:ObjectiveDigital voice assistant technology provides unique opportunities to enhance clinical practice. We aimed to understand factors influencing pediatric providers' current and potential use of this technology in clinical practice.MethodsWe surveyed pediatric providers regarding current use and interest in voice technology in the workplace. Regression analyses evaluated provider characteristics associated with voice technology use. Among respondents not interested in voice technology, we elicited individual concerns.ResultsAmong 114 respondents, 19 (16.7%) indicated current use of voice technology in clinical practice, and 51 (44.7%) indicated use of voice technology for nonclinical purposes. Fifty-four (47.4%) reported willingness to try digital voice assistant technology in the clinical setting. Providers who had longer clinic visits (odds ratio [OR], 3.11, 95% confidence interval [CI], 1.04, 9.33, p?=?0.04), fewer patient encounters per day (p?=?0.02), and worked in hospital-based practices (OR, 2.95, 95% CI, 1.08, 8.07, p?=?0.03) were more likely to currently use voice technology in the office. Younger providers (p?=?0.02) and those confident in the accuracy of voice technology (OR, 3.05, 95% CI, 1.38, 6.74, p?=?0.005) were more willing to trial digital voice assistants in the clinical setting. Among respondents unwilling or unsure about trying voice assistant technology, the most common reasons elicited were concerns related to its accuracy (35%), efficiency (33%), and privacy (28%).ConclusionThis national survey evaluating use and attitudes toward digital voice assistant technology by pediatric providers found that while only one-eighth of pediatric providers currently use digital voice assistant technology in the clinical setting, almost half are interested in trying it in the future. Younger provider age and confidence in the accuracy of voice technology are associated with provider interest in using voice technology in the clinical setting. Future development of voice technology for clinical use will need to consider accuracy of information, efficiency of use, and patient privacy for successful integration into the workplace.
| S-EPMC6494608 | biostudies-literature
Project description:BackgroundVoice assistants (VAs) are devices that respond to human voices and can be commanded to do a variety of tasks. Nowadays, VAs are being used to obtain health information, which has become a critical point of analysis for researchers in terms of question understanding and quality of response. Particularly, the COVID-19 pandemic has and still is severely affecting people worldwide, which demands studies on how VAs can be used as a tool to provide useful information.ObjectiveThis work aimed to perform a quality analysis of different VAs' responses regarding the actual and important subject of COVID-19 vaccines. We focused on this important subject since vaccines are now available and society has urged for the population to be rapidly immunized.MethodsThe proposed study was based on questions that were collected from the official World Health Organization website. These questions were submitted to the 5 dominant VAs (Alexa, Bixby, Cortana, Google Assistant, and Siri), and responses were evaluated according to a rubric based on the literature. We focused this study on the Portuguese language as an additional contribution, since previous works are mainly focused on the English language, and we believe that VAs cannot be optimized to foreign languages.ResultsResults showed that Google Assistant has a better overall performance, and only this VA and Samsung Bixby achieved high scores on question understanding in the Portuguese language. Regarding the obtained answers, the study also showed the best Google Assistant overall performance.ConclusionsUnder the urgent context of COVID-19 vaccination, this work can help to understand how VAs must be improved to be more useful to the society and how careful people must be when considering VAs as a source of health information. VAs have been demonstrated to perform well regarding comprehension and user-friendliness. However, this work has found that they must be better integrated to their information sources to be useful as health information tools.
| S-EPMC8942094 | biostudies-literature
Project description:BackgroundVoice assistants allow users to control appliances and functions of a smart home by simply uttering a few words. Such systems hold the potential to significantly help users with motor and cognitive disabilities who currently depend on their caregiver even for basic needs (eg, opening a door). The research on voice assistants is mainly dedicated to able-bodied users, and studies evaluating the accessibility of such systems are still sparse and fail to account for the participants' actual motor, linguistic, and cognitive abilities.ObjectiveThe aim of this work is to investigate whether cognitive and/or linguistic functions could predict user performance in operating an off-the-shelf voice assistant (Google Home).MethodsA group of users with disabilities (n=16) was invited to a living laboratory and asked to interact with the system. Besides collecting data on their performance and experience with the system, their cognitive and linguistic skills were assessed using standardized inventories. The identification of predictors (cognitive and/or linguistic) capable of accounting for an efficient interaction with the voice assistant was investigated by performing multiple linear regression models. The best model was identified by adopting a selection strategy based on the Akaike information criterion (AIC).ResultsFor users with disabilities, the effectiveness of interacting with a voice assistant is predicted by the Mini-Mental State Examination (MMSE) and the Robertson Dysarthria Profile (specifically, the ability to repeat sentences), as the best model shows (AIC=130.11).ConclusionsUsers with motor, linguistic, and cognitive impairments can effectively interact with voice assistants, given specific levels of residual cognitive and linguistic skills. More specifically, our paper advances practical indicators to predict the level of accessibility of speech-based interactive systems. Finally, accessibility design guidelines are introduced based on the performance results observed in users with disabilities.
| S-EPMC7547392 | biostudies-literature
Project description:The aim of this study was to evaluate the ability of Google Assistant, Alexa, and Siri to recognize and answer questions about male sexual health. Each VA was tested on a smart speaker: Alexa on Amazon Echo Dot 4th Gen., Google Assistant on Google Home Mini, and Siri on Apple HomePod. A pool of patients' frequently asked questions regarding erectile dysfunction (ED), premature ejaculation (PE), Peyronie's disease (PD), male infertility, and other aspects of male sexual health were identified by authors. The recognition of question was evaluated ("yes" or "not"). For each recognized question, the response characteristics (domains) were rated on a scale from 0 to 10 (according to the quality). We chose the recognition rate of the questions as the primary outcome and the quality of the answers as the secondary outcome. Overall, the best VA in recognizing questions was Siri, with a total of 83.3% questions compared with 64.0% for Alexa (p = 0.024) and 74.0% for Google Assistant (p = 0.061). Siri was associated with a significantly higher recognition rate than Alexa for PE (80% vs. 40%; p = 0.002) and PD (66.7% vs. 33.3%; p = 0.010). The quality of the responses was classified as low in 57 out of 105 cases (54.3%), intermediate in 46 cases (43.8%), and high in only 2 cases (1.9%), highlighting an overall intermediate-low quality of the answers. Male infertility was the condition associated with the highest mean scores in "Targeted response to the problem" (7.32 ± 2.57), "Scientific correctness of the answer", (5.9 ± 2.76) "Completeness of the answer" (5.14 ± 2.56), and "Understandability of the response for a patient" (5.3 ± 2.51) domains. Siri was associated with significantly higher scores than Alexa (p < 0.05) in several domains of all conditions evaluated. The question recognition rate of VAs is quite high; however, the quality of the answers is still intermediate-low. Siri seems superior to Alexa in both question recognition and response quality. Male infertility appears to be the sexual dysfunction best addressed by VAs.
| S-EPMC9914936 | biostudies-literature
Project description:IntroductionSocial isolation is a major public health concern, as isolated individuals are at increased risk of poor overall health, as well as at increased risk of unhealthy behaviors. During the COVID-19 pandemic, social distancing strategies have led to increased rates of loneliness and social isolation. There is a clear need for strategies to mitigate the effects of social isolation and loneliness on the mental and physical health of older adults. In this study, we sought to better understand how voice-controlled intelligent personal assistants (VIPAs) could be leveraged to reduce loneliness and social isolation among home-bound older adults.MethodsPatients and geriatric experts were recruited to use VIPA devices (Google Home) in their homes for 4 weeks and then provide feedback. No prior training was provided. Geriatric experts were recruited via email solicitation from the Northwestern Medicine Geriatrics Clinic, and patients were solicited directly from geriatric primary care physicians. The investigators used qualitative analysis to identify codes and overarching themes.ResultsA total of 288 comments were received from 16 participants. Eight major themes were identified: Administrative, Companionship, Home Control, Education, Emergencies, Entertainment, Health and Well-Being, and Reminders.DiscussionResults demonstrate that VIPAs can be useful across multiple domains and potentially play a role in providing physical, social, and cognitive stimulation to home-bound older adults. VIPAs have a wide range of functionality, many of which could be implemented to focus on common geriatric syndromes and may ultimately be a tool to help mitigate social isolation and the consequential loneliness.
| S-EPMC9106816 | biostudies-literature