Dataset Information

Just ask Siri? A pilot study comparing smartphone digital assistants and laptop Google searches for smoking cessation advice.

ABSTRACT: 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.

SUBMITTER: Boyd M

PROVIDER: S-EPMC5874038 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Just ask Siri? A pilot study comparing smartphone digital assistants and laptop Google searches for smoking cessation advice.

Boyd Matt M Wilson Nick N

PloS one 20180328 3

<h4>Objective</h4>To compare voice-activated internet searches by smartphone (two digital assistants) with laptop ones for information and advice related to smoking cessation.<h4>Design</h4>Responses to 80 questions on a range of topics related to smoking cessation (including the FAQ from a NHS website), compared for quality.<h4>Setting</h4>Smartphone and internet searches as performed in New Zealand.<h4>Main outcome measures</h4>Ranked responses to the questions.<h4>Results</h4>Google laptop in ...[more]

PMID: 29590168

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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.

Project description:PurposeEpidemic and seasonal infectious conjunctivitis outbreaks can impact education, workforce, and economy adversely. Yet conjunctivitis typically is not a reportable disease, potentially delaying mitigating intervention. Our study objective was to determine if conjunctivitis epidemics could be identified using Google Trends search data.DesignSearch data for conjunctivitis-related and control search terms from 5 years and countries worldwide were obtained. Country and term were masked. Temporal scan statistics were applied to identify candidate epidemics. Candidates then were assessed for geotemporal concordance with an a priori defined collection of known reported conjunctivitis outbreaks, as a measure of sensitivity.ParticipantsPopulations by country that searched Google's search engine using our study terms.Main outcome measuresPercent of known conjunctivitis outbreaks also found in the same country and period by our candidate epidemics, identified from conjunctivitis-related searches.ResultsWe identified 135 candidate conjunctivitis epidemic periods from 77 countries. Compared with our a priori defined collection of known reported outbreaks, candidate conjunctivitis epidemics identified 18 of 26 (69% sensitivity) of the reported country-wide or island nationwide outbreaks, or both; 9 of 20 (45% sensitivity) of the reported region or district-wide outbreaks, or both; but far fewer nosocomial and reported smaller outbreaks. Similar overall and individual sensitivity, as well as specificity, were found on a country-level basis. We also found that 83% of our candidate epidemics had start dates before (of those, 20% were more than 12 weeks before) their concurrent reported outbreak's report issuance date. Permutation tests provided evidence that on average, conjunctivitis candidate epidemics occurred geotemporally closer to outbreak reports than chance alone suggests (P < 0.001) unlike control term candidates (P = 0.40).ConclusionsConjunctivitis outbreaks can be detected using temporal scan analysis of Google search data alone, with more than 80% detected before an outbreak report's issuance date, some as early as the reported outbreak's start date. Future approaches using data from smaller regions, social media, and more search terms may improve sensitivity further and cross-validate detected candidates, allowing identification of candidate conjunctivitis epidemics from Internet search data potentially to complementarily benefit traditional reporting and detection systems to improve epidemic awareness.

Dataset Information

Just ask Siri? A pilot study comparing smartphone digital assistants and laptop Google searches for smoking cessation advice.

Publications

Just ask Siri? A pilot study comparing smartphone digital assistants and laptop Google searches for smoking cessation advice.

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