Can Alexa, Cortana, Google Assistant and Siri save your life? A mixed-methods analysis of virtual digital assistants and their responses to first aid and basic life support queries. Issue 1 (7th January 2020)
- Record Type:
- Journal Article
- Title:
- Can Alexa, Cortana, Google Assistant and Siri save your life? A mixed-methods analysis of virtual digital assistants and their responses to first aid and basic life support queries. Issue 1 (7th January 2020)
- Main Title:
- Can Alexa, Cortana, Google Assistant and Siri save your life? A mixed-methods analysis of virtual digital assistants and their responses to first aid and basic life support queries
- Authors:
- Picard, Christopher
Smith, Katherine Elizabeth
Picard, Kelly
Douma, Matthew John - Abstract:
- Abstract : Background: Virtual digital assistants are devices that interact with the user through natural language processing and artificial intelligence. They can respond to verbal requests for first aid information. This study analyses the responses provided by the four most common devices. Methods: This mixed-methods study employs structured interviews of the virtual digital assistants (Alexa, Cortana, Google Home and Siri) as well as descriptive statistical analyses. One hundred and twenty-three interview questions, based on 39 first aid topics, were employed. Responses were analysed for recognition and quality. Detection of query acuity was performed according to triage guidelines and response complexity was calculated. Results: Device performance was highly variable. Alexa and Google Home demonstrated high rates of recognition (92% vs 98% (p=0.03)) and low-to-moderate congruence with guidelines (19% vs 56% (p=0.04)). They appropriately recommended emergency response system activation 46% of the time vs 16% (p=0.01) of the time, respectively. The overall low quality responses of Cortana and Siri prohibited their analysis. Mean response complexity for Alexa was 'grade 10' vs 'grade 8' for Google Home (p<0.001). Interpretation: This is the first study to assess virtual digital assistants from a first aid and basic life support perspective, finding potential in this technology to provide life-saving instructions and activate the emergency response system. When asked commonAbstract : Background: Virtual digital assistants are devices that interact with the user through natural language processing and artificial intelligence. They can respond to verbal requests for first aid information. This study analyses the responses provided by the four most common devices. Methods: This mixed-methods study employs structured interviews of the virtual digital assistants (Alexa, Cortana, Google Home and Siri) as well as descriptive statistical analyses. One hundred and twenty-three interview questions, based on 39 first aid topics, were employed. Responses were analysed for recognition and quality. Detection of query acuity was performed according to triage guidelines and response complexity was calculated. Results: Device performance was highly variable. Alexa and Google Home demonstrated high rates of recognition (92% vs 98% (p=0.03)) and low-to-moderate congruence with guidelines (19% vs 56% (p=0.04)). They appropriately recommended emergency response system activation 46% of the time vs 16% (p=0.01) of the time, respectively. The overall low quality responses of Cortana and Siri prohibited their analysis. Mean response complexity for Alexa was 'grade 10' vs 'grade 8' for Google Home (p<0.001). Interpretation: This is the first study to assess virtual digital assistants from a first aid and basic life support perspective, finding potential in this technology to provide life-saving instructions and activate the emergency response system. When asked common first aid related questions Google Home and Alexa outperformed Siri and Cortana. Overall, the device responses were of mixed quality ranging from the provision of factual guideline-based information to no response at all. … (more)
- Is Part Of:
- BMJ innovations. Volume 6:Issue 1(2020)
- Journal:
- BMJ innovations
- Issue:
- Volume 6:Issue 1(2020)
- Issue Display:
- Volume 6, Issue 1 (2020)
- Year:
- 2020
- Volume:
- 6
- Issue:
- 1
- Issue Sort Value:
- 2020-0006-0001-0000
- Page Start:
- 26
- Page End:
- 31
- Publication Date:
- 2020-01-07
- Subjects:
- cardiovascular -- medical apps -- mHealth -- trauma
Medicine -- Research -- Periodicals
610.72 - Journal URLs:
- http://www.bmj.com/archive ↗
http://innovations.bmj.com/ ↗ - DOI:
- 10.1136/bmjinnov-2018-000326 ↗
- Languages:
- English
- ISSNs:
- 2055-8074
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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