Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study
BackgroundVoice-based systems such as Amazon Alexa may be useful for collecting self-reported information in real time from participants of epidemiology studies using verbal input. In epidemiological research studies, self-reported data tend to be collected using short, infre...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2023-03-01
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| Series: | JMIR mHealth and uHealth |
| Online Access: | https://mhealth.jmir.org/2023/1/e41117 |
| _version_ | 1827857449270378496 |
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| author | Louise A C Millard Laura Johnson Samuel R Neaves Peter A Flach Kate Tilling Deborah A Lawlor |
| author_facet | Louise A C Millard Laura Johnson Samuel R Neaves Peter A Flach Kate Tilling Deborah A Lawlor |
| author_sort | Louise A C Millard |
| collection | DOAJ |
| description |
BackgroundVoice-based systems such as Amazon Alexa may be useful for collecting self-reported information in real time from participants of epidemiology studies using verbal input. In epidemiological research studies, self-reported data tend to be collected using short, infrequent questionnaires, in which the items require participants to select from predefined options, which may lead to errors in the information collected and lack of coverage. Voice-based systems give the potential to collect self-reported information “continuously” over several days or weeks. At present, to the best of our knowledge, voice-based systems have not been used or evaluated for collecting epidemiological data.
ObjectiveWe aimed to demonstrate the technical feasibility of using Alexa to collect information from participants, investigate participant acceptability, and provide an initial evaluation of the validity of the collected data. We used food and drink information as an exemplar.
MethodsWe recruited 45 staff members and students at the University of Bristol (United Kingdom). Participants were asked to tell Alexa what they ate or drank for 7 days and to also submit this information using a web-based form. Questionnaires asked for basic demographic information, about their experience during the study, and the acceptability of using Alexa.
ResultsOf the 37 participants with valid data, most (n=30, 81%) were aged 20 to 39 years and 23 (62%) were female. Across 29 participants with Alexa and web entries corresponding to the same intake event, 60.1% (357/588) of Alexa entries contained the same food and drink information as the corresponding web entry. Most participants reported that Alexa interjected, and this was worse when entering the food and drink information (17/35, 49% of participants said this happened often; 1/35, 3% said this happened always) than when entering the event date and time (6/35, 17% of participants said this happened often; 1/35, 3% said this happened always). Most (28/35, 80%) said they would be happy to use a voice-controlled system for future research.
ConclusionsAlthough there were some issues interacting with the Alexa skill, largely because of its conversational nature and because Alexa interjected if there was a pause in speech, participants were mostly willing to participate in future research studies using Alexa. More studies are needed, especially to trial less conversational interfaces. |
| first_indexed | 2024-03-12T12:41:43Z |
| format | Article |
| id | doaj.art-bb1a827c1d4d4876aa2400fea9f3c0f0 |
| institution | Directory Open Access Journal |
| issn | 2291-5222 |
| language | English |
| last_indexed | 2024-03-12T12:41:43Z |
| publishDate | 2023-03-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR mHealth and uHealth |
| spelling | doaj.art-bb1a827c1d4d4876aa2400fea9f3c0f02023-08-28T23:50:05ZengJMIR PublicationsJMIR mHealth and uHealth2291-52222023-03-0111e4111710.2196/41117Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability StudyLouise A C Millardhttps://orcid.org/0000-0003-4787-8411Laura Johnsonhttps://orcid.org/0000-0001-8985-3154Samuel R Neaveshttps://orcid.org/0000-0002-4064-3794Peter A Flachhttps://orcid.org/0000-0001-6857-5810Kate Tillinghttps://orcid.org/0000-0002-1010-8926Deborah A Lawlorhttps://orcid.org/0000-0002-6793-2262 BackgroundVoice-based systems such as Amazon Alexa may be useful for collecting self-reported information in real time from participants of epidemiology studies using verbal input. In epidemiological research studies, self-reported data tend to be collected using short, infrequent questionnaires, in which the items require participants to select from predefined options, which may lead to errors in the information collected and lack of coverage. Voice-based systems give the potential to collect self-reported information “continuously” over several days or weeks. At present, to the best of our knowledge, voice-based systems have not been used or evaluated for collecting epidemiological data. ObjectiveWe aimed to demonstrate the technical feasibility of using Alexa to collect information from participants, investigate participant acceptability, and provide an initial evaluation of the validity of the collected data. We used food and drink information as an exemplar. MethodsWe recruited 45 staff members and students at the University of Bristol (United Kingdom). Participants were asked to tell Alexa what they ate or drank for 7 days and to also submit this information using a web-based form. Questionnaires asked for basic demographic information, about their experience during the study, and the acceptability of using Alexa. ResultsOf the 37 participants with valid data, most (n=30, 81%) were aged 20 to 39 years and 23 (62%) were female. Across 29 participants with Alexa and web entries corresponding to the same intake event, 60.1% (357/588) of Alexa entries contained the same food and drink information as the corresponding web entry. Most participants reported that Alexa interjected, and this was worse when entering the food and drink information (17/35, 49% of participants said this happened often; 1/35, 3% said this happened always) than when entering the event date and time (6/35, 17% of participants said this happened often; 1/35, 3% said this happened always). Most (28/35, 80%) said they would be happy to use a voice-controlled system for future research. ConclusionsAlthough there were some issues interacting with the Alexa skill, largely because of its conversational nature and because Alexa interjected if there was a pause in speech, participants were mostly willing to participate in future research studies using Alexa. More studies are needed, especially to trial less conversational interfaces.https://mhealth.jmir.org/2023/1/e41117 |
| spellingShingle | Louise A C Millard Laura Johnson Samuel R Neaves Peter A Flach Kate Tilling Deborah A Lawlor Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study JMIR mHealth and uHealth |
| title | Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study |
| title_full | Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study |
| title_fullStr | Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study |
| title_full_unstemmed | Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study |
| title_short | Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study |
| title_sort | collecting food and drink intake data with voice input development usability and acceptability study |
| url | https://mhealth.jmir.org/2023/1/e41117 |
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