Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study

JMIR mHealth and uHealth · 6 authors, 5 centres

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TL;DR

This development and usability study recruited 45 University of Bristol staff and students to test an Alexa voice skill for collecting self-reported food and drink intake over 7 days.

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This development and usability study recruited 45 University of Bristol staff and students to test an Alexa voice skill for collecting self-reported food and drink intake over 7 days. Participants submitted intake data via both Alexa and a parallel web form. Of 37 participants with valid data, 60.1% of Alexa entries matched the corresponding web entry for food and drink content. Intake date and time were largely entered accurately. However, the conversational interface was problematic: 51% of participants reported that Alexa often or always interjected during food and drink entry. Several participants reduced the information they provided to avoid Alexa cutting out. Limitations include the lack of absolute ground truth (only relative validity against the web form was assessed), potential interaction effects between the two data collection methods, and difficulty linking Alexa and web entries to the same intake event.

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other

SPECIALTY

research methods

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AI pipeline

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ORIGINAL PAPER

PMC10132002

Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study

JMIR mHealth and uHealth

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ABSTRACT

Abstract Background Voice-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. Objective We 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. Methods We 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. Results Of 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. Conclusions Although 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. Keywords: digital health, data collection, voice-based approaches, Amazon Alexa, self-reported data, food and drink

CITATION EXPORT

Louise A C Millard, Laura Johnson, Samuel R Neaves et al.. Collecting Food and Drink Intake Data With Voice Input: Development, Usability, and Acceptability Study. JMIR mHealth and uHealth. (2023). https://doi.org/10.2196/41117

AUTHORS

6 · 5 CENTRES

Louise A C Millard, Laura Johnson, Samuel R Neaves, Peter A Flach, Kate Tilling, Deborah A Lawlor

1Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
2Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
3Centre for Exercise, Nutrition and Health Sciences, School for Policy Studies, University of Bristol, Bristol, United Kingdom
4Centre for Health, National Centre for Social Research (NatCen), London, United Kingdom
5Faculty of Engineering, University of Bristol, Bristol, United Kingdom