"Alexa, I just ate a donut": A pilot study collecting food and drink intake data with voice input
Millard, L. A. C.; Johnson, L.; Neaves, S. R.; Flach, P.; Tilling, K.; Lawlor, D. A.
Show abstract
BackgroundVoice-based systems such as Amazon Alexa may be useful to collect self-reported information in realtime from participants of epidemiology studies, using verbal input. We demonstrate the technical feasibility of using Alexa, investigate participant acceptability, and provide an initial evaluation of the validity of the collected data. We use food and drink information as an exemplar. MethodsWe recruited 45 staff and students at the University of Bristol (UK). Participants were asked to tell Alexa what they ate or drank for 7 days, and also to submit this information using a web form. Questionnaires asked for basic demographic information and about their experience during the study and acceptability of using Alexa. ResultsOf the 37 participants with valid data, most were 20-39 years old (N=30; 81%) and 23 (62%) were female. Across 29 participants with Alexa and web entries corresponding to the same intake event, 357 Alexa entries (61%) contained the same food/drink information as the corresponding web entry. Participants often reported that Alexa interjected, and this was worse when entering the food and drink information compared with the event date and time. The majority said they would be happy to use a voice-controlled system for future research. ConclusionsWhile usability of our skill was poor, largely due to the conversational nature and because Alexa interjected if there was a pause in speech, participants were mostly open to participating in future research studies using Alexa. Many more studies are needed, in particular, to trial less conversational interfaces. KEY MESSAGESO_LIOver the last few years voice-controlled smart systems have emerged giving the possibility of collecting self-reported data using a voice-based approach. C_LIO_LIWe successfully collected epidemiology food and drink information in real-time, demonstrating that voice-based collection of self-reported data is technically feasible. C_LIO_LIThe conversational design of our skill meant that usability was poor, for example, most participants (86%) reported that Alexa either occasionally, often or always interjected during use, and the majority of participants who had previously used a paper diary or my fitness pal did not find Alexa as efficient to use compared with these approaches. C_LIO_LIAfter participating in this study, the majority of participants would be happy to use Alexa again, either at home or on a wearable device. C_LIO_LIOur results highlight that further work is needed to evaluate use of voice-based systems, including comparing Amazon Alexa with the Google Assistant, and trialling less conversational interfaces. C_LI
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Improving Heart disease risk through quality-focused diet logging: pre-post study of a diet quality tracking app 94%
- Acceptability of app-based contact tracing for COVID-19: Cross-country survey evidence 91%
- Challenges for non-technical implementation of digital proximity tracing: early experiences from Switzerland 91%
Similar papers in this journal
- Assessing the impact of a mandatory calorie labelling policy in out-of-home food outlets in England on consumer behaviour: a natural experimental study 93%
- A mixed methods study evaluating food insecurity and diet quality in households accessing food aid in England 92%
- How is the COVID-19 pandemic impacting our life, mental health, and well-being? Design and preliminary findings of the pan-Canadian longitudinal COHESION Study 91%
Similar papers in this journal
- Weight-normative messaging predominates on TikTok – a qualitative content analysis 92%
- Comprehensive profiling of social mixing patterns in resource poor countries: a mixed methods research protocol 91%
- Implementation and enforcement of mandatory calorie labelling regulations for the out-of-home sector in England: qualitative study of the experiences of business implementers and regulatory enforcers 91%
Similar papers in this journal
- Fitness tracking reveals task-specific associations between memory, mental health, and physical activity 93%
- Sociodemographic Characteristics of Missing Data in Digital Phenotyping 92%
- Healthier decisions in the cued-attribute food choice paradigm have high test-retest reliability across five task repetitions over 14 days 91%
Similar papers in this journal
- Reactions to an Online Demonstration of the Effect of Increased Fruit and Vegetable Consumption on Appearance: Survey 92%
- Tracking private WhatsApp discourse about COVID-19: A longitudinal infodemiology study in Singapore 91%
- Quantified Flu: an individual-centered approach to gaining sickness-related insights from wearable data 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.