Back

"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.

2022-06-28 epidemiology
10.1101/2022.06.28.22276999 medRxiv
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.

1
JMIR mHealth and uHealth
11 papers in training set
Top 0.1%
19.0%
2
BMC Public Health
158 papers in training set
Top 0.1%
12.8%
3
PLOS ONE
5266 papers in training set
Top 24%
6.9%
4
Scientific Reports
3612 papers in training set
Top 15%
5.6%
5
Journal of Medical Internet Research
87 papers in training set
Top 0.6%
4.2%
6
BMJ Open
601 papers in training set
Top 6%
3.5%
50% of probability mass above
7
International Journal of Behavioral Nutrition and Physical Activity
15 papers in training set
Top 0.2%
2.9%
8
PLOS Digital Health
106 papers in training set
Top 2%
2.0%
9
Appetite
18 papers in training set
Top 0.2%
1.8%
10
Frontiers in Nutrition
24 papers in training set
Top 0.4%
1.8%
11
Nature Communications
5641 papers in training set
Top 44%
1.8%
12
Nature Human Behaviour
95 papers in training set
Top 1%
1.8%
13
Behavior Research Methods
30 papers in training set
Top 0.3%
1.7%
14
Nutrients
67 papers in training set
Top 1%
1.4%
15
Wellcome Open Research
67 papers in training set
Top 1.0%
1.2%
16
npj Digital Medicine
118 papers in training set
Top 3%
1.2%
17
The Lancet Public Health
20 papers in training set
Top 0.3%
1.0%
18
Royal Society Open Science
214 papers in training set
Top 6%
0.9%
19
iScience
1154 papers in training set
Top 33%
0.9%
20
American Journal of Epidemiology
67 papers in training set
Top 1%
0.9%
21
Preventive Medicine
11 papers in training set
Top 0.2%
0.9%
22
Frontiers in Public Health
148 papers in training set
Top 6%
0.9%
23
JMIR Research Protocols
21 papers in training set
Top 1%
0.9%
24
BMJ Paediatrics Open
24 papers in training set
Top 0.5%
0.9%
25
BMC Research Notes
33 papers in training set
Top 1%
0.6%
26
Scientific Data
209 papers in training set
Top 3%
0.6%
27
Frontiers in Psychology
56 papers in training set
Top 2%
0.6%
28
Physiology & Behavior
31 papers in training set
Top 0.6%
0.6%
29
Public Health Nutrition
15 papers in training set
Top 0.5%
0.6%
30
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
42 papers in training set
Top 1.0%
0.6%