Cited by 41Technology Use by Older AdultsUsability and User Interface DesignMobile Health and mHealth Applications

Design and Usability Evaluation of Mobile Voice-Added Food Reporting for Elderly People: Randomized Controlled Trial

Open access
Liu, Ying-Chieh, Chen, Chien-Hung, Lin, Yu-Sheng, Chen, Hsin-Yun, Irianti, Denisa, Jen, Ting-Ni, Yeh, Jou-Yin, Chiu, Sherry Yueh-Hsia·2020·JMIR mHealth and uHealth

Published version of a preprint

Abstract

Background: Advances in voice technology have raised new possibilities for apps related to daily health maintenance. However, the usability of such technologies for older users remains unclear and requires further investigation. Objective: We designed and evaluated two innovative mobile voice-added apps for food intake reporting, namely voice-only reporting (VOR) and voice-button reporting (VBR). Each app features a unique interactive procedure for reporting food intake. With VOR, users verbally report the main contents of each dish, while VBR provides both voice and existing touch screen inputs for food intake reporting. The relative usability of the two apps was assessed through the metrics of accuracy, efficiency, and user perception. Methods: The two mobile apps were compared in a head-to-head parallel randomized trial evaluation. A group of 57 adults aged 60-90 years (12 male and 45 female participants) was recruited from a retirement community and randomized into two experimental groups, that is, VOR (n=30) and VBR (n=27) groups. Both groups were tested using the same set of 17 food items including dishes and beverages selected and allocated to present distinct breakfast, lunch, and dinner meals. All participants used a 7-inch tablet computer for the test. The resulting data were analyzed to evaluate reporting accuracy and time efficiency, and the system usability scale (SUS) was used to measure user perception. Results: For eight error types identified in the experiment, the VBR group participants were significantly (P<.001) more error prone owing to the required use of button-tapping actions. The highest error rates in the VOR group were related to incomprehensible reporting speech (28/420, 6.7%), while the highest error rates in the VBR group were related to failure to make required button taps (39/378, 10.3%). The VOR group required significantly (P<.001) less time to complete food reporting. The overall subjective reactions of the two groups based on the SUS surpassed the benchmark and were not significantly different (P=.20). Conclusions: Experimental results showed that VOR outperformed VBR, suggesting that voice-only food input reporting is preferable for elderly users. Voice-added apps offer a potential mechanism for the self-management of dietary intake by elderly users. Our study contributes an evidence-based evaluation of prototype design and selection under a user-centered design model. The results provide a useful reference for selecting optimal user interaction design. Trial Registration: International Standard Randomized Controlled Trial Registry ISRCTN17335889; http://www.isrctn.com/ISRCTN17335889.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/20317

Cites

35 of 35 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Older adults prefer voice interfaces over text-based ones.

    “highlighting their preference for voice interfaces over text-based ones [30, 34, 61].”

    From Situated Understanding of Errors in Older Adults' Interactions with Voice Assistants: A Month-Long, In-Home Study (2026) · cites this paper as [34]

    The Abstract Conclusions say the voice-only food-reporting app outperformed the voice-button app, suggesting it was preferable for elderly users. But the comparison was not with a text-based interface, and the Results section reports no significant difference in overall usability ratings between the two apps. The paper therefore does not establish the stated preference for voice over text. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

7 of the 42 references couldn’t be matched to a known paper.

Research works printed but not linked: 7

  1. [15]Ventola CL Mobile devices and apps for health care professionals: Uses and benefits Pharm Ther 2014 5 39 5 356 64 24883008 PMC4029126 24883008
  2. [17]Johnson J Finn K Designing User Interfaces for an Aging Population: Towards Universal Design 2017 2 16 Cambridge Morgan Kaufmann
  3. [19]Grindrod KA Li M Gates A Evaluating user perceptions of mobile medication management applications with older adults: A usability study JMIR Mhealth Uhealth 2014 3 14 2 1 e11 10.2196/mhealth.3048 25099993 25099993 PMC4114457 · DOI
  4. [33]Deng C Graz J Generating randomization schedules using SAS programming 2002 27th Annual SAS Users Group International Conference Apr 14-17, 2002 Orlando, FL
  5. [35]Sauro J Lewis JR Quantifying the User Experience: Practical Statistics for User Research 2016 7 12 Cambridge Morgan Kaufmann
  6. [36]Bangor A Kortum P Miller J Determining what individual SUS scores mean: adding and adjective rating scale Journal of Usability Studies 2009 5 4 3 114 123
  7. [41]Hartson R Pyla PS The UX Book: Agile UX Design for a Quality User Experience 2018 11 2 Cambridge Morgan Kaufmann

Cited by

Sorted by citations

Authors
Liu, Y.-C., Chen, C.-H., Lin, Y.-S., Chen, H.-Y., Irianti, D., Jen, T.-N., Yeh, J.-Y., & Chiu, S. Y.-H.
Affiliations
  • Chang Gung University (TW)
  • Institute for Information Industry (TW)
  • Chang Gung Memorial Hospital (TW)
Corresponding author
Chiu, Sherry Yueh-Hsia
Venue
JMIR mHealth and uHealth
Published
2020-09-28
Volume
8
Issue
9
Pages
e20317
ISSN
2291-5222 (ISSN-L)
OpenAlex
W3088002417
Cited by
41
References
42
Citations by year
2026: 2 · 2025: 6 · 2024: 7 · 2023: 5 · 2022: 12 · 2021: 8 · 2020: 1
FWCI
9.78
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • JMIR mhealth and uhealth (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Demography › Technology Use by Older Adults
  • Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Keywords
voice user interface, dietary self-management, older adults, usability, speech recognition errors, user-centered design, mobile health apps, System Usability Scale, interaction design, retirement community residents
MeSH terms
Aged, Aged, 80 and over, Eating, Female, Humans, Male, Middle Aged, Mobile Applications

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review