Patient Perceptions of Using Voice-Based Dietary Assessment Tools Among Older Adults

Tiffany M. Driesse, Xiaohui Liang, Michael Fowler, Jing Yuan, and John A. Batsis

Background: Poor diet among older adults is a risk factor for developing multiple chronic diseases. Dietary recall comprises an important component in intervention research and clinical care. Commonly used tools include the web-based automated self-administered 24-hour assessment (ASA-24). Yet voice assistant (VAS) systems (i.e., Amazon Alexa) have not been developed for this purpose. Hence, we evaluated patient perceptions on performing a VAS-based dietary assessment among older adults.

Methods: Community-dwelling adults (age 65+ years) participated in two virtual sessions who reported their past 24-hour intake, first using ASA-24, and then using a VAS. All completed a Likert questionnaire (binary, % strongly agree/strongly disagree reported) regarding the simplicity of using both systems, completion time, and user satisfaction. Semi-structured interviews allowed us to ask about technology use.

Results: Of the 40 participants (100% enrolled), mean age was 69±1.0 years (85% female, 100% white, 5% Latinx). Only 40% owned a VAS; 60% reported having VAS experience prior to the study. After completing both sessions, 80% preferred a VAS over the ASA-24. Participants reported that web-based recalls were unnecessarily complex (60%), time-consuming (50%), and 60% did not wish to use them. Comparatively, VAS recalls were intuitive (75%), easily reportable (85%), and there was willingness to report food while preparing meals (85%). In 16 participants, we evaluated themes of VAS use including easier navigation, less time, and ability to have a natural conversation.

Conclusion: A VAS provides a more convenient, conversational, and computerless interaction to report meals over web-based solutions suggesting they hold promise for dietary recall in older adults.

This poster has been accepted for presentation at the Gerontological Society of America (GSA) 2022 Annual Scientific Meeting 2022.

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