Exploring the design and utility of an integrated web-based chatbot for young adults to support healthy eating: a qualitative study

Author:

Ashton Lee M,Adam Marc TP,Whatnall Megan,Rollo Megan E,Burrows Tracy L,Hansen Vibeke,Collins Clare EORCID

Abstract

Abstract Background There is a lack of understanding of the potential utility of a chatbot integrated into a website to support healthy eating among young adults. Therefore, the aim was to interview key informants regarding potential utility and design of a chatbot to: (1) increase young adults’ return rates and engagement with a purpose-built healthy eating website and, (2) improve young adults’ diet quality. Methods Eighteen qualitative, semi-structured interviews were conducted across three stakeholder groups: (i) experts in dietary behaviour change in young adults (n = 6), (ii) young adult users of a healthy eating website (n = 7), and (iii) experts in chatbot design (n = 5). Interview questions were guided by a behaviour change framework and a template analysis was conducted using NVivo. Results Interviewees identified three potential roles of a chatbot for supporting healthy eating in young adults; R1: improving healthy eating knowledge and facilitating discovery, R2: reducing time barriers related to healthy eating, R3: providing support and social engagement. To support R1, the following features were suggested: F1: chatbot generated recommendations and F2: triage to website information or externally (e.g., another website) to address current user needs. For R2, suggested features included F3: nudge or behavioural prompts at critical moments and F4: assist users to navigate healthy eating websites. Finally, to support R3 interviewees recommended the following features: F5: enhance interactivity, F6: offer useful anonymous support, F7: facilitate user connection with content in meaningful ways and F8: outreach adjuncts to website (e.g., emails). Additional ‘general’ chatbot features included authenticity, personalisation and effective and strategic development, while the preferred chatbot style and language included tailoring (e.g., age and gender), with a positive and professional tone. Finally, the preferred chatbot message subjects included training (e.g., would you like to see a video to make this recipe?), enablement (e.g., healthy eating doesn’t need to be expensive, we’ve created a budget meal plan, want to see?) and education or informative approaches (e.g., “Did you know bananas are high in potassium which can aid in reducing blood pressure?”). Conclusion Findings can guide chatbot designers and nutrition behaviour change researchers on potential chatbot roles, features, style and language and messaging in order to support healthy eating knowledge and behaviours in young adults.

Funder

nib Foundation

Publisher

Springer Science and Business Media LLC

Subject

Nutrition and Dietetics,Physical Therapy, Sports Therapy and Rehabilitation,Medicine (miscellaneous)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3