The Use of Artificial Intelligence–Based Conversational Agents (Chatbots) for Weight Loss: Scoping Review and Practical Recommendations

Abstract

Background Overweight and obesity have now reached a state of a pandemic despite the clinical and commercial programs available. Artificial intelligence (AI) chatbots have a strong potential in optimizing such programs for weight loss. Objective This study aimed to review AI chatbot use cases for weight loss and to identify the essential components for prolonging user engagement. Methods A scoping review was conducted using the 5-stage framework by Arksey and O’Malley. Articles were searched across nine electronic databases (ACM Digital Library, CINAHL, Cochrane Central, Embase, IEEE Xplore, PsycINFO, PubMed, Scopus, and Web of Science) until July 9, 2021. Gray literature, reference lists, and Google Scholar were also searched. Results A total of 23 studies with 2231 participants were included and evaluated in this review. Most studies (8/23, 35%) focused on using AI chatbots to promote both a healthy diet and exercise, 13% (3/23) of the studies used AI chatbots solely for lifestyle data collection and obesity risk assessment whereas only 4% (1/23) of the studies focused on promoting a combination of a healthy diet, exercise, and stress management. In total, 48% (11/23) of the studies used only text-based AI chatbots, 52% (12/23) operationalized AI chatbots through smartphones, and 39% (9/23) integrated data collected through fitness wearables or Internet of Things appliances. The core functions of AI chatbots were to provide personalized recommendations (20/23, 87%), motivational messages (18/23, 78%), gamification (6/23, 26%), and emotional support (6/23, 26%). Study participants who experienced speech- and augmented reality–based chatbot interactions in addition to text-based chatbot interactions reported higher user engagement because of the convenience of hands-free interactions. Enabling conversations through multiple platforms (eg, SMS text messaging, Slack, Telegram, Signal, WhatsApp, or Facebook Messenger) and devices (eg, laptops, Google Home, and Amazon Alexa) was reported to increase user engagement. The human semblance of chatbots through verbal and nonverbal cues improved user engagement through interactivity and empathy. Other techniques used in text-based chatbots included personally and culturally appropriate colloquial tones and content; emojis that emulate human emotional expressions; positively framed words; citations of credible information sources; personification; validation; and the provision of real-time, fast, and reliable recommendations. Prevailing issues included privacy; accountability; user burden; and interoperability with other databases, third-party applications, social media platforms, devices, and appliances. Conclusions AI chatbots should be designed to be human-like, personalized, contextualized, immersive, and enjoyable to enhance user experience, engagement, behavior change, and weight loss. These require the integration of health metrics (eg, based on self-reports and wearable trackers), personality and preferences (eg, based on goal achievements), circumstantial behaviors (eg, trigger-based overconsumption), and emotional states (eg, chatbot conversations and wearable stress detectors) to deliver personalized and effective recommendations for weight loss.

SlimMe, a Chatbot With Artificial Empathy for Personal Weight Management: System Design and Finding

“…Therefore, an intervention that provides real-time and personalized emotional support, for instance, AI chatbots, yields a promising approach to prolonging the efficacy of weight loss intervention. However, this requires the chatbot to enhance its ability to have a more accurate human-like conversation, especially when users experience negative emotional feelings during a vulnerable situation in their weight loss efforts ( 9 ). A previous systematic review of chatbot intervention for weight management showed no valid evidence of the efficacy of chatbot intervention for weight loss ( 28 ).…”

“…Unlike traditional text-based messaging systems that still need a human operator to respond to a user message, chatbot technology enables users to have a real-time and engaging conversation with a computer as if they are talking to a human. This new communication platform has been shown to enrich the user experience and improve user engagement because it can quickly express empathy in response to user emotions, which is beneficial for successful long-term weight management ( 8 , 9 ).…”

“…Moreover, some AI chatbots are also equipped with real-time sentiment analysis features to recognize user emotions. Once the chatbot analyzes the user sentiment, it will then direct cognitive responses such as empathic conversation and human–machine emotional bonding, potentially enhancing user experience and prolonging user engagement ( 9 ).…”

“…Although there are several AI chatbots developed to support weight loss management, a systematic review on AI chatbot interventions in changing physical activity, healthy eating, and weight management behaviors showed that, among nine studies included, more than half of the studies focused on promoting physical activity and only limited studies focused on a healthy diet and weight status ( 28 ). Moreover, other scoping reviews on AI chatbots for weight loss showed that the use of empathic chatbot functions in supporting a behavior change framework to guide AI chatbot development is still unclear due to a limited number of publications ( 9 ). As a result, less is known about incorporating chatbot ability to express empathy in developing an effective weight management program.…”

User preferences for a physical activity chatbot connected to an activity tracker and integrated into a social media platform

“…Previous research shows that youth are interested in interacting with small talks with chatbots [21]. The human semblance of chatbots, use of emojis and use of colloquial tones that emulate human emotional expressions are also preferred users features that increase their engagement [22].…”