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        <title>Summarizing Behavioral Change Goals from SMS Exchanges to Support Health Coaches</title>
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    <abstract>Regular physical activity is associated with a reduced risk of chronic diseases such as type 2 diabetes and improved mental well-being. Yet, more than half of the US population is insufficiently active. Health coaching has been successful in promoting healthy behaviors. In this paper, we present our work towards assisting health coaches by extracting the physical activity goal the user and coach negotiate via text messages. We show that information captured by dialogue acts can help to improve the goal extraction results. We employ both traditional and transformer-based machine learning models for dialogue acts prediction and find them statistically indistinguishable in performance on our health coaching dataset. Moreover, we discuss the feedback provided by the health coaches when evaluating the correctness of the extracted goal summaries. This work is a step towards building a virtual assistant health coach to promote a healthy lifestyle.</abstract>
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%0 Conference Proceedings
%T Summarizing Behavioral Change Goals from SMS Exchanges to Support Health Coaches
%A Gupta, Itika
%A Di Eugenio, Barbara
%A Ziebart, Brian D.
%A Liu, Bing
%A Gerber, Ben S.
%A Sharp, Lisa K.
%S Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2021
%8 jul
%I Association for Computational Linguistics
%C Singapore and Online
%F gupta-etal-2021-summarizing
%X Regular physical activity is associated with a reduced risk of chronic diseases such as type 2 diabetes and improved mental well-being. Yet, more than half of the US population is insufficiently active. Health coaching has been successful in promoting healthy behaviors. In this paper, we present our work towards assisting health coaches by extracting the physical activity goal the user and coach negotiate via text messages. We show that information captured by dialogue acts can help to improve the goal extraction results. We employ both traditional and transformer-based machine learning models for dialogue acts prediction and find them statistically indistinguishable in performance on our health coaching dataset. Moreover, we discuss the feedback provided by the health coaches when evaluating the correctness of the extracted goal summaries. This work is a step towards building a virtual assistant health coach to promote a healthy lifestyle.
%U https://aclanthology.org/2021.sigdial-1.31
%P 276-289

Markdown (Informal)

[Summarizing Behavioral Change Goals from SMS Exchanges to Support Health Coaches](https://aclanthology.org/2021.sigdial-1.31) (Gupta et al., SIGDIAL 2021)

• Summarizing Behavioral Change Goals from SMS Exchanges to Support Health Coaches (Gupta et al., SIGDIAL 2021)

ACL

• Itika Gupta, Barbara Di Eugenio, Brian D. Ziebart, Bing Liu, Ben S. Gerber, and Lisa K. Sharp. 2021. Summarizing Behavioral Change Goals from SMS Exchanges to Support Health Coaches. In Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 276–289, Singapore and Online. Association for Computational Linguistics.