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Evaluating Domain-Independent Small Talk Conversations to Improve Clinical Communication Interaction for Human and Machine

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Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14028))

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Abstract

Conversation as trivial as “small talk” has a significant impact on human relationships, including in clinical care environments. Evidence suggests that small talk can improve health and clinical outcomes. This study aims to analyze the characteristics of domain-independent small talk collected from a sample of conversations. We reviewed the impact of personality factors of the conversation and present our findings on specific factors that are correlated with it. In addition, we discuss the possibility of integrating small talk into our existing ontology-driven dialogue systems, which can assist machines in engaging with and building trust with patients in the clinical environments. Future direction will involve implementing the ontology model and integrating it with a health dialogue engine to test the effectiveness of automated small talk.

C. Aguilar, M. Amith and L. Tang—Contributed Equally.

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Notes

  1. 1.

    Exemption status, IRB2021–0017 and HSC-SBMI-21-0230.

  2. 2.

    https://ipip.ori.org/newScoringInstructions.htm.

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Acknowledgement

Research was supported by NIH grant under Award Number U24AI163375, the Cancer Prevention Research Institute of Texas Grant # RP220244 and the UTHealth-Houston-CPRIT Innovation for Cancer Prevention Research Training Program Summer Undergraduate Fellowship (Cancer Prevention & Research Institute of Texas Grant #RP210042) and the UTHealth-Houston Prevention Research Center. We thank Mike Garcia for assisting in the evaluation process.

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Authors and Affiliations

  1. University of Texas, Austin, TX, 78705, USA

    Chloe Aguilar

  2. Department of Biostatistics and Data Science, School of Public and Population Health, Galveston, TX, 77555-0128, USA

    Muhammad Amith

  3. Texas A&M University, College Station, TX, 77843, USA

    Lu Tang & Tazrin Khan

  4. University of Texas Health Science Center at Houston, Houston, TX, 77030, USA

    Jane Hamilton, Lara S. Savas, Danniel Rhee & Cui Tao

  5. Department of Internal Medicine, John Sealy School of Medicine, Galveston, TX, 77555-0128, USA

    Muhammad Amith

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  1. Chloe Aguilar
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Correspondence to Cui Tao .

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  1. Purdue University, West Lafayette, IN, USA

    Vincent G. Duffy

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Aguilar, C. et al. (2023). Evaluating Domain-Independent Small Talk Conversations to Improve Clinical Communication Interaction for Human and Machine. In: Duffy, V.G. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. HCII 2023. Lecture Notes in Computer Science, vol 14028. Springer, Cham. https://doi.org/10.1007/978-3-031-35741-1_25

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  • DOI: https://doi.org/10.1007/978-3-031-35741-1_25

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