Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder

Yu Ching Lin; Yan Ming Chen; Chih Ching Chuang; Chien Wen Yuan; Nanyi Bi; Hu Ming Chang; Ming Chyi Huang; Chuang Wen You

doi:10.1145/3706599.3720128

Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder

Yu Ching Lin
, Yan Ming Chen
, Chih Ching Chuang
, Chien Wen Yuan
, Nanyi Bi
, Hu Ming Chang
, Ming Chyi Huang
, Chuang Wen You^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Chatbots are emerging as a promising tool for the provision of continuous care outside clinical settings; however, the perspectives of both patients and their companions on engaging with chatbot-based support for AUD interventions remain largely underexplored. This study employed a Kano two-factor model to evaluate the integration of chatbot-based technological support in AUD treatment. Our analysis revealed that patients tend to focus on self-management, while their companions prioritize communication and emotional support. Patients were enthusiastic about adjusting chatbot personality settings according to their current emotional state. They also strongly favored having the chatbot update their companions and act as a proxy in providing encouragement. These insights underscore the importance of designing chatbot systems tailored to both patients and companions, particularly in the development of personality settings and emotional support features.

Original language	English
Title of host publication	CHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems
Publisher	Association for Computing Machinery
ISBN (Electronic)	9798400713958
DOIs	https://doi.org/10.1145/3706599.3720128
Publication status	Published - 2025 Apr 26
Externally published	Yes
Event	2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025 - Yokohama, Japan Duration: 2025 Apr 26 → 2025 May 1

Publication series

Name	Conference on Human Factors in Computing Systems - Proceedings

Conference

Conference	2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025
Country/Territory	Japan
City	Yokohama
Period	2025/04/26 → 2025/05/01

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Alcohol Use Disorders
Chatbot Technology
Kano Method

ASJC Scopus subject areas

Human-Computer Interaction
Computer Graphics and Computer-Aided Design
Software

Access to Document

10.1145/3706599.3720128

Cite this

Lin, Y. C., Chen, Y. M., Chuang, C. C., Yuan, C. W., Bi, N., Chang, H. M., Huang, M. C., & You, C. W. (2025). Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder. In CHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems Article 566 (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3706599.3720128

Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder. / Lin, Yu Ching; Chen, Yan Ming; Chuang, Chih Ching et al.
CHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2025. 566 (Conference on Human Factors in Computing Systems - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lin, YC, Chen, YM, Chuang, CC, Yuan, CW, Bi, N, Chang, HM, Huang, MC & You, CW 2025, Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder. in CHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems., 566, Conference on Human Factors in Computing Systems - Proceedings, Association for Computing Machinery, 2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025, Yokohama, Japan, 2025/04/26. https://doi.org/10.1145/3706599.3720128

Lin YC, Chen YM, Chuang CC, Yuan CW, Bi N, Chang HM et al. Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder. In CHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2025. 566. (Conference on Human Factors in Computing Systems - Proceedings). doi: 10.1145/3706599.3720128

Lin, Yu Ching ; Chen, Yan Ming ; Chuang, Chih Ching et al. / Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder. CHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2025. (Conference on Human Factors in Computing Systems - Proceedings).

@inproceedings{aae76d52d90247c2b3b7b7ae0b2efbb1,

title = "Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder",

abstract = "Chatbots are emerging as a promising tool for the provision of continuous care outside clinical settings; however, the perspectives of both patients and their companions on engaging with chatbot-based support for AUD interventions remain largely underexplored. This study employed a Kano two-factor model to evaluate the integration of chatbot-based technological support in AUD treatment. Our analysis revealed that patients tend to focus on self-management, while their companions prioritize communication and emotional support. Patients were enthusiastic about adjusting chatbot personality settings according to their current emotional state. They also strongly favored having the chatbot update their companions and act as a proxy in providing encouragement. These insights underscore the importance of designing chatbot systems tailored to both patients and companions, particularly in the development of personality settings and emotional support features.",

keywords = "Alcohol Use Disorders, Chatbot Technology, Kano Method",

author = "Lin, \{Yu Ching\} and Chen, \{Yan Ming\} and Chuang, \{Chih Ching\} and Yuan, \{Chien Wen\} and Nanyi Bi and Chang, \{Hu Ming\} and Huang, \{Ming Chyi\} and You, \{Chuang Wen\}",

note = "Publisher Copyright: {\textcopyright} 2025 Copyright held by the owner/author(s).; 2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025 ; Conference date: 26-04-2025 Through 01-05-2025",

year = "2025",

month = apr,

day = "26",

doi = "10.1145/3706599.3720128",

language = "English",

series = "Conference on Human Factors in Computing Systems - Proceedings",

publisher = "Association for Computing Machinery",

booktitle = "CHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems",

}

TY - GEN

T1 - Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder

AU - Lin, Yu Ching

AU - Chen, Yan Ming

AU - Chuang, Chih Ching

AU - Yuan, Chien Wen

AU - Bi, Nanyi

AU - Chang, Hu Ming

AU - Huang, Ming Chyi

AU - You, Chuang Wen

PY - 2025/4/26

Y1 - 2025/4/26

N2 - Chatbots are emerging as a promising tool for the provision of continuous care outside clinical settings; however, the perspectives of both patients and their companions on engaging with chatbot-based support for AUD interventions remain largely underexplored. This study employed a Kano two-factor model to evaluate the integration of chatbot-based technological support in AUD treatment. Our analysis revealed that patients tend to focus on self-management, while their companions prioritize communication and emotional support. Patients were enthusiastic about adjusting chatbot personality settings according to their current emotional state. They also strongly favored having the chatbot update their companions and act as a proxy in providing encouragement. These insights underscore the importance of designing chatbot systems tailored to both patients and companions, particularly in the development of personality settings and emotional support features.

AB - Chatbots are emerging as a promising tool for the provision of continuous care outside clinical settings; however, the perspectives of both patients and their companions on engaging with chatbot-based support for AUD interventions remain largely underexplored. This study employed a Kano two-factor model to evaluate the integration of chatbot-based technological support in AUD treatment. Our analysis revealed that patients tend to focus on self-management, while their companions prioritize communication and emotional support. Patients were enthusiastic about adjusting chatbot personality settings according to their current emotional state. They also strongly favored having the chatbot update their companions and act as a proxy in providing encouragement. These insights underscore the importance of designing chatbot systems tailored to both patients and companions, particularly in the development of personality settings and emotional support features.

KW - Alcohol Use Disorders

KW - Chatbot Technology

KW - Kano Method

UR - https://www.scopus.com/pages/publications/105005757277

UR - https://www.scopus.com/pages/publications/105005757277#tab=citedBy

U2 - 10.1145/3706599.3720128

DO - 10.1145/3706599.3720128

M3 - Conference contribution

AN - SCOPUS:105005757277

T3 - Conference on Human Factors in Computing Systems - Proceedings

BT - CHI EA 2025 - Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

T2 - 2025 CHI Conference on Human Factors in Computing Systems, CHI EA 2025

Y2 - 26 April 2025 through 1 May 2025

ER -

Using the Kano Method to Evaluate Features of Chatbot-Based Technological Support for Recovery from Alcohol Use Disorder

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this