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The Construction of Critical Factors for Successfully Introducing Chatbots into Mental Health Services in the Army: Using a Hybrid MCDM Approach

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  • Ming-Ching Hsu

    (Department of Education, University of Taipei, Taipei 100234, Taiwan
    Military Common Curriculum Center, National Defense University, Taoyuan 334301, Taiwan)

Abstract

Previous research has shown that although military personnel are at high risk of developing mental disorders because of the excessive stress caused by their work, they also display low levels of intention to seek assistance because of the military culture. This, in turn, creates exorbitant costs for their respective countries. With the rapid development of artificial intelligence (AI)-related digital technologies, chatbots have been successfully applied to mental health services. Although the introduction of chatbots into the military to assist with mental health services is not common, it may become a future trend. This study aims to construct the critical factors for introducing chatbots into mental health services in the military, the relationships between the effects, and a weighting system, to ensure that the introduction of chatbots complies with sustainable practices. This includes four stages. In the initial stage, in accordance with the AI-readiness framework, in combination with the findings of previous research and specialist recommendations, preliminary indicators and items were developed. In the second stage, Fuzzy Delphi was used to confirm each dimension and indicator. In the third stage, using DEMATEL, an influential-network-relation map (INRM) of dimensions and indicators was created. In the fourth stage, using DANP, the relationships between the effects of the indicators and the weighting system were established. The findings of this study indicated that: (1) the key to success includes four dimensions and twenty-one indicators; (2) there is an interdependent relationship between the four dimensions and twenty-one indicators, and they influence each other; and (3) the four dimensions are technologies, goals, boundaries, and activities, in order of importance. Finally, specific suggestions are put forward to provide references for future practical applications and research, drawing on the results of this research.

Suggested Citation

  • Ming-Ching Hsu, 2023. "The Construction of Critical Factors for Successfully Introducing Chatbots into Mental Health Services in the Army: Using a Hybrid MCDM Approach," Sustainability, MDPI, vol. 15(10), pages 1-22, May.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:7905-:d:1144902
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    References listed on IDEAS

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    1. Davenport, Thomas H., 2018. "The AI Advantage: How to Put the Artificial Intelligence Revolution to Work," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262039176, December.
    2. Kuan-Wei Huang & Jen-Hung Huang & Gwo-Hshiung Tzeng, 2016. "New Hybrid Multiple Attribute Decision-Making Model for Improving Competence Sets: Enhancing a Company’s Core Competitiveness," Sustainability, MDPI, vol. 8(2), pages 1-26, February.
    3. Dominik Siemon & Rangina Ahmad & Henrik Harms & Triparna de Vreede, 2022. "Requirements and Solution Approaches to Personality-Adaptive Conversational Agents in Mental Health Care," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
    4. Seal, K.H. & Metzler, T.J. & Gima, K.S. & Bertenthal, D. & Maguen, S. & Marmar, C.R., 2009. "Trends and risk factors for mental health diagnoses among Iraq and Afghanistan veterans using department of Veterans Affairs Health Care, 2002-2008," American Journal of Public Health, American Public Health Association, vol. 99(9), pages 1651-1658.
    5. Iuan-Yuan Lu & Tsuanq Kuo & Ting-Syuan Lin & Gwo-Hshiung Tzeng & Shan-Lin Huang, 2016. "Multicriteria Decision Analysis to Develop Effective Sustainable Development Strategies for Enhancing Competitive Advantages: Case of the TFT-LCD Industry in Taiwan," Sustainability, MDPI, vol. 8(7), pages 1-31, July.
    6. Hong Chen & Ling Li & Yong Chen, 2021. "Explore success factors that impact artificial intelligence adoption on telecom industry in China," Journal of Management Analytics, Taylor & Francis Journals, vol. 8(1), pages 36-68, January.
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    2. James J. H. Liou & Tuong Thanh Vo, 2024. "Exploring the Relationships among Factors Influencing Healthcare Chatbot Adoption," Sustainability, MDPI, vol. 16(12), pages 1-25, June.
    3. Darıcı, Sefer & Riaz, Muhammad & Demir, Gülay & Gencer, Zekiye Tamer & Pamucar, Dragan, 2024. "How will I break AI? Post-Luddism in the AI age: Fuzzy MCDM synergy," Technological Forecasting and Social Change, Elsevier, vol. 202(C).

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