ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

Advances in Psychological Science ›› 2023, Vol. 31 ›› Issue (4): 669-683.doi: 10.3724/SP.J.1042.2023.00669

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How to establish a digital therapeutic alliance between chatbots and users: The role of relational cues

MO Ran1, FANG Zuozhi4,#, FANG Jiandong1,2,3()   

  1. 1Department of Psychology, Faculty of Education, Guangxi Normal University, Guilin 541006, China
    2Guangxi University and College Key Laboratory of Cognitive Neuroscience and Applied Psychology, Guangxi Normal University, Guilin 541006, China
    3Guangxi Ethnic Education Development Research Center, Key research base of Humanities and Social Sciences in Guangxi Universities, Guilin 541006, China
    4School of Psychology, Shaanxi Normal University, Xi’an 710062, China
  • Received:2022-06-11 Online:2023-04-15 Published:2022-12-30
  • Contact: FANG Jiandong E-mail:bdjs2004@163.com

Abstract:

Recently, the rapid development of Internet technology has constantly promoted the digital process of the mental health industry. Internet-based self-help interventions (ISIs) have gradually become an effective supplement to traditional psychological counseling/psychotherapy. Although the feasibility and effectiveness of ISIs have been widely verified, some problems, such as low user engagement and high dropout rate in the actual application process, affect the quality and efficiency of ISIs. To solve the above problems, researchers began to combine the concept of the therapeutic alliance (TA) with ISIs and tried to establish TA with users in a digital environment by using applications to promote user engagement. This TA formed in a digital environment is called a digital therapeutic alliance (DTA). The gap between the natural language conversation ability of chatbots and human beings has gradually narrowed due to the continuous breakthrough of artificial intelligence technology. Compared with traditional ISI programs, chatbots are more likely to develop real social relations with human beings. This study proposes to embed chatbots in ISI programs and use personified chatbots with emotion recognition and interaction capabilities to establish and develop DTAs with users to make up for the lack of human guidance in ISIs to some extent. Also, this study integrates multidisciplinary theories such as mind perception theory, social cue reduction theory, the investment model of personal relationships, and self-determination theory. These theories are useful as follows: first, to build a model from the perspective of human-computer interaction (HCI); second, to explore the influencing factors and mechanisms in the process of establishing DTA between chatbots and users from both cognitive and emotional aspects; and lastly, to put forward several design features of chatbots that are conducive to strengthening DTA. Specifically, we can design relational cues for chatbots based on the facilitation factors of TA in traditional psychological counseling/psychotherapy, such as making chatbots show the characteristics of amiability, respectfulness, listening, encouragement, sincere comprehension, and mutual trust. The users can have a positive cognitive and emotional experience and establish and develop high-quality DTAs with them. This scheme not only helps chatbots improve artificial wisdom but also provides a new way to solve the problem of low user engagement, promotes the development of HCI and DTA theories, and advances the intelligent process of digital mental health in China. In addition to a more rigorous investigation of the factors that affect DTA, future research should consider how to integrate advanced technologies in computer science into ISIs to optimize the user experience of ISIs and promote the development of DTA, prepare a special scale based on the particularity of ISIs types and scenes, and unify the measurement specifications. It is also necessary to test the influence of different therapies and subjects, such as age, sex, symptoms, and other factors, on DTA in ISIs.

Key words: digital therapeutic alliance, chatbot, relational cues

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