The Effects of Health Care Chatbot Personas With Different Social Roles on the Client-Chatbot Bond and Usage Intentions: Development of a Design Codebook and Web-Based Study

Background The working alliance refers to an important relationship quality between health professionals and clients that robustly links to treatment success. Recent research shows that clients can develop an affective bond with chatbots. However, few research studies have investigated whether this perceived relationship is affected by the social roles of differing closeness a chatbot can impersonate and by allowing users to choose the social role of a chatbot. Objective This study aimed at understanding how the social role of a chatbot can be expressed using a set of interpersonal closeness cues and examining how these social roles affect clients’ experiences and the development of an affective bond with the chatbot, depending on clients’ characteristics (ie, age and gender) and whether they can freely choose a chatbot’s social role. Methods Informed by the social role theory and the social response theory, we developed a design codebook for chatbots with different social roles along an interpersonal closeness continuum. Based on this codebook, we manipulated a fictitious health care chatbot to impersonate one of four distinct social roles common in health care settings—institution, expert, peer, and dialogical self—and examined effects on perceived affective bond and usage intentions in a web-based lab study. The study included a total of 251 participants, whose mean age was 41.15 (SD 13.87) years; 57.0% (143/251) of the participants were female. Participants were either randomly assigned to one of the chatbot conditions (no choice: n=202, 80.5%) or could freely choose to interact with one of these chatbot personas (free choice: n=49, 19.5%). Separate multivariate analyses of variance were performed to analyze differences (1) between the chatbot personas within the no-choice group and (2) between the no-choice and the free-choice groups. Results While the main effect of the chatbot persona on affective bond and usage intentions was insignificant (P=.87), we found differences based on participants’ demographic profiles: main effects for gender (P=.04, ηp2=0.115) and age (P<.001, ηp2=0.192) and a significant interaction effect of persona and age (P=.01, ηp2=0.102). Participants younger than 40 years reported higher scores for affective bond and usage intentions for the interpersonally more distant expert and institution chatbots; participants 40 years or older reported higher outcomes for the closer peer and dialogical-self chatbots. The option to freely choose a persona significantly benefited perceptions of the peer chatbot further (eg, free-choice group affective bond: mean 5.28, SD 0.89; no-choice group affective bond: mean 4.54, SD 1.10; P=.003, ηp2=0.117). Conclusions Manipulating a chatbot’s social role is a possible avenue for health care chatbot designers to tailor clients’ chatbot experiences using user-specific demographic factors and to improve clients’ perceptions and behavioral intentions toward the chatbot. Our results also emphasize the benefits of letting clients freely choose between chatbots

Chatbots as components of information and analytical systems for psychological support of athletes (literary review)

Рукопись поступила в редакцию: 16.09.2022. Принята к публикации: 15.10.2022.Received: 16.09.2022. Accepted: 15.10.2022.В статье рассматриваются актуальные вопросы цифровизации психологического сопровождения в спорте. Приводится обоснование востребованности современных решений, основанных на цифровых технологиях с использованием искусственного интеллекта, в подготовке спортсменов. Результаты проведенного литературного обзора показали, что для разработки информационно-аналитических систем психологического сопровождения спортсменов, как одного из перспективных решений систематизации научно-практического знания, в соответствии с государственной политикой РФ по развитию физической культуры и спорта с использованием цифровых технологий, целесообразно использование чат-ботов. Представленный обзор существующих разработок позволяет констатировать, что несмотря на их стремительное развитие в нашей повседневной жизни, в сфере спорта они представлены в меньшей степени. Существующие решения на данном этапе развития далеки от совершенства и нуждаются в серьезной доработке как с технической точки зрения, так и синтеза междисциплинарного научного знания.The article deals with topical issues of digitalization of psychological support in sports. The authors substantiate the demand for modern solutions based on digital technologies using artificial intelligence in the athletes’ preparation. The results of the literature review showed that for the development of information and analytical systems for psychological support of athletes, as one of the promising solutions for the systematization of scientific and practical knowledge, in accordance with the state policy of the Russian Federation on the development of physical culture and sports using digital technologies, it is advisable to use chatbots. The presented review of existing developments allows us to state that despite their rapid development in our daily life, they are less represented in the field of sports. The existing solutions at this stage of development are far from perfect and need serious refinement both from a technical point of view and synthesis of interdisciplinary scientific knowledge

ЧАТ-БОТЫ КАК КОМПОНЕНТЫ ИНФОРМАЦИОННО-АНАЛИТИЧЕСКИХ СИСТЕМ ПСИХОЛОГИЧЕСКОГО СОПРОВОЖДЕНИЯ СПОРТСМЕНОВ (ЛИТЕРАТУРНЫЙ ОБЗОР)

The article deals with topical issues of digitalization of psychological support in sports. The authors substantiate the demand for modern solutions based on digital technologies using artificial intelligence in the athletes’ preparation. The results of the literature review showed that for the development of information and analytical systems for psychological support of athletes, as one of the promising solutions for the systematization of scientific and practical knowledge, in accordance with the state policy of the Russian Federation on the development of physical culture and sports using digital technologies, it is advisable to use chatbots. The presented review of existing developments allows us to state that despite their rapid development in our daily life, they are less represented in the field of sports. The existing solutions at this stage of development are far from perfect and need serious refinement both from a technical point of view and synthesis of interdisciplinary scientific knowledge.В статье рассматриваются актуальные вопросы цифровизации психологического сопровождения в спорте. Приводится обоснование востребованности современных решений, основанных на цифровых технологиях с использованием искусственного интеллекта, в подготовке спортсменов. Результаты проведенного литературного обзора показали, что для разработки информационно-аналитических систем психологического сопровождения спортсменов, как одного из перспективных решений систематизации научно-практического знания, в соответствии с государственной политикой РФ по развитию физической культуры и спорта с использованием цифровых технологий, целесообразно использование чат-ботов. Представленный обзор существующих разработок позволяет констатировать, что несмотря на их стремительное развитие в нашей повседневной жизни, в сфере спорта они представлены в меньшей степени. Существующие решения на данном этапе развития далеки от совершенства и нуждаются в серьезной доработке как с технической точки зрения, так и синтеза междисциплинарного научного знания

Designing brand chatbots: The impact of chatbot’s personality on the user’s brand personality perception

Along with advancements in technologies, which include machine learning and artificial intelligence, chatbots are increasingly taking the place of employees that work as customer service agents and personal shoppers. Considering that the characteristics of employees can influence a consumer’s perception of brand personality (Aaker, 1997), this perception may also be affected by the chatbot’s personality. This paper aims to investigate the impact of a chatbot’s personality on a user’s perception of brand personality. Two brands, and their chatbots, are used as case studies. The empirical study comprises of two stages, in which the qualitative and the quantitative data are both gathered and analyzed. Firstly, an online survey was conducted to investigate the personalities of two existing brands and their respective chatbots. As a result, a gap in personality between one of the brands and its chatbot was identified. Next, two prototypes were built and then tested in the interview. One was the emulator of the current brand chatbot, and the other was a new chatbot designed to have a personality closer to the brand personality. The findings reveal that the chatbot’s personality may affect brand personality, even though the impact was smaller than expected because participants perceived that the two prototypes’ personalities were moderately close to the brand personality. Interestingly, interviewees revealed that the chatbot’s personality may have a greater influence if it is totally different from the brand personality. Based on the study findings, design considerations are suggested to help practitioners in designing brand chatbots

The Experience of Conversation and Relation with a Well-Being Chabot: Between Proximity and Remoteness

The article concerns the users’ experiences of interacting with well-being chatbots. The text shows how chatbots can act as virtual companions and, to some extent, therapists for people in their daily reality. It also reflects on why individuals choose such a form of support for their well-being, concerning, among others, the stigmatization aspect of mental health problems. The article discusses and compares various dimensions of users’ interactions with three popular chatbots: Wysa, Woebot, and Replika. The text both refers to the results of research on the well-being chatbots and, analytically, engages in a dialogue with the results discussed in the form of sociological (and philosophical) reflection. The issues taken up in the paper include an in-depth reflection on the aspects of the relationship between humans and chatbots that allow users to establish an emotional bond with their virtual companions. In addition, the consideration addresses the issue of a user’s sense of alienation when interacting with a virtual companion, as well as the problem of anxieties and dilemmas people may experience therein. In the context of alienation, the article also attempts to conceptualize that theme concerning available conceptual resources

AktiMotBot: A social media chatbot with activity tracker integration for motivating increased physical activity

The World Health Organization has reported that more than 80% of the world’s adolescent population is insufficiently physically active [1]. Up to five million deaths per year could be averted if the global population were more active[1]. The low adherence to physical activity shows the need to implement services that promote physical activity. In addition, it is crucial to educate people on the benefits of being physically active and the negative consequences sedentary behavior imposes. This thesis proposes a social media chatbot with the integration of an activity tracker that aims to motivate people to increase their daily step count. The chatbot, AktiMotBot, encourages people by implementing behavior change techniques in its messages and functionality. We use popular technology, such as social media applications, to ease access. Further, the use of chatbots has grown. A chatbot gives a service that is always available to the user and is cost-effective. In addition, chatbots have familiar interfaces that ease their use. Finally, activity data is integrated into the chatbot as a motivation and personalization tool, enabling monitoring behavior change. A thorough investigation of social media applications was conducted to ensure users’ privacy and security. A usability study investigated how potential users perceived the system, and the usability of the chatbot was scored as average. The results showed that the chatbot was able to increase the motivation of half of the participants. Finally, the findings from this research are that chatbots could motivate people to increase their physical activity levels and make people more aware of their step count

헬스케어를 위한 대화형 인공지능의 모사된 페르소나 디자인 및 사용자 경험 연구

학위논문(박사) -- 서울대학교대학원 : 인문대학 협동과정 인지과학전공, 2021.8. 이준환.디지털 헬스케어(Digital Healthcare) 기술의 발전은 일상 헬스케어 영역에서의 혁신을 주도 하고 있다. 이는 의학 전문가들의 정확한 진단, 질병의 치료를 도울 뿐만 아니라 사용자가 스스로 일상에서 자기관리를 할 수 있도록 돕는다. 디지털 헬스케어 기술의 대표적인 목표 중 하나는 효과적으로 헬스케어 서비스를 개인화 시키는 것인데, 이러한 측면에서 대화형 인공지능(Conversational AI)은 사용하기 쉽고 효율적인 비용으로 개인화된 서비스를 제공할 수 있기에 주목받고 있다. 기존의 개인화된 케어 서비스들의 경우는 대부분 의료기관의 질병치료 서비스들에 포함되었는데, 대화형 인공지능은 이러한 개인화된 케어 서비스의 영역을 일상에서의 질병 예방을 위한 관리로 확장하는데 기여한다. 일대일 대화를 통해 맞춤형 교육, 테라피, 그외의 관련 정보 등을 제공할 수 있다는 측면에서 일상 헬스케어에 적합한 디지털 헬스케어 기술로의 활용도가 높다. 이러한 이점으로 인해 다양한 역할을 가진 대화형 인공지능들의 개발이 이루어지고 있다. 그러나, 이러한 대화형 인공지능들에게 사용자의 선호도에 적합한 페르소나를 부여하는 연구는 드물게 이루어 지고 있다. 대화형 인공지능의 주요 기능인 자연어 기반 상호작용은 CASA 패러다임(CASA Paradigm)에서 제기하는 사용자가 시스템을 의인화하는 경향을 높인다. 때문에 페르소나에 대한 사용자의 선호도가 지속적인 대화형 인공지능의 사용과 몰입에 영향을 미친다. 또한 대화형 인공지능의 장기적인 사용을 위해서 적절한 사용자와의 사회적, 감정적 상호작용을 디자인 해 주어야 하는데, 인지된 페르소나에 대한 사용자의 선호도가 이 과정에도 유의미한 영향을 미친다. 때문에 지속적인 참여가 결과에 큰 영향을 미치는 일상 헬스케어 영역에서 대화형 인공지능을 활용하는데 개인화된 페르소나 디자인이 긍정적인 사용자 경험 및 사용자 건강 증진의 가능성을 높일 것으로 본 연구는 가정한다. 개인화된 페르소나 디자인을 위해 사용자와 현실에서 친밀한 관계에 있는 실존인물(호스트)의 페르소나를 대화형 인공지능에 적용하고 평가하는 것이 본 연구의 핵심적인 아아디어이다. 이를 검증하기 위해서 해당 학위 논문은 총 세 가지의 세부 연구를 포함한다. 첫째는 실존인물의 페르소나 중에서도 일상 건강관리에 적합한 호스트의 페르소나를 탐색하는 연구이다. 둘째는 호스트의 페르소나를 대화형 인공지능에 적용하기 위해 고려해야 할 언어적 요소들을 정의하는 연구이다. 마지막으로는 위의 과정을 통해 개발된 실존하는 인물의 페르소나를 가진 대화형 인공지능이 일상 헬스케어 영역에서 실제 효과를 보이는지를 평가하는 연구이다. 또한 해당 학위논문은 일련의 연구들에서 발견한 결과들을 바탕으로 사용자와 친밀한 관계에 있는 페르소나를 일상 헬스케어를 위한 대화형 인공지능에 적용할 때 고려해야할 디자인 함의점들을 도출하고 가이드라인을 제시한다.Advance in digital healthcare technologies has been leading a revolution in healthcare. It has been showing the enormous potential to improve medical professionals’ ability for accurate diagnosis, disease treatment, and the users’ daily self-care. Since the recent transformation of digital healthcare aims to provide effective personalized health services, Conversational AI (CA) is being highlighted as an easy-to-use and cost-effective means to deliver personalized services. Particularly, CA is gaining attention as a mean for personalized care by ingraining positive self-care behavior in a daily manner while previous methods for personalized care are focusing on the medical context. CA expands the boundary of personalized care by enabling one-to-one tailored conversation to deliver health education and healthcare therapies. Due to CA's opportunities as a method for personalized care, it has been implemented with various types of roles including CA for diagnosis, CA for prevention, and CA for therapy. However, there lacks study on the personalization of healthcare CA to meet user's preferences on the CA's persona. Even though the CASA paradigm has been applied to previous studies designing and evaluating the human-likeness of CA, few healthcare CAs personalize its human-like persona except some CAs for mental health therapy. Moreover, there exists the need to improve user experience by increasing social and emotional interaction between the user and the CA. Therefore, designing an acceptable and personalized persona of CA should be also considered to make users to be engaged in the healthcare task with the CA. In this manner, the thesis suggests an idea of applying the persona of the person who is in a close relationship with the user to the conversational CA for daily healthcare as a strategy for persona personalization. The main hypothesis is the idea of applying a close person's persona would improve user engagement. To investigate the hypothesis, the thesis explores if dynamics derived from the social relationship in the real world can be implemented to the relationship between the user and the CA with the persona of a close person. To explore opportunities and challenges of the research idea, series of studies were conducted to (1) explore appropriate host whose persona would be implemented to healthcare CA, (2) define linguistic characteristics to consider when applying the persona of a close person to the CA, and (3)implement CA with the persona of a close person to major lifestyle domains. Based on findings, the thesis provides design guidelines for healthcare CA with the persona of the real person who is in a close relationship with the user.Abstract 1 1 Introduction 12 2 Literature Review 18 2.1 Roles of CA in Healthcare 18 2.2 Personalization in Healthcare CA 23 2.3 Persona Design CA 25 2.4 Methods for Designing Chatbot’s Dialogue Style 30 2.4.1 Wizard of Oz Method 32 2.4.2 Analyzing Dialogue Data with NLP 33 2.4.3 Participatory Design 35 2.4.4 Crowdsourcing 37 3 Goal of the Study 39 4 Study 1. Exploring Candidate Persona for CA 43 4.1 Related Work 44 4.1.1 Need for Support in Daily Healthcare 44 4.1.2 Applying Persona to Text-based CA 45 4.2 Research Questions 47 4.3 Method 48 4.3.1 Wizard of Oz Study 49 4.3.2 Survey Measurement 52 4.3.3 Post Interview 54 4.3.4 Analysis 54 4.4 Results 55 4.4.1 System Acceptance 56 4.4.2 Perceived Trustfulness and Perceived Intimacy 57 4.4.3 Predictive Power of Corresponding Variables 58 4.4.4 Linguistic Factors Affecting User Perception 58 4.5 Implications 60 5 Study 2. Linguistic Characteristics to Consider When Applying Close Person’s Persona to a Text-based Agent 63 5.1 Related Work 64 5.1.1 Linguistic Characteristics and Persona Perception 64 5.1.2 Language Component 66 5.2 Research Questions 68 5.3 Method 69 5.3.1 Modified Wizard of Oz Study 69 5.3.2 Survey 72 5.4 Results 73 5.4.1 Linguistic Characteristics 73 5.4.2 Priority of Linguistic Characteristics 80 5.4.3 Differences between language Component 82 5.5 Implications 82 6 Study3.Implementation on Lifestyle Domains 85 6.1 Related Work 86 6.1.1 Family as Effective Healthcare Provider 86 6.1.2 Chatbots Promoting Healthy Lifestyle 87 6.2 Research questions 94 6.3 Implementing Persona of Family Member 95 6.3.1 Domains of Implementation 96 6.3.2 Measurements Used in the Study 97 6.4 Experiment 1: Food Journaling Chatbot 100 6.4.1 Method 100 6.4.2 Results 111 6.5 Experiment 2: Physical Activity Intervention 128 6.5.1 Method 131 6.5.2 Results 140 6.6 Experiment 3: Chatbot for Coping Stress 149 6.6.1 Method 151 6.6.2 Results 158 6.7 Implications from Domain Experiments 169 6.7.1 Comparing User Experience 170 6.7.2 Comparing User Perception 174 6.7.3 Implications from Study 3 183 7 Discussion 192 7.1 Design Guidelines 193 7.2 Ethical Considerations 200 7.3 Limitations 206 8 Conclusion 210 References 212 Appendix 252 국문초록 262박

Supporting Inclusive Learning Using Chatbots? A Chatbot-Led Interview Study

Supporting student academic success has been one of the major goals for higher education. However, low teacher-to-student ratio makes it difficult for students to receive sufficient and personalized support that they might want to. The advancement of artificial intelligence (AI) and conversational agents, such as chatbots, has provided opportunities for assisting learning for different types of students. This research aims at investigating the opportunities and requirements of chatbots as an intelligent helper to facilitate equity in learning. We developed a chatbot as an experimental platform to investigate the design opportunities of using chatbots to support inclusive learning. Through a chatbot-led user study with 215 undergraduate students, we found chatbots provide the opportunity to support students who are disadvantaged, with diverse life environments, and with varied learning styles. This could be achieved through an accessible, interactive, and confidential way

A smartphone-based health care chatbot to promote self-management of chronic pain (SELMA) : pilot randomized controlled trial

Background: Ongoing pain is one of the most common diseases and has major physical, psychological, social, and economic impacts. A mobile health intervention utilizing a fully automated text-based health care chatbot (TBHC) may offer an innovative way not only to deliver coping strategies and psychoeducation for pain management but also to build a working alliance between a participant and the TBHC. Objective: The objectives of this study are twofold: (1) to describe the design and implementation to promote the chatbot painSELfMAnagement (SELMA), a 2-month smartphone-based cognitive behavior therapy (CBT) TBHC intervention for pain self-management in patients with ongoing or cyclic pain, and (2) to present findings from a pilot randomized controlled trial, in which effectiveness, influence of intention to change behavior, pain duration, working alliance, acceptance, and adherence were evaluated. Methods: Participants were recruited online and in collaboration with pain experts, and were randomized to interact with SELMA for 8 weeks either every day or every other day concerning CBT-based pain management (n=59), or weekly concerning content not related to pain management (n=43). Pain-related impairment (primary outcome), general well-being, pain intensity, and the bond scale of working alliance were measured at baseline and postintervention. Intention to change behavior and pain duration were measured at baseline only, and acceptance postintervention was assessed via self-reporting instruments. Adherence was assessed via usage data. Results: From May 2018 to August 2018, 311 adults downloaded the SELMA app, 102 of whom consented to participate and met the inclusion criteria. The average age of the women (88/102, 86.4%) and men (14/102, 13.6%) participating was 43.7 (SD 12.7) years. Baseline group comparison did not differ with respect to any demographic or clinical variable. The intervention group reported no significant change in pain-related impairment (P=.68) compared to the control group postintervention. The intention to change behavior was positively related to pain-related impairment (P=.01) and pain intensity (P=.01). Working alliance with the TBHC SELMA was comparable to that obtained in guided internet therapies with human coaches. Participants enjoyed using the app, perceiving it as useful and easy to use. Participants of the intervention group replied with an average answer ratio of 0.71 (SD 0.20) to 200 (SD 58.45) conversations initiated by SELMA. Participants’ comments revealed an appreciation of the empathic and responsible interaction with the TBHC SELMA. A main criticism was that there was no option to enter free text for the patients’ own comments. Conclusions: SELMA is feasible, as revealed mainly by positive feedback and valuable suggestions for future revisions. For example, the participants’ intention to change behavior or a more homogenous sample (eg, with a specific type of chronic pain) should be considered in further tailoring of SELMA