A Field Test of Popular Chatbots’ Responses To Questions Concerning Negative Body Image

Background: Chatbots are computer programs, often built upon large artificial intelligence models, that employ dialogue systems to enable online, natural language conversations with users via text, speech, or both. Body image, broadly defined as a combination of thoughts and feelings about one’s physical appearance, has been implicated in many risk behaviors and health problems, especially among adolescents and young adults. Little is known about how chatbots respond to questions about body image. Methods: This study assessed the responses of 14 widely-used chatbots (eight companion and six therapeutic chatbots) to ten body image-related questions developed upon validated instruments. Chatbots’ responses were documented, with qualities systematically assessed by nine pre-determined criteria. Results: The overall quality of the chatbots’ responses was modest (an average score of five out of nine), with substantial variations in the content and quality of responses across chatbots (individual scores ranging from one to eight). Companion and therapeutic chatbots systematically differed in their responses (e.g., focusing on comforting users vs. trying to identify the causes of negative body image and recommending potential remedies). Some therapeutic chatbots recognized potential mental health crises (self-harm) in test users’ messages. Conclusion: Substantial heterogeneities in the responses were present across chatbots and assessment criteria. Adolescents and young adults struggling with body image could be vulnerable to misleading or biased remarks made by chatbots. Still, the technical and supervision challenges to prevent those adverse consequences remain paramount and unsolved

Exploring the potential of mobile health interventions to address behavioural risk factors for the prevention of non-communicable diseases in Asian populations: a qualitative study

Background Changing lifestyle patterns over the last decades have seen growing numbers of people in Asia affected by non-communicable diseases and common mental health disorders, including diabetes, cancer, and/or depression. Interventions targeting healthy lifestyle behaviours through mobile technologies, including new approaches such as chatbots, may be an effective, low-cost approach to prevent these conditions. To ensure uptake and engagement with mobile health interventions, however, it is essential to understand the end-users’ perspectives on using such interventions. The aim of this study was to explore perceptions, barriers, and facilitators to the use of mobile health interventions for lifestyle behaviour change in Singapore. Methods Six virtual focus group discussions were conducted with a total of 34 participants (mean ± SD; aged 45 ± 3.6 years; 64.7% females). Focus group recordings were transcribed verbatim and analysed using an inductive thematic analysis approach, followed by deductive mapping according to perceptions, barriers, facilitators, mixed factors, or strategies. Results Five themes were identified: (i) holistic wellbeing is central to healthy living (i.e., the importance of both physical and mental health); (ii) encouraging uptake of a mobile health intervention is influenced by factors such as incentives and government backing; (iii) trying out a mobile health intervention is one thing, sticking to it long term is another and there are key factors, such as personalisation and ease of use that influence sustained engagement with mobile health interventions; (iv) perceptions of chatbots as a tool to support healthy lifestyle behaviour are influenced by previous negative experiences with chatbots, which might hamper uptake; and (v) sharing health-related data is OK, but with conditions such as clarity on who will have access to the data, how it will be stored, and for what purpose it will be used. Conclusions Findings highlight several factors that are relevant for the development and implementation of mobile health interventions in Singapore and other Asian countries. Recommendations include: (i) targeting holistic wellbeing, (ii) tailoring content to address environment-specific barriers, (iii) partnering with government and/or local (non-profit) institutions in the development and/or promotion of mobile health interventions, (iv) managing expectations regarding the use of incentives, and (iv) identifying potential alternatives or complementary approaches to the use of chatbots, particularly for mental health

Engineering affect: emotion regulation, the internet, and the techno-social niche

Philosophical work exploring the relation between cognition and the Internet is now an active area of research. Some adopt an externalist framework, arguing that the Internet should be seen as environmental scaffolding that drives and shapes cognition. However, despite growing interest in this topic, little attention has been paid to how the Internet influences our affective life — our moods, emotions, and our ability to regulate these and other feeling states. We argue that the Internet scaffolds not only cognition but also affect. Using various case studies, we consider some ways that we are increasingly dependent on our Internet-enabled “techno-social niches” to regulate the contours of our own affective life and participate in the affective lives of others. We argue further that, unlike many of the other environmental resources we use to regulate affect, the Internet has distinct properties that introduce new dimensions of complexity to these regulative processes. First, it is radically social in a way many of these other resources are not. Second, it is a radically distributed and decentralized resource; no one individual or agent is responsible for the Internet’s content or its affective impact on users. Accordingly, while the Internet can profoundly augment and enrich our affective life and deepen our connection with others, there is also a distinctive kind of affective precarity built into our online endeavors as well

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

Disruptive innovation in the healthcare sector : the advent of AI chatbots

Over the last several decades, the healthcare sector has faced many challenges. These include a shortage of doctors, especially in rural areas, high clinical costs, and an increasing number of diseases needing to be treated. This thesis focuses on the potential and the limitations of an innovative way to solve problems in healthcare – use of AI chatbots. We highlight the user’s perspective concerning AI healthcare chatbot technology. Based on qualitative and quantitative research, we conclude that this novel technology offers new opportunities for diagnostics, enables work to be carried out more efficiently, and gives the patient the power to “self-diagnose”. AI chatbots have not yet reached their full potential due to legal restrictions, insufficient data, and the lack of capacity to integrate them into different systems. Even though the number of AI chatbot users is increasing, people trust chatbots less than doctors. To enhance user engagement and create a higher level of trust, credible entities such as doctors and the government could recommend the use of AI chatbots. The general acceptance of chatbots has to be analyzed per country since it is explained by socio-economic factors (education, age, income), personality-related factors (attitude to new things, curiosity) and communication behavior factors.Nas últimas décadas, o setor da saúde enfrentou muitos desafios. Nestes podem destacar-se a escassez de médicos, especialmente nas zonas rurais, custos de tratamento elevados e um número crescente de doenças a precisarem de ser tratadas. Esta tese foca-se no potencial e nas limitações de uma forma revolucionária de resolver problemas na área da saúde – o uso de chatbots de IA. Destacamos a perspetiva do utilizador em relação à assistência médica através da tecnologia de chatbot de IA. Com base em pesquisas qualitativas e quantitativas, concluímos que esta tecnologia inovadora oferece novas oportunidades para diagnósticos, permite que o trabalho seja realizado com mais eficiência e oferece ao paciente a capacidade de se autodiagnosticar. Os chatbots de IA ainda não atingiram todo o seu potencial devido a restrições legais, dados insuficientes e à falta de capacidade de integrá-los em diferentes sistemas. Ainda que o número de utilizadores de chatbot de IA esteja a aumentar, as pessoas confiam menos nos chatbots do que nos médicos. Para encorajar um maior envolvimento do utilizador e criar um nível mais alto de confiança, entidades credíveis como médicos e o governo podem recomendar o uso de chatbots de IA. A aceitação generalizada dos chatbots deve ser analisada por país, uma vez que é explicada por fatores socioeconómicos (educação, idade, rendimento), fatores relacionados com a personalidade (atitude perante coisas novas, curiosidade) e fatores de comportamento na comunicação

Human-Machine Communication: Complete Volume. Volume 3. Diffusion of Human-Machine Communication During and After the COVID-19 Pandemic

This is the complete volume of HMC Volume 3. Diffusion of Human-Machine Communication During and After the COVID-19 Pandemi

Territorial Violence and Design, 1950-2010: A Human-Computer Study of Personal Space and Chatbot Interaction

Personal space is a human’s imaginary system of precaution and an important concept for exploring territoriality, but between humans and technology because machinic agencies transfer, relocate, enact and reenact territorially. Literatures of territoriality, violence and affect are uniquely brought together, with chatbots as the research object to argue that their ongoing development as artificial agents, and the ambiguity of violence they can engender, have broader ramifications for a socio-technical research programme. These literatures help to understand the interrelation of virtual and actual spatiality relevant to research involving chatrooms and internet forums, automated systems and processes, as well as human and machine agencies; because all of these spaces, methods and agencies involve the personal sphere. The thesis is an ethical tale of cruel techno-science that is performed through conceptualisations from the creative arts, constituting a PhD by practice. This thesis chronicles four chatbots, taking into account interventions made in fine art, design, fiction and film that are omitted from a history of agent technology. The thesis re-interprets Edward Hall’s work on proxemics, personal space and territoriality, using techniques of the bricoleur and rudiments (an undeveloped and speculative method of practice), to understand chatbot techniques such as the pick-up, their entrapment logics, their repetitions of hateful speech, their nonsense talk (including how they disorientate spatial metaphors), as well as how developers switch on and off their learning functionality. Semi-structured interviews and online forum postings with chatbot developers were used to expand and reflect on the rudimentary method. To urge that this project is timely is itself a statement of anxiety. Chatbots can manipulate, exceed, and exhaust a human understanding of both space and time. Violence between humans and machines in online and offline spaces is explored as an interweaving of agency and spatiality. A series of rudiments were used to probe empirical experiments such as the Prisoner’s Dilemma (Tucker, 1950). The spatial metaphors of confinement as a parable of entrapment, are revealed within that logic and that of chatbots. The ‘Obedience to Authority’ experiments (Milgram, 1961) were used to reflect on the roles played by machines which are then reflected into a discussion of chatbots and the experiments done in and around them. The agency of the experimenter was revealed in the machine as evidenced with chatbots which has ethical ramifications. The argument of personal space is widened to include the ways machinic territoriality and its violence impacts on our ways of living together both in the private spheres of our computers and homes, as well as in state-regulated conditions (Directive-3, 2003). The misanthropic aspects of chatbot design are reflected through the methodology of designing out of fear. I argue that personal spaces create misanthropic design imperatives, methods and ways of living. Furthermore, the technological agencies of personal spaces have a confining impact on the transient spaces of the non-places in a wider discussion of the lift, chatroom and car. The violent origins of the chatbot are linked to various imaginings of impending disaster through visualisations, supported by case studies in fiction to look at the resonance of how anxiety transformed into terror when considering the affects of violence

Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study

Background Artificial intelligence (AI) is increasingly being used in healthcare. Here, AI-based chatbot systems can act as automated conversational agents, capable of promoting health, providing education, and potentially prompting behaviour change. Exploring the motivation to use health chatbots is required to predict uptake; however, few studies to date have explored their acceptability. This research aimed to explore participants’ willingness to engage with AI-led health chatbots. Methods The study incorporated semi-structured interviews (N-29) which informed the development of an online survey (N-216) advertised via social media. Interviews were recorded, transcribed verbatim and analysed thematically. A survey of 24 items explored demographic and attitudinal variables, including acceptability and perceived utility. The quantitative data were analysed using binary regressions with a single categorical predictor. Results Three broad themes: ‘Understanding of chatbots’, ‘AI hesitancy’ and ‘Motivations for health chatbots’ were identified, outlining concerns about accuracy, cyber-security, and the inability of AI-led services to empathise. The survey showed moderate acceptability (67%), correlated negatively with perceived poorer IT skills OR = 0.32 [CI95%:0.13–0.78] and dislike for talking to computers OR = 0.77 [CI95%:0.60–0.99] as well as positively correlated with perceived utility OR = 5.10 [CI95%:3.08–8.43], positive attitude OR = 2.71 [CI95%:1.77–4.16] and perceived trustworthiness OR = 1.92 [CI95%:1.13–3.25]. Conclusion Most internet users would be receptive to using health chatbots, although hesitancy regarding this technology is likely to compromise engagement. Intervention designers focusing on AI-led health chatbots need to employ user-centred and theory-based approaches addressing patients’ concerns and optimising user experience in order to achieve the best uptake and utilisation. Patients’ perspectives, motivation and capabilities need to be taken into account when developing and assessing the effectiveness of health chatbots

The Effects of a Healthcare Chatbots\u27 Language and Persona on User Trust, Satisfaction, and Chatbot Effectiveness

Healthcare technology is growing in its capabilities and capacity to impact people’s daily lives. One area of interest for growth is the use of chatbots and other telehealth applications that allow people to receive ubiquitous health information. The benefit of these systems is the ability to give access to pertinent, personalized healthcare information and services that could otherwise be inaccessible for some populations. With personalized information, patients may gain the information needed to make efficacious healthcare decisions which ideally will result in quicker recovery times and lower overall healthcare system costs. Chatbots have already been studied in the healthcare domain as resources for smoking cessation, diet recommendation, and other assistive applications. Yet, few studies have examined the specific design characteristics of healthcare chatbots. My research objective was to analyze two characteristics, language and persona, and their effect on outcomes such as effectiveness, usability, and trust in a chatbot. A between-subject study was performed where participants interacted with a chatbot. Each of chatbot conditions had a language of either technical or non-technical, and persona of Doctor, Nurse, or Nursing Student Sarah. Language was found to have a significant effect on effectiveness, but not trust or usability. In particular, participants who experienced technical language improved significantly greater than those who experienced non-technical language. Persona was found to not be significant for any of the outcomes. Overall, this study demonstrated a need to further study and understand how chatbot design characteristics impact users and how they comprehend the information given to them, particularly from a healthcare perspective

Examining the Impact of Design Features of Electronic Health Records Patient Portals on the Usability and Information Communication for Shared Decision Making

The use of the Electronic Health Records (EHR) patient portal has been shown to be effective in generating positive outcomes in patients’ healthcare, improving patient engagement and patient-provider communication. Government legislation also required proof of its meaningful use among patients by healthcare providers. Typical patient portals also include features such as health information and patient education materials. However, little research has examined the specific use of patient portals related to individuals with specific diseases such as inflammatory bowel diseases (IBDs). IBDs are life-long, not curable, chronic diseases that can impact the whole population. Individuals with IBDs may have higher needs to acquire health information from their EHR portals to properly self-manage their health conditions. The research aims of the present dissertation are to understand the online health information-seeking behaviors of a target group (IBDs) of patients, the use of EHR patient portals, and the impact of design features of EHR patient portals on the usability and information communication for shared decision making. Through this dissertation, I conducted four studies to address the above research aims. First, I identified how individuals with inflammatory bowel disease (IBD) used the internet for health information seeking, the factors impacting their use of the internet to obtain health information, and how they used the internet for health-related tasks. The purpose of this study is to get a general understanding of the online health information-seeking behaviors and to guide the study of health information presentation of EHR portals in the following research. Second, I examined what factors influenced an EHR patient portal user to believe that the portal is a valuable part of their health care. This part of the dissertation aimed to reveal the critical design factors that help design an EHR portal perceived as valuable in managing health. Third, I looked at how patients used EHR patient portals, what features of the portals facilitated their use and encouraged Shared Decision Making (SDM) and engagement in health management and what features acted as barriers to SDM and their engagement in health management. This part of my dissertation focused on a broad understanding of EHR portals usage by introducing more specific factors such as features of EHR portals. Fourth, I conducted an eye-tracking study to examine how information presentation methods and chatbots impact the use and effect of patient portals. This part of my dissertation built on the other studies within my dissertation and deepened the understanding of the influence of different EHR portal designs on their effectiveness and people’s willingness to participate in SDM. The results of this dissertation contribute to the literature of understanding the information-seeking behaviors of IBD patients and the use of portals, as well as the design considerations of how to make a suitable EHR portal to support the information-seeking needs of IBD patients. The results of this dissertation can be used to guide building proper patient education materials to support their health information needs of their specific health condition, especially for individuals with chronic diseases that require a certain amount of self-management. Meanwhile, examining artificial intelligence (AI) based chatbots use in EHR portals reveals a potential path of AI use in healthcare, such as information acquisition and patient education. Designing good usable EHR may also facilitate the process of informing patients of the advantages and disadvantages of treatment plans for their disease and, therefore, may increase their willingness to participate in SDM