Computer's human-likeness and its effects on willingness to disclose health-relevant information in healthy adults

This study will be a randomized controlled trial with three experimental conditions (intervention arms). Arm 1: A brief clinical assessment delivered by an online questionnaire Arm 2: A brief clinical assessment delivered by a chatbot interviewer (reading and typing interface) Arm 3: A brief clinical assessment delivered by a digital human (DH) interviewer A community sample of adults (18-35 years old) will be block-randomized by gender to any of the three experimental conditions in a 1:1:1 ratio. For each condition, participants will complete a semi-structured clinical assessment automatically delivered by their allocated technology. The assessment comprises 24 health-relevant items collecting personal information about health behaviours and recent emotional events. The assessment is estimated to last for about 25 minutes. The information below first describes the clinical assessment procedure and then the three types of digital assessment methods. The clinical assessment The semi-structured clinical assessment will be automatically delivered by a digital human (DH), a chatbot, or an online questionnaire. The assessment is broadly structured into three phases, namely, the initial rapport-building phase, the main assessment phase, and the closure. The initial phase is estimated to last for 5 minutes, involving the digital human (DH) or chatbot introducing themselves, initiating the conversation (e.g., “where are you from?”), and providing the scope for the interview (i.e., collecting some health-relevant information including health behaviours and recent emotional events). For the online questionnaire, the initial section will introduce the assessment scope and include the same rapport-building questions as in the chatbot or digital human condition. The main assessment phase is estimated to last for 15 minutes, comprising a list of close-ended questions asking for a wide range of health behaviours, and a few open-ended questions concerning experiences of recent emotional events. Finally, the closure phase is estimated to last for 5 minutes. The digital human (DH) or chatbot interviewer would remind the participants of the closure, deliver a generalized appreciation message (e.g., “I really appreciate your trust in sharing your personal experiences with me”), and close the interviewer with some uplifting questions (e.g., “Tell me about three things that you feel grateful to have in your life?). The interview questions will be delivered in a fixed sequence with some general receptive feedback provided in response to the answers. Participants can skip answering any questions by saying “I do not want to answer”. All of the assessment items are either selected from well-established mental health and addiction screening questionnaire, validated lifestyle surveys for adults, or previous studies that have examined adults' self-disclosure of health information to conversational agents. The health behaviours items asking for habits of exercise, sugary drinks consumption, vegetables eating are selected from a lifestyle survey for university students (Silliman et al., 2004). The items asking for substance uses (tobacco, alcohol, cannabis) are selected from the well-established Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) suitable to be used for adults in New Zealand (Humeniuk, 2006). The item asking for intoxication over the past month is adapted from Schuetzler et al.’ study (2015) which examined users’ socially desirable responding to health-relevant and other personal information. All the sexual risk behaviour items are taken from the validated Sexual Risk Behaviour Scale (Fino et al., 2021) for university students. Lastly, the item asking for drunk driving practice is taken from a health risk behaviour study by Laska and colleagues (2009). For the emotional experiences items, three items asking about perceived loneliness are selected from the well-established UCLA Loneliness Scale (Russel, 1996). In addition, the open-ended items asking about recent emotional events are adapted from a study by Lucas et al. (2014), which examined the effect of human presence on self-disclosure behaviours during semi-structured interviews. The digital human interviewer The digital human (DH) interviewer is developed by Soul Machines Ltd (Auckland, New Zealand). The digital human interviewer is modelled to be a young adult female of mixed ethnicities. The digital human (DH) interviewer is autonomously animated and present on a website accessible to users from their personal computers and tablets. The digital human (DH) interviewer will be programmed to deliver the semi-structured interview questions in a fixed sequence and provide some general receptive feedback to users. As the digital human (DH) interviewer speaks, she will engage in human-like facial and body gestures, including displaying facial expressions, maintaining eye gaze, and moving her head and shoulders. Participants will be informed that the digital human (DH) interviewer continuously collect speech and video data in order to communicate (e.g., to hear speech and make eye contact). These data will not be recorded, stored or analysed by the researchers. Soul Machines’ digital humans (DH) engage in data collection process compliant with the European Union General Data Protection Regulation (GDPR) (Soul Machines, 2021). The chatbot interviewer The chatbot interviewer is programmed using IBM Watson and then deployed to a personal website (Google Site). The chatbot interviewer will be displayed as a static humanoid character image on the web and accessed on a website from a computer. The chatbot interviewer will be programmed to deliver the semi-structured interview questions in a fixed sequence and provide some general receptive feedback. Participants will be informed that their responses to the assessment will be collected by the IBM Watson. IBM engages in data collection process compliant with the European Union General Data Protection Regulation (GDPR). The online questionnaire task The online questionnaire will be created using Qualtrics. The online questionnaire will include the same assessment questions as in the digital human DH and chatbot conditions, and ask these questions in the exact same sequence as in the other conditions. The questionnaire will not provide any feedback to users’ inputs until to the point of submission (i.e., Your responses have been recorded. Thanks for completing this assessment.). The intervention will take place on a desktop computer in a private clinic room at the University of Auckland Clinical Research Center. The total research session lasts for about 45 minutes. Participants will first be instructed to interact with their allocated technology by the researcher (a master's student) for about 10 minutes, including a demonstration of how to use the digital human or chatbot. Participants then will be left independently to complete a clinical assessment with their allocated technology. The researcher will be available (the master's student) in another room to provide help if needed. Participants' responses to the assessment will be recorded by the allocated technology. In addition, audio recordings will be taken for participants allocated to the digital human (DH) group (to double check the accuracy of their recorded verbal responses). Following the completion of the assessment, participants will spend about 10 minutes completing a follow-up online questionnaire on their impression of their allocated digital assessment method and their perceived sensitivty of each assessment item.