BACKGROUND: Systems incorporating virtual agents can play a major role in electronic-mental (e-mental) health care, as barriers to care still prevent some patients from receiving the help they need. To properly assist the users of these systems, a virtual agent needs to promote motivation. This can be done by offering motivational messages.
OBJECTIVE: The objective of this study was two-fold. The first was to build a motivational message system for a virtual agent assisting in post-traumatic stress disorder (PTSD) therapy based on domain knowledge from experts. The second was to test the hypotheses that (1) computer-generated motivating messages influence users' motivation to continue with therapy, trust in a good therapy outcome, and the feeling of being heard by the agent and (2) personalized messages outperform generic messages on these factors.
METHODS: A system capable of generating motivational messages was built by analyzing expert (N=13) knowledge on what types of motivational statements to use in what situation. To test the 2 hypotheses, a Web-based study was performed (N=207). Participants were asked to imagine they were in a certain situation, specified by the progression of their symptoms and initial trust in a good therapy outcome. After this, they received a message from a virtual agent containing either personalized motivation as generated by the system, general motivation, or no motivational content. They were asked how this message changed their motivation to continue and trust in a good outcome as well as how much they felt they were being heard by the agent. RESULTS: Overall, findings confirmed the first hypothesis, as well as the second hypothesis for the measure feeling of being heard by the agent. Personalization of the messages was also shown to be important in those situations where the symptoms were getting worse. In these situations, personalized messages outperformed general messages both in terms of motivation to continue and trust in a good therapy outcome.
CONCLUSIONS: Expert input can successfully be used to develop a personalized motivational message system. Messages generated by such a system seem to improve people's motivation and trust in PTSD therapy as well as the user's feeling of being heard by a virtual agent. Given the importance of motivation, trust, and therapeutic alliance for successful therapy, we anticipate that the proposed system can improve adherence in e-mental therapy for PTSD and that it can provide a blueprint for the development of an adaptive system for persuasive messages based on expert input.

Background: Digital health interventions can fill gaps in mental healthcare provision. However, autonomous e-mental health (AEMH) systems also present challenges for effective risk management. To balance autonomy and safety, AEMH systems need to detect risk situations and act on these appropriately. One option is sending automatic alerts to carers, but such 'auto-referral' could lead to missed cases or false alerts. Requiring users to actively self-refer offers an alternative, but this can also be risky as it relies on their motivation to do so. This study set out with two objectives. Firstly, to develop guidelines for risk detection and auto-referral systems. Secondly, to understand how persuasive techniques, mediated by a virtual agent, can facilitate self-referral. Methods: In a formative phase, interviews with experts, alongside a literature review, were used to develop a risk detection protocol. Two referral protocols were developed - one involving auto-referral, the other motivating users to self-refer. This latter was tested via crowd-sourcing (n = 160). Participants were asked to imagine they had sleeping problems with differing severity and user stance on seeking help. They then chatted with a virtual agent, who either directly facilitated referral, tried to persuade the user, or accepted that they did not want help. After the conversation, participants rated their intention to self-refer, to chat with the agent again, and their feeling of being heard by the agent. Results: Whether the virtual agent facilitated, persuaded or accepted, influenced all of these measures. Users who were initially negative or doubtful about self-referral could be persuaded. For users who were initially positive about seeking human care, this persuasion did not affect their intentions, indicating that a simply facilitating referral without persuasion was sufficient. Conclusion: This paper presents a protocol that elucidates the steps and decisions involved in risk detection, something that is relevant for all types of AEMH systems. In the case of self-referral, our study shows that a virtual agent can increase users' intention to self-refer. Moreover, the strategy of the agent influenced the intentions of the user afterwards. This highlights the importance of a personalised approach to promote the user's access to appropriate care.

Motivating users is an important task for virtual agents in behaviour chance support systems. In this study we present a system which generates motivational statements based on situation type, aimed at a virtual agent for Post-Traumatic Stress Disorder therapy. Using input from experts (n=13), we built a database containing what categories of motivation to use based on therapy progress and current user trust. A statistical analysis confirmed that we can significantly predict the category of statements to use. Using the database, we present a system that generates motivational statements. Because this system is based on expert data, it has the advantage of not needing large amounts of patient data. We envision that by basing the content directly on expert knowledge, the virtual agent can motivate users as a human expert would.

Although post-traumatic stress disorder (PTSD) is well treatable, many people do not get the desired treatment due to barriers to care (such as stigma and cost). This paper presents a system that bridges this gap by enabling patients to follow therapy at home. A therapist is only involved remotely, to monitor progress and serve as a safety net. With this system, patients can recollect their memories in a digital diary and recreate them in a 3D WorldBuilder. Throughout the therapy, a virtual agent is present to inform and guide patients through the sessions, employing an ontology-based question module for recollecting traumatic memories to further elicit a detailed memory recollection. In a usability study with former PTSD patients (n = 4), these questions were found useful for memory recollection. Moreover, the usability of the whole system was rated positively. This system has the potential to be a valuable addition to the spectrum of PTSD treatments, offering a novel type of home therapy assisted by a virtual agent.