Home-Based Virtual Reality Exposure Therapy with Virtual Health Agent Support

Hartanto, Dwi; Brinkman, Willem‐Paul; Kampmann, Isabel L.; Morina, Nexhmedin; Emmelkamp, Paul G. M.; Neerincx, Mark A.

doi:10.1007/978-3-319-32270-4_9

Cited by 16 publications

(15 citation statements)

References 13 publications

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“…The latter may be classified as behavior change support systems (BCSS), aiming to change unhealthy behavior patterns. Such systems can be developed for a range of different disorders such as substance abuse [7], anxiety [8], depression [9], or post-traumatic stress disorder (PTSD) [10]. For the success of such BCSS for mental health, the users need to stay motivated to use the system, because behavior change is difficult [11].…”

Section: Introductionmentioning

confidence: 99%

Design and Evaluation of Personalized Motivational Messages by a Virtual Agent that Assists in Post-Traumatic Stress Disorder Therapy

Tielman¹,

Neerincx²,

Brinkman³

2019

J Med Internet Res

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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.

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Section: Introductionmentioning

confidence: 99%

Design and Evaluation of Personalized Motivational Messages by a Virtual Agent that Assists in Post-Traumatic Stress Disorder Therapy

Tielman¹,

Neerincx²,

Brinkman³

2019

J Med Internet Res

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“…The reason is that the participants in the VR heard the voice double, once from the researcher and out of the headphones, even when using noise-cancelling headphones. On one hand, this opens up the opportunity to deliver therapy over distances using the internet as demonstrated in other systems [37]. On the other hand, we see the opportunity to use the system in other use-cases where social interaction plays a role, e.g.…”

Section: Discussionmentioning

confidence: 90%

Rich Interactions in Virtual Reality Exposure Therapy: A Pilot-Study evaluating a System for Presentation Training

Koller

Schäfer

Lochner

et al. 2019

2019 IEEE International Conference on Healthcare Informatics (ICHI)

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Public Speaking Anxiety (PSA) or discomfort while speaking in public is a wide spread cognitive disorder. Exposure therapy offers the opportunity to treat patients suffering PSA by exposing them to the phobic stimulus. To plan and organize an in-vivo exposure takes a lot of effort in recruiting people for an audience and orchestrating their behavior. Virtual Reality (VR) offers the possibility to generate the audiences that can be controlled by an orchestrator according patient's individual needs. This paper explores a system that enables the therapists to richly interact verbally and non-verbally with immersed presenters. For evaluation, we conducted a study with 24 healthy participants in two groups (12 participants each). Our results indicate that the direct verbal interaction between an orchestrator outside the VR and an immersed presenter are enhancing the presenter's experience and increasing the efficiency of therapy process. The non-verbal dimension is realized that an orchestrator can takeover an avatar using a motion-tracking camera that controls then the avatar's movements. Our results indicate that the transition of animations and movements are not impacting the experience negatively.

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“…Dialogues between virtual humans and participants were automated. That is, the system detected participants’ answers via a microphone by means of key word recognition and speech detection technology ( Hartanto et al, 2016 ). Dialogues were prewritten and therefore, the virtual human could not respond to the specific content of the participant’s answer.…”

Section: Methodsmentioning

confidence: 99%

Self-report questionnaires, behavioral assessment tasks, and an implicit behavior measure: do they predict social anxiety in everyday life?

Kampmann

Emmelkamp

Morina

2018

PeerJ

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Social anxiety is commonly assessed with self-report measures. This study aimed to investigate whether maximum anxiety levels during in vivo and virtual reality behavioral assessment tasks (BATs), and implicit approach-avoidance tendencies during the approach-avoidance task (AAT) explain more variation as predictors of daily social anxiety than self-report measures. A total of 62 university students (Mage = 20.79; SD = 4.91) with high levels of social anxiety completed self-report measures on fear of negative evaluation (FNE-B) as well as fear and avoidance in social situations (Liebowitz social anxiety scale-self report), in vivo and virtual reality BATs, and the AAT (independent variables) in the laboratory. On seven consecutive days, social anxiety, experiential avoidance, and negative social events (dependent variables) were assessed. The results revealed that fear of negative evaluation predicted everyday social anxiety and experiential avoidance. Fear and avoidance in social situations only predicted experiential avoidance. Neither implicit approach-avoidance tendencies during the AAT nor maximum anxiety levels during the in vivo and virtual reality BATs predicted any outcome variable. Our results support the use of self-report questionnaires in the assessment of social anxiety.

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Home-Based Virtual Reality Exposure Therapy with Virtual Health Agent Support

Cited by 16 publications

References 13 publications

Design and Evaluation of Personalized Motivational Messages by a Virtual Agent that Assists in Post-Traumatic Stress Disorder Therapy

Design and Evaluation of Personalized Motivational Messages by a Virtual Agent that Assists in Post-Traumatic Stress Disorder Therapy

Rich Interactions in Virtual Reality Exposure Therapy: A Pilot-Study evaluating a System for Presentation Training

Self-report questionnaires, behavioral assessment tasks, and an implicit behavior measure: do they predict social anxiety in everyday life?

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