Virtual Therapists Research Articles

Interdisciplinary Applications of AI: Dermatology and Psychology

Artificial Intelligence (AI) is profoundly transforming interdisciplinary domains like dermatology and psychology, providing revolutionary possibilities in the areas of diagnosis, treatment, and patient care. AI-driven solutions in dermatology are improving diagnostic accuracy by analyzing medical photos to identify skin disorders such as melanoma with a level of precision comparable to that of professional dermatologists. These technologies utilize machine learning algorithms that have been trained on extensive datasets to detect minor patterns and anomalies in skin lesions. This enables the early detection of skin conditions and the creation of personalized treatment strategies. Moreover, artificial intelligence (AI) assists in optimizing the efficiency of workflows, minimizing diagnostic inaccuracies, and enhancing the availability of dermatological treatment, particularly in places with limited access to healthcare services. Within the field of psychology, artificial intelligence (AI) has a significant influence. It is utilized to assess individuals' mental well-being by analyzing their text and speech patterns, employing techniques such as natural language processing and sentiment analysis. Artificial intelligence algorithms have the capability to observe and analyze patient interactions, offering immediate and accurate observations regarding emotional states and possible psychological illnesses. The incorporation of AI enables more precise evaluations and prompt actions, enhancing conventional therapeutic methods. In addition, chatbots and virtual therapists that utilise artificial intelligence provide instant assistance and ongoing supervision, thereby extending the accessibility of mental health care. The integration of AI with dermatology and psychology not only improves diagnostic skills and treatment results but also highlights the significance of interdisciplinary collaboration in advancing healthcare. By using artificial intelligence (AI), these industries can utilize data-driven analysis to provide more accurate, tailored, and easily accessible healthcare, thereby enhancing patient results and quality of life.

Chatbots for Well-Being: Exploring the Impact of Artificial Intelligence on Mood Enhancement and Mental Health

Introduction Over the past few years, Psychiatry has undergone a significant transformation with the integration of Artificial Intelligence (AI). This shift has been driven by the increasing demand for mental health services, as well as advances in AI technology. AI analyzes extensive datasets, including text, voice, and behavioral data, aiding in mental health diagnosis and treatment. Consequently, a range of AI-based interventions has been developed, including chatbots, virtual therapists and apps featuring cognitive-behavioral therapy (CBT) modules. Notably, chatbots, as conversational agents, have emerged as valuable tools, assisting users in monitoring emotions and providing evidence-based resources, well-being support, psychoeducation and adaptive coping strategies.ObjectivesThis study aims to investigate the impact of AI chatbots on improving mental health, evaluate their strengths and weaknesses and explore their potential for early detection and intervention in mental health issues.Methods A literature review was conducted through PubMed and Google Scholar databases, using keywords ‘artificial intelligence’, ‘chatbot’ and ‘mental health’. The selection focused on the most relevant articles published between January 2021 and September 2023.ResultsMental health chatbots are highly personalized, with a primary focus on addressing issues such as depression or anxiety within specific clinical population groups. Through the integration of Natural Language Processing (NLP) techniques and rule-based AI algorithms, these chatbots closely simulate human interactions and effectively instruct users in therapeutic techniques. While chatbots integrating CBT principles have gained widespread use and extensive research attention, some also incorporate alternative therapeutic approaches, including dialectical behavior therapy, motivational interviewing, acceptance and commitment therapy, positive psychology or mindfulness-based stress reduction. AI chatbots provide substantial advantages in terms of accessibility, cost-effectiveness and improved access to mental health support services. Nonetheless, they also exhibit limitations, including the absence of human connection, limited expertise, potential for misdiagnosis, privacy concerns, risk of bias and limitations in risk assessment accuracy.ConclusionsAI-based chatbots hold the potential to enhance patient outcomes by enabling early detection and intervention in mental health issues. However, their implementation in mental health should be approached with caution. Further studies are essential to thoroughly evaluate their effectiveness and safety.Disclosure of InterestNone Declared

Interactions with virtual therapists during motor rehabilitation in immersive virtual environments: a systematic review

Introduction: Virtual Reality applications for rehabilitation are increasing in popularity. In traditional as well as virtual rehabilitation, the guidance of an occupational therapist through physical and verbal interaction is often required. Several studies have attempted to implement a virtual therapist or assistant in immersive virtual environments for rehabilitation.Objective: This research aims to systematically review these studies, understanding the therapist’s role and how they are represented in the virtual environment, how the virtual therapist and patient interact and the experience of users. Our goal is to provide guidance for virtual therapist implementations into fully immersive virtual reality environments.Method: The researchers systematically reviewed the literature on virtual therapists in immersive virtual environments for motor rehabilitation (protocol prospectively registered with PROSPERO ID: CRD42022357369).Results and Conclusion: Seven studies were identified, with findings showing that virtual therapists are often human-like avatars that guide patients, requiring them to mimic the therapist’s movements. Visual, haptic, or one-direction audio feedback from the therapist to the patient was provided in five studies. The selected studies were all newly developed custom-made systems, with five systems developed using the same game engine. Studies carrying out user testing utilised several methods to understand user experience, evidencing a positive attitude from therapists and motivated and satisfied patients.Future Research: The roles of virtual therapists for motor rehabilitation needs to be explored further in rigorous empirical studies to gather data on patient and therapist user experience. Considerable potential was identified in the development of virtual therapists and therapeutic alliance in the virtual environment. Future systems should reduce manual input from therapists and include personalisation and individualised patient feedback.Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=357369], PROSPERO ID [CRD42022357369].

SentiSync: A Robust System for Sentiment Detection and Analyzing the Mental Health Care with ML-Driven Algorithms

The integration of artificial intelligence (AI) in mental health care represents a paradigm shift in the management and understanding of mental health disorders. This abstract explores the multifaceted applications of AI in mental health, emphasizing its potential to revolutionize diagnosis, treatment, and overall patient care. AI technologies, such as machine learning algorithms and natural language processing, exhibit remarkable capabilities in analysing vast datasets, identifying patterns, and extracting meaningful insights from diverse sources. In mental health, these technologies play a important role in early detection and accurate diagnosis of psychiatric conditions. By analysing a myriad of behavioural, biological, and contextual factors, AI models can provide more precise and personalized diagnostic assessments, reducing the reliance on subjective evaluations. Furthermore, AI-driven interventions are reshaping treatment approaches in mental health care. Virtual mental health assistants, powered by AI, offer scalable and accessible support, providing timely interventions and monitoring patients' well-being. Chatbots and virtual therapists equipped with sentiment analysis can involve users in natural conversations, offering empathy and support while continuously learning and adapting to individual needs

Artificial Intelligence for Mental Health: A Double-Edged Sword

Artificial intelligence (AI) in the context of mental health presents a complex scenario characterized by both advantageous prospects and inherent hazards. AI possesses the capacity to fundamentally transform the field of mental healthcare through the provision of individualized and readily accessible assistance. AI systems possess the capacity to analyze extensive quantities of data and identify patterns, thereby offering valuable assistance to doctors in the diagnosis of mental diseases, development of personalized treatment programs, and even prediction of relapses. Furthermore, there is ongoing development in the field of AI to create chatbots that utilize AI technology and serve as virtual therapists. These chatbots aim to provide individuals with continuous emotional support, available at any time of the day. Nonetheless, this technological advancement also gives rise to apprehensions about issues of privacy, ethical considerations, and an excessive dependence on automated systems. Robust security measures are crucial in safeguarding the anonymity of consumers while utilizing AI systems due to the sensitive nature of mental health data. Furthermore, it is important to consider the potential for dehumanization when patients only depend on interventions driven by machines, as opposed to fostering human connection and empathy. Achieving an optimal equilibrium between technical progress and preserving interpersonal connection remains a key aspect in fully using the capabilities of AI in the field of mental health, while simultaneously ensuring its effects on individual welfare are protected.

Could Artificial Intelligence be a Therapeutic for Mental Issues?

The utilization of artificial intelligence (AI) possesses the capacity to fundamentally transform the landscape of mental health care through the provision of very valuable therapeutic interventions. AI possesses the capacity to evaluate extensive quantities of data, enabling it to aid in the identification of early signs of mental health concerns and provide tailored solutions that cater to specific requirements. The utilization of virtual therapists powered by AI has the potential to provide a secure environment for persons experiencing social anxiety or worries associated with stigma. This form of therapy offers continuous support and diminishes the obstacles that hinder individuals from seeking assistance. In addition, AI algorithms possess the capability to effectively identify and analyze patterns and trends derived from many sources, including social media posts and smartphone usage. This enables the assessment of an individual’s mental health and facilitates the provision of timely solutions. Through the utilization of natural language processing and sentiment analysis, AI has the potential to augment current therapeutic practices by proficiently monitoring patient advancements and analyzing therapeutic dialogues. Therefore, the incorporation of AI into the realm of mental health intervention holds promise in enhancing accessibility, cost, and efficacy, while mitigating the strain on conventional healthcare systems.

AI-Based Personalized Virtual Therapist for Alcohol Relapse

Binge drinking is one type of harmful alcohol use that has a variety of negative health impacts in both the drinker and others, either globally or in Malaysia. According to previous research, one in two current drinkers in Malaysia who are 13 years and older reported having engaged in binge drinking. Therefore, increased attention should be given to understand the drinking pattern of an individual and propose a solution that can help with addiction relapse. Thus, this study identified interventions that could assist alcohol relapse recovery and proposed a new generation of relapse prevention solution based on artificial intelligence (AI). By using a deep learning approach and machine learning based recommendation technique, it predicts the relapse rate of users, providing recovery consultation based on the user’s data and clinical data through a chatbot. This study involved helpful data collection, advanced data modeling, prediction analysis to support the alcohol relapse recovery journey. Hence, the proposed AI solution acted as a personalized virtual therapist to help the addicts stay sober. The objective is to present the design and realization of the AI based solution for sober journey. The proposed solution was tested with pilot study and significant benefits of virtual therapists for alcohol addiction relapse is reported in this paper.

Virtual Reality Exposure Therapy for Treating Social Anxiety: A Scoping Review of Treatment Designs and Adaptation to Stuttering.

Virtual Reality Exposure Therapy (VRET) has been shown to be an effective technique for reducing social anxiety. People who stutter are at greater risk of developing heightened social anxiety. Cognitive behavior therapy protocols have shown promise in reducing social anxiety in people who stutter, but no studies have investigated VRET targeting social anxiety associated with stuttering. The aim of the current review is to provide an overview of VRET techniques used to treat social anxiety and insights into how these techniques might be adopted in the case of comorbid stuttering and social anxiety. Twelve studies were reviewed to understand key distinctions in VRET protocols used to treat social anxiety. Distinctions include exercises targeting public speaking vs. general social anxiety, computer-generated virtual environments vs. 360° video, and therapist guided vs. automated VRET. Based on the review findings, we propose how certain features could be applied in the case of stuttering. Virtual therapists, inhibitory learning techniques and integration into speech therapy may be suitable ways to tailor VRET. Regardless of these different techniques, VRET should consider the situations and cognitive-behavioral processes that underlie the experience of social anxiety amongst people who stutter.

First Impressions Count! The Role of the Human's Emotional State on Rapport Established with an Empathic versus Neutral Virtual Therapist

Intelligent virtual agents are being endowed with empathic behaviours to perform roles such as virtual therapists. Studies often evaluate the level of rapport established, but do not measure the therapeutic benefit and the relative advantage of empathic versus neutral behaviours. We have created two virtual (empathic/neutral) therapists. Our experiment with 63 participants consisted of one within-subjects (empathic/neutral) and one between-subjects (order) factors. Regardless of the virtual therapist used, improvements in baseline emotion were reported after the first interaction (time one) and further improvement after the second interaction (time two). Our study reveals that if the human initially expresses strong emotional feeling for a problem they are facing, rapport will be higher for the empathic therapist and the level of rapport established at the first meeting will persist regardless of whether the second encounter used empathic or neutral dialogue. Conversely, participants experiencing low emotional feeling reported greater rapport with the neutral therapist, and that level of rapport persisted in the second encounter with the alternative therapist. This study shows that an empathic agent will not necessarily build more rapport or deliver better emotional outcomes than a neutral agent. Further studies are needed to determine when tailoring and complex behaviours are justified.

The Effect of Multimodal Emotional Expression on Responses to a Digital Human during a Self-Disclosure Conversation: a Computational Analysis of User Language.

Digital humans show promise for use in healthcare as virtual therapists to deliver psychotherapy or companions for social support. For digital humans to be effective and engaging in these roles, it is important they can build close relationships with people. Emotional expressiveness can improve social closeness in human relationships, especially for females. However, it is unknown whether multimodal emotional expression improves relationships with digital humans. Participants were 185 adults aged 18years or older with English fluency. Participants were block-randomized by gender to complete the Relationship Closeness Induction Task with one of six versions of a digital human. The digital humans varied in modality richness (face, no face) and emotional expression (emotional voice, neutral voice; emotional face, neutral face). Participants' language was analysed for emotional content using Linguistic Inquiry and Word Count software. A series of three-way ANOVA and ANCOVA were conducted to evaluate the effect of digital human face type, voice type, and participant gender on emotional content in participant language. A digital human with no face was associated with more first-person singular pronoun use than a neutral face and an emotional face digital human. A digital human with no face and a neutral voice received more general negative emotion language than a digital human with no face and an emotional voice. Findings suggest the presence of a face and emotion in the voice may improve emotional responses to digital humans. Results provide evidence for aspects of the theoretical framework of embodied agent-patient communication.

Measuring Alliance Toward Embodied Virtual Therapists in the Era of Automated Treatments With the Virtual Therapist Alliance Scale (VTAS): Development and Psychometric Evaluation.

BackgroundAutomated virtual reality exposure therapies (VRETs) are self-help treatments conducted by oneself and supported by a virtual therapist embodied visually and/or with audio feedback. This simulates many of the nonspecific relational elements and common factors present in face-to-face therapy and may be a means of improving adherence to and efficacy of self-guided treatments. However, little is known about alliance toward the virtual therapist, despite alliance being an important predictor of treatment outcome.ObjectiveIn this study, we aimed to evaluate the first alliance instrument developed for use with embodied virtual therapists in an automated treatment format—the Virtual Therapist Alliance Scale (VTAS)—by (1) assessing its psychometric properties, (2) verifying the dimensionality of the scale, and (3) determining the predictive ability of the scale with treatment outcome.MethodsA psychometric evaluation and exploratory factor analysis of the VTAS was conducted using data from two samples of spider-fearful patients treated with VRET and the help of an embodied, voice-based virtual therapist (n=70). Multiple regression models and bivariate correlations were used to assess the VTAS relationship with treatment outcome, according to self-reported fear and convergence with presence and user-friendliness process measures.ResultsThe VTAS showed a sound two-factor solution composed of a primary factor covering task, goal, and copresence; adequate internal consistency; and good convergent validity, including moderate correlation (r=.310, P=.01) with outcomes over follow-up.ConclusionsThese preliminary results suggest that alliance toward a virtual therapist is a significant predictor of treatment outcome, favors the importance of a task-goal over bond-factor, and should be explored in studies with larger sample sizes and in additional forms of embodiment.

AI-powered therapy sets minds at rest

It made headline news when the leader of the UK's biggest relationship support charity revealed the organisation was considering the possibility of deploying chatbots using artificial intelligence (Al) for live chat counselling services. Developments in the potential of digital assistive technology to help treat a range of mental health issues are growing, and Al is proving a foundation technology for bots designed for human-like interaction with individuals. Their proponents say that these virtual therapists can help with disorders from low-level depression to social anxiety. They can also play a part in destigmatising mental health monitoring in homes and workplaces.

Online Treatment and Virtual Therapists in Child and Adolescent Psychiatry.

Online and virtual therapies are a well-studied and efficacious treatment option for various mental and behavioral health conditions among children and adolescents. However, many interventions have not considered the unique affordances offered by technologies that might align with the capacities and interests of youth users. In this article, the authors discuss learnings from child-computer interaction that can inform future generations of interventions and guide developers, practitioners, and researchers how to best use new technologies for youth populations. The article concludes with innovative examples illustrating future potentials of online and virtual therapies such as gaming and social networking.

Telerehabilitation, Virtual Therapists, and Acquired Neurologic Speech and Language Disorders

Telerehabilitation (telerehab) offers cost-effective services that potentially can improve access to care for those with acquired neurologic communication disorders. However, regulatory issues including licensure, reimbursement, and threats to privacy and confidentiality hinder the routine implementation of telerehab services into the clinical setting. Despite these barriers, rapid technological advances and a growing body of research regarding the use of telerehab applications support its use. This article reviews the evidence related to acquired neurologic speech and language disorders in adults, focusing on studies that have been published since 2000. Research studies have used telerehab systems to assess and treat disorders including dysarthria, apraxia of speech, aphasia, and mild Alzheimer disease. They show that telerehab is a valid and reliable vehicle for delivering speech and language services. The studies represent a progression of technological advances in computing, Internet, and mobile technologies. They range on a continuum from working synchronously (in real-time) with a speech-language pathologist to working asynchronously (offline) with a stand-in virtual therapist. One such system that uses a virtual therapist for the treatment of aphasia, the Web-ORLA™ (Rehabilitation Institute of Chicago, Chicago, IL) system, is described in detail. Future directions for the advancement of telerehab for clinical practice are discussed.