Waiting for a digital therapist: three challenges on the path to psychotherapy delivered by artificial intelligence

An Ethical Perspective on the Democratization of Mental Health With Generative AI

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Knowledge has become more open and accessible to a large audience with the "democratization of information" facilitated by technology. This paper provides a sociohistorical perspective for the theme issue "Responsible Design, Integration, and Use of Generative AI in Mental Health." It evaluates ethical considerations in using generative artificial intelligence (GenAI) for the democratization of mental health knowledge and practice. It explores the historical context of democratizing information, transitioning from restricted access to widespread availability due to the internet, open-source movements, and most recently, GenAI technologies such as large language models. The paper highlights why GenAI technologies represent a new phase in the democratization movement, offering unparalleled access to highly advanced technology as well as information. In the realm of mental health, this requires delicate and nuanced ethical deliberation. Including GenAI in mental health may allow, among other things, improved accessibility to mental health care, personalized responses, and conceptual flexibility, and could facilitate a flattening of traditional hierarchies between health care providers and patients. At the same time, it also entails significant risks and challenges that must be carefully addressed. To navigate these complexities, the paper proposes a strategic questionnaire for assessing artificial intelligence-based mental health applications. This tool evaluates both the benefits and the risks, emphasizing the need for a balanced and ethical approach to GenAI integration in mental health. The paper calls for a cautious yet positive approach to GenAI in mental health, advocating for the active engagement of mental health professionals in guiding GenAI development. It emphasizes the importance of ensuring that GenAI advancements are not only technologically sound but also ethically grounded and patient-centered.

Digital transformation of mental health therapy by integrating digitalized cognitive behavioral therapy and eye movement desensitization and reprocessing

Digital therapy has gained popularity in the mental health field because of its convenience and accessibility. One major benefit of digital therapy is its ability to address therapist shortages. Posttraumatic stress disorder (PTSD) is a debilitating mental health condition that can develop after an individual experiences or witnesses a traumatic event. Digital therapy is an important resource for individuals with PTSD who may not have access to traditional in-person therapy. Cognitive behavioral therapy (CBT) and eye movement desensitization and reprocessing (EMDR) are two evidence-based psychotherapies that have shown efficacy in treating PTSD. This paper examines the mechanisms and clinical symptoms of PTSD as well as the principles and applications of CBT and EMDR. Additionally, the potential of digital therapy, including internet-based CBT, video conferencing-based therapy, and exposure therapy using augmented and virtual reality, is explored. This paper also discusses the engineering techniques employed in digital psychotherapy, such as emotion detection models and text analysis, for assessing patients' emotional states. Furthermore, it addresses the challenges faced in digital therapy, including regulatory issues, hardware limitations, privacy and security concerns, and effectiveness considerations. Overall, this paper provides a comprehensive overview of the current state of digital psychotherapy for PTSD treatment and highlights the opportunities and challenges in this rapidly evolving field.

War, emotions, mental health, and artificial intelligence

During the war time dysregulation of negative emotions such as fear, anger, hatred, frustration, sadness, humiliation, and hopelessness can overrule normal societal values, culture, and endanger global peace and security, and mental health in affected societies. Therefore, it is understandable that the range and power of negative emotions may play important roles in consideration of human behavior in any armed conflict. The estimation and assessment of dominant negative emotions during war time are crucial but are challenged by the complexity of emotions' neuro-psycho-physiology. Currently available natural language processing (NLP) tools have comprehensive computational methods to analyze and understand the emotional content of related textual data in war-inflicted societies. Innovative AI-driven technologies incorporating machine learning, neuro-linguistic programming, cloud infrastructure, and novel digital therapeutic tools and applications present an immense potential to enhance mental health care worldwide. This advancement could make mental health services more cost-effective and readily accessible. Due to the inadequate number of psychiatrists and limited psychiatric resources in coping with mental health consequences of war and traumas, new digital therapeutic wearable devices supported by AI tools and means might be promising approach in psychiatry of future. Transformation of negative dominant emotional maps might be undertaken by the simultaneous combination of online cognitive behavioral therapy (CBT) on individual level, as well as usage of emotionally based strategic communications (EBSC) on a public level. The proposed positive emotional transformation by means of CBT and EBSC may provide important leverage in efforts to protect mental health of civil population in war-inflicted societies. AI-based tools that can be applied in design of EBSC stimuli, like Open AI Chat GPT or Google Gemini may have great potential to significantly enhance emotionally based strategic communications by more comprehensive understanding of semantic and linguistic analysis of available text datasets of war-traumatized society. Human in the loop enhanced by Chat GPT and Gemini can aid in design and development of emotionally annotated messages that resonate among targeted population, amplifying the impact of strategic communications in shaping human dominant emotional maps into a more positive by CBT and EBCS.

The Artificial Third: A Broad View of the Effects of Introducing Generative Artificial Intelligence on Psychotherapy

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This paper explores a significant shift in the field of mental health in general and psychotherapy in particular following generative artificial intelligence's new capabilities in processing and generating humanlike language. Following Freud, this lingo-technological development is conceptualized as the "fourth narcissistic blow" that science inflicts on humanity. We argue that this narcissistic blow has a potentially dramatic influence on perceptions of human society, interrelationships, and the self. We should, accordingly, expect dramatic changes in perceptions of the therapeutic act following the emergence of what we term the artificial third in the field of psychotherapy. The introduction of an artificial third marks a critical juncture, prompting us to ask the following important core questions that address two basic elements of critical thinking, namely, transparency and autonomy: (1) What is this new artificial presence in therapy relationships? (2) How does it reshape our perception of ourselves and our interpersonal dynamics? and (3) What remains of the irreplaceable human elements at the core of therapy? Given the ethical implications that arise from these questions, this paper proposes that the artificial third can be a valuable asset when applied with insight and ethical consideration, enhancing but not replacing the human touch in therapy.

Assessing the Alignment of Large Language Models With Human Values for Mental Health Integration: Cross-Sectional Study Using Schwartz's Theory of Basic Values

BACKGROUND

Large language models (LLMs) hold potential for mental health applications. However, their opaque alignment processes may embed biases that shape problematic perspectives. Evaluating the values embedded within LLMs that guide their decision-making have ethical importance. Schwartz's theory of basic values (STBV) provides a framework for quantifying cultural value orientations and has shown utility for examining values in mental health contexts, including cultural, diagnostic, and therapist-client dynamics.

OBJECTIVE

This study aimed to (1) evaluate whether the STBV can measure value-like constructs within leading LLMs and (2) determine whether LLMs exhibit distinct value-like patterns from humans and each other.

METHODS

In total, 4 LLMs (Bard, Claude 2, Generative Pretrained Transformer [GPT]-3.5, GPT-4) were anthropomorphized and instructed to complete the Portrait Values Questionnaire-Revised (PVQ-RR) to assess value-like constructs. Their responses over 10 trials were analyzed for reliability and validity. To benchmark the LLMs' value profiles, their results were compared to published data from a diverse sample of 53,472 individuals across 49 nations who had completed the PVQ-RR. This allowed us to assess whether the LLMs diverged from established human value patterns across cultural groups. Value profiles were also compared between models via statistical tests.

RESULTS

The PVQ-RR showed good reliability and validity for quantifying value-like infrastructure within the LLMs. However, substantial divergence emerged between the LLMs' value profiles and population data. The models lacked consensus and exhibited distinct motivational biases, reflecting opaque alignment processes. For example, all models prioritized universalism and self-direction, while de-emphasizing achievement, power, and security relative to humans. Successful discriminant analysis differentiated the 4 LLMs' distinct value profiles. Further examination found the biased value profiles strongly predicted the LLMs' responses when presented with mental health dilemmas requiring choosing between opposing values. This provided further validation for the models embedding distinct motivational value-like constructs that shape their decision-making.

CONCLUSIONS

This study leveraged the STBV to map the motivational value-like infrastructure underpinning leading LLMs. Although the study demonstrated the STBV can effectively characterize value-like infrastructure within LLMs, substantial divergence from human values raises ethical concerns about aligning these models with mental health applications. The biases toward certain cultural value sets pose risks if integrated without proper safeguards. For example, prioritizing universalism could promote unconditional acceptance even when clinically unwise. Furthermore, the differences between the LLMs underscore the need to standardize alignment processes to capture true cultural diversity. Thus, any responsible integration of LLMs into mental health care must account for their embedded biases and motivation mismatches to ensure equitable delivery across diverse populations. Achieving this will require transparency and refinement of alignment techniques to instill comprehensive human values.

Hypnosis in psychotherapy, psychosomatics and medicine. A brief overview

Aspects of hypnosis and its application in psychotherapy, psychosomatics and medicine are examined and contextualized in the 250-year history of hypnosis. Imagination as an essential element of hypnotic treatments appeared as early as 1784 as an argument rejecting the theory of animal magnetism of Franz Anton Mesmer. In somnambulism of German romanticism, another proto-form of hypnosis after 1800, concepts of the mind-body problem were dealt with, which still characterize the understanding of unconscious mental processes today. Hypnosis was at the beginning of psychoanalysis, but was not pursued further by Sigmund Freud from 1900 onwards. Nevertheless, there were some hypnoanalytical approaches in the 20th century, as well as attempts to integrate hypnosis into behavior therapy. Techniques of imagination and relaxation combine both; in particular findings from cognitive psychology explain processes of both hypnosis and cognitive behavioral therapy. The influence of social psychology brought a new perspective to the debate about the nature of hypnosis, which continues to this day: is hypnosis to be understood as a special state of consciousness or is it a completely normal, mundane interaction? The experiments that were carried out to support one side or the other were also dependent on the hypnotizability of the subjects involved, as the more difficult hypnotic phenomena such as paralysis, hallucinations or identity delusions can only be demonstrated by highly hypnotizable subjects. The fact that these are not mere compliance reactions has now been proven by many studies using imaging techniques. But even those who are moderately hypnotizable benefit from hypnosis rituals. Variables postulated by socio-cognitive hypnosis researchers, such as motivation and expectation, are relevant, as is a good "hypnotic rapport." Practical application of hypnotherapy today is characterized by the innovative techniques and strategies developed by Milton H. Erickson. Research into the effectiveness of hypnosis in the field of psychotherapy and psychosomatics still leaves much to be done. The situation is different in the field of medical hypnosis, where there are considerably more studies with a satisfactory design and verifiable effects. However, the impact in practical application in everyday medical practice is still low. Newer developments such as virtual reality and artificial intelligence are being looked at with critical interest.

Psychological interventions for depression in children and adolescents: A bibliometric analysis

BACKGROUND

Depression has gradually become a common psychological disorder among children and adolescents. Depression in children and adolescents affects their physical and mental development. Psychotherapy is considered to be one of the main treatment options for depressed children and adolescents. However, our understanding of the global performance and progress of psychological interventions for depression in children and adolescents (PIDCA) research is limited.

AIM

To identify collaborative research networks in this field and explore the current research status and hotspots through bibliometrics.

METHODS

Articles and reviews related to PIDCA from January 2010 to April 2023 were identified from the Web of Science Core Collection database. The Charticulator website, CiteSpace and VOSviewer software were used to visualize the trends in publications and citations, the collaborative research networks (countries, institutions, and authors), and the current research status and hotspots.

RESULTS

Until April 16, 2023, 1482 publications were identified. The number of documents published each year and citations had increased rapidly in this field. The United States had the highest productivity in this field. The most prolific institution was the University of London. Pim Cuijpers was the most prolific author. In the context of research related to PIDCA, both reference co-citation analysis and keywords co-occurrence analysis identified 10 research hotspots, including third-wave cognitive behavior therapy, short-term psychoanalytic psychotherapy, cognitive behavioral analysis system of psychotherapy, family element in psychotherapy, modular treatment, mobile-health, emotion-regulation-based transdiagnostic intervention program, dementia risk in later life, predictors of the efficacy of psychological intervention, and risks of psychological intervention.

CONCLUSION

This bibliometric study provides a comprehensive overview of PIDCA from 2010 to present. Psychological intervention characterized as psychological-process-focused, short, family-involved, modular, internet-based, emotion-regulation-based, and personalized may benefit more young people.

Potential use of large language models for mitigating students' problematic social media use: ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals' daily lives, interpersonal relationships, physical and mental health, and more. Currently, there are few methods and tools to alleviate problematic social media, and their potential is yet to be fully realized. Emerging large language models (LLMs) are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life. In mitigating problematic social media use, LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users, providing personalized information and resources, monitoring and intervening in problematic social media use, and more. In this process, we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT, leveraging their advantages to better address problematic social media use, while also acknowledging the limitations and potential pitfalls of ChatGPT technology, such as errors, limitations in issue resolution, privacy and security concerns, and potential overreliance. When we leverage the advantages of LLMs to address issues in social media usage, we must adopt a cautious and ethical approach, being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

Artificial intelligence and social intelligence: preliminary comparison study between AI models and psychologists

Background

Social intelligence (SI) is of great importance in the success of the counseling and psychotherapy, whether for the psychologist or for the artificial intelligence systems that help the psychologist, as it is the ability to understand the feelings, emotions, and needs of people during the counseling process. Therefore, this study aims to identify the Social Intelligence (SI) of artificial intelligence represented by its large linguistic models, "ChatGPT; Google Bard; and Bing" compared to psychologists.

Methods

A stratified random manner sample of 180 students of counseling psychology from the bachelor's and doctoral stages at King Khalid University was selected, while the large linguistic models included ChatGPT-4, Google Bard, and Bing. They (the psychologists and the AI models) responded to the social intelligence scale.

Results

There were significant differences in SI between psychologists and AI's ChatGPT-4 and Bing. ChatGPT-4 exceeded 100% of all the psychologists, and Bing outperformed 50% of PhD holders and 90% of bachelor's holders. The differences in SI between Google Bard and bachelor students were not significant, whereas the differences with PhDs were significant; Where 90% of PhD holders excel on Google Bird.

Conclusion

We explored the possibility of using human measures on AI entities, especially language models, and the results indicate that the development of AI in understanding emotions and social behavior related to social intelligence is very rapid. AI will help the psychotherapist a great deal in new ways. The psychotherapist needs to be aware of possible areas of further development of AI given their benefits in counseling and psychotherapy. Studies using humanistic and non-humanistic criteria with large linguistic models are needed.

Assessing the potential of ChatGPT for psychodynamic formulations in psychiatry: An exploratory study

Although there were several attempts to apply ChatGPT (Generative Pre-Trained Transformer) to medicine, little is known about therapeutic applications in psychiatry. In this exploratory study, we aimed to evaluate the characteristics and appropriateness of the psychodynamic formulations created by ChatGPT. Along with a case selected from the psychoanalytic literature, input prompts were designed to include different levels of background knowledge. These included naïve prompts, keywords created by ChatGPT, keywords created by psychiatrists, and psychodynamic concepts from the literature. The psychodynamic formulations generated from the different prompts were evaluated by five psychiatrists from different institutions. We next conducted further tests in which instructions on the use of different psychodynamic models were added to the input prompts. The models used were ego psychology, self-psychology, and object relations. The results from naïve prompts and psychodynamic concepts were rated as appropriate by most raters. The psychodynamic concept prompt output was rated the highest. Interrater agreement was statistically significant. The results from the tests using instructions in different psychoanalytic theories were also rated as appropriate by most raters. They included key elements of the psychodynamic formulation and suggested interpretations similar to the literature. These findings suggest potential of ChatGPT for use in psychiatry.