Cognitive Code: Integrating AI into Mental Health Practice

Bodhi, A Multidisciplinary Peer Reviewed Journal, 2024

Mental health refers to an individual's cognitive, emotional, and social well-being. It affects how people think, reacts to stressful situations, and deal with different conflicting situations. In the present article, the author discusses different factors of mental health viz., biological factors, social factors, and life experiences such as trauma or abuse. It is seen that there are lots of mental disorders such as anxiety disorder, mood disorder, schizophrenia, etc. that occurred. Psychologists have provided various signs that can help us to identify syndromes of mental illness and their treatments. In recent days, especially during the pandemic period, people could not reach psychiatrists and psychologists. For that reason, researchers feel to make a technology that could help us during such a helpless period. Researchers proposed an AI-powered chatbot therapy that might be helpful in this situation. In this article, the author tries to discuss whether machine therapy would be beneficial or not and whether it is more useful than face-to-face therapy.

International Journal of Research Publication and Reviews , 2023

Mental health is an important aspect of overall well-being and it has been widely recognized that Artificial intelligence (AI) technologies can play a significant role in improving mental health care. AI has made a significant impact on the healthcare industry, changing the perspectives of identifying, treating and monitoring patients. By enabling more individualized therapies and delivering more precise diagnoses, AI is significantly enhancing healthcare research and outcomes. The ability of AI in healthcare to quickly examine enormous amounts of clinical documentation aids in the identification of illness signs and trends that would otherwise go unnoticed by medical professionals. AI in the mental health field is an emerging field that uses AI techniques like machine learning, natural language processing, and other AI technologies to analyze large amounts of data in order to identify patterns, predict outcomes, and enhance the delivery of mental health care. Healthcare systems can become smarter, quicker, and more effective in providing treatment to millions of people worldwide by utilizing artificial intelligence in hospital and clinical settings.

This article is a write-up of a presentation “AI, New Technologies & Counselling: Challenges & Constructive Solutions” delivered in-person at the PSCA Conference entitled “Enhancing our Practice: Working Inclusively with Difference”, on May 1, 2025. This article discusses the implications of AI technologies on counselling in the following eight sections: [1] Distinctions between AI Chatbots and Conversational AI [2] Current research trends on AI Therapy platforms [3] An Overview of AI Chatbots for Mental Health [4] An Overview of Conversational AI for Mental Health [5] Challenges posed by AI Therapy platforms to counselling and mental health jobs [6] Six Risks posed by AI Software platforms to post-secondary students’ mental health [7] Seven Ways Counsellors may choose to work with AI software platforms and high technology for the Benefit of Students and [8] International Developments towards Mental Wellness Delivery at the Governmental, Think Tank, and Military Domains in the 21st Century.

Archives of Women Health and Care, 2025

The global mental health crisis, exacerbated by the pandemic, underscores the urgent need for innovative solutions. With approximately one in eight individuals experiencing a mental disorder, this review assesses the role of Artificial Intelligence (AI) in enhancing mental health care, particularly in Malaysia, where stigma, accessibility issues, and resource shortages hinder traditional services. A systematic literature review was conducted using databases such as PubMed and Scopus, focusing on studies published from 2022 to 2024. The review identified key AI applications, including chatbots and predictive analytics, which offer personalized and accessible mental health support. Results indicated that AI-driven solutions, exemplified by tools like "Chatbot Rakan Sihat," significantly improve engagement and mental health outcomes for underserved populations. Ethical concerns regarding data privacy and algorithmic bias were highlighted as critical challenges in AI integration. The findings emphasize AI's potential to reduce stigma and enhance service delivery in Malaysia's mental health landscape. This review's novelty lies in its focus on local implementation and ethical considerations, contributing to ongoing discourse on AI's integration into mental health care. Future research should investigate the long-term effectiveness of AI interventions, user experiences, and collaborative efforts to establish regulatory frameworks that prioritize patient welfare while optimizing mental health care accessibility and effectiveness.

InfoScience Trends, 2025

AI-driven psychological interventions offer scalable solutions for chronic illness patients in resource-limited settings, yet evidence gaps persist in low-income countries regarding efficacy, ethics, and implementation. A mixed-methods study (systematic review, survey of 122 Iranian health professionals, and 18 qualitative interviews) evaluated AI’s role in psychological support. The review analyzed 10 studies (2020–2025), while survey and interview data explored practitioner perceptions. The review identified efficacy in middle-income settings (e.g., chatbots reduced distress in Egyptian breast cancer patients [RCT, n=150]), but no studies in low-income countries. Survey results revealed high optimism for AI’s accessibility (90.2%) but significant concerns about privacy (76.2%) and cultural relevance (61.5%). Qualitative themes highlighted demands for dialect-adapted NLP, human escalation protocols, and integration with community health workers. AI tools show promise for expanding mental health care, but their success hinges on contextual adaptation, ethical safeguards, and infrastructure investment. Policymakers must address digital literacy and regulatory gaps to enable equitable deployment.

2nd RISEUP-PPD International Conference "Knowledge and Implementation Gaps in Peripartum Depression: Innovation and Future Directions", Sofia, September 21-22, 2023

Artificial Intelligence (AI) is present in various areas of society such as medicine, education, or science. Being able to store large amounts of data uninterruptedly thus proves to be more advantageous when compared to the learning capacity of the human being. The large amount of data collected, which includes details of private lives in common applications, includes personal health data that can now be more easily inferred from points outside the medical context. This new ability to create health data from online content, outside the medical context, which has been referred to as "emerging medical data", often occurs without the knowledge or consent of users, which has generated concern and proved to be a challenge. This communication aims to contribute to this area, making known the results of the work developed on the issues of ethics in research using AI, particularly around mental health research. For this purpose, a literature review was conducted covering the period between 2016 and 2023. In general, a generalized concern with ethical issues was identified, which can hardly keep up with the technological pace. However, the OECD and the European Union have already defined some guidelines and suggested further development of the management of large amounts of data, for example through the FAIR principles – Findability, Accessibility, Interoperability, and Reusability – and a more careful observation of ethical issues at the various stages of the data cycle. Keywords: artificial intelligence, mental health, ethics in research, FAIR principles

ISAR Journal of Medical and Pharmaceutical Sciences, 2025

The crisis of the global mental health is still gaining momentum, with yearly increasing rates of prevalence of mental disorders and the lacking ability of the health systems to respond to the ascending demand for psychological services. This load is exacerbating especially in low-and middle-income countries in which access to well-trained mental health specialists is still limited. To address these challenges, Artificial Intelligence (AI) has become one of the promising solutions, which provides scalable and cost-effective, highly personalized ways of caring for mental health. This study addresses the current and emerging uses of AI in psychotherapy range from AI-aided therapies like Cognitive Behavioural Therapy platforms, real-time emotion detection algorithms, and virtual reality environments for therapy. It critically examines some of the key implementation issues, including technological constraints of AI, cultural acceptance of machine-aided therapy and urgent ethical considerations of data privacy, consent as well as clinical supervision. Also, it recognizes controlling variables such as the quality of the therapeutic alliance, character and characteristics of individual clients, the ability of the therapist to be adaptable, all of which contribute to the success of AI-integrated interventions. It therefore concludes by giving strategic recommendations on how ethical and inclusive AI technology can be deployed in psychotherapy. It recommends blended care models that maintain irreplaceable human components of therapy as it exploits technological innovation. With such integration, AI will be able to make a considerable difference in the access, treatment engagement, and better therapeutic outcomes across the globe.

Journal Of Community Mental Health and Public Policy, 2024

Background: This paper focuses on the increasing relevance of AI in mental health care, particularly OpenAI's ChatGPT. It investigates the changing dynamics in mental health, analyzing ChatGPT's role, its benefits, drawbacks, and ethical complexities. Purpose: The objective is to assess ChatGPT's effectiveness in mental health, highlighting its strengths and limitations, and ethical issues. The study aims to understand how AI support can be balanced with the vital human aspect in mental health care. Methods: Comprehensive literature review of 7 pieces of literature from the Scopus database in 2023 (latest). Results: ChatGPT is found to be a useful initial mental health support tool, offering immediate access. However, it falls short in delivering the emotional depth that human health professionals provide. Key ethical concerns include data privacy and accountability. Conclusion: The study recommends a balanced approach, suggesting ChatGPT as an adjunct rather than a replacement for conventional mental health services. Effective use of ChatGPT in mental health care requires strict ethical guidelines and control measures to maintain the crucial human element in this field.

J. Electrical Systems, 2024

Objective: This review aims to explore the current and future trends in using artificial intelligence (AI) for diagnosing and treating mental health disorders. It emphasizes innovative diagnostic approaches and individualized therapy options made possible by AI technologies. Method: A comprehensive literature review was conducted, focusing on articles published between January 2010 and December 2022. Databases such as PubMed, IEEE Xplore, ACM Digital Library, and Google Scholar were searched using relevant keywords. Inclusion criteria required original research articles published in English, involving AI applications in mental health diagnosis, screening, monitoring, or therapy. The selected studies were assessed for quality using established checklists, and data were extracted on study aims, participants, AI techniques, and outcomes. Results: AI technologies, including machine learning algorithms, natural language processing (NLP), and speech analysis, have demonstrated significant potential in enhancing the accuracy of mental health diagnoses. For instance, AI systems have been able to distinguish between bipolar disorder and major depressive disorder with high accuracy. In treatment, AI-driven tools such as chatbots and mobile applications have shown efficacy in delivering cognitive behavioral therapy and other interventions. Wearable devices and virtual reality applications provide additional support by enabling continuous monitoring and exposure therapy. Conclusion: AI has the potential to revolutionize mental health care by improving diagnostic precision, personalizing treatment, and providing continuous support. However, ethical considerations, such as data privacy and algorithmic bias, must be addressed to ensure the responsible use of AI in clinical settings. With careful integration and oversight, AI can significantly enhance the effectiveness and accessibility of mental health services, offering new hope for patients and clinicians alike.

Journal of Medical Internet Research, 2019

Background: Research in embodied artificial intelligence (AI) has increasing clinical relevance for therapeutic applications in mental health services. With innovations ranging from ‘virtual psychotherapists’ to social robots in dementia care and autism disorder, to robots for sexual disorders, artificially intelligent virtual and robotic agents are increasingly taking on high-level therapeutic interventions that used to be offered exclusively by highly trained, skilled health professionals. In order to enable responsible clinical implementation, ethical and social implications of the increasing use of embodied AI in mental health need to be identified and addressed. Objective: This paper assesses the ethical and social implications of translating embodied AI applications into mental health care across the fields of Psychiatry, Psychology and Psychotherapy. Building on this analysis, it develops a set of preliminary recommendations on how to address ethical and social challenges in current and future applications of embodied AI. Methods: Based on a thematic literature search and established principles of medical ethics, an analysis of the ethical and social aspects of currently embodied AI applications was conducted across the fields of Psychiatry, Psychology, and Psychotherapy. To enable a comprehensive evaluation, the analysis was structured around the following three steps: assessment of potential benefits; analysis of overarching ethical issues and concerns; discussion of specific ethical and social issues of the interventions. Results: From an ethical perspective, important benefits of embodied AI applications in mental health include new modes of treatment, opportunities to engage hard-to-reach populations, better patient response, and freeing up time for physicians. Overarching ethical issues and concerns include: harm prevention and various questions of data ethics; a lack of guidance on development of AI applications, their clinical integration and training of health professionals; ‘gaps’ in ethical and regulatory frameworks; the potential for misuse including using the technologies to replace established services, thereby potentially exacerbating existing health inequalities. Specific challenges identified and discussed in the application of embodied AI include: matters of risk-assessment, referrals, and supervision; the need to respect and protect patient autonomy; the role of non-human therapy; transparency in the use of algorithms; and specific concerns regarding long-term effects of these applications on understandings of illness and the human condition. Conclusions: We argue that embodied AI is a promising approach across the field of mental health; however, further research is needed to address the broader ethical and societal concerns of these technologies to negotiate best research and medical practices in innovative mental health care. We conclude by indicating areas of future research and developing recommendations for high-priority areas in need of concrete ethical guidance.