Exploring the Role of Artificial Intelligence in Mental Healthcare: Current Trends and Future Directions – A Narrative Review for a Comprehensive Insight

Risk Management and Healthcare Policy, Год журнала: 2024, Номер Volume 17, С. 1339 - 1348

Опубликована: Май 1, 2024

Abstract: Mental health is an essential component of the and well-being a person community, it critical for individual, society, socio-economic development any country. healthcare currently in sector transformation era, with emerging technologies such as artificial intelligence (AI) reshaping screening, diagnosis, treatment modalities psychiatric illnesses. The present narrative review aimed at discussing current landscape role AI mental healthcare, including treatment. Furthermore, this attempted to highlight key challenges, limitations, prospects providing based on existing works literature. literature search was obtained from PubMed, Saudi Digital Library (SDL), Google Scholar, Web Science, IEEE Xplore, we included only English-language articles published last five years. Keywords used combination Boolean operators ("AND" "OR") were following: "Artificial intelligence", "Machine learning", Deep "Early diagnosis", "Treatment", "interventions", "ethical consideration", "mental Healthcare". Our revealed that, equipped predictive analytics capabilities, can improve planning by predicting individual's response various interventions. Predictive analytics, which uses historical data formulate preventative interventions, aligns move toward individualized preventive healthcare. In screening diagnostic domains, subset AI, machine learning deep learning, has been proven analyze sets predict patterns associated problems. However, limited studies have evaluated collaboration between professionals delivering these sensitive problems require empathy, human connections, holistic, personalized, multidisciplinary approaches. Ethical issues, cybersecurity, lack diversity, cultural sensitivity, language barriers remain concerns implementing futuristic approach Considering approaches, imperative explore aspects. Therefore, future comparative trials larger sample sizes are warranted evaluate different models across regions fill knowledge gaps. Keywords: intelligence, early interventions

Язык: Английский

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Ethical Considerations in Artificial Intelligence Interventions for Mental Health and Well-Being: Ensuring Responsible Implementation and Impact

Social Sciences, Год журнала: 2024, Номер 13(7), С. 381 - 381

Опубликована: Июль 22, 2024

AI has the potential to revolutionize mental health services by providing personalized support and improving accessibility. However, it is crucial address ethical concerns ensure responsible beneficial outcomes for individuals. This systematic review examines considerations surrounding implementation impact of artificial intelligence (AI) interventions in field well-being. To a comprehensive analysis, we employed structured search strategy across top academic databases, including PubMed, PsycINFO, Web Science, Scopus. The scope encompassed articles published from 2014 2024, resulting 51 relevant articles. identifies 18 key considerations, 6 associated with using wellbeing (privacy confidentiality, informed consent, bias fairness, transparency accountability, autonomy human agency, safety efficacy); 5 principles development technologies settings practice positive (ethical framework, stakeholder engagement, review, mitigation, continuous evaluation improvement); 7 practices, guidelines, recommendations promoting use (adhere transparency, prioritize data privacy security, mitigate involve stakeholders, conduct regular reviews, monitor evaluate outcomes). highlights importance By addressing privacy, bias, oversight, evaluation, can that like chatbots AI-enabled medical devices are developed deployed an ethically sound manner, respecting individual rights, maximizing benefits while minimizing harm.

Язык: Английский

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The use of artificial intelligence in psychotherapy: development of intelligent therapeutic systems

BMC Psychology, Год журнала: 2025, Номер 13(1)

Опубликована: Фев. 28, 2025

The increasing demand for psychotherapy and limited access to specialists underscore the potential of artificial intelligence (AI) in mental health care. This study evaluates effectiveness AI-powered Friend chatbot providing psychological support during crisis situations, compared traditional psychotherapy. A randomized controlled trial was conducted with 104 women diagnosed anxiety disorders active war zones. Participants were randomly assigned two groups: experimental group used daily support, while control received 60-minute sessions three times a week. Anxiety levels assessed using Hamilton Rating Scale Beck Inventory. T-tests analyze results. Both groups showed significant reductions levels. receiving therapy had 45% reduction on scale 50% scale, 30% 35% group. While provided accessible, immediate proved more effective due emotional depth adaptability by human therapists. particularly beneficial settings where therapists limited, proving its value scalability availability. However, engagement notably lower in-person therapy. offers scalable, cost-effective solution situations may not be accessible. Although remains reducing anxiety, hybrid model combining AI interaction could optimize care, especially underserved areas or emergencies. Further research is needed improve AI's responsiveness adaptability.

Язык: Английский

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AI in the Classroom: Insights from Educators on Usage, Challenges, and Mental Health

Education Sciences, Год журнала: 2025, Номер 15(2), С. 113 - 113

Опубликована: Янв. 21, 2025

This study examines educators’ perceptions of artificial intelligence (AI) in educational settings, focusing on their familiarity with AI tools, integration into teaching practices, professional development needs, the influence institutional policies, and impacts mental health. Survey responses from 353 educators across various levels countries revealed that 92% respondents are familiar AI, utilizing it to enhance efficiency streamline administrative tasks. Notably, many reported students using tools like ChatGPT for assignments, prompting adaptations methods promote critical thinking reduce dependency. Some saw AI’s potential stress through automation but others raised concerns about increased anxiety social isolation reduced interpersonal interactions. highlights a gap leading some establish own guidelines, particularly matters such as data privacy plagiarism. Furthermore, identified significant need focused literacy ethical considerations. study’s findings suggest necessity longitudinal studies explore long-term effects outcomes health underscore importance incorporating student perspectives thorough understanding role education.

Язык: Английский

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Utilizing natural language processing and large language models in the diagnosis and prediction of infectious diseases: A systematic review

American Journal of Infection Control, Год журнала: 2024, Номер 52(9), С. 992 - 1001

Опубликована: Апрель 6, 2024

Язык: Английский

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Large Language Models in Mental Health Care: A Systematic Scoping Review (Preprint)

Опубликована: Июль 8, 2024

The integration of large language models (LLMs) in mental health care is an emerging field. There a need to systematically review the application outcomes and delineate advantages limitations clinical settings. This aims provide comprehensive overview use LLMs care, assessing their efficacy, challenges, potential for future applications. A systematic search was conducted across multiple databases including PubMed, Web Science, Google Scholar, arXiv, medRxiv, PsyArXiv November 2023. All forms original research, peer-reviewed or not, published disseminated between October 1, 2019, December 2, 2023, are included without restrictions if they used developed after T5 directly addressed research questions From initial pool 313 articles, 34 met inclusion criteria based on relevance LLM robustness reported outcomes. Diverse applications identified, diagnosis, therapy, patient engagement enhancement, etc. Key challenges include data availability reliability, nuanced handling states, effective evaluation methods. Despite successes accuracy accessibility improvement, gaps applicability ethical considerations were evident, pointing robust data, standardized evaluations, interdisciplinary collaboration. hold substantial promise enhancing care. For full be realized, emphasis must placed developing datasets, development frameworks, guidelines, collaborations address current limitations.

Язык: Английский

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Applications of large language models in psychiatry: a systematic review

Frontiers in Psychiatry, Год журнала: 2024, Номер 15

Опубликована: Июнь 24, 2024

Background With their unmatched ability to interpret and engage with human language context, large models (LLMs) hint at the potential bridge AI cognitive processes. This review explores current application of LLMs, such as ChatGPT, in field psychiatry. Methods We followed PRISMA guidelines searched through PubMed, Embase, Web Science, Scopus, up until March 2024. Results From 771 retrieved articles, we included 16 that directly examine LLMs’ use particularly ChatGPT GPT-4, showed diverse applications clinical reasoning, social media, education within They can assist diagnosing mental health issues, managing depression, evaluating suicide risk, supporting field. However, our also points out limitations, difficulties complex cases underestimation risks. Conclusion Early research psychiatry reveals versatile applications, from diagnostic support educational roles. Given rapid pace advancement, future investigations are poised explore extent which these might redefine traditional roles care.

Язык: Английский

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Regulating AI in Mental Health: Ethics of Care Perspective

JMIR Mental Health, Год журнала: 2024, Номер 11, С. e58493 - e58493

Опубликована: Июль 20, 2024

This article contends that the responsible artificial intelligence (AI) approach-which is dominant ethics approach ruling most regulatory and ethical guidance-falls short because it overlooks impact of AI on human relationships. Focusing only principles reinforces a narrow concept accountability responsibility companies developing AI. proposes applying care to regulation can offer more comprehensive framework addresses AI's dual essential for effective in domain mental health care. The delves into emergence new "therapeutic" area facilitated by AI-based bots, which operate without therapist. highlights difficulties involved, mainly absence defined duty toward users, shows how implementing establish clear responsibilities developers. It also sheds light potential emotional manipulation risks involved. In conclusion, series considerations grounded developmental process AI-powered therapeutic tools.

Язык: Английский

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“It happened to be the perfect thing”: experiences of generative AI chatbots for mental health

npj Mental Health Research, Год журнала: 2024, Номер 3(1)

Опубликована: Окт. 27, 2024

Abstract The global mental health crisis underscores the need for accessible, effective interventions. Chatbots based on generative artificial intelligence (AI), like ChatGPT, are emerging as novel solutions, but research real-life usage is limited. We interviewed nineteen individuals about their experiences using AI chatbots health. Participants reported high engagement and positive impacts, including better relationships healing from trauma loss. developed four themes: (1) a sense of ‘ emotional sanctuary’ , (2) insightful guidance’ particularly relationships, (3) joy connection ’, (4) comparisons between therapist ’ human therapy. Some themes echoed prior rule-based chatbots, while others seemed to AI. emphasised safety guardrails, human-like memory ability lead therapeutic process. Generative may offer support that feels meaningful users, further needed effectiveness.

Язык: Английский

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The Future of Artificial Intelligence in Mental Health Nursing Practice: An Integrative Review

International Journal of Mental Health Nursing, Год журнала: 2025, Номер 34(1)

Опубликована: Янв. 23, 2025

ABSTRACT Artificial intelligence (AI) has been increasingly used in delivering mental healthcare worldwide. Within this context, the traditional role of health nurses changed and challenged by AI‐powered cutting‐edge technologies emerging clinical practice. The aim integrative review is to identify synthesise evidence AI‐based applications with relevance for, potential enhance, nursing Five electronic databases (CINAHL, PubMed, PsycINFO, Web Science Scopus) were systematically searched. Seventy‐eight studies identified, critically appraised synthesised following a comprehensive approach. We found that AI use vary widely from machine learning algorithms natural language processing, digital phenotyping, computer vision conversational agents for assessing, diagnosing treating challenges. overarching themes identified: assessment, identification, prediction, optimisation perception reflecting multiple levels embedding AI‐driven practice, how patients staff perceive settings. concluded hold great enhancing However, humanistic approaches may pose some challenges effectively incorporating into nursing. Meaningful conversations between nurses, service users developers should take place shaping co‐creation enhance care way promotes person‐centredness, empowerment active participation.

Язык: Английский

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