Large language models could change the future of behavioral healthcare: a proposal for responsible development and evaluation

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

Опубликована: Апрель 2, 2024

Abstract Large language models (LLMs) such as Open AI’s GPT-4 (which power ChatGPT) and Google’s Gemini, built on artificial intelligence, hold immense potential to support, augment, or even eventually automate psychotherapy. Enthusiasm about applications is mounting in the field well industry. These developments promise address insufficient mental healthcare system capacity scale individual access personalized treatments. However, clinical psychology an uncommonly high stakes application domain for AI systems, responsible evidence-based therapy requires nuanced expertise. This paper provides a roadmap ambitious yet of LLMs First, technical overview presented. Second, stages integration into psychotherapy are discussed while highlighting parallels development autonomous vehicle technology. Third, care, training, research discussed, areas risk given complex nature Fourth, recommendations evaluation provided, which include centering science, involving robust interdisciplinary collaboration, attending issues like assessment, detection, transparency, bias. Lastly, vision outlined how might enable new generation studies interventions at scale, these may challenge assumptions

Язык: Английский

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Co-design of a single session intervention chatbot for people on waitlists for eating disorder treatment: a qualitative interview and workshop study

Journal of Eating Disorders, Год журнала: 2025, Номер 13(1)

Опубликована: Март 11, 2025

Abstract Background Early treatment is critical to improve eating disorder prognosis. Single session interventions have been proposed as a strategy provide short term support people on waitlists for treatment, however, it not always possible access this early intervention. Conversational artificial intelligence agents or “chatbots” reflect unique opportunity attempt fill gap in service provision. The aim of research was co-design novel chatbot capable delivering single intervention adults the waitlist across diagnostic spectrum and ascertain its preliminary acceptability feasibility. Methods A Double Diamond approach employed which included four phases: discover, define, develop, deliver. There were 17 participants total Australia; ten with lived experience an seven registered psychologists working field disorders, who participated online interviews workshops. Thematic content analyses undertaken interview/workshop transcriptions findings from previous phase informing ideas development next phase. final prototype presented deliver Results identified main themes that present phases interviews/workshops: conversational tone, safety risk management, user journey structure, content. Conclusions Overall, feedback positive throughout process both psychologists. Incorporating allowed refinement chatbot. Further required evaluate chatbot’s efficacy settings.

Язык: Английский

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Potential benefits and limitations of machine learning in the field of eating disorders: current research and future directions

Journal of Eating Disorders, Год журнала: 2022, Номер 10(1)

Опубликована: Май 8, 2022

Abstract Advances in machine learning and digital data provide vast potential for mental health predictions. However, research using the field of eating disorders is just beginning to emerge. This paper provides a narrative review existing explores benefits, limitations, ethical considerations aid detection, prevention, treatment disorders. Current primarily uses predict disorder status from females’ responses validated surveys, social media posts, or neuroimaging often with relatively high levels accuracy. early work evidence improve current screening methods. ability these algorithms generalise other samples be used on mass scale only explored. One key benefit over traditional statistical methods simultaneously examine large numbers (100s 1000s) multimodal predictors their complex non-linear interactions, but few studies have explored this Machine also being develop chatbots psychoeducation coping skills training around body image disorders, implications intervention. The use personalise options, ecological momentary interventions, clinicians discussed. accurate, rapid, cost-effective More needed diverse participants ensure that models are unbiased, generalisable all people There important limitations utilising practice. Thus, rather than magical solution, should seen as an tool researchers, eventually clinicians, identification,

Язык: Английский

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Development and usability testing of a chatbot to promote mental health services use among individuals with eating disorders following screening

International Journal of Eating Disorders, Год журнала: 2022, Номер 55(9), С. 1229 - 1244

Опубликована: Авг. 18, 2022

Abstract Objective A significant gap exists between those who need and receive care for eating disorders (EDs). Novel solutions are needed to encourage service use address treatment barriers. This study developed evaluated the usability of a chatbot designed pairing with online ED screening. The tool aimed promote mental health utilization by improving motivation self‐efficacy among individuals EDs. Methods prototype, Alex, was using decision trees theoretically‐informed components: psychoeducation, motivational interviewing, personalized recommendations, repeated administration. Usability testing conducted over four iterative cycles, user feedback informing refinements next iteration. Post‐testing, participants (N= 21) completed System Scale (SUS), Usefulness, Satisfaction, Ease Use Questionnaire (USE), semi‐structured interview. Results Interview detailed aspects enjoyed necessitating improvement. Feedback converged on themes: experience, qualities, content, ease use. Following refinements, users described Alex as humanlike, supportive, encouraging. Content perceived novel personally relevant. USE scores across domains were generally above average (~5 out 7), SUS indicated “good” “excellent” final iteration receiving highest score. Discussion Overall, reflected positively interactions including initial version. Refinements cycles further improved experiences. provides preliminary evidence feasibility acceptance services Public Significance Low rates have been observed following disorder Tools needed, scalable, digital options, that can be easily paired screening, improve addressing utilization.

Язык: Английский

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Use of AI in Mental Health Care: Community and Mental Health Professionals Survey

JMIR Mental Health, Год журнала: 2024, Номер 11, С. e60589 - e60589

Опубликована: Окт. 11, 2024

Abstract Background Artificial intelligence (AI) has been increasingly recognized as a potential solution to address mental health service challenges by automating tasks and providing new forms of support. Objective This study is the first in series which aims estimate current rates AI technology use well perceived benefits, harms, risks experienced community members (CMs) professionals (MHPs). Methods involved 2 web-based surveys conducted Australia. The collected data on demographics, comfort, attitudes toward AI, specific cases, experiences benefits harms from use. Descriptive statistics were calculated, thematic analysis open-ended responses conducted. Results final sample consisted 107 CMs 86 MHPs. General varied, with reporting neutral MHPs more positive attitudes. Regarding usage, 28% (30/108) used primarily for quick support (18/30, 60%) personal therapist (14/30, 47%). Among MHPs, 43% (37/86) AI; mostly research (24/37, 65%) report writing (20/37, 54%). While majority found be generally beneficial (23/30, 77% 34/37, 92% MHPs), concerns 47% (14/30) 51% (19/37) There was an equal mix negative sentiment future care open feedback. Conclusions Commercial tools are being Respondents believe will offer advantages terms accessibility, cost reduction, personalization, work efficiency. However, they equally concerned about reducing human connection, ethics, privacy regulation, medical errors, misuse, security. Despite immense potential, integration into systems must approached caution, addressing legal ethical while developing safeguards mitigate harms. Future planned track acceptability associated issues over time.

Язык: Английский

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Does the Digital Therapeutic Alliance Exist?: An Integrative Review (Preprint)

JMIR Mental Health, Год журнала: 2025, Номер 12, С. e69294 - e69294

Опубликована: Янв. 17, 2025

Abstract Background Mental health disorders significantly impact global populations, prompting the rise of digital mental interventions, such as artificial intelligence (AI)-powered chatbots, to address gaps in access care. This review explores potential for a “digital therapeutic alliance (DTA),” emphasizing empathy, engagement, and alignment with traditional principles enhance user outcomes. Objective The primary objective this was identify key concepts underlying DTA AI-driven psychotherapeutic interventions health. secondary propose an initial definition based on these identified concepts. Methods PRISMA (Preferred Reporting Items Systematic Reviews Meta-Analyses) scoping reviews Tavares de Souza’s integrative methodology were followed, encompassing systematic literature searches Medline, Web Science, PsycNet, Google Scholar. Data from eligible studies extracted analyzed using Horvath et al’s conceptual framework alliance, focusing goal alignment, task agreement, bond, quality assessed Newcastle-Ottawa Scale Cochrane Risk Bias Tool. Results A total 28 pool 1294 articles after excluding duplicates ineligible studies. These informed development DTA, elements facilitators barriers affecting primarily focused AI-powered psychotherapy, other tools. Conclusions findings provide foundational concept report its replicate mechanisms trust, collaboration While shows promise enhancing accessibility engagement care, further research innovation are needed challenges personalization, ethical concerns, long-term impact.

Язык: Английский

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Large language models could change the future of behavioral healthcare: A proposal for responsible development and evaluation

Опубликована: Апрель 24, 2023

Large language models (LLMs) such as Open AI’s GPT-3 and -4 (which power ChatGPT) Google’s PaLM, built on artificial intelligence, hold immense potential to support, augment, or even eventually fully automate psychotherapy. Enthusiasm about applications is mounting in the field well industry. These developments promise address insufficient mental healthcare system capacity scale individual access personalized treatments. However, clinical psychology an uncommonly high stakes application domain for AI systems, responsible evidence-based therapy requires nuanced expertise. This paper provides a roadmap ambitious yet of LLMs First, technical overview presented. Second, stages integration into psychotherapy are discussed while highlighting parallels development autonomous vehicle technology. Third, care, training, research discussed, areas risk given complex nature Fourth, recommendations evaluation provided, which include centering science, involving robust interdisciplinary collaboration, attending issues like assessment, detection, transparency, bias. Lastly, vision outlined how might enable new generation studies interventions at scale, these may challenge assumptions

Язык: Английский

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Ethical Challenges in AI Approaches to Eating Disorders

Journal of Medical Internet Research, Год журнала: 2023, Номер 25, С. e50696 - e50696

Опубликована: Авг. 14, 2023

The use of artificial intelligence (AI) to assist with the prevention, identification, and management eating disorders body image concerns is exciting, but it not without risk. Technology advancing rapidly, ensuring that responsible standards are in place mitigate risk protect users vital success safety technologies users.

Язык: Английский

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Debate and Dilemmas Regarding Generative AI in Mental Health Care: Scoping Review

Interactive Journal of Medical Research, Год журнала: 2024, Номер 13, С. e53672 - e53672

Опубликована: Авг. 12, 2024

Background Mental disorders have ranked among the top 10 prevalent causes of burden on a global scale. Generative artificial intelligence (GAI) has emerged as promising and innovative technological advancement that significant potential in field mental health care. Nevertheless, there is scarcity research dedicated to examining understanding application landscape GAI within this domain. Objective This review aims inform current state knowledge identify its key uses domain by consolidating relevant literature. Methods Records were searched 8 reputable sources including Web Science, PubMed, IEEE Xplore, medRxiv, bioRxiv, Google Scholar, CNKI Wanfang databases between 2013 2023. Our focus was original, empirical with either English or Chinese publications use technologies benefit health. For an exhaustive search, we also checked studies cited Two reviewers responsible for data selection process, all extracted synthesized summarized brief in-depth analyses depending approaches used (traditional retrieval rule-based techniques vs advanced techniques). Results In 144 articles, 44 (30.6%) met inclusion criteria detailed analysis. Six emerged: disorder detection, counseling support, therapeutic application, clinical training, decision-making goal-driven optimization. Advanced systems been mainly focused applications (n=19, 43%) support (n=13, 30%), training being least common. Most (n=28, 64%) broadly health, while specific conditions such anxiety (n=1, 2%), bipolar (n=2, 5%), eating posttraumatic stress schizophrenia 2%) received limited attention. Despite use, efficacy ChatGPT detection remains insufficient. addition, 100 articles traditional found, indicating diverse areas where could enhance Conclusions study provides comprehensive overview care, which serves valuable guide future research, practical applications, policy development While demonstrates promise augmenting care services, inherent limitations emphasize role supplementary tool rather than replacement trained providers. A conscientious ethical integration necessary, ensuring balanced approach maximizes benefits mitigating challenges practices.

Язык: Английский

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Designing Digital Interventions for Eating Disorders

Current Psychiatry Reports, Год журнала: 2023, Номер 25(4), С. 125 - 138

Опубликована: Март 16, 2023

Язык: Английский

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