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Identifying depression and its determinants upon initiating treatment: ChatGPT versus primary care physicians

Family Medicine and Community Health 2023年第4期11卷 56-67页

作者： inbar levkovich Zohar Elyoseph Oranim Academic College TivonIsrael Department of Psychology and Educational Counseling Max Stern Academic College Of Emek YezreelEmek YezreelIsrael Department of Brain Sciences Imperial College LondonLondonUK

Objective To compare evaluations of depressive episodes and suggested treatment protocols generated by Chat Generative Pretrained Transformer(ChatGPT)-3 and ChatGPT-4 with the recommendations of primary care *** Vignettes were input to the ChatGPT *** vignettes focused primarily on hypothetical patients with symptoms of depression during initial *** creators of these vignettes meticulously designed eight distinct versions in which they systematically varied patient attributes(sex,socioeconomic status(blue collar worker or white collar worker)and depression severity(mild or severe)).Each variant was subsequently introduced into ChatGPT-3.5 and *** vignette was repeated 10 times to ensure consistency and reliability of the ChatGPT *** For mild depression,ChatGPT-3.5 and ChatGPT-4 recommended psychotherapy in 95.0%and 97.5%of cases,*** care physicians,however,recommended psychotherapy in only 4.3%of *** severe cases,ChatGPT favoured an approach that combined psychotherapy,while primary care physicians recommended a combined *** pharmacological recommendations of ChatGPT-3.5 and ChatGPT-4 showed a preference for exclusive use of antidepressants(74%and 68%,respectively),in contrast with primary care physicians,who typically recommended a mix of antidepressants and anxiolytics/hypnotics(67.4%).Unlike primary care physicians,ChatGPT showed no gender or socioeconomic biases in its *** ChatGPT-3.5 and ChatGPT-4 aligned well with accepted guidelines for managing mild and severe depression,without showing the gender or socioeconomic biases observed among primary care *** the suggested potential benefit of using atificial intelligence(AI)chatbots like ChatGPT to enhance clinical decision making,further research is needed to refine AI recommendations for severe cases and to consider potential risks and ethical issues.

关键词： GPT treatment initiating

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Assessing prognosis in depression:comparing perspectives of AI models,mental health professionals and the general public

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Family Medicine and Community Health 2024年第S1期12卷 34-42页

作者： Zohar Elyoseph inbar levkovich Shiri Shinan-Altman Department of Psychology and Educational Counseling The Center for Psychobiological ResearchMax Stern Yezreel Valley CollegeYezreel ValleyIsrael Department of Brain Sciences Imperial College LondonLondonUK Faculty of Graduate Studies Oranim Academic CollegeTivonIsrael The Louis and Gabi Weisfeld School of Social Work Bar-Ilan UniversityRamat GanTel AvivIsrael

Background Artificial intelligence(AI)has rapidly permeated various sectors,including healthcare,highlighting its potential to facilitate mental health *** study explores the underexplored domain of AI’s role in evaluating prognosis and long-term outcomes in depressive disorders,offering insights into how AI large language models(LLMs)compare with human *** Using case vignettes,we conducted a comparative analysis involving different LLMs(ChatGPT-3.5,ChatGPT-4,Claude and Bard),mental health professionals(general practitioners,psychiatrists,clinical psychologists and mental health nurses),and the general public that reported *** evaluate the LLMs ability to generate prognosis,anticipated outcomes with and without professional intervention,and envisioned long-term positive and negative consequences for individuals with *** In most of the examined cases,the four LLMs consistently identified depression as the primary diagnosis and recommended a combined treatment of psychotherapy and antidepressant ***-3.5 exhibited a significantly pessimistic prognosis distinct from other LLMs,professionals and the ***-4,Claude and Bard aligned closely with mental health professionals and the general public perspectives,all of whom anticipated no improvement or worsening without professional *** long-term outcomes,ChatGPT 3.5,Claude and Bard consistently projected significantly fewer negative long-term consequences of treatment than *** This study underscores the potential of AI to complement the expertise of mental health professionals and promote a collaborative paradigm in mental *** observation that three of the four LLMs closely mirrored the anticipations of mental health experts in scenarios involving treatment underscores the technology’s prospective value in offering professional clinical *** pessimistic outlook presented by ChatGPT 3.5 is concerning

关键词： prognosis consequences offering

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