A chat about bipolar disorder

Author:

Parker Gordon1ORCID,Spoelma Michael J.12ORCID

Affiliation:

1. Discipline of Psychiatry and Mental Health, School of Clinical Medicine, Faculty of Medicine and Health University of New South Wales Sydney New South Wales Australia

2. Black Dog Institute Sydney New South Wales Australia

Abstract

AbstractObjectivesThis study aimed to assess the capabilities of ChatGPT (Chat Generative Pre‐Trained Transformer) in generating informative content related to bipolar disorders. The objectives were to evaluate its ability to provide accurate information on symptoms, classification, causes, and management of bipolar disorder and to explore its creativity in generating topic‐related songs.MethodsChatGPT3 was used for the study, and a series of clinically relevant questions were asked to test its knowledge and creativity. Questions ranged from common symptom descriptions to more artistic requests for songs related to bipolar disorder.ResultsChatGPT demonstrated the capacity to provide basic and informative material on bipolar disorders, including descriptions of symptoms, classification types, causes, and treatment options. It also showed creativity in generating songs that capture the nuances of bipolar symptoms, both during high and low states.ConclusionsWhile ChatGPT3 can offer superficial information on psychiatric topics like bipolar disorder, its inability to provide accurate and up‐to‐date references limits its utility for creating a comprehensive review article for scientific journals. However, it may be helpful in generating educational material and assisting in component tasks for those with bipolar disorder or other psychiatric conditions. As newer versions of AI models are continually developed, their capabilities in producing more accurate and advanced content will need further evaluation.

Funder

National Health and Medical Research Council

Publisher

Wiley

Subject

Biological Psychiatry,Psychiatry and Mental health

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3