Cara Gallegos, Ryoko Kausler, Jenny Alderden, Megan Davis, Liya Wang
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Two independent reviewers reviewed a total of 5768 abstracts.</p><p><strong>Results: </strong>Fifty-four articles were chosen for further review, with 10 articles included in the final analysis. Regarding quality assessment, the overall quality of the evidence was lower than expected. Overall, most studies showed positive trends in improving anxiety, stress, and depression.</p><p><strong>Discussion: </strong>Overall, using an artificial intelligence chatbot for mental health has some promising effects. However, many studies were done using rudimentary versions of artificial intelligence chatbots. In addition, lack of guardrails and privacy issues were identified. More research is needed to determine the effectiveness of artificial intelligence chatbots and to describe undesirable effects.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Can Artificial Intelligence Chatbots Improve Mental Health?: A Scoping Review.\",\"authors\":\"Cara Gallegos, Ryoko Kausler, Jenny Alderden, Megan Davis, Liya Wang\",\"doi\":\"10.1097/CIN.0000000000001155\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background and objectives: </strong>Mental health disorders, including anxiety and depression, are the leading causes of global health-related burden and have increased dramatically since the 1990s. 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引用次数: 0
摘要
背景和目标:包括焦虑症和抑郁症在内的精神疾病是造成全球健康相关负担的主要原因,自 20 世纪 90 年代以来,精神疾病的发病率急剧上升。使用人工智能聊天机器人提供心理保健服务可能是缩小心理保健服务差距的一种选择。本范围综述的总体目标是描述使用人工智能聊天机器人进行心理保健(压力、焦虑、抑郁)的用途、功效和优缺点:方法:检索了 PubMed、PsycINFO、CINAHL 和 Web of Science 数据库。在可能的情况下,结合关键词搜索医学主题词。两位独立审稿人共审阅了 5768 篇摘要:结果:54 篇文章被选中进行进一步审查,其中 10 篇文章被纳入最终分析。在质量评估方面,证据的总体质量低于预期。总体而言,大多数研究在改善焦虑、压力和抑郁方面显示出积极的趋势:讨论:总体而言,使用人工智能聊天机器人促进心理健康具有一些积极的效果。然而,许多研究使用的是初级版本的人工智能聊天机器人。此外,还发现了缺乏防护措施和隐私问题。需要进行更多的研究来确定人工智能聊天机器人的有效性,并描述其不良影响。
Can Artificial Intelligence Chatbots Improve Mental Health?: A Scoping Review.
Background and objectives: Mental health disorders, including anxiety and depression, are the leading causes of global health-related burden and have increased dramatically since the 1990s. Delivering mental healthcare using artificial intelligence chatbots may be one option for closing the gaps in mental healthcare access. The overall aim of this scoping review was to describe the use, efficacy, and advantages/disadvantages of using an artificial intelligence chatbot for mental healthcare (stress, anxiety, depression).
Methods: PubMed, PsycINFO, CINAHL, and Web of Science databases were searched. When possible, Medical Subject Headings terms were searched in combination with keywords. Two independent reviewers reviewed a total of 5768 abstracts.
Results: Fifty-four articles were chosen for further review, with 10 articles included in the final analysis. Regarding quality assessment, the overall quality of the evidence was lower than expected. Overall, most studies showed positive trends in improving anxiety, stress, and depression.
Discussion: Overall, using an artificial intelligence chatbot for mental health has some promising effects. However, many studies were done using rudimentary versions of artificial intelligence chatbots. In addition, lack of guardrails and privacy issues were identified. More research is needed to determine the effectiveness of artificial intelligence chatbots and to describe undesirable effects.
期刊介绍:
For over 30 years, CIN: Computers, Informatics, Nursing has been at the interface of the science of information and the art of nursing, publishing articles on the latest developments in nursing informatics, research, education and administrative of health information technology. CIN connects you with colleagues as they share knowledge on implementation of electronic health records systems, design decision-support systems, incorporate evidence-based healthcare in practice, explore point-of-care computing in practice and education, and conceptually integrate nursing languages and standard data sets. Continuing education contact hours are available in every issue.