{"title":"Artificial Intelligence in Mental Health Care: Implications for Psychiatric Mental Health Nursing-A Scoping Review.","authors":"Euna Si, Ki Han Kwon","doi":"10.1111/inm.70361","DOIUrl":null,"url":null,"abstract":"<p><p>AI is increasingly being integrated into mental health support, with applications spanning chatbots, large language models, digital therapeutics and clinical decision-support systems. Although these technologies have demonstrated potential to improve access to care and support clinical practice, their implications for psychiatric mental health nursing (PMHN) remain insufficiently synthesized. This scoping review aimed to examine how AI is being applied in mental health care and to synthesize its implications for psychiatric mental health nursing practice and related nursing-relevant outcomes. A scoping review was conducted following established scoping review methodology and reported in accordance with the PRISMA Extension for Scoping Reviews (PRISMA-ScR). Searches were conducted across four databases for studies published between January 2022 and May 2026. A total of 42 sources of evidence met the inclusion criteria. Five overarching themes were identified: (1) AI-based psychosocial interventions and mental health care delivery; (2) suicide prevention and risk management; (3) therapeutic relationships and human-centred care; (4) ethics, safety and governance; and (5) nursing readiness, education and professional transformation. AI applications were associated with improved accessibility of mental health support, enhanced symptom management and more efficient risk assessment. However, concerns regarding privacy, algorithmic bias, transparency and the preservation of therapeutic relationships were consistently reported. AI demonstrates considerable potential to support care delivery, suicide prevention and clinical decision-making, yet raises important ethical, relational and professional challenges. AI should be viewed as a complementary tool that supports rather than replaces psychiatric mental health nursing practice. Educational programmes should strengthen AI literacy, digital ethics and critical appraisal skills to support safe and person-centred AI integration.</p>","PeriodicalId":94051,"journal":{"name":"International journal of mental health nursing","volume":"35 5","pages":"e70361"},"PeriodicalIF":3.3000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of mental health nursing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/inm.70361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
AI is increasingly being integrated into mental health support, with applications spanning chatbots, large language models, digital therapeutics and clinical decision-support systems. Although these technologies have demonstrated potential to improve access to care and support clinical practice, their implications for psychiatric mental health nursing (PMHN) remain insufficiently synthesized. This scoping review aimed to examine how AI is being applied in mental health care and to synthesize its implications for psychiatric mental health nursing practice and related nursing-relevant outcomes. A scoping review was conducted following established scoping review methodology and reported in accordance with the PRISMA Extension for Scoping Reviews (PRISMA-ScR). Searches were conducted across four databases for studies published between January 2022 and May 2026. A total of 42 sources of evidence met the inclusion criteria. Five overarching themes were identified: (1) AI-based psychosocial interventions and mental health care delivery; (2) suicide prevention and risk management; (3) therapeutic relationships and human-centred care; (4) ethics, safety and governance; and (5) nursing readiness, education and professional transformation. AI applications were associated with improved accessibility of mental health support, enhanced symptom management and more efficient risk assessment. However, concerns regarding privacy, algorithmic bias, transparency and the preservation of therapeutic relationships were consistently reported. AI demonstrates considerable potential to support care delivery, suicide prevention and clinical decision-making, yet raises important ethical, relational and professional challenges. AI should be viewed as a complementary tool that supports rather than replaces psychiatric mental health nursing practice. Educational programmes should strengthen AI literacy, digital ethics and critical appraisal skills to support safe and person-centred AI integration.
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