Volume 15, Issue 6 And S7 (Artificial Intelligence- In Press 2025)
J Research Health 2025, 15(6 And S7): 6-6 |
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Bagheri Sheykhangafshe F, Tajbakhsh K, Pour Saeid V, Gharibi Loroun S, Shah Hosseini M. The Effectiveness of Artificial Intelligence Interventions in the Treatment of Psychological Disorders: A Systematic Review. J Research Health 2025; 15 (6) :6-6
URL: http://jrh.gmu.ac.ir/article-1-2850-en.html
URL: http://jrh.gmu.ac.ir/article-1-2850-en.html
Farzin Bagheri Sheykhangafshe1 
, Khazar Tajbakhsh2 , Vahid Pour Saeid3 , Shima Gharibi Loroun4 , Mahtab Shah Hosseini5
, Khazar Tajbakhsh2 , Vahid Pour Saeid3 , Shima Gharibi Loroun4 , Mahtab Shah Hosseini5
1- Department of Psychology, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran , farzinbagheri73@gmail.com
2- Department of Psychology, University of Milano-Bicocca, Milan, Italy
3- Department of Clinical Psychology, Islamic Azad University of Medical Sciences, Tabriz Branch, Tabriz, Iran
4- Department of Clinical Psychology, Islamic Azad University, Ardabil Branch, Ardabil, Iran
5- Department of Clinical Psychology, Islamic Azad University, Garmsar Branch, Garmsar, Iran
2- Department of Psychology, University of Milano-Bicocca, Milan, Italy
3- Department of Clinical Psychology, Islamic Azad University of Medical Sciences, Tabriz Branch, Tabriz, Iran
4- Department of Clinical Psychology, Islamic Azad University, Ardabil Branch, Ardabil, Iran
5- Department of Clinical Psychology, Islamic Azad University, Garmsar Branch, Garmsar, Iran
Abstract: (36 Views)
Background: The rapid advancement of artificial intelligence (AI) technologies has opened new avenues in the diagnosis, treatment, and management of psychological disorders. With increasing global demand for mental health services and a shortage of qualified professionals, AI-based interventions offer scalable, data-driven solutions. This systematic review aims to evaluate the effectiveness of AI interventions in treating psychological disorders by analyzing recent empirical evidence.
Methods: In this systematic review, English-language articles examining the effectiveness of AI interventions in the treatment of psychological disorders were identified using targeted keywords across major international databases, including Google Scholar, PubMed, ProQuest, Embase, PsycINFO, and Scopus, covering the period from January 2017 to April 2025. The initial screening and selection process was guided by predefined inclusion and exclusion criteria. To ensure methodological rigor, all studies were evaluated using the PRISMA framework. Following a comprehensive quality assessment, 39 articles that met the required standards and aligned with the research objectives were selected for in-depth analysis to address the study's research questions.
Results: Key findings from the 39 reviewed studies show that AI interventions significantly improve diagnostic accuracy and enable early detection of psychological disorders, particularly depression and anxiety. AI tools, such as chatbots, mobile apps, and digital platforms, contributed to symptom reduction and enhanced treatment personalization based on patient-specific data. Many studies highlighted the scalability, accessibility, and cost-effectiveness of AI-supported interventions. Patients generally showed high acceptance, especially for tools aiding in symptom monitoring, while clinicians expressed more caution.
Conclusions: This systematic review highlights the significant potential of AI interventions to transform the diagnosis and treatment of psychological disorders. AI technologies improve diagnostic precision, facilitate early detection, and enable personalized treatment approaches, offering scalable and cost-effective mental health solutions. Despite promising outcomes, successful integration of AI requires addressing ethical issues, data privacy, and algorithmic bias, as well as ensuring proper clinician training.
Methods: In this systematic review, English-language articles examining the effectiveness of AI interventions in the treatment of psychological disorders were identified using targeted keywords across major international databases, including Google Scholar, PubMed, ProQuest, Embase, PsycINFO, and Scopus, covering the period from January 2017 to April 2025. The initial screening and selection process was guided by predefined inclusion and exclusion criteria. To ensure methodological rigor, all studies were evaluated using the PRISMA framework. Following a comprehensive quality assessment, 39 articles that met the required standards and aligned with the research objectives were selected for in-depth analysis to address the study's research questions.
Results: Key findings from the 39 reviewed studies show that AI interventions significantly improve diagnostic accuracy and enable early detection of psychological disorders, particularly depression and anxiety. AI tools, such as chatbots, mobile apps, and digital platforms, contributed to symptom reduction and enhanced treatment personalization based on patient-specific data. Many studies highlighted the scalability, accessibility, and cost-effectiveness of AI-supported interventions. Patients generally showed high acceptance, especially for tools aiding in symptom monitoring, while clinicians expressed more caution.
Conclusions: This systematic review highlights the significant potential of AI interventions to transform the diagnosis and treatment of psychological disorders. AI technologies improve diagnostic precision, facilitate early detection, and enable personalized treatment approaches, offering scalable and cost-effective mental health solutions. Despite promising outcomes, successful integration of AI requires addressing ethical issues, data privacy, and algorithmic bias, as well as ensuring proper clinician training.
Keywords: Artificial intelligence, digital mental health, psychological disorders, machine learning, mental health technology
Type of Study: Review Article |
Subject:
● Artificial Intelligence
Received: 2025/07/20 | Accepted: 2025/11/4 | Published: 2025/11/4
Received: 2025/07/20 | Accepted: 2025/11/4 | Published: 2025/11/4
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