Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review

Course overview

Course Description: This course is based on material published in the Journal of Medical Internet Research and is available as an open-access article. Anxiety and depression are the most common mental disorders worldwide. Owing to the lack of psychiatrists around the world, the incorporation of artificial intelligence (AI) into wearable devices (wearable AI) has been exploited to provide mental health services. This review aimed to explore the features of wearable AI used for anxiety and depression to identify application areas and open research issues. We searched 8 electronic databases (MEDLINE, PsycINFO, Embase, CINAHL, IEEE Xplore, ACM Digital Library, Scopus, and Google Scholar) and included studies that met the inclusion criteria. Then, we checked the studies that cited the included studies and screened studies that were cited by the included studies. The study selection and data extraction were carried out by 2 reviewers independently. The extracted data were aggregated and summarized using narrative synthesis. Of the 1203 studies identified, 69 (5.74%) were included in this review. Approximately two-thirds of the studies used wearable AI for depression, whereas the remaining studies used it for anxiety. The most frequent application of wearable AI was in diagnosing anxiety and depression; however, none of the studies used it for treatment purposes. Most studies targeted individuals aged between 18 and 65 years. The most common wearable device used in the studies was Actiwatch AW4 (Cambridge Neurotechnology Ltd). Wrist-worn devices were the most common type of wearable device in the studies. The most commonly used category of data for model development was physical activity data, followed by sleep data and heart rate data. The most frequently used data set from open sources was Depression. The most commonly used algorithm was random forest, followed by support vector machine. Wearable AI can offer great promise in providing mental health services related to anxiety and depression. Wearable AI can be used by individuals for the prescreening assessment of anxiety and depression. Further reviews are needed to statistically synthesize the studies results related to the performance and effectiveness of wearable AI. Given its potential, technology companies should invest more in wearable AI for the treatment of anxiety and depression. This course on the use of wearable artificial intelligence tools as a method of diagnosing and treating anxiety and depression is designed for social workers, professional counselors, psychologists, nurses, and substance abuse counselors who do clinical work. In addition, this course is appropriate for intermediate and advanced-level practitioners who wish to develop their knowledge of the use of wearable artificial intelligence tools as a method of diagnosing and treating anxiety and depression. The course material includes a literature review of interventions and research. It may also be useful for licensed clinicians who require continuing clinical education courses for license renewal. The course is based on a journal article that includes research. It contains statistical analysis and data that some clinicians enjoy reading, and others do not. A significant benefit of reading research-based articles for continuing education is they provide practitioners with the latest findings in their field. Authors: Abd-alrazaq, AlSaad, Aziz, Ahmed, Denecke, Househ, Farooq, Sheikh Learning Objectives: This course will provide the practitioner with detailed information regarding the use of wearable artificial intelligence tools as a method of diagnosing and treating anxiety and depression. Specifically, a professional will: Identify characteristics and effects of anxiety and depression disorders. Recognize features of wearable devices and artificial intelligence. Describe the benefits and limitations of wearable artificial intelligence as a diagnostic tool for mental illnesses. Citation: Abd