Description
Book SynopsisThis innovative book focuses on potential, limitations, and recommendations for the digital mental health landscape. Authors synthesize existing literature on the validity of digital health technologies, including smartphones apps, sensors, chatbots and telepsychiatry for mental health disorders. They also note that collecting real-time biological information is usually better than just collect filled-in forms, and that will also mitigate problems related to recall bias in clinical appointments. Limitations such as confidentiality, engagement and retention rates are moreover discussed. Presented in fifteen chapters, the work addresses the following questions: may smartphones and sensors provide more accurate information about patients’ symptoms between clinical appointments, which in turn avoid recall bias? Is there evidence that digital phenotyping could help in clinical decisions in mental health? Is there scientific evidence to support the use of mobile interventions in mental health?
Digital Mental Health will help clinicians and researchers, especially psychiatrists and psychologists, to define measures and to determine how to test apps or usefulness, feasibility and efficacy in order to develop a consensus about reliability. These professionals will be armed with the latest evidence as well as prepared to a new age of mental health.
Table of Contents1. The Dawn of Digital Psychiatry
2. Digital Biomarkers and Passive Digital Indicators of Generalized Anxiety Disorder
3. Digital phenotyping in mood disorders
4. Mental health assessment via Internet: the psychometrics in the digital era
5. Smartphone-based treatment in psychiatry – a systematic review
6. Digital therapies for insomnia
7. The efficacy of smartphone-based interventions in bipolar disorder
8. Chatbots in the field of mental health: challenges and opportunities
9. How to evaluate a mobile app and advise your patient about it?
10. Telepsychiatry
11. Prediction of suicide risk using machine learning and big data
12. Electronic Health Records to Detect Psychosis Risk
13. The use of artificial intelligence to identify trajectories of severe mental disorders
14. The use of machine-learning techniques to solve problems in forensic psychiatry
15. Gaming Disorder and Problematic Use of Social Media
