This 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.…mehr
This 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 mentalhealth?
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. Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Artikelnr. des Verlages: 89210711, 978-3-031-10700-9
1st ed. 2023
Seitenzahl: 276
Erscheinungstermin: 3. Januar 2024
Englisch
Abmessung: 235mm x 155mm x 15mm
Gewicht: 473g
ISBN-13: 9783031107009
ISBN-10: 3031107004
Artikelnr.: 69601062
Herstellerkennzeichnung
Books on Demand GmbH
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22848 Norderstedt
info@bod.de
040 53433511
Autorenporträt
Ives Cavalcante Passos, MD, PhD, is a professor of psychiatry at the Universidade Federal do Rio Grande do Sul (UFRGS), Brazil. He completed his postdoctoral neuroscience and artificial intelligence at the University of Texas Health Science Center at Houston (UTHealth) - Houston, Texas USA. In 2016, he was selected as Young Physician Leader by the Interacademy Medical Panel and M8 Alliance of Academic Health Centers. Dr. Passos has a total of 97 peer-reviewed articles published in top psychiatric journals in Pubmed. He has also published a Springer book entitled "Personalized Psychiatry - Big Data Analytics in Mental Health". Francisco Diego Rabelo-da-Ponte is a psychologist. He completed his M.Sc and Ph.D in psychiatry and behavioral sciences at the Federal University of Rio Grande do Sul, Brazil. He was visiting PhD student at the University of Central Lancashire (UK) focused on neurodevelopment and neuroimmunology. In 2019, Rabelo-da-Ponte received the Samuel Gershon Award for Junior Investigators organized by International Society for Bipolar Disorders (ISBD). In 2020, he received the International Travel Grant Award from the International Brain Research Organization (IBRO). Dr. Rabelo-da-Ponte has a total of 26 peer-reviewed articles in top psychiatric journals in Pubmed. Currently, he is a post-doctorate researcher at King's College of London. Flávio Kapczinski, MD, PhD, is a leader in the field of research on bipolar disorder and a Professor of Psychiatry at McMaster University. Prof. Kapczinski has also served as a mentor, with several former trainees currently occupying important academic positions around the globe. Currently he is among the three most productive researchers in the field of bipolar disorder, and among the five most influential researchers in psychiatry in Canada. In 2013, he received the Mogens Schou Prize for Education from the International Society of bipolar disorders. Clarivate Inc (formerly Thomson Reuters) lists Prof. Kapczinski among the most influential minds in academia, and he has a total of 548 peer-reviewed articles in Pubmed. He published a total of 8 books, including the Springer book entitled "Personalized Psychiatry - Big Data Analytics in Mental Health".
Inhaltsangabe
1. 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.
1. 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.
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