Digital Mental Health: A Practitioner's Guide

Description

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 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. Foreword Preface Contents Chapter 1: The Dawn of Digital Psychiatry Introduction Digital Mental Health Digital Clinic Regulation of Mobile Apps Artificial Intelligence Future References Chapter 2: Digital Biomarkers and Passive Digital Indicators of Generalized Anxiety Disorder Introduction GAD as a Diagnostic Category Current GAD Assessment Reliance on Retrospective Self-Report Limitation in Accounting for Contextual and Time-Dependent Factors Heterogeneity in GAD Potential for Improvements with the Use of Passively Collected Data Machine Learning Models Applied to Passive Data Passive Sensing of GAD with Data from the Electronic Medical Record Passive Sensing of GAD with Data from Mobile and Wearable Devices Overview and Basis Passive Sensing of GAD with Social Media Data Conclusions Limitations Ethical and Privacy Considerations References Chapter 3: Digital Phenotyping in Mood Disorders Introduction Digital Phenotyping Data Data Sources Data Processing Digital Phenotyping as a Resource for Mood Disorders As a Biomarker As a Diagnosis Tool Monitoring Treatment Tailored-Treatment Delivery Addressing Special Populations Limitations Ethical Issues Conclusion References Chapter 4: Mental Health Assessment via Internet: The Psychometrics in the Digital Era Introduction Psychometrics: A Brief Overview Content Validity The Internal Structure of the Scale Internal Consistency Reliability Construct Validity (Convergent Validity and Discriminant Validity) Convergent Validity Discriminant Validity Criterion Validity (Concurrent and Predictive Validity) The Psychological Process Used in the Scale Responses Consequences of Using Test Psychometric of Mental Health Instruments: Paper-and-Pencil Versus Digital Formats Online Web Page Self-Reported Questionnaires Computer-Based Instruments Mobile Application (App) Format Conclusion References Chapter 5: Smartphone-Based Treatment in Psychiatry: A Systematic Review Introduction Methods Study Selection and Search Strategy Study Selection and Data Extraction Risk of Bias in Individual Studies Results Search Strategy and Selection of Trials Trials According to Psychiatric Disorder Psychotic Disorders Risk of Bias Affective Disorders Risk of Bias Other Disorders Risk of Bias Discussion Limitations Limitations on a Study Level Limitations on Chapter Level Recommendations for Future Trials References Chapter 6: Digital Therapies for Insomnia Insomnia Disorder and Current Treatments Current Evidence for the Efficacy of dCBT-I and dMBT-I Using dCBT-I in Real World Settings: Evidence from Effectiveness Trials What Factors Influence the Effectiveness of dCBT-I and MBTI? Integration of Digital Tools for Insomnia with Standard Care Conclusions: What Are the Next Steps for Digital Therapeutics for Insomnia? References Chapter 7: The Efficacy of Smartphone-Based Interventions in Bipolar Disorder Bipolar Disorders The Digital Revolution and the Growing Interest and Use of Mental Health Tools Digital Phenotyping in Bipolar Disorder Smartphone-Related Research in Bipolar Disorder: State of the Art The Dissociation Between Private Corporations and the Academic Field The Efficacy of Smartphone-Based Interventions in Mental Health Disorders Smartphone-Based Interventions in Bipolar Disorder The Efficacy of Smartphone-Based Interventions in Bipolar Disorder (RCTs) Smartphone-App Characteristics and Type of Interventions The Potential Influence of Baseline Affective Symptoms Active or Inactive Control Groups User-Engagement Indicators of Smartphone Interventions The Effectiveness of Smartphone-Based Interventions in Bipolar Disorder (Observational Studies) Limitations of the Studies Assessing the Efficacy of Smartphone-Based Interventions and Potential Solutions Evidence-Based Smartphone Interventions Still Trapped in Lab Cages Future Directions References Chapter 8: Chatbots in the Field of Mental Health: Challenges and Opportunities Human–Computer Interaction and Social Rules What Is a Chatbot? Mental Health Applications of Chatbots Benefits of Using Chatbots Increasing Access to Mental Health Care Data Collection and Management in Research and Clinical Settings Promoting Disclosure Ethical and Safety Concerns Privacy Breaches and Confidentiality of Data Serious Health Concerns and Adverse Incidents Attachment to Bot and Developmental Concerns Future Directions References Chapter 9: How to Evaluate a Mobile App and Advise Your Patient About It? References Chapter 10: Telepsychiatry Telepsychiatry and the COVID-19 Pandemic Applying Telepsychiatry in Real Life Special Populations Barriers of Telepsychiatry and Strategies to Overcome it Patients Experiences and Future Implications Conclusion References Chapter 11: Prediction of Suicide Risk Using Machine Learning and Big Data Introduction Prediction of Suicide Risk Machine Learning Models for Prediction of Suicide Risk Populations at Higher Risk for Suicide Electronic Health Records as Source of Data Social Media and Other Sources of Data Challenges and Limitations Ethical Implications of Machine Learning and Big Data Applications in Suicide Risk Assessment Conclusion References Chapter 12: Electronic Health Records to Detect Psychosis Risk Primary Indicated Prevention and the Clinical High-Risk State Challenges of Detecting Individuals at Risk Detection Strategies in Primary Care Development and Validation of a Transdiagnostic Risk Calculator for Psychosis in Secondary Mental Health Care Replication of the Transdiagnostic Risk Calculator in Other Settings UK Replications International Replication Implementation of the Transdiagnostic Risk Calculator Updating and Refining the Transdiagnostic Risk Calculator Dynamic Risk Prognostication Conclusion References Chapter 13: The Use of Artificial Intelligence to Identify Trajectories of Severe Mental Disorders Introduction Bipolar Disorder Major Depressive Disorder Schizophrenia Conclusion References Chapter 14: The Use of Machine Learning Techniques to Solve Problems in Forensic Psychiatry Prevalence of Criminality Among Those with Mental Illness Reoffending: Prevalence and Assessment Tools Differences Between Actuarial and Machine Learning Approaches Predictive Models of Criminal and Violence-Related Outcomes in Psychiatry Predictive Models of Criminal and Violence-Related Outcomes in Non-psychiatric Individuals Predictive Models of Malingering Methodological Recommendations Integrating Evidence-Based and Novel Biological and Physiological Features Predicting Treatment Response to Routine Clinical Care Predicting the Timing of Short-Term Inpatient Outcomes Data-Driven Phenotyping of Forensic Patients Methodological Pipeline for Prospective Machine Learning Cohorts in Forensic Psychiatry Conclusion References Chapter 15: Gaming Disorder and Problematic Use of Social Media Gaming Disorder Introduction Etiology and Explanatory Models Assessment of Gaming Disorder Treatment Strategies Hikikomori Problematic Use of Social Media Fear of Missing Out Dating Apps Healthy Use of Social Media Fake News and Hate Speech Online Subcultures Conclusion References Index