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Chatbots as Mental Health Assistants: The Promise and Perils of Digital Phenotyping

The Promise and Perils of Digital Phenotyping

In-Person
1.5 CE Hour
General

Presented By

Dates and Times

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    In-Person

Location

Description

Digital health technologies—such as smartphone apps and chatbots—have the potential to augment mental healthcare through more ecological and scalable assessments and interventions. In this presentation, we will review the current state of technology in digital mental health, with a case study of how an artificial-intelligence (AI) tool has been integrated into a recovery-center setting to monitor treatment progress and outcomes. First, we will provide an update on recent technological advances in “digital phenotyping”—using smartphone and computer devices to understand mental health through multimodal assessment (e.g., using screen, microphone, and camera inputs to analyze language, voice, and facial expressions) in a more ecological context (i.e., as part of someone’s lived experience and not just in the clinic). Second, we will discuss the most promising use cases for this technology, from self-screening and early detection of mental health problems to long-term monitoring of chronic psychiatric conditions, with a focus on how this technology can improve upon measurements collected from Likert-scale questionnaires like the PHQ-9. Third, we discuss the challenges and opportunities of implementing technological innovations into mental health care systems, using our firsthand experience of developing and deploying a digital tool for monitoring depression and suicide risk in the context of a recovery program. We have found that some people feel more comfortable conversing with a chatbot, which provides an opportunity to improve detection of distress for individuals who feel uncomfortable with face-to-face contact. We conclude that the potential benefits of these tools outweigh their risks, but their use should ideally be supervised by a mental health professional in the context of a broader treatment plan—both as a guard rail against “edge cases” (atypical inputs that cause an AI system to produce erroneous output) and to encourage user engagement and accountability.

Target Audience
  • • Social Worker
  • • Psychologist
  • • Marriage & Family Therapist
  • • Counselor
  • • Substance Use Disorder Professionals
Learning Objectives

At the end of this course, participants will be able to:

  • Discuss 3 current industry trends in applying machine learning and artificial intelligence to mental health assessment and interventions.

  • Identify 3 ways in which mental health assessment using multimodal digital phenotyping can improve on Likert‐scale questionnaires.

  • Describe 2 potential benefits and 2 potential risks of incorporating digital mental health tools into clinical practice.

  • Define 3 standards for critically evaluating claims of efficacy and 3 checks for assessing privacy standards of digital mental health tools

References

  • Graham, S., Depp, C., Lee, E. E. et al. (2019). Artificial Intelligence for Mental Health and Mental Illnesses: an Overview. Curr Psychiatry Rep 21, 116. https://doi.org/10.1007/s11920-019-1094-0

  • Huckvale K., Torous J., Larsen M. E. (2019). Assessment of the Data Sharing and Privacy Practices of Smartphone Apps for Depression and Smoking Cessation. JAMA Netw Open. 2019;2(4):e192542. https://doi.org/10.1001/jamanetworkopen.2019.2542

  • Lau N., O'Daffer A., Colt S., Yi-Frazier J. P., Palermo T. M., McCauley E ., Rosenberg A. R. (2020). Android and iPhone Mobile Apps for Psychosocial Wellness and Stress Management: Systematic Search in App Stores and Literature Review. JMIR Mhealth Uhealth 2020;8(5):e17798 https://doi.org/10.2196/17798

  • Lucas, G. M., Gratch, J., King, A., & Morency, L. (2014). It’s only a computer: Virtual humans increase willingness to disclose. Computers in Human Behavior, 37, 94-100. https://doi.org/10.1016/j.chb.2014.04.043.

  • McCarthy J. F., Cooper S. A., Dent K. R., et al. (2021). Evaluation of the Recovery Engagement and Coordination for Health–Veterans Enhanced Treatment Suicide Risk Modeling Clinical Program in the Veterans Health Administration. JAMA Netw Open. 4(10):e2129900. https://doi.org/10.1001/jamanetworkopen.2021.29900

  • Torous J., Bucci S., Bell I. H., Kessing L. V., Faurholt-Jepsen M., Whelan P., Carvalho A. F., Keshavan M., Linardon J., Firth J. (2021). The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry. 2021 Oct;20(3):318-335. https://doi.org/10.1002/wps.20883

Introductory
General
Social Worker

Trusted Provider Network, LLC is recognized by the New York State Education Department’s State Board for Social Work as an approved provider of continuing education for licensed social workers #SW-0654.

TPN.health is approved by the California Association of Marriage and Family Therapists (Provider #1000101) to sponsor continuing education for LCSWs. TPN.health maintains responsibility for this program/course and its content. Course meets the qualifications for 1.5 hours of continuing education credit for LCSWs as required by the California Board of Behavioral Sciences.

TPN.health, #1766, is approved to offer social work continuing education by the Association of Social Work Boards (ASWB) Approved Continuing Education (ACE) program. Organizations, not individual courses, are approved as ACE providers. State and provincial regulatory boards have the final authority to determine whether an individual course may be accepted for continuing education credit. TPN.health maintains responsibility for this course. ACE provider approval period: 03/31/2022 – 03/31/2025. Social workers completing this course receive 1.5 General continuing education credits.

Psychologist

Trusted Provider Network is approved by the American Psychological Association to sponsor continuing education for psychologists. Trusted Provider Network maintains responsibility for this program and its content.

Marriage & Family Therapist

Trusted Provider Network, LLC is recognized by the New York State Education Department’s State Board for Mental Health Practitioners as an approved provider of continuing education for licensed marriage and family therapists #MFT-0097.

TPN.health is approved by the California Association of Marriage and Family Therapists (Provider #1000101) to sponsor continuing education for LMFTs. TPN.health maintains responsibility for this program/course and its content. Course meets the qualifications for 1.5 hours of continuing education credit for LMFTs as required by the California Board of Behavioral Sciences.

Counselor

Trusted Provider Network, LLC is recognized by the New York State Education Department’s State Board for Mental Health Practitioners as an approved provider of continuing education for licensed mental health counselors. #MHC-0220.

TPN.health is approved by the California Association of Marriage and Family Therapists (Provider #1000101) to sponsor continuing education for LPCCs. TPN.health maintains responsibility for this program/course and its content. Course meets the qualifications for 1.5 hours of continuing education credit for LPCCs as required by the California Board of Behavioral Sciences.

TPN.health has been approved by NBCC as an Approved Continuing Education Provider, ACEP No. 7267. Programs that do not qualify for NBCC credit are clearly identified. TPN.health is solely responsible for all aspects of the programs.

Substance Use Disorder Professionals

This course has been approved by TPN.health, as a NAADAC Approved Education Provider, for educational credits. NAADAC Provider #198061, TPN.health is responsible for all aspects of the programming.This course has been approved by TPN.health, as a NAADAC Approved Education Provider, for educational credits. NAADAC Provider #198061, TPN.health is responsible for all aspects of the programing. Counselor Skill Group: Legal, Ethical and Professional Development

CE Policy
This course is fiscally sponsored by Exchange Events. There may be potential biases or conflicts of interest inherent to this relationship, and it must be disclosed to participants. These conflicts of interest have no bearing on the course content and have been resolved.
  • Workshop Begins
  • Workshop Ends
Dr. Jason Shumake

Dr. Shumake has 20+ years of scientific research experience and has co-authored more than 60 journal articles in the fields of behavioral neuroscience, experimental psychology, statistics, and machine learning. As the former chief data scientist at the Institute for Mental Health Research, he advanced research in precision psychological medicine and digital mental health. Dr. Shumake brings a valuable set of hybrid skills at the intersection of experimental design, psychometrics, statistical analysis, machine learning, and behavioral science theory/methods.

Dr. Tammy Malloy

Dr. Tammy Malloy received her PhD in Social Work, from Barry University, and is a Licensed Clinical Social Worker as well as a Certified Sex Addiction Therapist. Dr. Malloy has facilitated research for over ten year and has published in academic journals on Addiction, Depression and Spirituality as well as clinical personality pathology and syndromes. Dr. Malloy’s most recent research is in the area of internet pornography use among young adult women. Dr. Malloy has worked in the field of behavioral health for over fifteen years and brings a wealth of knowledge in trauma informed care, family systems, and high-risk behaviors that encompass all addictive behaviors. Dr. Malloy has spoken at conferences both Nationally and Internationally on substance use disorders, co-occurring mental health disorders, and high-risk sexual behaviors. Dr. Malloy’s passion is for teaching others while empowering staff and patients to take ownership of improving their overall quality of life.

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