Pre-Conference Workshops

Sunday September 18, 2022

Half-day workshops will start at 1pm with registration/lunch at 12 noon. 

Full-day workshop (E) will start with registration at 9am and break for lunch at 12 noon.

A) Getting Started with Augmented Reality (half-day)

Presenters

  • Dmitriy Babichenko, Clinical Associate Professor, Department of Informatics and Networked Systems, School of Computing and Information, University of Pittsburgh

  • Pat Healy, Doctoral Student, Department of Informatics and Networked Systems, School of Computing and Information, University of Pittsburgh

Description- This workshop will provide a basic Introduction to Augmented Reality (AR). Participants will learn about different types of AR applications and gain foundational knowledge about how AR works. Participants will create a simple AR project with Unity3D and Vuforia using plane tracking and image recognition. Participants will also learn how to create AR applications, place digital objects into physical environments, and project 360 images and videos into physical spaces. This workshop does not require prior programming experience and does not assume any prior knowledge of AR technologies.

 

B) Introduction to the Connected and Open Research Ethics (CORE): A Resource for Developing Ethical, Compliant and Socially Responsible Digital Health Research (half-day)'

This workshop has been cancelled

Presenters

  • Camille Nebeker, EdD, MS, Director, University of California San Diego (UCSD) Research Ethics Program; Co-Founder/Director ReCODE Health; Associate Professor, UCSD School of Public Health

  • Rebecca Bartlett Ellis, PhD, Associate Professor, Indiana University School of Nursing

  • John Torous, MD, MBI, Director, Digital Psychiatry Program, Beth Israel Deaconess Medical Center, Harvard Medical School

  • Brian McInnis, PhD, Affiliated Investigator, ReCODE Health and UCSD Design Lab

Description- Researchers and ethics review boards are challenged with how to apply regulations and ethical principles to design and evaluate digital health research studies. The Connected and Open Research Ethics (CORE) platform was designed with the research community to bridge this gap. Workshop attendees will learn how to: (1) identify and address ethical and social implications in their grants; (2) address key points on their IRB applications; and (3) contribute to a research agenda involving the CORE learning community.

C) How to Develop and Deliver an Effective “Pitch” (half-day)

Presenter

  • Ellen Beckjord, PhD, MPH; Vice President, Population Health and Clinical Optimization, UPMC Health Plan

Description- Academic trainees and professionals often have ample experience in presenting their research but comparatively less experiencing “pitching” their ideas using basics of persuasive communication. Being able to successfully and succinctly convince others of the importance and value of your ideas – that is, knowing how to deliver a great ”pitch”– is an advantageous skill set to add to your presentation arsenal. In this session, participants will learn the key elements of developing and delivering an effective, two-minute “pitch”. They will also hear an example “pitch” from the presenter, create a Message Map to form the foundation of their “pitch”, and then receive feedback from other participants on their Message Map. Finally, participants will draft and deliver a two-minute “pitch” to workshop participants.

D) Machine Learning for Mental Health (half-day)

Presenters

  • Burkhardt Funk, PhD, Professor of Business Information Systems, Research Center for Digital Transformation, Leuphana Universiteit Lüneburg

  • Mark Hoogendoorn, PhD, Professor of Artificial Intelligence, Department of Computer Science, Vrije Universiteit Amsterdam

  • Pepijn van de Ven, MSc, PhD, Senior Lecturer Artificial Intelligence and Machine Learning, Health Research Institute, University of Limerick

  • Eoin Grua, PhD, Postdoctoral Researcher Machine Vision, Department of Electronic & Computer Engineering, University of Limerick

  • Eduardo Maekawa, Doctoral Student, Department of Electronic & Computer Engineering, University of Limerick

  • Darragh Glavin, Doctoral Student, Department of Electronic & Computer Engineering, University of Limerick

Description- This workshop will provide an in-depth discussion of how machine learning (ML) techniques, being part of the domain of artificial intelligence, can be applied to the domain of mental health. First, the presenters will discuss ML techniques and then focus on applications for predictive modeling (both predicting therapeutic outcome as well as short term developments for patients) and personalization of therapies. They will then use real-life case studies to illustrate these techniques that feature hands-on activities to provide attendees with a deeper understanding of ML.

E) Optimizing Digital Interventions: The Multiphase Optimization Strategy (MOST) Way (full-day)

Presenters

  • Linda M. Collins, PhD, School of Global Public Health, New York University

  • Inbal Billie Nahum-Shani, PhD, Institute for Social Research, University of Michigan

Description- Advances in digital technologies have created unprecedented opportunities to deliver effective and scalable behavior change interventions. Two-arm randomized controlled trials (RCTs) provide an excellent way to determine whether a digital intervention package is effective. However, this approach is less helpful in providing empirical information that can be used to optimize an intervention to achieve improved effectiveness and efficiency, while maintaining a desired level of economy and/or scalability. This workshop will present the multiphase optimization strategy (MOST), a three-phase methodological framework for optimizing behavioral interventions based on ideas inspired by engineering methods that stress both ongoing improvement of products and careful management of research and implementation resources. The presenters will use case studies to introduce three types of experimental approaches - the factorial design, the sequential multiple assignment randomized trial (SMART), and the micro-randomized trial (MRT) - and explain how the concepts presented can be applied to optimize attendees’ digital interventions.