2025 PRE-CON WORKSHOPS
Monday, August 4, 2025
The following pre-conference workshops will be available for registration through the ISRII 13th Scientific Meeting registration form (*hyperlink reg form). Each workshop will run for half a day (3.5 hours).
Incorporating Human-Centered Design Methods in Research: Crafting a rigorous approach and communicating it clearly in proposals
Workshop length: Half-day
Presenters:
Andrew Berry, PhD; Assistant Professor, Northwestern University Feinberg School of Medicine
Elena Agapie, PhD; Assistant Professor, University of California-Irvine
Carolyn Foster, MD, MS; Assistant Professor of Pediatrics, Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago
Description
The purpose of the workshop is to provide hands-on experience and expert coaching in planning and communicating human-centered design (HCD) methods for research proposals. In the first, didactic portion of the workshop, participants will learn frameworks and methods associated with key phases of the HCD process: conducting user research to understand the sociotechnical context of an intervention, translating user research findings into design requirements for an intervention, and developing prototypes to meet those requirements. This will include strengths and limitations of different approaches (e.g., contrasting interviews and design workshops). This will also include concrete examples of how HCD has been applied in different clinical contexts.
In the second, hands-on portion of the workshop, participants will join small groups to critique and refine research proposals under development. Participants are encouraged to bring their own proposals, but participants without a proposal will still learn through critique and peer mentoring. For each proposal, participants will discuss how to incorporate and refine HCD methods based on concepts from the didactic portion. Facilitators will provide a priori prompts and dynamic feedback based on participants’ needs.
The intended audience includes researchers from any career stage (trainees, early career scientists, established scientists) who will soon conceptualize or submit a research proposal (i.e., a publicly-funded grant or a thesis proposal). Participants should want to improve their capacities to plan HCD processes and communicate those methods effectively. Participants need not be experts in HCD. It will help to have familiarity with HCD, including why it is important and some associated methods, but participants do not need to have applied these methods previously. Participants should bring a laptop or other device on which to share and edit documents.
Learning objectives
Participants will learn to list and describe:
- the principles and phases of a HCD process
- design frameworks and methods for conducting user research, translating research to design, developing prototypes for an intervention
- components of sociotechnical context of an intervention and its role in design
- examples for how to tailor HCD methods and communicate them in the Specific Aims and/or Research Strategy for a research proposal
Introduction to AI & Machine Learning for Mental Health
Workshop length: Half-day
Presenters
Ms Niharika Bhardwaj, PhD Student, University of Limerick, Ireland
Ms Rebecca Ndukwe, PhD Student, University of Limerick, Ireland
Pepijn van de Ven, University of Limerick, Ireland
Description
Are you curious about the potential of machine learning (ML) but have no prior experience? This workshop is perfect for you!
Machine learning is part of the domain of artificial intelligence (AI) and currently very much the popular aunt/uncle in the AI family. Machine learning is the collective name for algorithms that learn from experience, just like humans do. Instead of giving it detailed instructions for every task, you provide the algorithm with data and let it figure out patterns and make decisions based on that data.
Join us for a hands-on, beginner-friendly session where you’ll get a practical overview of how machine learning techniques can be applied to mental health.
What to Expect:
- Interactive Learning: Engage in active participation and discussions.
- Comprehensive Overview: Understand the basics of machine learning and its applications in health.
- In-Depth Case Study: Build your own ML model and see how it supports decision-making in complex clinical scenarios.
Why Attend?
- No Prior Knowledge Required: This workshop is designed for beginners.
- Practical Insights: Learn how ML can transform mental health research and practice.
- Hands-On Experience: All software and data will be provided. Just bring your own laptop!
Don’t miss this opportunity to dive into the world of machine learning and discover its potential in mental health. We look forward to seeing you there!
The ABCs of LLMs: Designing and Integrating AI Chatbots for Digital Mental Health Interventions
Workshop length: Half-day
Presenters:
Eduardo Bunge Ph.D (Palo Alto University, Co-Founder of ParenteAI)
Juan Dellarroquelle (CTO and Co-Founder at Parente AI)
Description
Recent advances in Large Language Models (LLMs) have created new opportunities for digital mental health interventions. However, many clinicians, researchers, and developers remain uncertain about how to safely and effectively integrate LLM-powered conversational agents (CAs) into clinical practice.
This hands-on workshop is designed to bridge this gap by providing a practical introduction to the capabilities and limitations of LLMs in mental health. Participants will explore the evolution of conversational agents, comparing rule-based systems to generative artificial intelligence (GenAI) models, and reviewing existing research on their effectiveness, including treatment outcomes, therapeutic alliance, engagement, and attrition.
We will then shift to applied learning, introducing the fundamentals of LLM architecture and the key components necessary for building AI-driven chatbots tailored to digital mental health interventions. Topics will include prompt engineering, guardrails for safety, few-shot learning, multi-agent approaches, and fine-tuning for specific populations.
A focal point of the session will be the concept of an AI co-therapist developed for parent management training programs. Through interactive exercises, participants will gain hands-on experience in structuring CA dialogues, implementing ethical safeguards, and how to integrate them into clinical practice (see figure 1).
By the end of this workshop, attendees will have a foundational understanding of LLM-powered CA, along with practical strategies for safely integrating them into research and clinical workflows.
This session is ideal for clinicians, researchers, and digital mental health innovators seeking to harness AI for therapeutic applications.
*Registered participants are requested to bring their own laptop to be able to work on relevant materials during the workshop.
Key Learning objectives:
- Understand the evolution of conversational agents in mental health, distinguishing between rule-based and LLM-powered models.
- Evaluate the evidence base for AI-driven mental health interventions, including treatment outcomes, engagement, and therapeutic alliance.
- Learn how LLMs work and explore different techniques for using them for specific mental health applications.
- Implement safety measures such as guardrails, and multi-agent architectures to ensure ethical and effective AI deployment.
- Apply practical design strategies to develop or integrate AI chatbots into their research or clinical practice, using an AI co-therapist for parent management training as a case study.
Workshop Structure (3–3.5 hours):
- Introduction to Conversational Agents (30 min)
- History and evolution of chatbots in mental health
- Comparing rule-based vs. LLM-based systems
- Research findings on engagement, alliance, and attrition
- How LLMs Work (45 min)
- Basics of generative AI
- Strengths and limitations in mental health applications
- Designing Safe and Effective AI Chatbots (45 min)
- Guardrails and ethical considerations
- Prompt engineering, Retrieval augmented generation, and Multi-agent approaches
- Hands-on Session: AI Co-Therapist for Parent Training (60 min)
- Case study: An AI co-therapist supporting evidence-based parenting programs
- Interactive exercise: testing a structured dialogue flow
- Group discussion on implementation challenges and opportunities
- Q&A and Next Steps (30 min)
- Discussion of practical applications for attendees’ work
- Resources for continued learning and collaboration.
Figure 1. Example of ParenteAI’s conceptual framework
Designing sophisticated and interactive digital interventions, without coding and at little to no cost: The Computerized Intervention Authoring System v. 3.0
Workshop length: Half-day
Presenters:
Steven J. Ondersma, PhD
Jordan M. Braciszewski, PhD
Amy M. Loree, PhD
Frank Mueller, PhD
Eva Noack, MD, PhD, Michigan State University, Henry Ford Health, University Medical Center Göttingen
Description
The Computerized Intervention Authoring System (CIAS; www.cias.app) is an NIH-funded, open-source, non-commercial platform that enables researchers to easily develop, edit, and share sophisticated interactive content without coding of any kind. Interventions built with CIAS deploy as cross-platform compatible web/mobile web apps of any duration, with easy personalization, integrated one- and two-way tailored SMS, optional animated narrators who speak aloud in over 40 languages, and instant translation. Researchers can either use the hosted platform at Michigan State University to build and deploy their interventions (without worrying about the technicalities of platform maintenance) or deploy the platform on their server. A GDPR-compliant instance of CIAS—which will be available to researchers throughout the EU—is also in process at University Medical Center Göttingen, Germany.
This workshop will proceed in four phases. First, we will highlight the advantages of mobile web apps and no-code Software as a Service (SaaS) platforms. Second, we will introduce attendees to CIAS 3.0, highlighting key features and capabilities, followed by independent practice while the presenters circulate and provide guidance. Third, we will consolidate learning from the prior section by helping attendees develop a simple app. Fourth and finally, the presenters will share their experience in disseminating and implementing CIAS-developed applications in healthcare settings. Workshop attendees will leave with the information and skills needed to start developing their own custom digital interventions using CIAS, including access to templates and training resources.
Key learning objectives:
- Workshop participants will understand the implications of a no-code, open-source digital intervention development platform and how it can accelerate research.
- Participants will understand how to access and use CIAS to develop any kind of digital intervention, in any language, and how to use additional features like tailored SMS, aggregate data visualization, and secure live chat.
- Participants will learn how to access ongoing CIAS support and how to collaborate on intervention development with other teams.
*Registered participants are requested to bring their own laptop to be able to work on CIAS platform during the workshop.
Images below are just small examples of the CIAS dashboard and what you can create with it.
