HALF DAY WORKSHOPS

EHPS 2026 will accommodate three (3) Half Day workshops, which will be held on Monday 31st of August 2026. Conference attendees who wish to participate in these workshops will be required to register and pay the appropriate fee. You can see the relevant workshop registration fees below. 

A minimum number of participants (5) are required for the workshop to be held. If by the week before the conference starts the minimum number of participants is not reached, the workshop will be cancelled and any participants who signed up will be asked to either move to a workshop which will be held, or be refunded fully for the registration fee of the cancelled workshop.

The registration fee covers one (1) coffee break and Certificate of Attendance for the workshop (on request)

Half Day Workshop 1

Mixed-methods in health psychology research: What? Why? How?

Outline
Mixed-methods can allow deeper and broader understanding of health issues than single-method studies. They can add experiential ‘flesh’ from qualitative methods to statistical ‘bones’ from quantitative studies. They also allow well-rounded skill development for PhD candidates.

Learning outcomes
• Understand when and how to apply mixed-methods
• Balance philosophical and pragmatic concerns
• Design a mixed-methods study
• Plan writing and publication

Activities
Participants will be asked to bring an outline of a mixed-method project, or research questions that could be addressed using mixed-methods.
In each of five sections, the facilitator will outline key principles, and participants will apply these to the outlines/questions they bring to the workshop:
1] Why consider mixed-method research? We will discuss why mixed-method studies can offer more than single-method studies, and what the various components could be.
2] Philosophical issues. Quantitative and qualitative methods may have different ontological and epistemological foundations. We will discuss how to balance philosophical issues with a pragmatic focus on producing meaningful and useful results.
3] Planning mixed-method research. We will discuss how to arrange different components within an overall study design – conceptually and temporally – using examples of different concurrent and sequential designs, and apply these to participants’ outlines/questions.
4] Integrating findings across studies. We will discuss different ways to combine the findings of component studies to produce a coherent overall conclusion. Examples of different approaches will be given, and applied to participants’ outlines/questions.
5] Writing and publishing. Combining the components of mixed-method designs into a coherent narrative is essential. We will address different approaches to reporting mixed-method designs in the context of restrictive word limits and within dissertations.

Facilitator:

Half Day Workshop 2

Building responsible AI expertise in research teams: the ARC approach

1. Objectives

The workshop enables participants to:

• Experience an ARC session and understand how this format supports responsible, effective and efficient AI use within research practice through collective learning and structured ethical reflection.
• Critically appraise the methodological and ethical implications of applying AI to core research tasks, including generative writing support and literature exploration.
• Reflect on how responsible AI use can be embedded within research workflows through shared standards, documentation practices and transparent decision-making.
• Design ways to adapt and implement key ARC principles, such as sandbox experimentation, hybrid meet-ups and dynamic agenda-setting, within their own research groups.

2. Activities

This half-day workshop consists of three main components:

1. ARC session (approx. 2 hours): Participants engage in a complete ARC session. They select from structured “sandbox” sprints focused on (a) applying generative AI in academic writing or (b) AI-supported literature searching. Each sprint combines step-by-step experimentation with structured prompts encouraging critical reflection on authorship, plagiarism, privacy and human oversight.
2. Model deconstruction and discussion: Facilitators present the ARC framework, including its dynamic agenda, hybrid format, pedagogical principles and living-guideline approach. Participants analyse the methodological and organisational foundations of the model.
3. Implementation design exercise: In small groups, participants outline how ARC-like practices could be adapted within their own institutional or disciplinary contexts and briefly pitch their implementation ideas.

3. Description of the intended participants

Researchers, lecturers, doctoral candidates and students who are interested in practicing the responsible application of AI tools and integrating them into research workflows in a responsible way. An interdisciplinary mix is welcome; the sprints are designed to be adaptable to participants’ individual research contexts.

4. Maximum number of participants

Approximately 30 participants.

Facilitator:

Half Day Workshop 3

Modelling self-efficacy in behaviour change using LEGO® Serious Play®

1. Objectives
By the end of this workshop, participants will be able to:
1. Explain the role of self-efficacy within Social Cognitive Theory and its relevance to digital
and AI-enabled behaviour change interventions.
2. Translate self-efficacy theory into structured facilitation prompts for participatory design
contexts.
3. Use LEGO® Serious Play® (LSP) to model barriers, supports, and mechanisms influencing
efficacy beliefs in digital health settings.
4. Critically evaluate how participatory modelling can ensure psychological mechanisms remain
central in the design and implementation of technology-driven health interventions.
2. Activities
As AI-enabled health tools proliferate, behaviour change mechanisms risk being optimised for
engagement metrics rather than grounded in psychological theory. This workshop introduces LEGO®
Serious Play® (LSP) as a structured participatory modelling methodology for making self-efficacy
theory tangible and actionable in digital health intervention design.
Following a brief overview of self-efficacy and its four determinants – mastery experiences, social
modelling, verbal persuasion, and physiological states – participants will work in small groups,
progressing through a skills-building warm-up and three structured build–share–reflect cycles. Builds
address barriers undermining self-efficacy, supports strengthening efficacy beliefs, and reconstruction
of models to incorporate intervention supports. A shared landscape activity connects individual builds
into a collective representation of intervention design.
A structured AI reflection activity is embedded within the session, where participants photograph
their models and apply theory-based prompts to an AI tool. Participants critically evaluate what the AI
captures or omits, engaging with the possibilities and limits of machine-readable psychological
knowledge.
The workshop concludes with synthesis discussion and provision of a structured template to support
translation into participants’ own research and practice.
3. Intended Participants
Health psychologists, behavioural scientists, intervention developers, and researchers working at the
intersection of behaviour change and digital health.
4. Maximum Number of Participants
16
5. Conflict of Interest
The convenor declares no conflicts of interest related to the content of this workshop. The workshop
is not affiliated with any EHPS Special Interest Group.

Facilitator: