Designing and Delivering Process Evaluations within Clinical Trials: A One‐Day Intensive Workshop

Designing and Delivering Process Evaluations within Clinical Trials is a full-day in-person workshop provided by experienced and qualified Monash University researchers. The workshop provides practical guidance, tools, and resources to support the design, conduct, analysis, and publication of process evaluations embedded within health
and medical intervention trials.

Process evaluations examine how an intervention is delivered and experienced by key stakeholders within a clinical trial, such as trial participants, family members, and clinicians, and is conducted alongside assessment of primary outcomes. It helps explain why an intervention was or was not effective, complementing effectiveness data from Phase III trials. Importantly, process evaluation findings can inform Phase IV trial design, support translation of effective interventions into clinical practice, and increase the impact of your trial work.

Target audience

This course is aimed at researchers, clinical trialists, clinicians and students conducting or interpreting clinical trials.

The workshop provide a foundational overview of topics including: Process evaluation theories; Consumer and stakeholder engagement in process evaluation design; Process evaluation frameworks; Logic model development; Data collection methods; Data analysis and publication.

Learning objectives:

- Apply theory, process evaluation frameworks and logic models.
- How to engage consumers and stakeholders in the design of process evaluations.
- Select and implement appropriate data collection and analysis methods for process evaluations within clinical trials.
- How to publish and disseminate process evaluations findings.

Facilitators: 

Professor Natasha Lannin.
Professor Lannin specialises in scientifically rigorous clinical trials that inform the evidence-base of neurorehabilitation, and is best known for her whole-of-pipeline approach to improving clinical care, from phase II (pilot, feasibility trials) to phase IV (implementation) trials.  She holds a post-graduate certificate in Implementation Science from University of California San Francisco, and works alongside other trialists to plan for rapid translation of their trial findings into everyday clinical care in broader neurological populations (such as epilepsy) and rehabilitation groups (such as chronic respiratory conditions).

Dr Madeleine Smith. 
Dr Smith is a biomedical researcher with extensive experience in bidirectional translation across preclinical and clinical research. She has applied a range of process evaluation methodologies, including survey design and qualitative interviews, and has led co-design activities with people with lived experience across studies. Her research program ranges from the development of novel therapeutics (e.g. stem cell therapies) to the evaluation of complex post-stroke interventions, including understanding stroke survivors’ experiences of returning to work.

Dr Katherine Sewell.
Dr Sewell is a clinician–researcher with extensive experience conducting process evaluations using qualitative and mixed‑methods approaches. She has led and contributed to evaluations embedded within complex health and medical trials, with a particular focus on understanding how and why interventions succeed in real‑world clinical contexts. Her work spans brain injury rehabilitation, stroke recovery, and mental health interventions, where she has developed expertise in capturing stakeholder perspectives, analysing implementation processes, and translating findings into practical improvements in care. 

Event details:

Venue: 'The Terraces' within the Innovation & Education Hub at The Alfred [55 Commercial Road, Melbourne]

Date: 23rd April 2026

Time: 9am - 4pm

Designing and Delivering Process Evaluations within Clinical Trials: A One‐Day Intensive Workshop

119946
Only %1 left
More Information
Contact NameNatasha Lannin
Contact EmailNatasha.Lannin@monash.edu
I consent to the  collection and processing of my personal data.