New publication: Assessment of patient preferences in digital health trials
What happens when patients don't receive the treatment they would have chosen themselves?
Research suggests that patient preferences can influence treatment outcomes in studies where participants are not blinded. Yet many digital health trials still do not systematically assess preferences, making it difficult to understand how much they matter.
In our newly published study, we developed and tested a fully automated procedure for assessing patient preferences in digital health trials with two active treatment options. Importantly, the assessment was designed to not only capture patient preferences, but also to support patients in their treatment decision-making process.
Some findings:
- The structured three-step process appears feasible in trials with digital health interventions and guides the patient to identify a preferred option, even when they were initially unsure.
- Using this process in our randomized controlled trial ICanSelfCare, the majority of cancer patients were able to identify their preferred treatment option immediately in the first assessment step.
- Preferences were influenced by more than expected treatment benefits. Participants also considered factors such as personal interest, ease of use, curiosity, and whether the treatment concept resonated with them.
Why does this matter?
Non-specific treatment effects might be driven by patient preferences. That’s why assessing them should not be an afterthought. Understanding what patients want, and why they want it, may help us better interpret trial results and design more patient-centered digital health interventions.
Full publication (open access)
Barth J, Thomae AV, Tietjen AK, Witt CM. Assessment of patient preferences in digital health trials: procedure development and implementation in a preference-based trial. BMJ Open. 2026 May 26;16(5):e115137.