People with dementia tend to exercise less than their peers, despite clear benefits for strength, mobility and independence. To address this gap, Marieke van Heuvelen, Assistant Professor of Human Movement Sciences, and Nienke de Vries, associated professor active lifestyle and prevention UMCG, developed a structured decision model for personalised exercise advice. With support from the Impact Accelerator Grant, this model is now being translated into a digital application to enable large-scale implementation and practical use.
Dementia is a highly heterogeneous condition, with large variation in physical capability, cognitive function, motivation and living situation. As a result, one-size-fits-all exercise recommendations are not effective.
Because of this, people with dementia and their caregivers often lack the knowledge and tools to incorporate appropriate physical activity into daily routines. Van Heuvelen explains: ‘Personalising exercise guidance may sound straightforward, but in practice it requires integrating multiple individual factors into structured and evidence-based recommendations.’
To overcome this challenge, van Heuvelen and her colleagues developed an evidence-based personalised exercise recommendation model that translates individual characteristics into tailored exercise advice. Information is collected through a questionnaire completed by the person with dementia and their caregiver. The questionnaire gathers information about physical abilities, cognitive function, motivation, living situation and daily context. These inputs are processed through structured decision trees to generate personalised exercise recommendations.
Even during the development, the value of this personalised approach became clear. ‘People who walk regularly still need muscle-strengthening exercises to maintain independence. This was often overlooked,’ van Heuvelen explains.
The initial version of the recommendation model was paper-based, requiring manual translation of questionnaire results into exercise recommendations. With support from the Impact Accelerator Grant, the team has programmed the complex decision trees into a digital application. This allows exercise recommendations to be generated automatically, making the tool faster and easier to implement in practice.
The digital tool is currently being tested and refined to ensure that the generated advice is accurate, understandable and feasible in practice. ‘Our ambition is to make the tool widely accessible so that people living with dementia receive structured support for safe and effective exercise. Ultimately, the goal is to help people stay physically active so they can maintain their independence for as long as possible,’ de Vries emphasizes.
With an ageing population and rising numbers of dementia, tools that translate research insights into practical solutions are becoming increasingly important. Moreover, in the future, the tool may also be adapted for other patient groups, such as people living with Parkinson’s disease. ‘If people continue to function better physically, this can make a meaningful difference in healthcare,’ van Heuvelen concludes.
The UMCG offers the Impact Accelerator Grant to help researchers translate their findings into real-world impact. The grant is intended for ongoing or recently completed projects without funding for impact-oriented activities outside of academia. It provides funding for activities such as focus groups, public engagement, developing business models or other activities that help bridge the gap from research findings to impact. For more information about the Grant and the conditions, contact the Impact team.
