Background

The population of older migrants is increasing, mirroring demographic trends in the general population. However, people with a migration background face specific challenges. According to a recent OECD study, older migrants are more likely to experience relative poverty than native-born populations. They also receive less support from health care services. Contributing factors include language barriers, cultural differences, low levels of health literacy, and experiences of marginalization or discrimination. The lack of translation services and intercultural mediation, together with rigid health system structures that fail to account for cultural diversity and fall short of person-centered care, further exacerbate these inequities.

Project Content

Social Assistive Robots (SARs) demonstrate considerable potential to enhance access to personalized social and community care for older adults. These robots can detect risks and help avoid them, monitor medication adherence, provide companionship, and even reduce depressive symptoms. However, further research is needed to customize such solutions to individual users and better reflect the needs of minorities from diverse cultural backgrounds. In particular, older migrants may have distinct needs and preferences that are not adequately captured by current robotic features. We aim to address this gap by collecting data on older migrants in Canada and the European Union. The insights gained will be used to design AI-based robots that are tailored to the specific care needs of this population.

Aims

This project addresses the urgent need to transform healthcare systems in Europe and Canada to support inclusive, community-based ageing for older migrants. It focuses on the co-design and evaluation (using Citizen Science methods) of how social assistive robots serving this group can be integrated into primary and community care ecosystems across five countries.

We aim to lay out a roadmap for strengthening person-centered perspectives in primary and community care for older migrants. Our approach entails the use of co-designed, innovative technologies. Moreover, we provide policymakers and decision-makers with evidence-based knowledge to support the integration of social assistive robots into care delivery.

Method

The project study comprises three main phases:

• Qualitative research to understand the needs, barriers, and opportunities related to the use of social assistive robots in care delivery. Considering diverse cultural backgrounds, the project builds on the expertise of caregivers, healthcare professionals, and AI experts as well as uses Citizen Science methods.
• Proof-of-concept studies in primary and community care settings to evaluate the effectiveness of a co-designed, AI-based social assistive robot, with the aim to improve health and social care for older migrants.
• Knowledge translation and transfer: The study results are made available to policymakers, industry partners, health and care managers, researchers, and community stakeholders.

Result

Leveraging an international partnership between Europe and Canada, the project adopts an innovative approach to social assistive robots. Its primary focus is on paving the way for systems that empower older adults and informal caregivers from minority cultural backgrounds to better manage their health and daily activities.

The project brings together healthcare professionals from multiple countries. This collaboration not only improves health and social care outcomes, but also strengthens cooperation among healthcare professionals and community actors, enabling an international exchange of knowledge and expertise.