Engaging underrepresented populations in public health monitoring: Strategies for people with mild intellectual disability or low literacy skills

Theunissen, M.C.M.
Koks-Leensen, M.C.J.
van Geenen, J.
Leusink, G.L.
Naaldenberg, J.
Bevelander, K.E.

The COVID-19 Health Monitor (CHM) was a research project conducted in the Netherlands between September 2020 and July 2022. The CHM aimed to assess the impact of the COVID-19 pandemic on the (mental) health and well-being of people with mild intellectual disabilities (MID) and/or limited literacy (LL), two groups often underrepresented in public health monitoring. During the project, extensive qualitative documentation was created to capture the development, implementation, and evaluation of the CHM. A total of 456 documents were initially archived by the research team and stakeholders, of which 319 were selected for analysis in this study based on criteria of authenticity, credibility, representativeness, and meaning. These documents include meeting notes, reports from usability tests and cognitive interviews, project proposals, and co-researcher input. The documents cover three rounds including five distinct project phases, each reflecting iterative development and adaptation based on user feedback and testing. The CHM data reflect an inclusive development trajectory with detailed attention to accessibility and user experience. Document analysis focused on strategies to reach people with MID/LL and elements that influence the accessibility of online health monitors. The data were thematically coded using qualitative software, and codes were continually refined in collaboration with co-researchers. The result is a conceptual framework describing key strategies and accessibility elements relevant for inclusive public health monitoring. Please note: The 319 selected and analysed documents are not included in this sharing repository. The dataset contains identifiable information and was not originally collected for public sharing or research purposes. No informed consent was obtained for data sharing, making the dataset ethically unsuitable for open access. Instead, this repository provides supporting materials (e.g., the conceptual framework and coding scheme) that illustrate the analytical process and main outcomes. Researchers interested in further information may contact the project team to discuss whether controlled access to specific anonymized excerpts is feasible under strict confidentiality conditions.