The value of visual co-analysis models for an inclusive citizen science approach. Inspired by co-creation methods from design thinking

Abstract

Citizen science entails the collaboration of citizens and scientists. The process of this collaboration can take on many forms: identifying a research question, collecting data, analysing data to support or refute a hypothesis, monitoring environmental or health conditions for management or policy development. Citizen science propagates the inclusion of citizens not only as participants engaged in the design research process but also involved in designing the research process itself. In order to address issues of a citizen science approach, it is important that potentially everyone can contribute. Therefore, methodologies need to be fine-tuned to improve the involvement of non-professional researchers in the research process. Co-creation methods may be an effective methodology for doing so and bring different types of knowledge (e.g., insights, experiences, data, information) to the ‘table of science’ and, ultimately, improve the constructive exchange and evaluation of this knowledge. This article describes the process of a pilot where professional researchers, informal caregivers, and human resource advisors use visual co-analysis to create a research plan. For the framing of this research a theme was proposed which focused on the possibility of technological support for work-related challenges experienced by informal caregivers working in healthcare. Five semi-structured interviews were conducted by researchers with informal caregiver in the first phase of ‘Empathize’ within design thinking (i.e., human centred approach). The goal of the interviews was to understand and relate to the caregiver’s perception of their current informal care situation (e.g., balance, bottlenecks, opportunities, well-being). Quotes selected from theses interviews were the input for a bottom-up methodology for citizen science using the KJ Method (i.e., affinity diagramming) as a form of visual analysis model. The (co-)analysis was done by the team of caregivers, HR advisors and researchers using the online tool Miro. This article aims to describe how the use of visual analysis models as a group consensus technique can facilitate the involvement of non-professional researchers and thereby support the establishment of inclusiveness of a citizen science approach. In other words, to obtain equal collaboration, an inclusive citizen science approach must allow communication about, and analysis of data by all participants, instead of non-professional researchers merely being presented with the finalized results of the analysis phase within research. An inclusive citizen science approach might lead to a period of uncertainty where problem definitions, research questions or predefined categories posed early on are (re-)assessed. However, this bottom-up approach will ultimately lead to a positive impact in finding the root problem for innovative scientific outcomes. Together, the pilot study and descriptive review offer guidance for understanding visual co-analysis models as the starting point for an inclusive citizen science approach.