Citizen Science in het Globale Zuiden: Beleidsmakersperspectieven en Conceptuele Kaders omtrent Motivatie en Participatie Casestudy over citizen science voor het beheer van natuurlijke risico’s en de bestrijding van vectoroverdraagbare ziekten in Oeg

The lack of extensive, high-quality, and timely data stands out as a significant obstacle to reaching and monitoring progress towards the Sustainable Development Goals (SDGs), particularly in low- and middle-income countries (LMICs). As the 2030 deadline for the SDGs approaches, conventional methods alone may not be sufficient to achieve these goals, leading to calls for alternative approaches such as citizen science (CS). CS offers a promising solution by empowering communities to actively engage in different processes related to the SDGs such as data collection, monitoring, implementation and evaluation. This approach is particularly relevant for regions such as sub-Saharan Africa, facing multiple challenges like high health burdens, environmental degradation, natural hazards and biodiversity loss. However, the adoption and application of CS in these regions is neither well-established nor widespread, often relying on guidelines developed in high-income countries (HICs). Therefore, there are many uncertainties regarding the core aspects of CS in LMICs, including its implementation, participant engagement, the scientific rigour of the data collected, and integration of this data into policymaking. This doctoral thesis, therefore, investigates the factors that shape CS and formulates effective strategies for implementing CS initiatives in LMICs. To this end, the research focuses on CS case studies from Uganda and the Democratic Republic of Congo (DRC), comparing their practices to those in HICs. More specifically, the thesis identifies participant and policy-level factors influencing CS by examining two CS networks set up in southwest Uganda: Action Towards Reducing Aquatic snail-borne Parasitic diseases (ATRAP) that monitored and collected data on freshwater snails that transmit snail-borne diseases like bilharzia and the Geo-Observer (GO) network that monitored and collected data on natural disasters. Additionally, the thesis investigates the ATRAP project set up in both Uganda and DRC to identify the differences and or similarities in the strategies employed and later compare them to commonly observed practices in HICs. Ultimately, the findings of the thesis are synthesized to formulate best practices for implementing CS in LMICs, building on strategies developed in HICs. Considering that CS participants are the backbone of these initiatives, examining the key factors that influence participant engagement was thus the starting point. Specifically, the study assessed motivational, behavioural, and constraining factors impacting participation in the Ugandan CS networks using a mixed methods approach. The motivational and behavioural factors were assessed using widely applied theoretical frameworks, the Volunteer Functions Inventory (VFI) and the Theory of Planned Behaviour (TPB). However, the internal consistency reliability scores for the majority of the evaluated factors were poor, indicating a potential mismatch between some of the questions derived from these frameworks and the participants' lived experiences. Consequently, relying solely on frameworks developed for psychology or volunteering-related research in HICs may lead to misleading conclusions, highlighting the need for further validation of the existing frameworks and the development of frameworks specific to CS and LMICs. Drawing from the factors retained after the internal consistency reliability analysis above, the study identified the pursuit of knowledge and a sense of contributing to the community's well-being as the primary driving factors for individuals in both CS networks. Additionally, financial compensation and project organizational attributes emerged as critical factors sustaining participation for the ATRAP and GO participants respectively. The major obstacles to participation included personal (e.g., sickness) and external (e.g., bad weather conditions) factors. This implies that future CS initiatives in similar locations could tailor their recruitment and engagement strategies to highlight learning opportunities and positive community impact, whilst alleviating constraining factors. Next, the study examined the perspectives of relevant policy actors (i.e., health officials for ATRAP and environmental officers for the GO network) towards CS and CS-generated data (CGD). The findings indicate that despite the policy actors being unfamiliar with the term CS, they expressed high levels of trust in CGD due to the direct involvement of community members as contributors. Data and participant credibility were identified as key trust drivers, while collaborative engagement with local stakeholders was pointed out as the core element for building trust in CS and CGD. A detailed framework of trust pathways is also presented to serve as a practical guide for CS practitioners aiming to implement CS initiatives in similar locations. Lastly, the ATRAP project recruitment strategies in Uganda and DRC were examined and compared to practices in HICs. This revealed challenges in recruiting female participants, especially in DRC with local leaders playing a significant role in recruitment. Moreover, while providing resources such as smartphones was crucial for maintaining participant engagement in both Uganda and DRC, one needs to consider socio-economic factors when implementing technology-based solutions in LMICs. Also, the study highlighted that ATRAP's recruitment and retention strategies varied between Uganda and DRC, and deviated from conventional CS practices, emphasizing the necessity of adapting practices to local contexts to maximize impact, relevance and acceptability. Lessons for future CS projects underscore conducting more comprehensive community entry assessments to thoroughly understand the local context and adapt strategies accordingly. In conclusion, the study identified participant and policy-level factors specific to resource-constrained regions, thus advancing CS theory and practice in LMICs. Instead of a 'one size fits all' approach, the study builds upon the Ten principles of CS developed by the European Citizen Science Association to propose modifications and adaptations to each principle that might be necessary for the effective implementation of CS in locations such as Uganda and DRC. The proposed framework represents a first structured attempt to tailor CS working guidelines for LMICs, and thus further refinement and validation of these modifications is needed. Nonetheless, in the absence of locally developed guidelines, these criteria present practical recommendations for CS practitioners in LMICs. This in turn will stimulate the uptake of CS in LMICs to address complex challenges, ultimately contributing to the SDGs.