Fuzzy cognitive mapping in participatory research and decision making: a practice review

Abstract

Background: Fuzzy cognitive mapping (FCM) is a graphic technique to describe causal understanding in a wide range of applications. This practice review summarises the experience of a group of participatory research specialists and trainees who used FCM to include stakeholder views in addressing health challenges. From a meeting of the research group, this practice review reports 25 experiences with FCM in nine countries between 2016 and 2023.

Results: The methods, challenges and adjustments focus on participatory research practice. FCM portrayed multiple sources of knowledge: stakeholder knowledge, systematic reviews of literature, and survey data. Methodological advances included techniques to contrast and combine maps from different sources using Bayesian procedures, protocols to enhance the quality of data collection, and tools to facilitate analysis. Summary graphs communicating FCM findings sacrificed detail but facilitated stakeholder discussion of the most important relationships. We used maps not as predictive models but to surface and share perspectives of how change could happen and to inform dialogue. Analysis included simple manual techniques and sophisticated computer-based solutions. A wide range of experience in initiating, drawing, analysing, and communicating the maps illustrates FCM flexibility for different contexts and skill bases.

Conclusions: A strong core procedure can contribute to more robust applications of the technique while adapting FCM for different research settings. Decision-making often involves choices between plausible interventions in a context of uncertainty and multiple possible answers to the same question. FCM offers systematic and traceable ways to document, contrast and sometimes to combine perspectives, incorporating stakeholder experience and causal models to inform decision-making. Different depths of FCM analysis open opportunities for applying the technique in skill-limited settings.

Keywords: Fuzzy cognitive mapping; Fuzzy logic; Global health; Participatory modelling; Public health; Stakeholder engagement; Weight of evidence.

Fig. 1

Fuzzy cognitive map of causes of a healthy maternity according to indigenous traditional midwives in Guerrero, Mexico. (a) Graphical display of a fuzzy cognitive map. The boxes are nodes, and the arrows are directed edges. Strong lines indicate positive influences, and dashed lines indicate negative influences. Thicker lines correspond to stronger effects. (b) Adjacency matrix with the same content as the map. Rows and columns correspond to the nodes. The value in each cell indicates the strength of the influence of one node (row) on another (column). Reproduced without changes with permission from the authors of [26]

Fig. 2

Fuzzy cognitive maps from group sessions in Uganda and Nigeria. (a) A group of women in Uganda discusses what contributes to increasing institutional childbirths in rural communities. They used sticky notes and markers on white paper to draw the maps. (b) A group of men in Northern Nigeria uses a whiteboard and magnetic tiles to draw a map on causes of short birth intervals

Fig. 3

Maps from questionnaire data from the study on dengue control in Guerrero, Mexico. Green arrows are positive influences, and red arrows correspond to negative influences. The control group showed a negative influence in the results chain with a cumulative net influence of 0.88; the intervention group showed no such block and a cumulative net influence of 1.92. Reproduced without changes with permission from the authors of [43]