Qualitative research includes collecting and analysing data from observation, interviews or focus groups which can provide a richer understanding of how and why individuals behave in the way that they do in a set of hypothetical situations (Tubaro et al., 2010). It can be used to inform model assumptions and may be able to provide more valid assumptions than those developed based on quantitative data alone. When making decisions about behaviours, people often use heuristics which are “strategies that ignore part of the information, with the goal of making decisions more quickly, frugally, and/or accurately than more complex methods” (Gigerenzer et al., 2011, Kahneman, 2012). For instance, within an ABM, a heuristic decision tree may be used, where alternative cues affecting a decision are taken sequentially in order of importance, termed the fast and frugal approach (Crooks et al., 2019), and these could be informed by qualitative research.
Process tracing is another way of describing the mechanisms between a cause (e.g., the intervention) and an outcome (e.g., the behaviour of interest), by observing how the intervention works within a set of individual cases (Beach et al., 2013). Theory about why there is a relationship between a cause and outcome is developed and empirical observational data is collected to test and amend the theory within an iterative process. This could then be incorporated within a health economic model. However, this is a resource intensive process, and the theory should only be generalised very cautiously beyond the population within which it is tested.
Existing qualitative studies may be reviewed (Flemming et al., 2019) or primary qualitative data collection and analyses could be undertaken where feasible. Data could be collected from a diverse set of people from the target population, or qualitative research may be useful for filling gaps in knowledge about the influences on behaviour for an understudied high-risk subgroup.