Treating symptoms or root causes: How does information about causal mechanisms affect interventions?

TL;DR

Providing detailed causal mechanism information alone has limited impact on people's preference for root cause interventions over symptom treatments in complex problem-solving scenarios.

Contribution

This study investigates how explicit causal mechanism information influences decision-making regarding interventions, highlighting its limited effect on preferences.

Findings

Mechanism information slightly reduces skepticism towards indirect interventions.

Participants still prefer symptom-fixing interventions despite causal information.

Detailed causal diagrams have minimal impact on promoting root cause solutions.

Abstract

When deciding how to solve complex problems, it seems important not only to know whether an intervention is helpful but also to understand why. Therefore, the present study investigated whether explicit information about causal mechanisms enables people to distinguish between multiple interventions. It was hypothesised that mechanism information helps them appreciate indirect interventions that treat the root causes of a problem instead of just fixing its symptoms. This was investigated in an experimental hoof trimming scenario in which participants evaluated various interventions. To do so, they received causal diagrams with different types of causal information and levels of mechanistic detail. While detailed mechanism information and its embedding in the context of other influences made participants less sceptical towards indirect interventions, the effects were quite small. Moreover, it did not mitigate participants' robust preference for interventions that only fix a problem's symptoms. Taken together, the findings suggest that in order to help people choose sustainable interventions, it is not sufficient to make information about causal mechanisms available.