Citation

Baucum M, John R. Acta Psychol. 2018; 186: 90-103.

Affiliation

University of Southern California, Department of Psychology, United States.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.actpsy.2018.03.003

PMID

29627061

Abstract

Today's information-rich society demands constant evaluation of cause-effect relationships; behaviors and attitudes ranging from medical choices to voting decisions to policy preferences typically entail some form of causal inference ("Will this policy reduce crime?", "Will this activity improve my health?"). Cause-effect relationships such as these can be thought of as depending on two qualitatively distinct forms of evidence: covariation-based evidence (e.g., "states with this policy have fewer homicides") or mechanism-based (e.g., "this policy will reduce crime by discouraging repeat offenses"). Some psychological work has examined how people process these two forms of causal evidence in instances of "everyday" causality (e.g., assessing why a car will not start), but it is not known how these two forms of evidence contribute to causal judgments in matters of public risk or policy. Three studies (n = 715) investigated whether judgments of risk and policy scenarios would be affected by covariation and mechanism evidence and whether the evidence types interacted with one another (as suggested by past studies).

RESULTS showed that causal judgments varied linearly with mechanism strength and logarithmically with covariation strength, and that the evidence types produced only additive effects (but no interaction). We discuss the results' implications for risk communication and policy information dissemination.

Copyright © 2018 Elsevier B.V. All rights reserved.

Language: en

Keywords

Causal inference; Contingency; Evidence; Mechanisms