Our paper on how Heaven and Hell Beliefs Predict National Crime Rates now up at PLoS One

Posted by on June 18, 2012 in News, Slider | 1 comment

Our paper on how Heaven and Hell Beliefs Predict National Crime Rates now up at PLoS One

Our new paper with Mijke Rhemtulla on how nations’ rates of belief in Heaven and Hell oppositely predict crime rates has just been posted at PLoS One.

Click here to see the paper (open-access to everyone), and here to see the University of Oregon press release.

Abstract:

Researchers have proposed that the emergence of religion was a cultural adaptation necessary for promoting self-control. Self-control, in turn, may serve as a psychological pillar supporting a myriad of adaptive psychological and behavioral tendencies. If this proposal is true, then subtle reminders of religious concepts should result in higher levels of self-control. In a series of four experiments, we consistently found that when religious themes were made implicitly salient, people exercised greater self-control, which, in turn, augmented their ability to make decisions in a number of behavioral domains that are theoretically relevant to both major religions and humans’ evolutionary success. Furthermore, when self-control resources were minimized, making it difficult for people to exercise restraint on future unrelated self-control tasks, we found that implicit reminders of religious concepts refueled people’s ability to exercise self-control. Moreover, compared with morality- or death-related concepts, religion had a unique influence on self-control.

Figure 1. Crime rate z-scores as a function of how much higher the proportion of a nation that believes in heaven is compared to the proportion that believes in hell. R2 = .54.

1 Comment

  1. Difference variables have been seen as problematic in my area of study. Specifically, it can be shown mathematically that any algebraic difference score used as a predictor constrains the effects of those variables to be equal in magnitude but opposite in sign. An alternative method would be to consider polynomial regression which requires no such constraints.

    For further information on this technique and the shortcomings of difference scores, you might consider these sources from a tangential field of study:

    Edwards, J. R. (1994). Regression analysis as an alternative to difference scores. Journal of Management, 20, 683-689.

    Edwards, J. R. (2001). Ten difference score myths. Organizational Research Methods, 4, 264-286.

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