Why True Believers Make the Ultimate Sacrifice: Sacred Values, Moral Convictions, or Identity Fusion?

Recent research has identified three promising candidates for predicting extreme behavior: sacred values, moral convictions, and identity fusion. Each construct is thought to motivate extreme behavior in unique ways: Sacred values trigger extreme actions when people are asked to compromise cause-related values for personal gain; moral convictions trigger extreme actions when a cause is aligned with one’s moral compass; and identity fusion triggers extreme actions when a cause is inextricably associated (“fused”) with the personal self. In six studies, we asked which of the three constructs (either alone or in combination) was most predictive of sacrifice for a cause. We measured all three constructs with respect to either of two causes: gun rights (Studies 1–3) or abortion rights (4–6). The outcome measure was endorsement of fighting and dying for the cause. Although all three constructs were significant predictors of the outcome measure when considered separately, identity fusion consistently emerged as the strongest predictor of endorsement of self-sacrifice when all three were considered simultaneously. This pattern occurred regardless of the target cause (gun or abortion rights), the participant’s position on the cause (i.e., pro-gun or anti-gun, pro-choice, or pro-life), or nationality (American vs. Spanish). Also, there was no evidence that the predictors interacted to predict the outcome measure. Finally, a manipulation that threatened the validity of the personal self strengthened the relationship between endorsement of self-sacrifice and both (a) identity fusion and (b) moral convictions. The latter finding suggests that threats to the validity of one’s self-views may amplify the extreme behaviors of true believers.

Devoted fans release more cortisol when watching live soccer matches

Why do some sports fans experience intense emotions when watching live matches? Identity fusion is a strong form of group alignment in which personal and group identities are activated synergistically to produce a visceral sense of 'oneness' with one's team. Here we examine the role of fusion (using a three-item state measure with high internal validity) in elevating salivary cortisol levels while watching football (n = 41). Our evidence was gathered at field laboratories during the 2014 sFIFA World Cup in Natal, Brazil, with live screenings of two Brazilian victories (Colombia, 2-1; Chile, 1-1 with penalties), and the historic semi-final loss to Germany (1-7). We replicated previous studies showing that salivary cortisol concentrations fluctuate during live football events and are related to group membershipbut we also extended them by showing that identity fusion is even more strongly related to cortisol concentrations than identification. We found an interaction between match outcome and cortisol, such that watching a loss, i.e. dysphoria, was associated with particularly high cortisol concentrations. While women were more fused to the team than men, there were no other gender effects. Taken together, these findings suggest that identity fusion modulates physiological reactivity, resulting in distinct psycho-physiological profiles during stressful events.

Amazon's Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data?

Amazon's Mechanical Turk (MTurk) is a relatively new website that contains the major elements required to conduct research: an integrated participant compensation system; a large participant pool; and a streamlined process of study design, participant recruitment, and data collection. In this article, we describe and evaluate the potential contributions of MTurk to psychology and other social sciences. Findings indicate that (a) MTurk participants are slightly more demographically diverse than are standard Internet samples and are significantly more diverse than typical American college samples; (b) participation is affected by compensation rate and task length, but participants can still be recruited rapidly and inexpensively; (c) realistic compensation rates do not affect data quality; and (d) the data obtained are at least as reliable as those obtained via traditional methods. Overall, MTurk can be used to obtain high-quality data inexpensively and rapidly.

Amazon's Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data?

Amazon's Mechanical Turk (MTurk) is a relatively new website that contains the major elements required to conduct research: an integrated participant compensation system; a large participant pool; and a streamlined process of study design, participant recruitment, and data collection. In this article, we describe and evaluate the potential contributions of MTurk to psychology and other social sciences. Findings indicate that (a) MTurk participants are slightly more demographically diverse than are standard Internet samples and are significantly more diverse than typical American college samples; (b) participation is affected by compensation rate and task length, but participants can still be recruited rapidly and inexpensively; (c) realistic compensation rates do not affect data quality; and (d) the data obtained are at least as reliable as those obtained via traditional methods. Overall, MTurk can be used to obtain high-quality data inexpensively and rapidly.