Saturday, September 2, 2017

Much ado about grit: A meta-analytic synthesis of the grit literature

Credé, M., Tynan, M. C., & Harms, P. D. (2017). Much ado about grit: A meta-analytic synthesis of the grit literature. Journal of Personality and Social Psychology, 113(3), 492-511.
http://dx.doi.org/10.1037/pspp0000102

Abstract: Grit has been presented as a higher order personality trait that is highly predictive of both success and performance and distinct from other traits such as conscientiousness. This paper provides a meta-analytic review of the grit literature with a particular focus on the structure of grit and the relation between grit and performance, retention, conscientiousness, cognitive ability, and demographic variables. Our results based on 584 effect sizes from 88 independent samples representing 66,807 individuals indicate that the higher order structure of grit is not confirmed, that grit is only moderately correlated with performance and retention, and that grit is very strongly correlated with conscientiousness. We also find that the perseverance of effort facet has significantly stronger criterion validities than the consistency of interest facet and that perseverance of effort explains variance in academic performance even after controlling for conscientiousness. In aggregate our results suggest that interventions designed to enhance grit may only have weak effects on performance and success, that the construct validity of grit is in question, and that the primary utility of the grit construct may lie in the perseverance facet.

We cannot be impartial most of the time... Our judgement gets clouded by our political preferences --- again

Kahan, Dan M. and Peters, Ellen, Rumors of the 'Nonreplication' of the 'Motivated Numeracy Effect' are Greatly Exaggerated (August 26, 2017). Available at SSRN: https://ssrn.com/abstract=3026941

Abstract: This paper does three things. First, it describes the design defects (principally, the lack of statistical power) that make it misleading for Ballarini & Sloman (2017) to claim that they “failed to replicate” the results of Kahan, Peters et al. (2017). Second, it presents the positive results of our own replication study. Finally, we conclude with a brief discussion of why confining assertions of non-replication to studies that satisfy emerging replication protocols—in particular the imperative of “faithful recreation of a study with high statistical power” (Brandt, Ijzerman et al 2014, p. 217)—is essential to the contribution such studies can make as building blocks of a cumulative science.

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The authors ask a neutral problem (if a skin cream works well or not for some rash), and a politicized question (is a change in gun laws associated to more or to less crime?) in a form called covariance detection task (they present fictional studies with fictional results and ask the subjects whether the study supports one answer or the other). They do not ask subjects what they think of the real world, just if the study supports or not an answer or the other... But the subjects cannot be neutral. The authors add:

This “covariance detection” task is hard. Consistent with existing literature, ***only 30%*** of the MN sample overall supplied the correct answer in the “skin rash” group. Skin-rash group participants who scored in the 95th percentile of numeracy, in contrast, tended to get the correct answer in the “skin rash” treatment group ***around 75%*** of the time.

The high-numeracy participants in that group also tended to identify the correct solution—but only when that solution affirmed the position associated with their political identity (crime increases for “Liberal Democrat” vs. crime decreases for “Conservative Republican”). When the correct answer disconfirmed (or “threatened”) the position associated with their political identity (crime increased for Liberal Democrat and crime decreased for Conservative Republican), the high-numeracy participants performed no better than the low- and moderately-numerate participants who shared their identity (Kahan, Peters, et al., 2017).

This result is not consistent with the widespread assumption that political and cultural conflict over scientific data is rooted in the prevalence of System-1 thinking in the general population. It is more consistent with an alternative view that sees numeracy and other forms of System-2 reasoning as re-sources that can be used in the service of identity-protective cognition, a form of motivated information processing that aims to maintain correspondence between an individual’s factual beliefs and the factual beliefs known to be markers of membership in, and loyalty to, one’s cultural group (Bolsen et al. 2014; Kahan 2013, 2009; Sherman & Cohen 2006).

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Check also: Biased Policy Professionals. Sheheryar Banuri, Stefan Dercon, and Varun Gauri. World Bank Policy Research Working Paper 8113. https://t.co/Jga1EUEkbF.

And: Dispelling the Myth: Training in Education or Neuroscience Decreases but Does Not Eliminate Beliefs in Neuromyths. Kelly Macdonald et al. Frontiers in Psychology, Aug 10 2017. https://doi.org/10.3389/fpsyg.2017.01314

And: Wisdom and how to cultivate it: Review of emerging evidence for a constructivist model of wise thinking. Igor Grossmann. European Psychologist, in press. Pre-print: https://osf.io/preprints/psyarxiv/qkm6v/

Facial Width-to-height Ratio Does Not Predict Self-reported Behavioral Tendencies

Kosinski, Michal. 2017. “Facial Width-to-height Ratio Does Not Predict Self-reported Behavioral Tendencies”. PsyArXiv. September 2. doi:10.1177/0956797617716929.

Abstract: A growing number of studies have linked facial width-to-height ratio (fWHR) with various antisocial or violent behavioral tendencies. However, those studies have predominantly been laboratory based and low powered. This work reexamined the links between fWHR and behavioral tendencies in a large sample of 137,163 participants. Behavioral tendencies were measured using 55 well-established psychometric scales, including self-report scales measuring intelligence, domains and facets of the five-factor model of personality, impulsiveness, sense of fairness, sensational interests, self-monitoring, impression management, and satisfaction with life. The findings revealed that fWHR is not substantially linked with any of these self-reported measures of behavioral tendencies, calling into question whether the links between fWHR and behavior generalize beyond the small samples and specific experimental settings that have been used in past fWHR research.

Contrary to the hypothesis, predicted pleasure eating sweets was significantly lower than observed pleasure

Fallon, Matthew D., "The Role of Affective Forecasting and the Impact Bias in Nutritional Health Behaviors" (2017). Grand Valley State University, Masters Theses. 854. http://scholarworks.gvsu.edu/theses/854

Abstract: Previous literature on affective forecasting has studied its role in health decisions, but there is little research investigating affective forecasting in diet choices and eating behaviors. The present study collected affective forecasts from 43 college participants before eating an indulgent snack and then observed emotions immediately after eating the snack. We predicted that emotion predictions would be significantly stronger than observed emotions, in support of previous literature on the impact bias. We also predicted that optimism would predict a stronger impact bias and that extraversion and neuroticism would have a role in forecasts and observed emotions. Contrary to our hypothesis, predicted pleasure (M=2.12) was significantly lower than observed pleasure (M=2.34), F(1,42)=5.44, p=.025. Likewise, for participants who ate M&Ms rather than cookies or chips, participants had significantly higher observed positive emotion (M=1.95) than they had predicted (1.73), F(1,14)=5.78, p=.031. Trait optimism had significant interaction effects for positive affect, for each food chosen, such that as optimism increases, predicted affect increased more rapidly than observed affect. Neuroticism and extraversion were found to significantly influence predicted and observed positive affect, but had no effect on the accuracy of the affective forecasts. The present findings did not indicate the presence of an impact bias, but support previous affective forecasting literature in other aspects. These findings indicate that many of the phenomena in affective forecasting influence food forecasts. This holds implications for future research on affective forecasting in food choice and interventions targeting forecasting errors to improve diet.