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Using the Deese-Roediger-McDermott task and E. Tulving's (1985) remember-know judgments for recognition memory, the authors explored whether emotional words can show the false memory effect. Participants studied lists containing nonemotional, orthographic associates (e.g., cape, tape, ripe; part, perk, dark) of either emotional (e.g., rape) or nonemotional (e.g., park) critical lures. This setup produced significant false "remembering" of emotional lures, even though initially no emotional words appeared at study. When 3 emotional nonlure words appeared at study, emotional-lure false recognition more than doubled. However, when these 3 study words also appeared on the recognition test, false memory for the emotional lures was reduced. Across experiments, participants misremembered nonemotional lures more often than they did emotional lures, but they were more likely to rate emotional lures as "remembered," once they had been recognized as "old." The authors discuss findings in light of J. J. Freyd and D. H. Gleave's (1996) criticisms of this task.

Well-being is a construct spanning multiple disciplines including psychology, economics, health, and public policy. In many ways, well-being is a nexus of inter-correlated variables, much like the g nexus. Here, we created an index of well-being for the geographical and political subdivisions of the United States (i.e., states). The measure resulted from hierarchical principal components analyses of state-level data on various hypothesized sub-domains of well-being, including general mental ability, education, economics, religiosity, health, and crime. A single, general component of well-being emerged, explaining between 52 and 85% of the variance in the sub-domains. General mental ability loaded substantially on global state well-being (.83). The relationship between global well-being and other important state-level outcomes was examined next. We conclude by offering parallels between the g nexus and the well-being nexus.

An article’s keywords are distinct because they represent what authors feel are the most important words in their papers. Combined, they can even shed light on which research topics in a field are popular (or less so). Here we conducted bibliometric keyword analyses of articles published in the journal, Intelligence (2000–2016). The article set comprised 916 keyword-containing papers. First, we analyzed frequencies to determine which keywords were most/least popular. Second, we analyzed Web of Science (WOS) citation counts for the articles listing each keyword and we ran regression analyses to examine the effect of keyword categories on citation counts. Third, we looked at how citation counts varied across time. For the frequency analysis, “g factor”, “psychometrics/statistics”, and “education” emerged as the keywords with the highest counts. Conversely, the WOS citation analysis showed that papers with the keywords “spatial ability”, “factor analysis”, and “executive function” had the highest mean citation values. We offer tentative explanations for the discrepant results across frequencies and citations. The analysis across time revealed several keywords that increased (or decreased) in frequency over 17 years. We end by discussing how bibliometric keyword analysis can detect research trends in the field, both now and in the past.

Using data from the Philadelphia Neurodevelopmental Cohort, we examined whether European ancestry predicted cognitive ability over and above both parental socioeconomic status (SES) and measures of eye, hair, and skin color. First, using multi-group confirmatory factor analysis, we verified that strict factorial invariance held between self-identified African and European-Americans. The differences between these groups, which were equivalent to 14.72 IQ points, were primarily (75.59%) due to difference in general cognitive ability (g), consistent with Spearman's hypothesis. We found a relationship between European admixture and g. This relationship existed in samples of (a) self-identified monoracial African-Americans (B = 0.78, n = 2,179), (b) monoracial African and biracial African-European-Americans, with controls added for self-identified biracial status (B = 0.85, n = 2407), and (c) combined European, African-European, and African-American participants, with controls for self-identified race/ethnicity (B = 0.75, N = 7,273). Controlling for parental SES modestly attenuated these relationships whereas controlling for measures of skin, hair, and eye color did not. Next, we validated four sets of polygenic scores for educational attainment (eduPGS). MTAG, the multi-trait analysis of genome-wide association study (GWAS) eduPGS (based on 8442 overlapping variants) predicted g in both the monoracial African-American (r = 0.111, n = 2179, p < 0.001), and the European-American (r = 0.227, n = 4914, p < 0.001) subsamples. We also found large race differences for the means of eduPGS (d = 1.89). Using the ancestry-adjusted association between MTAG eduPGS and g from the monoracial African-American sample as an estimate of the transracially unbiased validity of eduPGS (B = 0.124), the results suggest that as much as 20%-25% of the race difference in g can be naïvely explained by known cognitive ability-related variants. Moreover, path analysis showed that the eduPGS substantially mediated associations between cognitive ability and European ancestry in the African-American sample. Subtest differences, together with the effects of both ancestry and eduPGS, had near-identity with subtest g-loadings. This finding confirmed a Jensen effect acting on ancestry-related differences. Finally, we confirmed measurement invariance along the full range of European ancestry in the combined sample using local structural equation modeling. Results converge on genetics as a potential partial explanation for group mean differences in intelligence.Psych 2019, 1 433 between ancestry and outcomes or that ancestry is a non-causal correlate of the trait in question that's actually caused by something else if the mediation is not spurious. Ultimately, controls alone cannot establish causality [50].Four studies we know of have related genetically-assessed ancestry to cognitive ability in samples of 25,51,52]. Others have done this for Hispanic Americans [24,25] and various groups in Latin America [53][54][55]. Of these, the earlier ones [51-54] re...

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Current research shows that geo-political units (e.g., the 50 U.S. states) vary meaningfully on psychological dimensions like intelligence (IQ) and neuroticism (N). A new scientific discipline has also emerged, differential epidemiology, focused on how psychological variables affect health. We integrate these areas by reporting large correlations between aggregate-level IQ and N (measured for the 50 U.S. states) and state differences in rates of chronic disease (e.g., stroke, heart disease). Controlling for health-related behaviors (e.g., smoking, exercise) reduced but did not eliminate these effects. Strong relationships also existed between IQ, N, disease, and a host of other state-level variables (e.g., income, crime, education). The nexus of inter-correlated state variables could reflect a general fitness factor hypothesized by cognitive epidemiologists, although valid inferences about causality will require more research.

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