The Flynn Effect within Subgroups in the U.S.: Gender, Race, Income, Education, and Urbanization Differences in the NLSY-Children Data

Investigating changes in IQ scores over a decade in Brazil: factors at play

PURPOSE

This study aimed to determine whether the factors underlying potential differences between two birth cohorts, born in 1982 and 1993, influence the changes in IQ over time.

METHODS

Data from two Brazilian birth cohorts were used (1993 and 1982 Pelotas Birth Cohorts). The IQ scores were assessed using the WAIS-III test.

RESULTS

Results showed that women born in 1993 had a higher average IQ score than those born in 1982, but no difference was found among men. The increase in IQ scores was only limited to participants from families with an income ranging from 1.1 to 3 times the minimum wage at the time of birth. The mean IQ score of participants born to mothers below the age of 20 remained stable over time, but increase for participants whose mothers were 20 years of age or older at the time of birth.

CONCLUSIONS

This study emphasizes the importance of considering socio-economic and demographic factors when examining differences in IQ scores over time. Further research is needed to understand the underlying mechanisms of these findings.

Does Students' Level of Intelligence Moderate the Relationship Between Socio-Economic Status and Academic Achievement?

The association between school students' social background and school achievement is well documented. Recent studies demonstrated that this association might be moderated by the level of cognitive potential. Based on these results, we recruited an elementary school sample (N = 837) and an adolescent sample at the end of their compulsory school time (N = 2100) to investigate whether the associations between students' social background and their academic achievement in math and language arts were moderated by the level of their general cognitive competencies, i.e., intelligence. To this end, we assessed intelligence, math and reading competencies, teacher-reported grades, and students' socio-economic background (number of books at home). In both samples, the association between students' socio-economic background and language arts grades was moderated by their intelligence level but not the ones with math grades, reading, and math competencies. The association between socio-economic background and language arts grades was strongest in the average intelligence sample and smaller in the above-average intelligence sample. Results are discussed with regard to their implications for the discussion of social injustice in schools.

Cognitive performance trends among European older adults: exploring variations across cohorts, gender, and educational levels (2007-2017)

BACKGROUND

This study explores recent cohort trends in cognitive performance among older Europeans from 2007 to 2017, addressing three key questions: (1) Did cognitive performance improve universally and across the performance distribution during this period? (2) Did these improvements occur across educational levels and for both men and women? (3) Can established risk factors explain these performance gains?

METHODS

Using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) across 12 European countries, we assessed immediate recall, delayed recall, and verbal fluency in individuals aged 60 to 94 in both 2007 and 2017 (n = 32 773). Differences between the two time points were estimated with linear mixed effects regression models and quantile regression.

RESULTS

Cognitive performance improved in all age groups, across educational levels, and for both men and women between 2007 and 2017. Notably, improvements were more pronounced at the upper end of the performance distribution for delayed recall and verbal fluency. Education explained approximately 20% of the observed improvements. Risk factors did not explain the observed improvements.

CONCLUSIONS

European cohorts of both younger-old and older adults continue to exhibit improvements in cognitive performance. Variation in the size of the cohort improvements across the performance distributions in delayed recall and in verbal fluency may contribute to growing inequalities in cognitive outcomes. Future research should further investigate the potential heterogeneity in cognitive performance gains.

TRIAL REGISTRATION

Not applicable.

Cohort Changes and Sex Differences After Age 50 in Cognitive Variables in the English Longitudinal Study of Ageing

OBJECTIVES

This paper models cognitive aging, across mid and late life, and estimates birth cohort and sex differences in both initial levels and aging trajectories over time in a sample with multiple cohorts and a wide span of ages.

METHODS

The data used in this study came from the first 9 waves of the English Longitudinal Study of Ageing, spanning 2002-2019. There were n = 76,014 observations (proportion male 45%). Dependent measures were verbal fluency, immediate recall, delayed recall, and orientation. Data were modeled using a Bayesian logistic growth curve model.

RESULTS

Cognitive aging was substantial in 3 of the 4 variables examined. For verbal fluency and immediate recall, males and females could expect to lose about 30% of their initial ability between the ages of 52 and 89. Delayed recall showed a steeper decline, with males losing 40% and females losing 50% of their delayed recall ability between ages 52 and 89 (although females had a higher initial level of delayed recall). Orientation alone was not particularly affected by aging, with less than a 10% change for either males or females. Furthermore, we found cohort effects for initial ability level, with particularly steep increases for cohorts born between approximately 1930 and 1950.

DISCUSSION

These cohort effects generally favored later-born cohorts. Implications and future directions are discussed.

It Runs in the Family: Testing for Longitudinal Family Flynn Effects

The Flynn effect refers to increases over time in measured (particularly fluid) intelligence of approximately 3 IQ points per decade. We define the Flynn effect at the family level, using longitudinal data and two new family-level cohort definitions. Multilevel growth curve analyses of the National Longitudinal Survey of Youth 1979 data showed that children in families with later-born mothers had higher average PIAT math scores, and lower average reading comprehension scores and growth, in young and middle childhood. Children in families where the first child was born later had higher average PIAT math, reading recognition, and reading comprehension scores, as well as larger developmental growth. The latter family-level Flynn effects were of higher magnitudes than the usual individual-level Flynn effect found in previous studies. Our results, showing family level-intercept and slope Flynn effects for both maternal birthyear and first child birthyear, have implications for research aiming to explain the Flynn effect.

Establishing cognitive baseline in three generations: Framingham Heart Study

Introduction

Generational changes warrant recalibrating normative cognitive measures to detect changes indicative of dementia risk within each generation.

Methods

We performed linear regressions to compare eight neuropsychological (NP) tests among three-generation cohorts at baseline in Framingham Heart Study (FHS, n = 4787) and conducted Cox regressions to investigate the relationships of NP tests with generation-specific dementia risk.

Results

The FHS second and third generations performed better than the first generation for seven NP tests (0.14-0.81 standard deviation improvement, P ≤ .001) while the second and third generations performed similarly for six of eight NP tests (P > .05). One standard deviation better performance was associated with a higher reduction in incident dementia risk in the second than the first generation (35% vs. 24%, P interaction = .02) for the similarities test.

Discussion

Our findings suggest cohort-based norms are needed for cognitive assessment for the diagnosis of cognitive impairment and dementia.

A Half Century of Progress in US Student Achievement: Agency and Flynn Effects, Ethnic and SES Differences

Policymakers, conceptualized here as principals, disagree as to whether US student performance has changed over the past half century. To inform conversations, agents administered seven million psychometrically linked tests in math (m) and reading (rd) in 160 survey waves to national probability samples of cohorts born between 1954 and 2007. Estimated change in standard deviations (sd) per decade varies by agent (m: –0.10sd to 0.27sd, rd: –0.02sd to 0.12sd). Consistent with Flynn effects, median trends show larger gains in m (0.19sd) than in rd (0.04sd), though rates of progress for cohorts born since 1990 have increased in rd but slowed in m. Greater progress is shown by students tested at younger ages (m: 0.31sd, rd: 0.08sd) than when tested in middle years of schooling (m: 0.17sd, rd: 0.03sd) or toward the end of schooling (m: 0.06sd, rd: 0.02sd). Young white students progress more slowly (m: 0.28sd, rd: 0.09sd) than Asian (m: 46sd, rd: 0.28sd), black (m: 0.36sd, rd: 0.19sd), and Hispanic (m: 0.29sd, rd: 0.13sd) students. These ethnic differences generally attenuate as students age. Young students in the bottom quartile of the SES distribution show greater progress than those in the top quartile (difference in m: 0.08sd, in rd: 0.15sd), but the reverse is true for older students. Moderators likely include not only changes in families and schools but also improvements in nutrition, health care, and protection from contagious diseases and environmental risks. International data suggest that subject and age differentials may be due to moderators more general than just the United States.

Home Improvement: Evaluating Secular Changes in NLSY HOME-Cognitive Stimulation and Emotional Support Scores

This study evaluated changes over time in the quality of children's home environment, using the Home Observation Measurement of the Environment (HOME). Longitudinal increases in HOME scores were predicted by both theory and past empirical results. Analysis of the National Longitudinal Survey of Youth Children data (N = 5715, aged 0-14) suggested that HOME scores have been increasing, and that the increase is a family-level phenomenon. The data were a sample of children born to mothers who were approximately representative of the United States in 1979. An increase in HOME scores occurred primarily for the three age categories younger than ten. Effect sizes were of approximately the same magnitude as the Flynn effect for intelligence. These results have implications for policy and future research regarding the home environment.

Changes in the Intelligence Levels and Structure in Russia: An ANOVA Method Based on Discretization and Grouping of Factors

In the present paper, we investigate how the general intelligence quotient (IQ) and its subtests changed for students from Russian University from 1991 to 2013. This study of the effect of such factors as gender, department, and year on the IQ response is carried out using the ANOVA model. Given the unevenness of the initial sample by years and departments, and consequently, heterogeneity of variances when divided by the original natural categories, we decided to aggregate the values of explanatory variables to build an adequate model. The paper proposes and investigates an algorithm for joint discretization and grouping, which uses the procedure of partial screening of solutions. It is an intermediate option between the greedy algorithm and exhaustive search. As a goodness function (an optimality criterion), we investigate 26 intermediate options between the AIC and BIC criteria. The BIC turned out to be the most informative and the most acceptable criterion for interpretation, which penalizes the complexity of the model, due to some decrease in accuracy. The resulting partition of the explanatory variables values into categories is used to interpret the modeling results and to arrive at the final conclusions of the data analysis. As a result, it is revealed that the observed features of the IQ dynamics are caused by changes in the education system and the socio-economic status of the family that occurred in Russia during the period of restructuring the society and intensive development of information technologies.

IQ differences between patients with first episode psychosis in London and Palermo reflect differences in patterns of cannabis use

AIMS

Cognitive impairment is a possible indicator of neurodevelopmental impairment, but not all psychotic patients are cognitively compromised. It has been suggested that heavy cannabis use may precipitate psychosis in those who show no such compromise. This study compares two samples of patients with first-episode psychosis and their respective non-psychotic controls, in London (UK) and Palermo (Italy), and examines whether different patterns of cannabis use are reflected in differences in IQ.

METHODS

The two studies used the same inclusion/exclusion criteria and instruments. The sample comprised 249 subjects from London (106 patients and 143 controls) and 247 subjects from Palermo (120 patients and 127 controls). ANCOVA was performed with IQ as the dependent variable and city and frequency of cannabis use as predictors. This was then repeated with the case group only, by adjusting for relevant confounders.

RESULTS

We found a greater amount of cannabis use in the London sample, compared to Palermo and patients from London had higher IQ than patients from Palermo, a difference that was more significant than that reflected between controls (F_^group*city(1, 402) = 7.6, p = 0.006). Once corrected for symptomatology and treatment, patients from London who had never used cannabis were similar to patients from Palermo regarding IQ. Thus the higher IQ of patients from London was mainly due to the subgroup of cannabis-using patients (F_{cannabis*city}(2,145) = 4.6, p = 0.011).

CONCLUSIONS

We can speculate that a greater amount of cannabis-use may have contributed by precipitating psychosis in patients with a higher IQ in London but less so in patients from Palermo.

Double Decomposition of Level-1 Variables in Multilevel Models: An Analysis of the Flynn Effect in the NSLY Data

This paper introduces an extension of cluster mean centering (also called group mean centering) for multilevel models, which we call "double decomposition (DD)." This centering method separates between-level variance, as in cluster mean centering, but also decomposes within-level variance of the same variable. This process retains the benefits of cluster mean centering but allows for context variables derived from lower level variables, other than the cluster mean, to be incorporated into the model. A brief simulation study is presented, demonstrating the potential advantage (or even necessity) for DD in certain circumstances. Several applications to multilevel analysis are discussed. Finally, an empirical demonstration examining the Flynn effect (Flynn, 1987 ), our motivating example, is presented. The use of DD in the analysis provides a novel method to narrow the field of plausible causal hypotheses regarding the Flynn effect, in line with suggestions by a number of researchers (Mingroni, 2014 ; Rodgers, 2015 ).

Cross-cultural differences in social desirability scales: Influence of cognitive ability

Orientation: The use of personality tests for selection and screening has been consistently criticised resulting from the risk of socially desirable responding amongst job applicants. Research purpose: This study examined the magnitude of culture and language group meanscore differences amongst job applicants and the moderating effect of race on the relationship between social desirability and cognitive ability. Motivation for the study: The influence of cognitive ability and potential race and ethnic group differences in social desirability scale scores, which can lead to disproportional selection ratios, has not been extensively researched in South Africa. Research design, approach and method: A quantitative, cross-sectional research design, based on secondary datasets obtained from the test publisher, was employed. The dataset consisted of 1640 job applicants across industry sectors. Main findings: Moderated multiple regression analyses revealed that the relationship between social desirability and general reasoning was moderated by culture and language, with group differences in social desirability being more pronounced at the low general reasoning level. This suggests that social desirability scales may be an ambiguous indicator of faking as the scales may indicate tendency to fake, but not the ability to fake, that is likely to be connected to the level of cognitive ability of the respondent.Practical/managerial implications: Individual differences in social desirability are not fully explained by cognitive ability as cultural differences also played a role. Responding in a certain manner, reflects a level of psychological sophistication that is informed by the level of education and socio-economic status. In relation to selection practice, this study provided evidence of the potentially adverse consequences of using social desirability scales to detect response distortion. Contribution/value-add: The exploration of cross-cultural differences in the application of social desirability scales and the influence of cognitive ability is seen as a major contribution, supported by possible explanations for the differences observed and recommendations regarding the practice of universal corrections and adjustments.

Fighting for Intelligence: A Brief Overview of the Academic Work of John L. Horn

John L. Horn (1928-2006) was a pioneer in multivariate thinking and the application of multivariate methods to research on intelligence and personality. His key works on individual differences in the methodological areas of factor analysis and the substantive areas of cognition are reviewed here. John was also our mentor, teacher, colleague, and friend. We overview John Horn's main contributions to the field of intelligence by highlighting 3 issues about his methods of factor analysis and 3 of his substantive debates about intelligence. We first focus on Horn's methodological demonstrations describing (a) the many uses of simulated random variables in exploratory factor analysis; (b) the exploratory uses of confirmatory factor analysis; and (c) the key differences between states, traits, and trait-changes. On a substantive basis, John believed that there were important individual differences among people in terms of cognition and personality. These sentiments led to his intellectual battles about (d) Spearman's g theory of a unitary intelligence, (e) Guilford's multifaceted model of intelligence, and (f) the Schaie and Baltes approach to defining the lack of decline of intelligence earlier in the life span. We conclude with a summary of John Horn's unique approaches to dealing with common issues.