In a recent study (N = 1075), Dunkel et al. (2023) concluded that maternal supportiveness is important for children's general intelligence. Maternal supportiveness was measured at ages 14, 24, and 36 months while children's intelligence was measured at ages 14, 24, and 36 months and at 4 and 10 years. The effects of maternal supportiveness at time T (β = 0.12), of maternal supportiveness at time T + 1 (β = 0.08), and of the child's intelligence at T + 1 (β = 0.49) on the child's intelligence at T + 2, were all positive and statistically significant when adjusting for one another. However, it is known that such adjusted cross-lagged effects may be biased due to residual confounding and regression to the mean. In the present study, we fitted various models, including latent change score models, on data simulating the data used by Dunkel et al. We found discrepant effects. For example, a positive effect of supportiveness on subsequent increase in children's intelligence (β = 0.04) was accounted for by maternal intelligence (β = 0.01 after adjustment). Another effect indicated that low supportiveness may compensate for having a mother with low intelligence and allow children to achieve the same intelligence as children to more intelligent and supportive mothers (β = 0.34). These divergent findings suggested that it may be premature to assume an increasing effect of maternal supportiveness on children's intelligence. It is important for researchers to bear in mind that correlations, also in superficially more advanced forms like cross-lagged effects, do not prove causality.

Intelligence is correlated with a range of left-wing and liberal political beliefs. This may suggest intelligence directly alters our political views. Alternatively, the association may be confounded or mediated by socioeconomic and environmental factors. We studied the effect of intelligence within a sample of over 300 biological and adoptive families, using both measured IQ and polygenic scores for cognitive performance and educational attainment. We found both IQ and polygenic scores significantly predicted all six of our political scales. Polygenic scores predicted social liberalism and lower authoritarianism, within-families. Intelligence was able to significantly predict social liberalism and lower authoritarianism, within families, even after controlling for socioeconomic variables. Our findings may provide the strongest causal inference to date of intelligence directly affecting political beliefs.

This study investigates neural mechanisms of divergent and convergent thinking in the verbal knowledge domain while taking into account activation related to working memory (WM). Divergent thinking was assessed using the Alternate Uses Task (AUT) and convergent thinking using the Compound Remote Associates task (RAT). We analyzed upper alpha band (10–12 Hz) oscillatory activity, in which we accounted for the temporal dynamics of both thinking processes by investigating three different time points during each trial for both tasks. We subtracted WM-related oscillatory activity measured by a serial recall task within the same knowledge domain and by using highly similar stimulus material as in both divergent and convergent thinking tasks. Our results show a strong upper alpha synchronization during divergent relative to convergent thinking, most pronounced at fronto-parietal electrodes. Moreover, we observed highest synchronization towards the middle (in contrast to the beginning and end) of each trial during both thinking processes. The results of the present study extend previous findings in the visuo-spatial knowledge domain, using a highly similar analytical approach to investigate divergent and convergent thinking. Together, these findings provide theoretical implications on how divergent and convergent thinking interact beyond WM across different knowledge domains by emphasizing their complex interplay.

Gignac and Zajenkowski (2020) recommended testing the Dunning-Kruger (DK) hypothesis with a combination of polynomial regression and LOESS regression, as the conventional approach to testing the hypothesis (i.e., quartile split) confounds regression toward the mean and the better-than-average effect. Building upon Gignac and Zajenkowski (2020), an insightful method to estimate the magnitude and prevalence of a DK effect is introduced based on comparing linear and LOESS regression predicted values. Based on simulated data specified to exhibit a plausible DK effect for cognitive abilities, the magnitude of the DK effect was empirically modeled. The effect peaked at a 20-point relative overestimation at an IQ of 55, impacting only 0.14% of the population, and decreased to a 7-point relative overestimation at an IQ of 70, affecting 2.3% of the population. Analysing two large field data samples (N ≈ 3500 each) from participants who completed intelligence subtests in grammar and logical reasoning, the DK effect was found to account for a maximum relative ability overestimation of 7 to 9 percentile points. Notably, this effect was confined to only ≈ 0.2% of the participants (IQ ≈ 55), all of whom scored at chance levels. Finally, low levels of conditional reliability (≈ 0.40) at distribution extremes were found to complicate interpreting results that superficially support the DK hypothesis. It is concluded that, when analyzed using appropriate methods, it is unlikely that the DK effect will ever be demonstrated as an unambiguously meaningful psychological phenomenon affecting an appreciable portion of the population.

A dimensionality reduction method was used to determine the task-timing-related functional brain networks underlying the Raven's Standard Progressive Matrices (RSPM), a non-verbal estimate of fluid intelligence (Gf). We identified five macro-scale task-based blood‑oxygen-level-dependent (BOLD)-signal brain networks and interpreted their network-level task-induced BOLD changes to provide functional interpretations separately for each network. This led to new observations about the brain networks underlying the RSPM: (1) the multiple demand network (MDN) for solution searching peaked early in the trial (∼9 s peak), followed by response (RESP) for response selection (∼12 s), and re-evaluation (RE-EV) for solution checking (∼18 s peak), (2) high activity in the MDN was correlated with high activity in the later-peaking RE-EV network, proposed to underpin cooperative solution searching (MDN) and checking (RE-EV) processes, and (3) high activity in the MDN in all conditions was associated with low accuracy in the hard RSPM condition, suggesting that those with lower performance on hard problems allocate more resources into solution-searching across all conditions. These findings corroborate the MDN's significance in Gf solution searching, and add the RE-EV network as playing an important checking role, providing overlap with the proposed abstraction/elaboration and hypothesis testing phases of the Parieto-Frontal Integration Theory (P-FIT). Therefore, this set of results not only supports past theoretical work on the brain networks underlying Gf and the RSPM task, but extends it by providing more complete anatomical, temporal, and functional information based on a set of brain task-based networks which replicate over many tasks.

The study examines how intensive hockey training is linked with spatial ability and academic performance. Participants were hockey players from top junior teams (N = 225, mean age = 14.25, all boys) and their unselected peers (N = 278, mean age = 15.47, all boys). Compared to the unselected group, hockey players showed lower results in 10 small-scale spatial tests (Cohen's d ranging from 0.42 to 1.04), Raven's Progressive Matrices (d = 0.41), and 12 school subjects (d for the sum of grades = 1.17). The differences in spatial ability remained significant after controlling for Raven's (d varying from 0.26 to 1.03). The absence of spatial advantage in athletes suggests that effects of sports on cognition are complex: spatial ability facet-specific, sport-specific, professional and intensity level-specific. Moreover, these effects might be confounded by differences in academic engagement, investment of effort and psychological and physiological effects of intensive sports engagement.

Jackson and Winston (2021) claim there is no taboo against research on race and intelligence. We argue, to the contrary, that there is a taboo against such research. We begin by addressing Jackson and Winston's arguments concerning expert surveys, as well as their criticisms of our published database of controversies. We then provide additional evidence of the taboo, and explain why it would be expected given the features of academic social science in Western countries. We also point out that Jackson and Winston's paper exemplifies the very taboo they claim does not exist.

The rise of large-scale collaborative panel studies has generated a need for fast, reliable, and valid assessments of cognitive abilities. In these studies, a detailed characterization of participants' cognitive abilities is often unnecessary, leading to the selection of tests based on convenience, duration, and feasibility. This often results in the use of abbreviated measures or proxies, potentially compromising their reliability and validity. Here we evaluate the mini-q (Baudson & Preckel, 2016), a three-minute speeded reasoning test, as a brief assessment of general cognitive abilities. The mini-q exhibited excellent reliability (0.96–0.99) and a substantial correlation with general cognitive abilities measured with a comprehensive test battery (r = 0.57; age-corrected r = 0.50), supporting its potential as a brief screening of cognitive abilities. Working memory capacity accounted for the majority (54%) of the association between test performance and general cognitive abilities, whereas individual differences in processing speed did not contribute to this relationship. Our results support the notion that the mini-q can be used as a brief, reliable, and valid assessment of general cognitive abilities. We therefore developed a computer-based version, ensuring its adaptability for large-scale panel studies. The paper- and computer-based versions demonstrated scalar measurement invariance and can therefore be used interchangeably. We provide norm data for young (18 to 30 years) and middle-aged (31 to 60 years) adults and provide recommendations for incorporating the mini-q in panel studies. Additionally, we address potential challenges stemming from language diversity, wide age ranges, and online testing in such studies.

Meta-analytic structural equation modeling was used to estimate the relative contributions of general cognitive ability or g (defined by executive functions, short-term memory, and intelligence) and basic domain-specific mathematical abilities to performance in more complex mathematics domains. The domain-specific abilities included mathematics fluency (e.g., speed of retrieving basic facts), computational skills (i.e., accuracy at solving multi-step arithmetic, algebra, or geometry problems), and word problems (i.e., mathematics problems presented in narrative form). The core analysis included 448 independent samples and 431,344 participants and revealed that g predicted performance in all three mathematics domains. Mathematics fluency contributed to the prediction of computational skills, and both mathematics fluency and computational skills predicted word problem performance, controlling g. The relative contribution of g was consistently larger than basic domain-specific abilities, although the latter may be underestimated. The patterns were similar across younger and older individuals, individuals with and without a disability (e.g., learning disability), concurrent and longitudinal assessments, and family socioeconomic status, and have implications for fostering mathematical development.

Complex problem solving (CPS) is a key competence in educational contexts with strong conceptual links to students' overall intelligence. However, the mechanisms underlying successful CPS are not fully understood. Therefore, this study investigated several factors presumed to be relevant to CPS success using log file data to code each individual student action during six CPS tasks with different characteristics (N = 1276). We coded individual strategy combinations per student for each item for different strategy combinations of vary-one-thing-at-a-time (VOTAT), hold-one-thing-at-a-time (HOTAT), vary-no-thing-at-a-time (NOTAT), and change-all (CA). Results from generalized linear mixed models showed that CPS success was likely to be achieved by using VOTAT. However, there was an increased chance of solving an item when additional strategies, such as NOTAT or NOTAT plus HOTAT were used. This result was moderated by the presence/absence of eigendynamics as an important determinant of item difficulty. Strategy combinations of VOTAT together with other strategies (all including NOTAT) showed higher chances of CPS success when eigendynamics were present. Additionally, higher chances of solving an item when using VOTAT with additional strategies was demonstrated for items without eigendynamics. Overall, our results suggest that flexibility in strategy application is the driving force for successful CPS performance. Implications are discussed in light of the presumed benefit of pedagogically relevant metacognitive skills, such as planning, monitoring and reflecting, for CPS success. Based on our findings, we provide specific recommendations for the development of computer-based learning simulations to train CPS and related competencies, ultimately enhancing students' skills in educational contexts.