Wonderlic, working memory capacity, and fluid intelligence

Prospective associations between intelligence, working memory capacity, and intrusive memories of a traumatic film: Potential mediating effects of rumination and memory disorganization

The investment hypothesis proposes that fluid intelligence drives the accumulation of crystallized intelligence, such that crystallized intelligence increases more substantially in individuals with high rather than low fluid intelligence. However, most investigations have been conducted on adolescent cohorts or in two-wave data sets. There are few longitudinal representative studies with which to observe the growth of intelligence in young adulthood. A large community representative sample of 20- to 24-year-olds was recruited in 1999 and followed in 2003 and 2007. The Spot-the-Word Test Version A, a lexical decision task, was used to assess crystallized intelligence. The Symbol–Digit Modalities Test, a test of perceptual speed, was used as a measure of fluid intelligence. Latent growth models were used to examine whether growth in fluid intelligence drives the acquisition of crystallized intelligence. Fluid and crystallized intelligence are coupled; crystallized intelligence accrues in the 20s, but the rate of increase of crystallized intelligence is not associated with the level of fluid intelligence. Although young adulthood is associated with “the getting of wisdom,” accelerated development of crystallized intelligence in those with high fluid intelligence was not observed. Hence, no support was found for the investment hypothesis.

Studies in cultural evolution have uncovered many types of social learning strategies that are adaptive in certain environments. The efficiency of these strategies also depends on the individual characteristics of both the observer and the demonstrator. We investigate the relationship between intelligence and the ways social and individual information is utilised to make decisions in an uncertain environment. We measure fluid intelligence and study experimentally how individuals learn from observing the choices of a demonstrator in a 2-armed bandit problem with changing probabilities of a reward. Participants observe a demonstrator with high or low fluid intelligence. In some treatments they are aware of the intelligence score of the demonstrator and in others they are not. Low fluid intelligence individuals imitate the demonstrator more when her fluid intelligence is known than when it is not. Conversely, individuals with high fluid intelligence adjust their use of social information, as the observed behaviour changes, independently of the knowledge of the intelligence of the demonstrator. We provide evidence that intelligence determines how social and individual information is integrated in order to make choices in a changing uncertain environment.

Although the existing literature has explored the link between cognitive functioning and speech recognition in noise, the specific role of fluid intelligence still needs to be studied. Given the established association between working memory capacity (WMC) and fluid intelligence and the predictive power of WMC for speech recognition in noise, we aimed to elucidate the mediating role of fluid intelligence. We used data from the n200 study, a longitudinal investigation into aging, hearing ability, and cognitive functioning. We analyzed two age-matched samples: participants with hearing aids and a group with normal hearing. WMC was assessed using the Reading Span task, and fluid intelligence was measured with Raven's Progressive Matrices. Speech recognition in noise was evaluated using Hagerman sentences presented to target 80% speech-reception thresholds in four-talker babble. Data were analyzed using mediation analysis to examine fluid intelligence as a mediator between WMC and speech recognition in noise. We found a partial mediating effect of fluid intelligence on the relationship between WMC and speech recognition in noise, and that hearing status did not moderate this effect. In other words, WMC and fluid intelligence were related, and fluid intelligence partially explained the influence of WMC on speech recognition in noise. This study shows the importance of fluid intelligence in speech recognition in noise, regardless of hearing status. Future research should use other advanced statistical techniques and explore various speech recognition tests and background maskers to deepen our understanding of the interplay between WMC and fluid intelligence in speech recognition.

The Job Demands–Resources Theory (JD-R) is one of the most influential theoretical frameworks for explaining work engagement. The JD-R postulates the existence of a health impairment process in which job demands lead to strain, and of a motivational process in which job resources lead to work engagement. Although cognitive functions are among the most important characteristics of employees related to job, still little is known about its moderating role in JD-R processes; hence in this study we make a novel attempt to test the invariance of JD-R propositions among employees at different levels of cognitive functioning. A group of 383 multioccupational employees completed a set of questionnaires measuring job resource: co-worker support, supervisor support, performance feedback; job demands: emotional demands, occupational constraints, work-home interferences; Utrecht Work Engagement Scale; Oldenburg Burnout Inventory along with 2 working memory and 3 fluid intelligence tests. The multigroup invariance analysis with latent variables revealed that both the health impairment process and the motivational process as postulated by JD-R are invariant across groups of employees with either high or low levels of fluid intelligence and working memory capacity. This result provides the first piece of evidence for JD-R robustness among employees at different levels of cognitive functioning. Our findings counterintuitively suggest that employees with high cognitive functioning are not more resistant to job demands than employees with low cognitive functioning and that in order to be work-engaged they need job resources, no less than their colleagues with low cognitive functioning. Med Pr 2018;69(5):483–496

It is well established that measures of reasoning ability and of working memory capacity (WMC) correlate positively. However, the question of what explains this relationship remains open. The purpose of this study was to investigate the capacity hypothesis, which ascribes causality to WMC. This hypothesis holds that people high in WMC are more successful in capacity-demanding cognitive tasks than people lower in WMC because they can temporarily maintain more information in the form of sub-goals, hypotheses, and partial solutions. Accordingly, this hypothesis predicts that the correlation between WMC and reasoning performance should increase as the capacity demands of the reasoning items increase. We tested this prediction using items from Raven's Progressive Matrices and two measures of WMC, complex span and the k estimate from the Visual Arrays task. Neither WMC measure showed the effect predicted by the capacity hypothesis. Furthermore, the results cannot be attributed to restriction of range in performance on the individual reasoning items. This finding adds to existing evidence calling into question the capacity hypothesis, and, more generally, the view that WMC has a causal influence on fluid intelligence.

A previous study found that task shifting and fluid intelligence, but not working memory capacity (WMC) and prior knowledge, influenced the worked example effect (Schwaighofer, Buhner, & Fischer, 2016). To increase confidence in these findings, we report a preregistered extended replication study of Schwaighofer et al.’s investigation. University students (N = 231, Mage = 22.40 [SD = 4.33], 87% women) solved statistical problems with textbook materials presented on a laptop in one of four conditions in a 2 × 2 factorial between-subjects design. We compared worked examples versus problem-solving (replication) and with versus without time pressure (extension). Time pressure was added to test whether learners in the original study were able to offload WMC demands, which would explain why the WMC moderation was not found. Results showed that the advantage of worked examples over problem-solving decreased with increasing prior knowledge, suggesting that problem-solving becomes eventually more effective than worked example study. Similarly, the benefit of worked examples over problem-solving decreased with increasing shifting ability of a learner. However, contingencies on WMC or fluid intelligence were not detected. Our extension analysis indicated that the worked example effect was also not contingent on WMC even when learners were under time pressure. These findings underline the important role that task shifting might play in scaffolded learning environments and suggest that trading in the focus on WMC for a broader perspective on cognitive architecture provides novel explanations for instructional effectiveness. Our study further highlights the importance of more customized instructional support. (PsycInfo Database Record (c) 2020 APA, all rights reserved)

An enduring question is unity vs. separability of executive deficits resulting from impaired frontal lobe function. In previous studies, we have asked how executive deficits link to a conventional measure of fluid intelligence, obtained either by standard tests of novel problem-solving, or by averaging performance in a battery of novel tasks. For some classical executive tasks, such as the Wisconsin Card Sorting Test (WCST), Verbal Fluency, and Trail Making Test B (TMTB), frontal deficits are entirely explained by fluid intelligence. However, on a second set of executive tasks, including tests of multitasking and decision making, deficits exceed those predicted by fluid intelligence loss. In this paper we discuss how these results shed light on the diverse clinical phenomenology observed in frontal dysfunction, and present new data on a group of 15 schizophrenic patients and 14 controls. Subjects were assessed with a range of executive tests and with a general cognitive battery used to derive a measure of fluid intelligence. Group performance was compared and fluid intelligence was introduced as a covariate. In line with our previous results, significant patient-control differences in classical executive tests were removed when fluid intelligence was introduced as a covariate. However, for tests of multitasking and decision making, deficits remained. We relate our findings to those of previous factor analytic studies describing a single principal component, which accounts for much of the variance of schizophrenic patients' cognitive performance. We propose that this general factor reflects low fluid intelligence capacity, which accounts for much but not all cognitive impairment in this patient group. Partialling out the general effects of fluid intelligence, we propose, may clarify the role of additional, more specific cognitive impairments in conditions such as schizophrenia.

Working memory capacity consistently correlates with fluid intelligence. It has been suggested that this relationship is partly attributable to strategy use: Participants with high working memory capacity would use more effective strategies, in turn leading to higher performance on fluid intelligence tasks. However, this idea has never been directly investigated. In 2 experiments, we tested this hypothesis by directly manipulating strategy use in a combined experimental-correlational approach (Experiment 1; N = 250) and by measuring strategy use with a self-report questionnaire (Experiment 2; N = 93). Inducing all participants to use an effective strategy in Raven's matrices decreased the correlation between working memory capacity and performance; the strategy use measure fully mediated the relationship between working memory capacity and performance on the matrices task. These findings indicate that individual differences in strategic behavior drive the predictive utility of working memory. We interpret the results within a theoretical framework integrating the multiple mediators of the relationship between working memory capacity and high-level cognition.

The relationship between baseline pupil size and intelligence

Mental speed theories of intelligence suggest that people are smarter because they are faster. We argue that attention control plays an important and fundamental role in mediating the relationship between basic sensory processes and more complex cognitive processes such as fluid intelligence. One of the most successful paradigms for establishing a mental speed theory of intelligence is the inspection time task. In this article, we examine the mental speed and the attention control perspectives on the inspection time task and its relationship with fluid intelligence. Integrating experimental and correlational approaches, we find that attention control statistically explains the inspection time task's correlation with fluid intelligence and working memory capacity. Attention control and inspection time are correlated beyond their relationship with other measures of processing speed. Further, while we find no evidence that selective attention specifically is related to inspection time performance, both attention control and inspection time predicted declines in accuracy as participants sustained their attention over time; other measures of processing speed did not predict sustained attention performance. Collectively, these results indicate that inspection time is related to the ability to control attention, especially the ability to sustain attention over time. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Recently, there has been an explosive growth in graphical modeling approaches for estimating brain functional networks. In a detailed study, we show that surprisingly, standard graphical modeling approaches for fMRI data may not yield accurate estimates of the brain network due to the inability to suitably account for temporal correlations. We propose a novel Bayesian matrix normal graphical model that jointly models the temporal covariance and the brain network under a separable structure for the covariance to obtain improved estimates. The approach is implemented via an efficient optimization algorithm that computes the maximum-a-posteriori network estimates having desirable theoretical properties and which is scalable to high dimensions. The proposed method leads to substantial gains in network estimation accuracy compared to standard brain network modeling approaches as illustrated via extensive simulations. We apply the method to resting state fMRI data from the Human Connectome Project involving a large number of time scans and brain regions, to study the relationships between fluid intelligence and functional connectivity, where it is not computationally feasible to apply existing matrix normal graphical models. Our proposed approach led to the detection of differences in connectivity between high and low fluid intelligence groups, whereas these differences were less pronounced or absent using the graphicallasso.

Individuals scoring higher in tests of general cognitive abilities tend to perform better on novel and familiar mathematical tasks. It has been scarcely investigated how this superior mathematical performance relates to the amount of cognitive resources that is invested to solve a given task. In this study we propose that, on novel tasks, individuals with high cognitive abilities outperform less able individuals, because they allocate a higher amount of resources. On familiar tasks, however, individuals with higher abilities profit from more efficient processes compared to individuals of lower cognitive abilities. We tested this hypothesis by administering to 11th graders a geometric analogy task not practiced at school and an algebraic transformation task comprising operations that are routinely required during mathematical courses. General cognitive abilities were measured with Ravens Advanced Progressive matrices (fluid intelligence), the d2 (focused attention) and KAI-N (working memory capacity). Resource allocation was measured by assessing pupil diameter during the problem-solving process. Performance on both the analogy and the algebra task was correlated with general cognitive abilities, especially fluid intelligence. In line with our assumptions, a positive correlation between fluid intelligence and resource allocation was observed in the novel geometric analogy task, whereas the correlation was not significant in the more familiar algebra task.

This literature review aims to analyze the role of individual differences in working memory capacity in following instructions based on theoretical perspectives and empirical evidence. Individual differences in working memory capacity have an impact on the encoding, and retrieval stage. In general, the output from the review stated that the performance difference between individuals relates to the experimental design and treatment, which include delivery of the instructions, presentation of objects, the length of instructions, involvement of dual tasks, and retrieval methods. In addition, the contents of instructions can be transferred into working memory space if the individuals can give a high level of attention and control the attention to suppress the distractors. Therefore, the ability to follow instructions depends on the individual's understanding of the instructions' meaning and matching them with the available space of their working memory (capacity). This review also adds value and suggestions to the need to conduct more research on the role of working memory capacity in following instructions.

The effects of working memory (WM) capacity on mathematical ability are well known. This relationship is seen mainly for the capacity of visuospatial WM, while the capacity of the phonological loop of WM, which is associated with processing sound and speech information, has been suggested to have a minor effect on mathematical ability in adults. Nonetheless, involvement of the language neural networks in mathematical thought remains controversial. We have studied the effects of the capacity of the phonological loop of WM on the rate and correctness of solution of mathematical and verbal tasks in young, healthy, right-handed volunteers who either had higher education or were students at institutions teaching mathematics and humanities. Subjects in the mathematics group (N = 10) solved all tasks with measures of solution correctness (CA) and response time (RT) which were significantly better than values for subjects of the humanities group (N = 10). The capacity of the phonological loop of WM showed no difference between the two groups but had different effects on CA and RT values for tasks in mathematicians and humanities specialists. Spearman correlation analysis for each group separately showed that the capacity of WM had positive effects on CA for all mathematical tasks only in the mathematicians group, where it had no effect on RT, while the reverse tendency was seen in the humanities group. The capacity of WM in the mathematicians group correlated inversely with RT for logical tasks on arithmetic sequences. Our results provide indirect evidence that WM in the verbal domain can influence mathematical ability, especially when tasks require the involvement of logical thought.