The Relationship Between Diverse Components of Intelligence and Creativity

Intelligence and creativity are accounted for in terms of two different mental operations referred to as ‘convergent thinking’ and ‘divergent thinking’, respectively. Nevertheless, psychometric evidence on the relationship between intelligence and creativity has been controversial. To clarify their relationship, we characterized the relationship between diverse components of intelligence and creativity through the administration of psychometric tests on a large sample (WAIS, RPM, and TTCT‐figural: n = 215; TTCT‐verbal: n = 137). The general intelligence factor (g) score showed significant correlations with both TTCT‐figural and TTCT‐verbal scores. However, sub‐dimensional analysis demonstrated that their association was attributable to the specific components of both TTCTs (TTCT‐figural: Abstractness of Titles, Elaboration, and Resistance to Premature Closure; TTCT‐verbal: Flexibility) rather than to their common components (Fluency and Originality). Among the intelligence sub‐dimensions, crystallized intelligence (gC) played a pivotal role in the association between g and the specific components of both TTCTs. When the total sample was divided into two IQ groups, these phenomena were more evident in the average IQ group than in the high IQ group. These results suggest that the mental operation of creativity may be different from that of intelligence, but gC may be used as a resource for the mental operation of creativity.     

Intelligence and Creativity: Over the Threshold Together?

Threshold theory predicts a positive correlation between IQ and creativity scores up to an IQ level of 120 and no correlation above this threshold. Primary school children were tested at beginning (N = 98) and ending (N = 70) of the school year. Participants performed the standard progressive matrices (SPM) and the Test of Creative Thinking—Drawing Production (TCT-DP). Each child with IQ ≥ 120 was grade-and-gender matched to a child with IQ < 120. Results in accordance with the threshold theory were found only for female children in the highest grade level (Grade 4). Longitudinal analysis implies that a subgroup of children goes down in IQ and creativity simultaneously, possibly due to motivational issues. Their correlated scores may be a source of evidence for the threshold theory. The relationship between intelligence and creativity is not straightforward and depends on a combination of factors including grade level and gender.     

The Getting of Wisdom: Fluid Intelligence Does Not Drive Knowledge Acquisition

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.     

Threshold Theory Tested in an Organizational Setting: The Relation Between Perceived Innovativeness and Intelligence in a Large Sample of Leaders

A large sample of leaders (N = 4257) was used to test the link between leader innovativeness and intelligence. The threshold theory of the link between creativity and intelligence assumes that below a certain IQ level (approximately IQ 120), there is some correlation between IQ and creative potential, but above this cutoff point, there is no correlation. Support for the threshold theory of creativity was found, in that the correlation between IQ and innovativeness was positive and significant below a cutoff point of IQ 120. Above the cutoff, no significant relation was identified, and the two correlations differed significantly. The finding was stable across distinct parts of the sample, providing support for the theory, although the correlations in all subsamples were small. The findings lend support to the existence of threshold effects using perceptual measures of behavior in real-world organizational settings, and thus beyond creative potential measures applied in the psychological laboratory where it has previously been documented.     

Environment and high IQ—A consideration of fluid and crystallized intelligence

Attention is drawn to some causes of distancing between fluid and crystallized intelligence through detailed testing, environmental observations and responses of 210 children, their families and teachers. High Gc children (with IQ scores of 141+) were associated with educationally-superior home backgrounds, but not with abnormal emotional or personality features. High Gf children (99th% Raven's scorers) were found to reflect specifically the Cultural Milieu and Achievement-Related Facilities of their homes in their high IQ scores, but where Gf was insufficiently provided with opportunity, Gc appeared to suffer.Calculated proportions of fluid and crystallized intelligence in high IQ were varied, the scores becoming more heavily loaded with environmental influences towards the top of the scale, being 26% for children of exceptionally-high Gf and 13% for those of average to high Gf. It is suggested that where an IQ test is used, a cut-off point of IQ 130 be taken for the identification of intellectually-gifted children, along with verbal and other specific-ability tests.     

The validity of the Comprehensive Test of Nonverbal Intelligence as a measure of fluid intelligence

The current investigation examined the validity of the Comprehensive Test of Nonverbal Intelligence (CTONI), an intelligence test that is purported to measure fluid intelligence. The CTONI was evaluated in comparison with the Kaufman Adolescent and Adult Intelligence Test (KAIT), an established measure of fluid and crystallized intelligence. Ninety-seven adults were administered these instruments in counterbalanced order. Results indicated that the sample's mean CTONI Nonverbal IQ (NIQ) deviated significantly from the mean KAIT Crystallized, Fluid, and Composite IQs. The CTONI mean NIQ underestimated KAIT Fluid and Composite IQs when individual participants were subdivided into existing KAIT ability categories and mean score comparisons were made. Results also indicated that the CTONI NIQ correlated strongly and positively with the KAIT Composite and Fluid IQs. Furthermore, the CTONI Geometric NIQ scale clearly demonstrated discriminant and convergent validity, whereas, the CTONI Pictorial NIQ (PNIQ) did not.     

Dextroamphetamine and measures of intelligence

A sample of 320 male high school students was drawn on the basis of their neuroticism and extraversion scores from a population of 2500 students. By following a 4 × 4 randomized block design (replicated 20 times) an attempt was made to study the effects of dextroamphetamine on the test scores of fluid and crystallized intelligence of high school children. The study lends support to the hypothesis that the drug will have a differetial effect on the test scores of fluid and crystallized intelligence.     

Relationship between Cattell’s 16PF and fluid and crystallized intelligence

The aim of the study was to explore the relationship between the five global factors and 16 dimensions of Cattell’s personality model and fluid and crystallized intelligence. A total of 105 third graders (45.7% males) of three high schools participated in the research. Fluid intelligence was measured by Raven’s Advanced Progressive Matrices and crystallized intelligence was measured by the Mill Hill Vocabulary Scale. Personality traits were measured by the Sixteen Personality Factor Questionnaire. Anxiety is correlated neither with fluid nor with crystallized intelligence. Extraversion and Self-Control are negatively correlated with fluid intelligence whereas Tough-Mindedness is positively correlated with it. Independence is positively correlated with crystallized intelligence and Tough-Mindedness is negatively correlated with it. Regression analysis reveals that all broad personality factors, except anxiety, are significant predictors of fluid intelligence. When combined together, these factors account for 25% of the variance of fluid intelligence scores. The regression model with crystallized intelligence as a criterion variable is not statistically significant. The study results are consistent with the Chamorro-Premuzic and Furnham’s (2005) two-level conceptual framework. Although using a different taxonomy of personality, the results are in accordance with the model’s presuppositions.     

The effect of training in categorization on free recall: Some implications for Jensen's two-level theory

The effect of training in categorization on free recall learning was investigated in order to clarify an issue relating to Jensen's two-level theory of ability, namely, whether training in categorizetion would eliminate the reported association between free recall of categorized lists and socioeconomic status (SES). The subjects were 132 children partitioned into three groups on the basis of SES and two ability tests measuring fluid and crystallized intelligence (Cattell, 1963). Half the children in each group underwent training in categorization, and half were allocated to a control condition. The results revealed an interaction between ability and training. Low SES children of high fluid intelligence benefitted from categorization training and improved substantially in free recall of a categorized list so as to equal the performance of middle SES children. In contrast, low SES children matched for crystallized intelligence but scoring low in fluid intelligence did not benefit from training. The same three groups of children also learned an uncategorized list. The results did not support Jensen's hypothesis that free recall of uncategorized lists is unrelated to intelligence and SES.     

Not all executive functions are related to intelligence

Accumulating evidence suggests that executive functions (EFs) are related to intelligence, despite neuropsychological results initially considered evidence of no such relation. However, findings that EFs are not unitary raise the issue of how intelligence relates to different EFs. This study examined the relations of fluid and crystallized intelligence and Wechsler Adult Intelligence Scale IQ to three separable EFs--inhibiting prepotent responses (inhibiting), shifting mental sets (shifting), and updating working memory (updating)--in young adults. Updating was highly correlated with the intelligence measures, but inhibiting and shifting were not. Furthermore, in structural equation models controlling for the inter-EF correlations, updating remained strongly related to intelligence, but the relations of inhibiting and shifting to intelligence were small and not significant. The results indicate that intelligence measures differentially relate to these three EFs, suggesting that current intelligence measures do not equally assess a wide range of executive control abilities likely required for many "intelligent" behaviors.     

Is speed of information processing related to fluid or to crystallized intelligence?

Speed of information processing was examined in relation to the theory of fluid and crystallized intelligence. Sixty sixth grade children completed the Standard Progressive Matrices test and the Mill Hill Vocabulary scale, both untimed, as measures of fluid and crystallized intelligence, and three RT tasks: Memory Scanning, Picture Identification, and Sentence-Picture Comparison. As predicted, RT parameters, with the exception of slope on two tasks, were negatively correlated with scores on both tests. There were no consistent differences between the two tests in the size of correlations with RT, and partial correlations, eliminating the effects of fluid and crystallized intelligence respectively, failed to support any causal relationship between fluid and crystallized intelligence in either direction. Some limitations of the research, specifically in the possible effect of error rates on the speed-intelligence relationship, and in the application to individuals of task parameters derived from group performance, are noted.     

成人认知功能的发展与老化：一项控制同辈效应的横断研究

为探索成人认知功能的发展与认知老化轨迹,基于中华成人智力量表常模样本数据,统计控制教育水平和职业构成以部分消除同辈效应,考察智商和智力指数的年龄趋势。结果晶体智力指数(CI)在25~44岁间增加0.69分后缓慢递减,高低差值3.3分;注意记忆指数(AMI)在25~44岁间共减少3.3分,45岁后各组均数以3分左右的速度递减。流体智力指数(FI)和智商的年龄差异模式与AMI类似,幅度缩减。提示中国成人晶体智力在74岁前比较稳定,没有明显老化,流体智力和注意记忆能力可能在45岁开始明显线性老化。     

Group differences in intelligence and speed of information-processing

Three samples of different levels of mental ability, but each of average or above- average intelligence, were administered a battery of reaction time test which measure the speed with which persons can execute various elementary cognitive processes. Discriminant analyses revealed significant differences between the groups in reaction times and intraindividual standard deviations, and univariate analyses indicated that higher ability groups tended to obtain significantly faster mean reaction times and to show significantly less intraindividual variability than lower ability groups. Groups which differed the most in mental ability differed to the greatest extent on the more complex reaction time tests but this pattern was reversed for groups which were relatively close in mean IQ. Generally, the results support the hypothesis that speed- of-processing is an important factor unferlying intelligence, but a number of puzzling findings indicate the need for continued research in this area.     

Personality and biological markers of creativity

The aim of the present study was to test (i) Eysenck's theory that psychoticism (P) should be related to creativity, (ii) whether testosterone (T), due to its association with P claimed in the literature, can be identified as a biological marker of creativity, and (iii) whether the SEEK dimension of the Affective Neuroscience Personality Scales (ANPS) was also related to creativity and to testosterone due to its relationship to Sensation Seeking. In a sample of N = 48 male and female subjects, test scores on figural, verbal, and numeric creativity were compared between high and low P‐scorers as well as between high and low SEEK‐scorers. Effects were controlled for fluid intelligence as measured by Cattell's CFT‐3 and crystallized intelligence as assessed by the Structure‐of‐Intelligence‐Test (Intelligenz‐Struktur‐Test, I‐S‐T 2000 R). Neither a main effect of P or T nor an interaction effect P×T on creativity could be obtained. Instead, SEEK was related to all components of creativity and explained more than 15% of the variance of total creativity. Moreover, significant differences in SEEK could be explained by differences in T, independently of gender. Furthermore, 39% of the variance of SEEK could be explained by the two uncorrelated indicators testosterone and creativity. Copyright © 2004 John Wiley & Sons, Ltd.     

Creative thinking and juvenile delinquency: a study of delinquent and nondelinquent youth on the Torrance Tests of Creative Thinking.

Using the T.T.C.T. this study examined the creative thinking of 32 delinquent and 32 nondelinquent adolescent males. The delinquent group was composed of juveniles on parole status. The nondelinquent group was composed of public school students. On the variables of IQ, age, and socioeconomic class, t-test results indicated no significant differences, except on socioeconomic class, between the groups. Analysis of variance procedures were performed to determine the possibility of an interaction between levels of intelligence and delinquent status with regard to verbal and figural creativity test scores. There were no significant main effects or interaction between IQ and adjudication status with respect to figural creativity. There was a significant main effect due to adjudication status for the dependent variable of verbal creativity scores, respectively while blocking on the intelligence variable. The results were parallel to the ANOVAS which did not specifically control for the intelligence variable between the two groups.     

Processing speed, intelligence, creativity, and school performance: Testing of causal hypotheses using structural equation models

According to mental speed theory of intelligence, the speed of information processing constitutes an important basis for cognitive abilities. However, the question, how mental speed relates to real world criteria, like school, academic, or job performance, is still unanswered. The aim of the study is to test an indirect speed-factor model in comparison to rivaling models explaining the relationships between different mental abilities and performance. In this speed-factor model, basic cognitive processing is assumed to influence higher mental abilities (IQ and creativity). Intelligence and creativity themselves should be valid predictors of school performance. We computed bivariate correlations and structural equation models to test this hypothesis, using indicators of processing speed [Zahlen-Verbindungs-Test (ZVT) and Coding Test], psychometric intelligence [Kognitiver Fähigkeits-Test (KFT) and Raven's Advanced Progressive Matrices (APM)], creativity [Verbaler Kreativitäts-Test (VKT) and Verwendungs-Test (VWT)] and school performance (grades). In a sample of 271 students from German gymnasiums (Class Levels 9 to 11) the speed-factor model can reproduce at best the empirical relationships between processing speed, intelligence, creativity, and school performance: It assumes that processing speed influences higher mental abilities (intelligence and creativity), which, in the sequel, influence school performance. Therefore, processing speed seems to have no direct effect on school performance; the effect is indirect as it operates via mediation through higher cognitive abilities.     

Mitochondrial DNA marker EST00083 is not associated with high vs. average IQ in a German sample

In a recent report in this journal (Plomin & Petrill, 1997), a mitochondrial DNA marker (EST00083) yielded significant associations with high vs. low IQ in two population-based samples of children in the U.S. The present study tested this allelic association for German adults with high vs. average IQ scores. The high IQ adults (N=47) were members of Mensa, an organization whose membership criterion is an IQ score above 130. Their EST00083 allelic frequencies were compared to the allelic frequencies for a control group of adults (N=77) whose IQ scores were less than 110 as estimated from short-term memory and speed-of information-processing tests. Although the differences between the two studies are considerable, the present results do not provide support for the hypothesis that EST00083 is associated with high IQ.     

Provitamin A Selection by Vitamin A Depleted Rats

G. T. scores on the Army General Classification Test (AGCT) as indicants of intelligence were correlated with scores on the Creative Imagination Test (CIT) for two groups of men differing on intelligence. Results supported the prediction of closer correspondence of intelligence and creativity scores in a low intelligence range (r = .437, p < .01) than in a high intelligence range. Intelligence was unrelated statistically to creativity (r = .10) when only the high intelligence range above 111 was considered. Guilford's triagular scatterplot conceptualization of intelligence-creativity relationship seemed most congruent with the present and earlier data. Intelligence was described as allowing the development of creativity, but not insuring such development. Personality and environmental factors may be important in creativity expression especially at upper intelligence ranges.     

Dynamic spatial performance and general intelligence

A computerized video-game-like dynamic spatial ability measure and a paper-and-pencil group test of intelligence were administered to 94 university students. The purpose of the study was threefold: (a) to evaluate the reliability of the dynamic spatial measure; (b) to investigate the extent to which the dynamic spatial measure is saturated with variance associated with traditional measures of fluid and crystallized intellectual ability; and (c) to explore the possibility that dynamic computer based performance measures define factors that are distinct from those associated with traditional paper-and-pencil measures. The number of times the participant hit a moving target served as the dependent variable for the dynamic spatial measure. Number of hits proved to be correlated with Performance IQ, but was not significantly correlated with Verbal IQ. Maximum likelihood factor analysis revealed that the dynamic spatial measure did not load substantially on a factor of general intellectual ability but provided additional evidence that it is related to a performance component.     

Intelligence, reaction times, and peripheral nerve conduction velocity

Two studies (with sample sizes of 85 and 88) are reported that investigated relationships among measures of intelligence, speed of information processing, and peripheral nerve conduction velocity (NCV). In both studies, NCV was significantly correlated with IQ scores (rs = .42 and .48) and with reaction times (RTs; rs = −.28 and −.18): Thus, faster NCV was associated with higher IQ scores and faster speed of processing. In both studies, NCV and RTs contributed significantly, in combination, to the prediction of fullscale IQ (shrunken multiple Rs = .53 and .57), but the expected pattern of causal relationships between the variables was not borne out. The results are interpreted in terms of a “neural efficiency” model of intelligence, which has recieved support from other studies of physiological correlates of human intelligence.