Predicting army cadets’ performance: The role of character strengths, GPA and GMA

The purpose of this study was to examine how well a set of 12 character strengths (Leadership, Integrity, Open-Mindedness, Bravery, Teamwork, Persistence, Social Intelligence, Love of Learning, Fairness, Self-Regulation, Perspective and Creativity) will predict academic performance (AP) and military performance (MP), compared to high school grade point average (GPA) and general mental ability (GMA). The study sample comprised 123 army cadets of two cohorts from the three-year bachelor's degree programme at the Norwegian Military Academy (NMA). GPA predicted AP (r = 0.32, p ≤ 0.05), but not MP (r = 0.14, n.s.), while GMA correlated significantly with neither AP nor MP. All 12 character strengths correlated significantly with MP (rs ranging from 0.27 to 0.65), and all except for Fairness correlated significantly with AP (rs ranging from 0.18 to 0.58). An average score of the 12 character strengths showed incremental validity beyond GMA and GPA in predicting both AP and MP. Our results suggest that character strengths should be considered when selecting and training army cadets.

General Intelligence: An Analysis of the Saudi Students’ General Mental Ability and Elementary Cognitive Task Performance

Previous studies on human intelligence has revealed that varied factors influence cognitive performance, and some studies have hypothesized the presence of “general intelligence” (g factor) that is responsible for intelligence. However, most studies have been centered on Western cultures. This study thus examines the Saudi students and the g factor hypothesis. A group of Saudi college students participated in a battery of general mental ability tests and elementary cognitive tasks and were assessed for the influence of various factors on cognitive performance. The study results revealed an increase in the average of Saudi students’ intelligence compared to the results of the previous studies, but it did not yield a g factor.

Brain Functional Correlates of Intelligence Score in ADHD Based on EEG

It has been shown that intelligence as a general mental ability is related to structure and function of the brain regions. However, specificity of this regional dependencies to the intelligence scores in the typical and atypical developed individuals needs to be well understood. In this study, we hypothesized that neural correlates of IQ should not have a fixed pattern rather it must follow a dynamic pattern to compensate the functional deficits caused by a neurodevelopmental disorder. Therefore, EEG correlates of normal IQ in various subtypes of attention deficit hyperactive disorder (ADHD) were compared to a group of healthy controls. Sixty-three ADHD subjects comprising of combined, inattentive, and hyperactive individuals diagnosed by a psychiatrist using structural clinical interview for DSM-V, and 46 healthy controls with similar normal IQ scores were recruited in this study. The subjects’ EEG data were then recorded during an eye-closed resting condition. The subjects’ intelligence level was measured by the Raven’s standard progressive matrices. Then, association between IQ and power of EEG signal were computed in the conventional frequency bands. Subsequently, topographical representations of these associations were compared between the groups. Our results demonstrated that association between IQ score and EEG power is not the same in various ADHD subtypes, and healthy controls. This finding suggests a compensatory mechanism in ADHD individuals for changing the regional oscillatory pattern to maintain the IQ within a normal range.

g versus c: comparing individual and collective intelligence across two meta-analyses

Collective intelligence (CI) is said to manifest in a group’s domain general mental ability. It can be measured across a battery of group IQ tests and statistically reduced to a latent factor called the “c-factor.” Advocates have found the c-factor predicts group performance better than individual IQ. We test this claim by meta-analyzing correlations between the c-factor and nine group performance criterion tasks generated by eight independent samples (N = 857 groups). Results indicated a moderate correlation, r, of .26 (95% CI .10, .40). All but four studies comprising five independent samples (N = 366 groups) failed to control for the intelligence of individual members using individual IQ scores or their statistically reduced equivalent (i.e., the g-factor). A meta-analysis of this subset of studies found the average IQ of the groups’ members had little to no correlation with group performance (r = .06, 95% CI −.08, .20). Around 80% of studies did not have enough statistical power to reliably detect correlations between the primary predictor variables and the criterion tasks. Though some of our findings are consistent with claims that a general factor of group performance may exist and relate positively to group performance, limitations suggest alternative explanations cannot be dismissed. We caution against prematurely embracing notions of the c-factor unless it can be independently and robustly replicated and demonstrated to be incrementally valid beyond the g-factor in group performance contexts.

Incremental Validity of Character Strengths as Predictors of Job Performance Beyond General Mental Ability and the Big Five

Over the last decades, various predictors have proven relevant for job performance [e.g., general mental ability (GMA), broad personality traits, such as the Big Five]. However, prediction of job performance is far from perfect, and further potentially relevant predictors need to be investigated. Narrower personality traits, such as individuals' character strengths, have emerged as meaningfully related to different aspects of job performance. However, it is still unclear whether character strengths can explain additional variance in job performance over and above already known powerful predictors. Consequently, the present study aimed at (1) examining the incremental validity of character strengths as predictors of job performance beyond GMA and/or the Big Five traits and (2) identifying the most important predictors of job performance out of the 24 character strengths, GMA, and the Big Five. Job performance was operationalized with multidimensional measures of both productive and counterproductive work behavior. A sample of 169 employees from different occupations completed web-based self-assessments on character strengths, GMA, and the Big Five. Additionally, the employees' supervisors provided web-based ratings of their job performance. Results showed that character strengths incrementally predicted job performance beyond GMA, the Big Five, or GMA plus the Big Five; explained variance increased up to 54.8, 43.1, and 38.4%, respectively, depending on the dimension of job performance. Exploratory relative weight analyses revealed that for each of the dimensions of job performance, at least one character strength explained a numerically higher amount of variance than GMA and the Big Five, except for individual task proactivity, where GMA exhibited the numerically highest amount of explained variance. The present study shows that character strengths are relevant predictors of job performance in addition to GMA and other conceptualizations of personality (i.e., the Big Five). This also highlights the role of socio-emotional skills, such as character strengths, for the understanding of performance outcomes above and beyond cognitive ability.

The Good, the Bad, and the Clever: Faking Ability as a Socio-Emotional Ability?

Socio-emotional abilities have been proposed as an extension to models of intelligence, but earlier measurement approaches have either not fulfilled criteria of ability measurement or have covered only predominantly receptive abilities. We argue that faking ability—the ability to adjust responses on questionnaires to present oneself in a desired manner—is a socio-emotional ability that can broaden our understanding of these abilities and intelligence in general. To test this theory, we developed new instruments to measure the ability to fake bad (malingering) and administered them jointly with established tests of faking good ability in a general sample of n = 134. Participants also completed multiple tests of emotion perception along with tests of emotion expression posing, pain expression regulation, and working memory capacity. We found that individual differences in faking ability tests are best explained by a general factor that had a large correlation with receptive socio-emotional abilities and had a zero to medium-sized correlation with different productive socio-emotional abilities. All correlations were still small after controlling these effects for shared variance with general mental ability as indicated by tests of working memory capacity. We conclude that faking ability is indeed correlated meaningfully with other socio-emotional abilities and discuss the implications for intelligence research and applied ability assessment.

Investigating the Structure of Intelligence Using Latent Variable and Psychometric Network Modeling: A Commentary and Reanalysis

In a recent publication in the Journal of Intelligence, Dennis McFarland mischaracterized previous research using latent variable and psychometric network modeling to investigate the structure of intelligence. Misconceptions presented by McFarland are identified and discussed. We reiterate and clarify the goal of our previous research on network models, which is to improve compatibility between psychological theories and statistical models of intelligence. WAIS-IV data provided by McFarland were reanalyzed using latent variable and psychometric network modeling. The results are consistent with our previous study and show that a latent variable model and a network model both provide an adequate fit to the WAIS-IV. We therefore argue that model preference should be determined by theory compatibility. Theories of intelligence that posit a general mental ability (general intelligence) are compatible with latent variable models. More recent approaches, such as mutualism and process overlap theory, reject the notion of general mental ability and are therefore more compatible with network models, which depict the structure of intelligence as an interconnected network of cognitive processes sampled by a battery of tests. We emphasize the importance of compatibility between theories and models in scientific research on intelligence.

Effect of yoga practices on general mental ability in urban residential school children

IntroductionMental ability of children represents functioning of brain in different aspects of competency including verbal, mathematical, logical reasoning and spatial, which is of prime importance for academic performance.ObjectiveThe objective of this study was to assess the effect of yoga on general mental ability of urban residential school children.MethodsSixty-six urban school children aged 11–15 years were selected as participants. All the selected participants were staying in a residential school in Pune District. A stratified random sampling method was used to divide the students into experimental and control groups. There were 32 students in experimental group and 29 students in control group. Both experimental and control groups were assessed for general mental ability by using standard questionnaire at the baseline and at the end of 12 weeks of yoga training. The study participants of experimental group underwent yoga training for 12 weeks, for 1 h in the morning for a period of 12 weeks. The control group did not undergo any yoga training during this time period.ResultsThe experimental group participants showed significant improvement in general mental ability as compared to control group.ConclusionThe findings of this study indicate that yoga practices could improve general mental ability of urban residential school children.