Estimating One’s Own and One’s Relatives’ Multiple Intelligence: A Study from Argentina

Participantes de Argentina (N = 217) estimaron su propia inteligencia global y múltiple, así como las de su pareja, sus padres y sus abuelos. Los datos argentinos mostraron que los varones proporcionaron estimaciones globales más altas que las mujeres (M = 110.4 vs. 105.1) además de estimaciones más altas en inteligencia numérica y espacial. Los participantes se percibían algo menos inteligentes que sus padres (2 puntos del CI) pero más inteligentes que sus madres (6 puntos), sus abuelos (8 puntos), y, en especial, sus abuelas (11 puntos). Las regresiones mostraron que los participantes creían que el CI verbal y numérico eran los mejores predictores del CI global. En general, los resultadosran similares a otros estudios del área. También se compararon los datos británicos con el mismo cuestionario. Los participantes británicos tendían a adjudicarse estimaciones significativamente más altas que a sus parientes, aunque, en general, el patrón era similar. Se comentan los resultados en términos de estudios en el mismo área.Participants from Argentina (N = 217) estimated their own, their partner’s, their parents’ and their grandparents’ overall and multiple intelligences. The Argentinean data showed that men gave higher overall estimates than women (M = 110.4 vs. 105.1) as well as higher estimates on mathematical and spatial intelligence. Participants thought themselves slightly less bright than their fathers (2 IQ points) but brighter than their mothers (6 points), their grandfathers (8 points), but especially their grandmothers (11 points). Regressions showed that participants thought verbal and mathematical IQ to be the best predictors of overall IQ. Results were broadly in agreement with other studies in the area. A comparison was also made with British data using the same questionnaire. British participants tended to give significantly higher self-estimates than for relatives, though the pattern was generally similar. Results are discussed in terms of the studies in the field

Personality and intellectual competence: a psychometric examination of the relation between the big 5, academic performance and intelligence

This thesis concerns the relationship between personality traits and intellectual competence. It contains five chapters and ten independent but related empirical studies. Chapter one presents a review of the salient literature in the area. It is divided into three sub-sections: personality and psychometric intelligence, personality and academic performance (AP), and personality and subjectively-assessed intelligence (SAI). Chapter two (studies 1 to 4) examines the relationship between the Big Five personality traits with several psychometric intelligence tests, SAL and gender. Results indicated that personality traits (notably Neuroticism and Agreeableness) are significantly related to SAI, but not to psychometric intelligence. Since SAI is also significantly related to psychometric intelligence, it is suggested that SAI may mediate the relationship between personality and psychometric intelligence. Chapter three (studies5 to 8) examines the relationship between psychometric intelligence and personality (the Big Five and the Gigantic Three) with AP. Results indicate that personality traits (notably Conscientiousness and Psychoticism) are significant predictors of AP, accounting for unique variance in AP even when psychometric intelligence and academic behaviour are considered as predictors. Chapter four (studies 9& 10) looks at the relationship between personality and psychometric intelligence with a measure of art judgement as well as several indicators of previous art experience. Results indicate that art judgement is related to both personality and intelligence, and may therefore be considered a mixed construct. Chapter five presents a brief summary of the results and conclusions

New Talent Signals: Shiny New Objects or a Brave New World?

Almost 20 years after McKinsey introduced the idea of a war for talent, technology is disrupting the talent identification industry. From smartphone profiling apps to workplace big data, the digital revolution has produced a wide range of new tools for making quick and cheap inferences about human potential and predicting future work performance. However, academic industrial–organizational (I-O) psychologists appear to be mostly spectators. Indeed, there is little scientific research on innovative assessment methods, leaving human resources (HR) practitioners with no credible evidence to evaluate the utility of such tools. To this end, this article provides an overview of new talent identification tools, using traditional workplace assessment methods as the organizing framework for classifying and evaluating new tools, which are largely technologically enhanced versions of traditional methods. We highlight some opportunities and challenges for I-O psychology practitioners interested in exploring and improving these innovations

The relationship between the entrepreneurial personality and the Big Five personality traits

Although meta-analyses show that the Big Five personality traits predict business intention, creation, and success (Brandstätter, 2011), they also indicate that narrow personality traits, such as innovativeness, predict these outcomes better than broad traits, such as Conscientiousness and Extraversion (Rauch & Frese, 2007). The current study extends previous research to examine the relationship between the Big Five and a wider range of entrepreneurial outcomes (e.g. founding charitable organisations, organising events, and changing organisational practices). Additionally, it establishes the incremental validity of a narrow measure of entrepreneurial personality over the Big Five (META, Ahmetoglu, & Chamorro-Premuzic, 2010). Both the Big Five and META significantly predict various forms of entrepreneurial success, though META does so more consistently. This suggests that narrow personality traits have incremental validity in predicting entrepreneurial success vis-à-vis the Big Five. Theoretical and applied implications are discussed

Stronger Together: Personality, Intelligence and the Assessment of Career Potential

Personality and intelligence have a long history in applied psychology, with research dating back more than 100 years. In line, early developments in industrial-organizational psychology were largely founded on the predictive power of personality and intelligence measures vis-à-vis career-related outcomes. However, despite a wealth of evidence in support of their utility, the concepts, theories, and measures of personality and intelligence are still widely underutilized in organizations, even when these express a commitment to making data-driven decisions about employees and leaders. This paper discusses the value of personality and intelligence to understand individual differences in career potential, and how to increase the adoption of theories and tools for evaluating personality and intelligence in real-world organizational contexts. Although personality and intelligence are distinct constructs, the assessment of career potential is incomplete without both

When and why entrepreneurial employees want to quit their job: Exploring two conflicting mechanisms

Past turnover research has posited personality traits as important antecedents to quit intentions. Nevertheless, previous literature has not investigated the relationship between employees’ entrepreneurial tendencies—a constellation of domain specific traits—and turnover. Drawing on dispositional trait theory and attraction‐selection‐attrition theory, we propose engagement and intentions to start a business as mediators of the relationship between entrepreneurial tendencies and quit intentions. We test our predictions in a sample of full‐time employees from the United Kingdom (N = 224). In line with our hypotheses, an inconsistent mediation is found, where both positive and negative links between entrepreneurial tendencies and turnover intentions were mediated by engagement and intentions to start a business respectively. Thus, entrepreneurial employees were more likely to be engaged, but at the same time also more likely to be considering starting their own business, leading to a conflicting relationship to turnover intentions. The current study informs the human resource management literature concerning the motivational mechanisms explaining turnover intentions among entrepreneurial employees. It also provides practical insights with regards to the effective management of this workforce

Therapist characteristics and their effect on training outcomes: what counts?

Background: Evidence exists for a relationship between individual characteristics and both job and training performance; however relationships may not be generalizable. Little is known about the impact of therapist characteristics on performance in postgraduate therapist training programmes. Aims: The aim of this study was to investigate associations between the grades of trainee Low-Intensity and High-Intensity cognitive behavioural therapists and individual characteristics. Method: Trainee Low-Intensity (n=81) and High-Intensity (n=59) therapists completed measures of personality and cognitive ability; demographic and course grade data for participants were collected. Results: Degree classification emerged as the only variable to be significantly associated with performance across assessments and courses. Higher undergraduate degree classifications were associated with superior academic and clinical performance. Agreeableness was the only dimension of personality to be associated (positively) with clinical skill. Age was weakly and negatively associated with performance. Conclusions: Relationships between individual characteristics and training outcomes are complex and may be context specific. These results could have important implications for the selection and development of therapists for Low or High-Intensity cognitive behavioural therapy (CBT) training

Learning approaches: Associations with Typical Intellectual Engagement, intelligence and the Big Five

Learning approaches, i.e. students’ learning strategies and motives, predict academic performance but it is not clear how much variance they share with intelligence and personality. Here, the relationship of the Big Five personality traits, intelligence, and Typical Intellectual Engagement (TIE) with deep, achieving and surface learning was explored in a sample of 579 British undergraduate students. A structural equation model showed that (a) intelligence was negligibly associated with learning approaches; (b) TIE was strongly related to all three types of learning approaches; (c) deep learning shared the greatest amount of variance with TIE, while (d) achieving learning was best explained by Extraversion, Openness to Experience, and Conscientiousness. Only 25% of the variance in surface learning was accounted for by intelligence and personality. Thus, personality traits and learning approaches share much variance but not enough to dismiss either construct as redundant