Emotional intelligence and job-demands resources model

Occupational stress research has consistently demonstrated negative effects for employees. Research also describes potential moderators of this relationship. While research has revealed some positive effects of emotional intelligence (EI) on employee adjustment, it has neglected investigation of their potential stress buffering effects. Based on the Job-Demand Resources model, it was predicted that higher trait emotional intelligence would act as a buffer to the potential negative effects of stressors on employee adjustment. Hierarchical multiple regression analyses with a sample of 306 nurses found no main effects of EI but revealed eight moderating effects. While some interactions support the buffering hypothesis, others revealed buffering for those with low EI. Findings are discussed in terms of theoretical and practical implications.

Can different measures of intelligence be used interchangeably? A comparison of the Wechsler and Stanford-Binet scales

The Wechsler and Stanford Binet scales are among the most commonly used tests of intelligence. In clinical practice, they often seem to be used interchangeably. This paper reports the results of two studies that compared the most recent editions of two Wechsler scales (WPPSI-III and WISC-IV) with the Stanford-Binet Fifth Edition (SB5). The participants in the first study were 36 typically developing 4-year-old children who completed the WPPSI-III and SB5 in counter-balanced order. Although correlations of composite scores ranged from r = .59 to r = .82 and were similar to those reported for earlier versions of the two instruments, more than half the sample had a score discrepancy greater than 10 points across the two instruments. In the second study, the WISC-IV and SB5 were administered to 30 children aged 12-14 years. There was a significant difference between Full Scale IQs on the two measures, with scores being higher on the WISC-IV. Differences between the two verbal scales were also significant and favoured the WISC-IV. There were moderate correlations of Full Scale IQs (r = .58) and Nonverbal IQs (r = .54) but the relationship between the two Verbal scales was not significant. For some children, notable score differences led to different categorisations of their level of intellectual ability The findings suggest that the Wechsler and Stanford Binet scales cannot be presumed to be interchangeable. The discussion focuses on how psychologists might reconcile large differences in test scores and the need for caution when interpreting and comparing test results.

Is member-rated project success influenced by leadership team emotional intelligence?

Large complex projects often fail spectacularly in terms of cost overruns and delays; witness the London Olympics and the Airbus A380. In this project, we studied the emotional intelligence (EI) of leadership teams involved in such projects. We collected our data from 370 employees in 40 project teams working on large Australian defense contracts. We asked leadership team members to complete a scale measuring their EI, and project team members to rate the success of the projects. We found it was not the mean score, but the highest EI score in the leadership team that predicted members’ project success ratings.

Gamifying collective intelligence for the common good

The rise of the mobile internet enables the creation of applications that provide new and easier ways for people to organise themselves, raise issues, take action and interact with their city. At the same time, society faces new problems that can only be solved when citizens work together. Nevertheless, a lack of motivation or knowledge often prevents many citizens from regularly contributing to the common good. In this position paper, we present DoGood – a mobile app – as a socio-technological system that aims at supporting the collective intelligence of citizens in their pursuit of civic engagement and civic collaboratories. Our study asks to what extent gamification can motivate users to “do good” deeds. The DoGood app uses gamified elements to encourage citizens to submit and promote their civic activities as well as to join the activities of others. Gamification is sometimes criticised for simply adding a limited number of game elements, such as leaderboards, on top of an existing experience with the hope of increasing motivation. However, in the case of the DoGood app, the process of game design was an integral part of the development, and the gamified elements target the user’s intrinsic motivations instead of providing them with an external reward. In this paper, we present design elements of the app and discuss their potential to support collective intelligence for the common good.

Brain fiber architecture, genetics, and intelligence: a high angular resolution diffusion imaging (HARDI) study

We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling the spherical fiber orientation distribution functions (ODFs) in appropriate Riemannian manifolds, after ODF regularization and sharpening. Fitting structural equation models (SEM) from quantitative genetics, we evaluated genetic influences on the Jensen-Shannon divergence (JSD), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (GFA) a measure of fiber integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (IQ). Fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.

Schizophrenia Genetic Variants are not Associated with Intelligence

Background Schizophrenia is associated with lower pre-morbid intelligence (IQ) in addition to (pre-morbid) cognitive decline. Both schizophrenia and IQ are highly heritable traits. Therefore, we hypothesized that genetic variants associated with schizophrenia, including copy number variants (CNVs) and a polygenic schizophrenia (risk) score (PSS), may influence intelligence. Method IQ was estimated with the Wechsler Adult Intelligence Scale (WAIS). CNVs were determined from single nucleotide polymorphism (SNP) data using the QuantiSNP and PennCNV algorithms. For the PSS, odds ratios for genome-wide SNP data were calculated in a sample collected by the Psychiatric Genome-Wide Association Study (GWAS) Consortium (8690 schizophrenia patients and 11 831 controls). These were used to calculate individual PSSs in our independent sample of 350 schizophrenia patients and 322 healthy controls. Results Although significantly more genes were disrupted by deletions in schizophrenia patients compared to controls (p = 0.009), there was no effect of CNV measures on IQ. The PSS was associated with disease status (R 2 = 0.055, p = 2.1 × 10 -7) and with IQ in the entire sample (R 2 = 0.018, p = 0.0008) but the effect on IQ disappeared after correction for disease status. Conclusions Our data suggest that rare and common schizophrenia-associated variants do not explain the variation in IQ in healthy subjects or in schizophrenia patients. Thus, reductions in IQ in schizophrenia patients may be secondary to other processes related to schizophrenia risk. © Cambridge University Press 2013.

Collision avoidance between UAV clusters using swarm intelligence techniques

In this article, several basic swarming laws for Unmanned Aerial Vehicles (UAVs) are developed for both two-dimensional (2D) plane and three-dimensional (3D) space. Effects of these basic laws on the group behaviour of swarms of UAVs are studied. It is shown that when cohesion rule is applied an equilibrium condition is reached in which all the UAVs settle at the same altitude on a circle of constant radius. It is also proved analytically that this equilibrium condition is stable for all values of velocity and acceleration. A decentralised autonomous decision-making approach that achieves collision avoidance without any central authority is also proposed in this article. Algorithms are developed with the help of these swarming laws for two types of collision avoidance, Group-wise and Individual, in 2D plane and 3D space. Effect of various parameters are studied on both types of collision avoidance schemes through extensive simulations.

Swarm intelligence-based solver for parameter estimation of laboratory through-diffusion transport of contaminants

Theoretical approaches are of fundamental importance to predict the potential impact of waste disposal facilities on ground water contamination. Appropriate design parameters are generally estimated be fitting theoretical models to data gathered from field monitoring or laboratory experiments. Transient through-diffusion tests are generally conducted in the laboratory to estimate the mass transport parameters of the proposed barrier material. Thes parameters are usually estimated either by approximate eye-fitting calibration or by combining the solution of the direct problem with any available gradient-based techniques. In this work, an automated, gradient-free solver is developed to estimate the mass transport parameters of a transient through-diffusion model. The proposed inverse model uses a particle swarm optimization (PSO) algorithm that is based on the social behavior of animals searching for food sources. The finite difference numerical solution of the forward model is integrated with the PSO algorithm to solve the inverse problem of parameter estimation. The working principle of the new solver is demonstrated and mass transport parameters are estimated from laboratory through-diffusion experimental data. An inverse model based on the standard gradient-based technique is formulated to compare with the proposed solver. A detailed comparative study is carried out between conventional methods and the proposed solver. The present automated technique is found to be very efficient and robust. The mass transport parameters are obtained with great precision.

Emotional intelligence development in student radiation therapists: A longitudinal pilot study

Emotional intelligence (EI) is defined as “the ability to recognise, understand and manage emotions in ourselves and others” [1]. Initially identified as a concept applied to leadership and management, EI is now recognised as an important skill in a number of areas, including healthcare [2]. Empathy (the ability to see the world through someone else’s eyes) is known to play an important role in the therapeutic relationship with patients [3]. As EI has been shown to improve empathy [4], it is clear that developing the EI of student health professionals should benefit patients in the long term. It is not surprising, then, that a number of studies have investigated the role of EI in medical, dental and nursing students, however there is little reported evidence relating to EI development in pre-registration radiation therapy (RT) students.

Emotional intelligence development in radiation therapy students: A longitudinal study

Purpose: Emotional intelligence (EI) is an increasingly important aspect of a health professional’s skill set. It is strongly associated with empathy, reflection and resilience; all key aspects of radiotherapy practice. Previous work in other disciplines has formed contradictory conclusions concerning development of EI over time. This study aimed to determine the extent to which EI can develop during a radiotherapy undergraduate course and identify factors affecting this. Methods and materials: This study used anonymous coded Likert-style surveys to gather longitudinal data from radiotherapy students relating to a range of self-perceived EI traits during their 3-year degree. Data were gathered at various points throughout the course from the whole cohort. Results: A total of 26 students provided data with 14 completing the full series of datasets. There was a 17·2% increase in self-reported EI score with a p-value<0·0001. Social awareness and relationship skills exhibited the greatest increase in scores compared with self-awareness. Variance of scores decreased over time; there was a reduced change in EI for mature students who tended to have higher initial scores. EI increase was most evident immediately after clinical placements. Conclusions: Radiotherapy students increase their EI scores during a 3-year course. Students reported higher levels of EI immediately after their clinical placement; radiotherapy curricula should seek to maximise on these learning opportunities.

Emotional intelligence development in student radiation therapists: A longitudinal pilot study

Emotional intelligence (EI) is defined as “the ability to recognise, understand and manage emotions in ourselves and others”. Initially identified as a concept applied to leadership and management, EI is now recognised as an important skill in a number of areas, including healthcare [2]. Empathy (the ability to see the world through someone else’s eyes) is known to play an important role in the therapeutic relationship with patients [3]. As EI has been shown to improve empathy [4], it is clear that developing the EI of student health professionals should benefit patients in the long term. It is not surprising, then, that a number of studies have investigated the role of EI in medical, dental and nursing students, however there is little reported evidence relating to EI development in pre-registration radiation therapy (RT) students.

Effects of self-reported wisdom on happiness: Not much more than emotional intelligence?

Wisdom and emotional intelligence are increasingly popular topics among happiness scholars. Despite their conceptual overlap, no empirical research has examined their interrelations and incremental predictive validities. The aims of this study were (a) to investigate associations between multidimensional conceptualizations of self-reported wisdom (Ardelt in Res Aging 25(3):275-324, 2003, 2004) and emotional intelligence (Davies et al. in J Pers Soc Psychol 75:989-1015, 1998) and (b) to examine the joint effects of self-reported wisdom and emotional intelligence on dimensions of happiness (life satisfaction as well as positive and negative affect). Data were provided by two samples: 175 university students and 400 online workers. Correlations between a composite wisdom score, a composite emotional intelligence score, and happiness facets were positive and moderate in size. Regression analyses showed that the effects of composite wisdom on life satisfaction and positive affect (but not negative affect) became weaker and non-significant when composite emotional intelligence was controlled. Additional analyses including three dimensions of the self-reported wisdom (cognitive, reflective, and affective wisdom) and four dimensions of emotional intelligence (self- and others-emotions appraisal, use and regulation of emotion) revealed a more differentiated pattern of results. Implications for future research on wisdom and happiness are discussed.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Cues in the environment: A design principle for ambient intelligence

The aim of this paper is to propose design principles for ambient intelligence (AmI) environments. The question we are investigating is how these environments can be designed to support a group to be able to carry out common goal-oriented activities. The approach we are taking in answering this question is informed by the concept of collective intelligence (CI). We are applying the concept of CI to AmI as we have found it works well in biological and social systems. Examples from nature demonstrate the power of CI stimulated by implicit cues in the environment. We use these examples to derive design principles for AmI environments. By applying these design principles to a concrete scenario, we are able to propose ways to help decrease environmental pollution within urban areas.