Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

The assessment of pain relies mostly on methods that require a person to communicate. However, for people with cognitive and verbal impairments, existing ...

Ulm University

The meta-analytic finding that faking does not affect the criterion validity of self-report measures in applicant selection suggests cognitive abilities are crucial to fake personality to an expected optimal profile in self-report measures. Previous studies in this field typically focus on how the  of faking changes self-report measurement. However, the effect of faking  is rarely considered. In Study 1 ( = 151), we link two questionnaires, the WSQ and the NEO-PI-R, to use them for later faking ability tasks. With ONET expert ratings and the linked questionnaires, we establish veridical responses of optimal personality profiles for both questionnaires. Based on this, in Study 2, we develop six faking ability task employing both questionnaires and three common jobs to fake for. To score the tasks, we introduce profile similarity metrics that compare faked response vectors to optimal profile vectors. The faking ability tasks were administered to a community sample ( = 210) who additionally completed measures of cognitive abilities, namely general mental ability, crystallized intelligence, and interpersonal abilities. For all, based on previous research, it can be argued that they should predict individual differences in faking ability. We establish a measurement model of faking ability and its relation to the other cognitive abilities. Using structural equations modeling, we find the strongest effect for crystallized intelligence and weaker effects for general mental ability and interpersonal abilities, all positively predicting faking ability. We show for the first time that we can measure faking ability with psychometrically sound techniques, establish a confirmatory factor model of faking ability and that it is largely explained by other cognitive abilities. We conclude that research supporting a positive link between self-reported personality and job performance is presumably confounded by cognitive abilities, because they are predictive of both faking self-reported personality and job performance. We recommend researchers to broaden their measurements with assessments of faking ability or other cognitive abilities (besides general mental ability) in research regarding applicant selection.

The "g" in Faking: Doublethink the Validity of Personality Self-Report Measures for Applicant Selection.

Worries about possible harmful effects of new technologies (modern health worries) have intensely been investigated in the last decade. However, the comparability of translated self-report measures across countries is often problematic. This study aimed to overcome this problem by developing psychometrically sound brief versions of the widely used 25-item Modern Health Worries Scale (MHWS) suitable for multi-country use. Based on data of overall 5,176 individuals from four European countries (England, Germany, Hungary, Sweden), Ant Colony Optimization was used to identify the indicators that optimize model fit and measurement invariance across countries. Two scales were developed. A short (12-item) version of the MHWS that represents the four-factor structure of the original version and an ultra-short (4-item) scale that only measures the general construct. Both scales show that overall levels of health worries were highest in England and Hungary, but that the main reason for concern (e.g. electromagnetic radiation or food related fears) differs considerably between these countries. This study also shows that even if measurement invariance of translated self-report instruments across countries is problematic, it can be optimized by using adequate item selection procedures. Differences of modern health worries across countries and recommendations for cross-cultural research are discussed.

Modern health worries: Deriving two measurement invariant short scales for cross-cultural research with Ant Colony Optimization.

Situational Judgment Tests (SJTs) are criterion valid low fidelity measures that have gained much popularity as predictors of job performance. A broad variety of SJTs have been studied, but SJTs measuring personality are still rare. Personality traits such as Conscientiousness are valid predictors of many educational, work and life-related outcomes and SJTs are less prone to faking than classical self-report measurements. We developed an SJT measure of Dependability, a core facet of Conscientiousness, by gathering critical incidents in semi-structured interviews using the construct definition of Dependability as a prompt. We examined the psychometric properties of the newly developed SJTs across two studies (N = 546 general population; N = 440 sales professionals). The internal validity of the SJTs was examined by correlating the SJT scores with related self-report measures of Dependability and Conscientiousness, as well as testing the unidimensionality of the measure with CFA. Additionally, we specified a bi-factor model of SJT, self-report and behavioral checklist measures of Dependability accounting for common and specific measurement variance. External validity was examined by correlating the SJT scale and specific factor with work-related outcomes. The results show that the Dependability SJTs with an expert based scoring procedure were psychometrically sound and correlated moderately to highly with traditional self-report measures of Dependability and Conscientiousness. However, a large proportion of SJT variance cannot be accounted for by personality alone. This supports the notion that SJTs measure general domain knowledge about the effectiveness of personality-related behaviors. We conclude that SJT measures of personality can be a promising addition to classical self-report assessments and can be used in a wide variety of applications beyond measurement and selection, for instance as formative assessments of personality.

Oliver Wilhelm

Department of Individual Differences and Psychological Assessment

Ulm University

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Oliver Wilhelm

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Individual Differences and Psychological Assessment

Ulm University

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Department of Individual Differences and Psychological Assessment