Noncompliant responding:Comparing exclusion criteria in MTurk personality research to improve data quality

Studies on Amazon Mechanical Turk (MTurk) often include check questions in personality inventories to ensure data quality. However, a subset of MTurk workers may give only meaningful responses to these checks while giving noncompliant responses to the other questions. We demonstrate in an analysis of five MTurk datasets using the statistical approach of Lee and Ashton (2018) that this selectively responsive subset can be detected on the HEXACO personality inventory. Our lower bound estimate is that at least 2% in each sample did not get caught with the check questions while giving noncompliant responses on the personality inventory. Overall, researchers who strive to remove noise due to noncompliant responding may benefit from complementing check questions with a statistical approach

The Main Dimensions of Sport Personality Traits: A Lexical Approach

To uncover the main dimensions of sport personality traits, a lexical study was conducted. In the first two phases, 321 adjectives denoting the way somebody practices sports were selected. In the third phase, 555 respondents self-rated the adjectives. Congruence analyses provided evidence of six factors, five of which are sport personality trait factors (friendly fairness, resilience, drive, perfectionism, and inventiveness) plus one physical individual difference factor (agility). Marker scales from the sport personality trait factors show convergent correlations with the generic HEXACO personality obtained years earlier. Furthermore, meaningful relations with the six most frequently practiced sport and leisure activities were observed. Contextualized sport personality trait factors can be useful in research on sport preferences, sport behaviors, and sport outcomes

Development and validation of a HEXACO situational judgment test

The purpose of this study was to develop and validate a construct-based situational judgment test of the HEXACO personality dimensions. In four studies, among applicants, employees, and Amazon Mechanical Turk participants (Ns = 72–305), we showed that it is possible to assess the six personality dimensions with a situational judgment test and that the criterion-related validity of the situational judgment test is comparable to the criterion-related validity of traditional self-reports but lower than the criterion-related validity of other-reports of personality. Test–retest coefficients (with a time interval of 2 weeks) varied between.55 and.74. Considering personality is the most commonly assessed construct in employee selection contexts (Ryan et al., 2015), this situational judgment test may provide human resources professionals with an alternative assessment tool

How do people think about interdependence? A multidimensional model of subjective outcome interdependence

Interdependence is a fundamental characteristic of social interactions. Interdependence Theory states that 6 dimensions describe differences between social situations. Here we examine if these 6 dimensions describe how people think about their interdependence with others in a situation. We find that people (in situ and ex situ) can reliably differentiate situations according to 5, but not 6, dimensions of interdependence: (a) mutual dependence, (b) power, (c) conflict, (d) future interdependence, and (e) information certainty. This model offers a unique framework for understanding how people think about social situations compared to another recent model of situation construal (DIAMONDS). Furthermore, we examine factors that are theorized to shape perceptions of interdependence, such as situational cues (e.g., nonverbal behavior) and personality (e.g., HEXACO and Social Value Orientation). We also study the implications of subjective interdependence for emotions and cooperative behavior during social interactions. This model of subjective interdependence explains substantial variation in the emotions people experience in situations (i.e., happiness, sadness, anger, and disgust), and explains 24% of the variance in cooperation, above and beyond the DIAMONDS model. Throughout these studies, we develop and validate a multidimensional measure of subjective outcome interdependence that can be used in diverse situations and relationships-the Situational Interdependence Scale (SIS). We discuss how this model of interdependence can be used to better understand how people think about social situations encountered in close relationships, organizations, and society

Broad versus narrow traits: Conscientiousness and Honesty-Humility as predictors of academic criteria

Recent research has suggested that the six-dimensional personality model, and especially the dimension Honesty-Humility/Integrity, adds incremental validity to the prediction of important criteria. We expected both this dimension and the dimension Conscientiousness to explain incremental variance in two academic criteria, namely grade point average (GPA) and counterproductive academic behaviour (CAB). In addition, we expected the more specific, so-called narrow traits of Conscientiousness and Honesty-Humility/Integrity to be stronger predictors of academic criteria than the broad traits. To test these expectations, two studies were conducted using the HEXACO Personality Inventory Revised (HEXACO-PI-R) and the Multicultural Personality Test-Big Six (MPT-BS). The results confirmed our expectations and suggest that academic criteria may be predicted with greater accuracy by focusing on the narrow traits of Conscientiousness and Honesty-Humility/Integrity. © 2010 John Wiley & Sons, Ltd

Applicant reactions to algorithm- versus recruiter-based evaluations of an asynchronous video interview and a personality inventory

In two studies, we examined the effects of algorithm based (vs. recruiter-based) evaluations of an asynchronous video interview and a personality inventory on applicant reactions. In line with our expectations, we found several negative applicant reactions to the use of algorithms. Specifically, in Study 1 (N = 172), informing participants that an algorithm, rather than a recruiter, had analysed their interview and personality inventory increased feelings of emotional creepiness, and reduced fairness perceptions, perceived predictive validity and feedback acceptance. In Study 2 (N = 276), we were able to replicate these effects for fairness perceptions and perceived predictive validity. Furthermore, in both studies, algorithm based evaluations negatively affected feedback acceptance, organizational attraction and job acceptance intentions through fairness perceptions. However, in contrast with our expectations, selection decision favour ability did not influence the impact of evaluation source (recruiter vs. algorithm) on applicant reactions. In Study 2, we also found some tentative evidence that applicant reactions to algorithm based evaluations are not affected by the type of information source (i.e. verbal vs. nonverbal cues) on which the algorithm is based

Exploring the application of a text-to-personality technique in job interviews

This research’s purpose was to develop a valid and transparent text-to-personality technique to fit the requirements for personnel selection assessments. In this research we developed an advanced word-counting technique, the HEXACO text-to-personality (HTTP) technique, based on prior lexical personality research to assess personality from job interviews. To evaluate the technique’s construct and criterion-related validity we conducted three studies and analysed the transcripts of asynchronous (n = 102 and 72) and face-to-face (n = 155) interviews. These studies provided four key insights. First, the HTTP technique showed small to medium correlations with self-reported and interviewer-rated personality. Second, the technique showed mixed, but generally favourable, evidence for criterion-related validity. Third, the technique produced a more construct valid personality score when the interview questions activated the predicted personality trait. Fourth, the technique’s additional features (i.e., having weighted keywords and adjusting the keywords’ weight for adjacent quantifiers) did not improve its validity; unit-weighing was approximately equally effective. Altogether, the results show that a word-count text-analysis technique can discover traces of personality in interview transcripts. Still, significant improvements are needed before these types of automatically computed text-to-personality ratings can be used to replace or supplement interviewer ratings

What are we measuring? Convergence of leadership with interpersonal and non-interpersonal personality.

Since leadership styles have been most commonly defined in terms of interpersonal influence, one would assume that they have their main projections on the interpersonal circumplex. In this study, the relations between leadership styles from the Multifactor Leadership Questionnaire and Leader Behaviour Description Questionnaire and both interpersonal and HEXACO personality scales are investigated. As expected, charismatic leadership and leader's consideration have strong projections on the interpersonal circumplex, with main projections on the warm-agreeable octant. Transactional leadership, passive leadership, and task-oriented leadership have considerably weaker or no projections on the circumplex. Leader's consideration is most strongly related to interpersonal personality while both transactional and passive leadership are most strongly related to non-interpersonal personality. It is concluded that especially charismatic leadership and leader's consideration are captured almost fully by the HEXACO personality inventory. Copyright © 2008 SAGE Publications

Higher-order factors of personality: Do they exist?

Scales that measure the Big Five personality factors are often substantially intercorrelated. These correlations are sometimes interpreted as implying the existence of two higher order factors of personality. The authors show that correlations between measures of broad personality factors do not necessarily imply the existence of higher order factors and might instead be due to variables that represent same-signed blends of orthogonal factors. Therefore, the hypotheses of higher order factors and blended variables can only be tested with data on lower level personality variables that define the personality factors. The authors compared the higher order factor model and the blended variable model in three participant samples using the Big Five Aspect Scales, and found better fit for the latter model. In other analyses using the HEXACO Personality Inventory, they identified mutually uncorrelated markers of six personality factors. The authors conclude that correlations between personality factor scales can be explained without postulating any higher order dimensions of personality. © 2009 by the Society for Personality and Social Psychology, Inc