Psychometric properties of the Polish versions of the HEXACO-60 and the HEXACO-100 personality inventories

Skimina, Ewa; Strus, Włodzimierz; Cieciuch, Jan; Szarota, Piotr; Izdebski, Paweł

doi:10.5114/cipp.2020.98693

Cited by 10 publications

(13 citation statements)

References 62 publications

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“…Table 5 presents t-test results for mean difference between female (N = 5,673) and male (N = 5,760) on predicted trait scores. These findings of gender differences are similar to that reported by others using standard self-rated item inventories (Feingold, 1994;Ashton and Lee, 2009;Wakabayashi, 2014;Lee and Ashton, 2020;Skimina et al, 2020).…”

Section: Resultssupporting

confidence: 90%

“…Table 4 presents the inter-correlations between the personality scores inferred using the InterviewBERT-CLS model on an independent group of N = 11,433 candidates. This demonstrates that there are strong inter-correlations (|r| > 0.20) between some personality traits, and these correlations are consistent with previous findings in literature (Ashton and Lee, 2009;Lee and Ashton, 2018;Moshagen et al, 2019;Skimina et al, 2020). Figure 4 shows an example of four attention heatmaps from InterviewBERT for answers from two candidates with corresponding tokens related to Openness (O) and extraversion (X); tokens with higher attention are in darker color.…”

Section: Resultssupporting

confidence: 88%

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Explainable Personality Prediction Using Answers to Open-Ended Interview Questions

2022

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In this work, we demonstrate how textual content from answers to interview questions related to past behavior and situational judgement can be used to infer personality traits. We analyzed responses from over 58,000 job applicants who completed an online text-based interview that also included a personality questionnaire based on the HEXACO personality model to self-rate their personality. The inference model training utilizes a fine-tuned version of InterviewBERT, a pre-trained Bidirectional Encoder Representations from Transformers (BERT) model extended with a large interview answer corpus of over 3 million answers (over 330 million words). InterviewBERT is able to better contextualize interview responses based on the interview specific knowledge learnt from the answer corpus in addition to the general language knowledge already encoded in the initial pre-trained BERT. Further, the “Attention-based” learning approaches in InterviewBERT enable the development of explainable personality inference models that can address concerns of model explainability, a frequently raised issue when using machine learning models. We obtained an average correlation of r = 0.37 (p < 0.001) across the six HEXACO dimensions between the self-rated and the language-inferred trait scores with the highest correlation of r = 0.45 for Openness and the lowest of r = 0.28 for Agreeableness. We also show that the mean differences in inferred trait scores between male and female groups are similar to that reported by others using standard self-rated item inventories. Our results show the potential of using InterviewBERT to infer personality in an explainable manner using only the textual content of interview responses, making personality assessments more accessible and removing the subjective biases involved in human interviewer judgement of candidate personality.

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Section: Resultssupporting

confidence: 90%

Section: Resultssupporting

confidence: 88%

Explainable Personality Prediction Using Answers to Open-Ended Interview Questions

2022

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“…Compared to the Big Five, HEXACO is more responsive in different cultural environments ( Lee and Ashton, 2008 , 2012 , 2013 ; Saucier, 2009 ). And HEXACO struggled to respond well in all cultural contexts ( Skimina et al, 2020 ). From the available findings, only Social Self-Regulation (Conscientiousness, Honesty-Humility, and Agreeableness) and Dynamism (Openness to Experience and eXtraversion) can be free from the shackles of the cultural context in the process of application ( Saucier et al, 2014 ; Saucier and Srivastava, 2015 ; Strus and Cieciuch, 2019 ; Thalmayer et al, 2019 ).…”

Section: Literature Reviewmentioning

confidence: 99%

RETRACTED: The effect of personality traits on employees’ annual salaries in Chinese startups

Zhao

2022

Front. Psychol.

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Personality is a relatively regular habit of a person. It exerts a specific influence on personal behavior and the corresponding results. At the same time, personality can provide a certain degree of explanation for the differences among individuals in behavior and the related consequences. Economic differences are one of the discrepancies that exist among individuals. In order to explore the quantitative relationship between personality and individual income, this study takes 376 active employees of Chinese startups as the primary research objects. Additionally, considering the simplification and convenience of the survey, the annual salary investigated by this study is the pre-tax income of active startup employees. It uses quantitative methods to analyze the relationship between their personality traits and annual salary. Unlike the measures used in previous studies, this study employed the HEXACO-60 Inventory created by Ashton and Lee to investigate employees’ personality traits. Compared to the Big Five model, HEXACO (Honesty-Humility, Emotionality, eXtraversion, Consciousness, Open to Experience, and Agreeableness) adds a new dimension to evaluate personality traits, called Honesty-Humility (H-H). H-H did not appear in previous studies related to personality and individual income. Therefore, there is no reference to the relationship between H-H and personal earnings. Considering that the content of H-H is highly consistent with the components of inter locus of control and the core spirit advocated by the Confucian culture, which influences Chinese people profoundly, this paper proposes a bold hypothesis, that is, H-H has a positive correlation with employees’ annual salaries. Meanwhile, other corresponding hypotheses for the correlation between the other personality traits in HEXACO and employees’ annual salaries are proposed. After that, the above hypotheses are tested with the help of correlation analysis. Then, the following conclusions can be quickly drawn. Consciousness, eXtraversion, Open to Experience, and Honesty-Humility positively correlate with employees’ annual salaries. In comparison, Emotionality and Agreeableness negatively correlate with employees’ annual salaries.

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“…For the present study, the subscale Cronbach’s alpha values were as follows: H (0.71; 95%CI: 0.68, 0.75), E (0.70; 95%CI: 0.65, 0.75), X (0.73; 95%CI: 0.68, 0.77), A (0.80; 95%CI: 0.75, 0.85), C (0.82; 95%CI: 0.75, 0.90), and O (0.76; 95%CI: 0.70, 0.81). In the current study, the construct validity of the six-factor model of HEXACO-60 was analyzed using the same technique as in previous studies 48 – 50 namely principal axis factoring extraction method with varimax rotation. The results of the factorial analysis showed that the six common factors accounted for 35.2% of the item variance (similar to those reported for the original English version, i.e., 37.4% and 29.1%) 48 .…”

Section: Methodsmentioning

confidence: 99%

Personality and socio-demographic variables in teacher burnout during the COVID-19 pandemic: a latent profile analysis

Răducu

Stănculescu

2022

Sci Rep

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Although it is well-known that teaching is one of the most stressful jobs, teacher burnout during the COVID-19 pandemic has not been thoroughly investigated. The main aims of this study were to identify distinct teacher burnout profiles and examine their association with HEXACO personality factors and sociodemographic variables. Data were collected from 522 teachers (77% women; Mage = 37.45 years, SD = 9.28) in November 2021. Latent profile analysis (LPA) identified five latent profiles: “No burnout risk” (41.3%), “Low burnout risk” (21.9%), “Cynics” (7.7%), “Exhausted and cynics” (16.1%), and “High burnout risk” (13%). Our results showed a significant correlation between all six HEXACO personality traits and teacher burnout based on the variable-centered method, but the LPA highlighted that only the emotionality trait was antecedent of profile membership. In terms of sociodemographic variables, gender and rural/urban teaching environment did not have significant impact on teacher burnout profiles, but professional experience did. This study is the first to explore teacher burnout during the COVID-19 pandemic in relation to dispositional traits based on the HEXACO model using a person-centered approach. Our results can inform specialists about the role of emotionality in the occurrence of teacher burnout and the greater vulnerability of experienced teachers in the context of remote learning. Tailored programs of intervention are necessary.

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Psychometric properties of the Polish versions of the HEXACO-60 and the HEXACO-100 personality inventories

Cited by 10 publications

References 62 publications

Explainable Personality Prediction Using Answers to Open-Ended Interview Questions

Explainable Personality Prediction Using Answers to Open-Ended Interview Questions

RETRACTED: The effect of personality traits on employees’ annual salaries in Chinese startups

Personality and socio-demographic variables in teacher burnout during the COVID-19 pandemic: a latent profile analysis

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