ABSTRACT
PROBLEM: The German version of the Highly Sensitive Person Scale (HSPS-G) is an instrument for the assessment of sensitivity. Validity of the scale was confirmed in prior research (Konrad & Herzberg, 2017). This paper provides norm values of the HSPS-G for German-speaking countries. METHOD: To generate norms, data from 7458 participants (6251 female, 1207 male; age ranging: 14-80 years; mean=37.80; SD=11.75) were collected in an online assessment. Participants were German-speaking citizens of Germany, Austria, and Switzerland. RESULTS: Analysis of variance suggested systematic gender differences in the scores. Thus, gender-specific norms were created for the subscales and the total score of the HSPS-G. The resulting norm values comprising percentiles and T-values enable comparative interpretation of the results of the HSPS-G, enabling the assessment of inter- and intraindividual differences with respect to demographic variables.
Subject(s)
Self-Assessment , Adolescent , Adult , Aged , Aged, 80 and over , Austria , Female , Germany , Humans , Male , Middle Aged , Psychometrics , Reference Values , Reproducibility of Results , Surveys and Questionnaires , Switzerland , Young AdultABSTRACT
Music is a universal phenomenon that has existed in every known culture around the world. It plays a prominent role in society by shaping sociocultural interactions between groups and individuals, and by influencing their emotional and intellectual life. Here, we provide evidence for a new theory on musical preferences. Across three studies we show that people prefer the music of artists who have publicly observable personalities ("personas") similar to their own personality traits (the "self-congruity effect of music"). Study 1 (N = 6,279) and Study 2 (N = 75,296) show that the public personality of artists correlates with the personality of their listeners. Study 3 (N = 4,995) builds on this by showing that the fit between the personality of the listener and the artist predicts musical preferences incremental to the fit for gender, age, and even the audio features of music. Our findings are largely consistent across two methodological approaches to operationalizing an artist's public personality: (a) the public personality as reported by the artist's fans, and (b) the public personality as predicted by machine learning on the basis of the artist's lyrics. We discuss the importance of the self-congruity effect of music in the context of group-level process theories and adaptionist accounts of music. (PsycInfo Database Record (c) 2021 APA, all rights reserved).