Traits and values as predictors of the frequency of everyday behavior: Comparison between models and levels

Abstract

The aims of this study were to compare (a) personality traits vs personal values, (b) Five-Factor Model (FFM) vs HEXACO model of personality traits, and (c) broad vs narrow personality constructs in terms of their relationship with the frequency of everyday behaviors. These relationships were analyzed at three organizational levels of self-reported behavior: (a) single behavioral acts, (b) behavioral components (empirically derived categories of similar behaviors), and (c) two higher-order factors. The study was conducted on a Polish sample (N = 532, age range 16-72). We found that (a) even the frequencies of single behavioral acts were related to various personality constructs instead of one narrow trait or value, (b) personality traits and personal values were comparable as predictors of a wide range of everyday behaviors, (c) HEXACO correlated with the frequency of behaviors slightly higher than FFM, and (d) narrow and broad personality constructs did not differ substantially as predictors of everyday behavior at the levels of acts and components, but at the level of higher-order behavioral factors, broad personality measures were better predictors than narrow ones.

Explaining Everyday Behaviours and Situational Context by Personality Metatraits and Higher–Order Values

“…Listening to music and reading correlated with openness also in previous studies (e.g. Skimina et al, ). Talking with friends can express Stimulation or Hedonism, as well as openness to new ideas.…”

“…For instance, Alessandri and Vecchione () showed that Stability accounted for variance in job performance beyond that of the Big Five. In a study conducted by Skimina et al (), Beta/Plasticity was related to surfing the Internet and game‐playing more strongly than any basic trait or facet of personality. Because the metatraits postulated by the Circumplex of Personality Metatraits reflect specific psychological meanings that go beyond the shared variance of lower‐level traits (Strus & Cieciuch, ), they should be good predictors of daily activities and situational context.…”

“…The Oregon Avocational Interest Scales includes items describing activities in various life domains, excluding work and school. Skimina et al () categorized these activities into 20 clusters, for instance, ‘Drank in a bar or night club’ is an example of drinking and partying, ‘Cleaned the house’ is an example of housekeeping, and ‘Read the comics to a child’ is an example of childcare. The highest correlates of Alpha/Stability were found for the activities classified as household ( r = .33), drinking alcohol and partying ( r = −.29), gardening ( r = .29), religious practices ( r = .26), Internet dating ( r = −.24), and childcare ( r = .24), and the highest correlates of Beta/Plasticity were found for surfing the Internet ( r = .45), physical activity ( r = .40), travelling ( r = .32), reading ( r = .39), music ( r = .31), drinking alcohol and partying ( r = .30), game‐playing ( r = .28), and creative hobbies ( r = .31).…”

“…Previous research has demonstrated that personality traits and value preferences are complementary constructs that can be combined to explain outcome variables (e.g. Grankvist & Kajonius, ; Pozzebon & Ashton, ; Skimina, Cieciuch, & Strus, ). Therefore, in this study, we use both personality metatraits and value preferences to predict everyday behaviours and context.…”

The Integration of Problem Solving and Value Approach: the Shift Toward How to Think

“…As Keeney (1996) represents decisionmaking approach, he underlines that starting point for decision-making process are values primary expressed in the goals. Skimina, Cieciuch, & Strus (2018) assert that values reflect the content of the goals. On the whole, values represent the essential foundation for problem solving and could be integrated into it by several ways (see Figure 2).…”