ORIGINAL RESEARCH published: 27 October 2021 doi: 10.3389/fpsyg.2021.717705 Decision-Making and the Alternative Five Factor Personality Model: Exploring the Role of Personality Traits, Age, Sex and Social Position Patricia Urieta 1,2 , Anton Aluja 1,2* , Luis F. Garcia 2,3 , Ferran Balada 2,4 and Elena Lacomba 1,2 1 Department of Psychology, Universitat de Lleida, Lleida, Spain, 2 Lleida Institute for Biomedical Research (IRBLleida), Lleida, Spain, 3 Department of Biological Psychology and Health, Autonomous University of Madrid, Madrid, Spain, 4 Department of Psychobiology and Methodology of Health Sciences, Universitat Autònoma de Barcelona, Barcelona, Spain This study explores the relationship between decision-making style, as measured by the Melbourne Decision Making Questionnaire, and personality based on alternative five-factor model along with effect of age, sex and social position on such styles. A large sample of community and undergraduate students (n = 1,562; Mage = 40.03, SD = 18.43) was analyzed. The results showed that Neuroticism and Extraversion were significantly related to the non-vigilant styles Hypervigilance, Edited by: Buck-passing and Procrastination. Women scored significantly lower in Vigilance and Sebastian Ludyga, higher in Hypervigilance, Buck-passing and Procrastinations than men. Age was University of Basel, Switzerland significantly related to decision-making style in a U-shaped fashion. The Social Position Reviewed by: Evangelia Karagiannopoulou, Index was significantly related to all decision-making styles. The most predictive University of Ioannina, Greece personality domains regarding decision-making scales were Aggressiveness (negatively) Craig Leth-Steensen, Carleton University, Canada and Activity for Vigilance, and Neuroticism for Hypervigilance, Buck-passing and *Correspondence: Procrastination. Age, sex and social position had a small/medium overall effect on Anton Aluja the four dimensions of Melbourne Decision Making Questionnaire (p < 0.001) with anton.aluja@udl.cat a η2 of 0.038, 0.068, 0.050, and 0.031 for Vigilance, Hypervigilance, Buck-passing Specialty section: and Procrastination, respectively. Based on scores on a single factor dimension of the This article was submitted to MDMQ, the profile of participants with higher scores was characterized by lower age, Psychopathology, more likely to be females, lower social position, higher levels of Aggressiveness, less a section of the journal Frontiers in Psychology Activity, less Extraversion, and higher Neuroticism. Received: 31 May 2021 Keywords: decision-making, conflict theory, Alternative Five Factor Personality Model, ZKA-PQ/SF, MDMQ Accepted: 06 October 2021 Published: 27 October 2021 Citation: INTRODUCTION Urieta P, Aluja A, Garcia LF, Balada F and Lacomba E (2021) Making decisions involves choosing a course of action, a possibility derived from a judgment Decision-Making and the Alternative about a problem or a condition that demands a choice and is characterized by personal beliefs Five Factor Personality Model: Exploring the Role of Personality about what resources can allow someone to achieve their own goals (Baron, 2008). Janis and Traits, Age, Sex and Social Position. Mann (1977) suggested a theory about conflict and decision-making. It assumed that decision- Front. Psychol. 12:717705. making entails a conflict that causes psychological stress due to concern about the serious personal, doi: 10.3389/fpsyg.2021.717705 material and social losses that could be caused by the chosen alternative, and a concern about the Frontiers in Psychology | www.frontiersin.org 1 October 2021 | Volume 12 | Article 717705 Urieta et al. Decision-Making, Personality, Age, Sex, SP loss of reputation and self-esteem if the decision goes wrong. Heidari and Arani, 2017) and Openness (Di Fabio and Busoni, The most remarkable symptoms of such conflicts are hesitation, 2006; Di Fabio and Palazzeschi, 2012; Heidari and Arani, 2017), vacillation, feelings of uncertainty, and signs of emotional stress while these relationships are in the opposite direction for when the decision becomes the focus of attention. Decision- Neuroticism (Rahaman, 2014; Heidari and Arani, 2017). On making is complex in its nature and planning and decision- the other hand, the three non-vigilant MDMQ scales have a making processes depend on different variables that contribute significant positive relationship with Neuroticism (Vigilance; to whether they work out successfully or not. In this way, Rahaman, 2014; Procastination and Hypervigilance; Rahaman, decision-making has been related in previous studies to different 2014; Heidari and Arani, 2017). Indeed, the latter three MDMQ individual and psychological variables such as age, sex and scales generally show opposite results to those observed personality (Bouckenooghe et al., 2007; Heidari and Arani, 2017; for the Vigilance scale. For instance, a negative correlation Filipe et al., 2020). To a lesser extent, it has also been related to with Extroversion has been reported for Buck-passing and socioeconomic status (Sheehy-Skeffington, 2020). Procrastination (Di Fabio and Busoni, 2006; Peter and Gurnáková, 2014; Rahaman, 2014), and Hypervigilance (Di Fabio Decision-Making Assessment and Busoni, 2006; Peter and Gurnáková, 2014; Rahaman, 2014; Several self-reported questionnaires have been used in the field Heidari and Arani, 2017). This is also theoretically congruent of decision-making research. Among them are the Rational with cognitive approach to personality since introverted-anxious Intuitive Decision Style Scale (RI-DSS) and the Proactive people have an anticipatory bias toward threat signals, become Decision-Making Questionnaire (PDMS) (Siebert and Kunz, more consciously and automatically aware of these threats, and 2016), but the most cited in the literature are the General focus attention on these threatening signals (Eysenck, 1992). Decision-Making Style (GDMS) (Scott and Bruce, 1995) and the The Buck-passing scale also shows negative correlations with Melbourne Decision-Making Questionnaire (MDMQ) (Mann Conscientiousness (Rahaman, 2014; Heidari and Arani, 2017) et al., 1997). The MDMQ is a shortened 22-item version of and Openness (Di Fabio and Busoni, 2006; Rahaman, 2014), the Flinders Decision-Making Questionnaire (Mann, 1982). This although Peter and Gurnáková (2014) found it to have a positive version measures coping patterns of decisional conflict and relationship with the latter personality factor. Similarly, the has been adapted to different languages and countries with Procrastination and Hypervigilance have shown a negative satisfactory psychometric properties. For details, see the recent relationships with Agreeableness (Rahaman, 2014; Heidari review by Filipe et al. (2020). and Arani, 2017), Conscientiousness (Di Fabio and Busoni, The shortened version of the MDMQ assesses decision- 2006; Rahaman, 2014; Heidari and Arani, 2017) and Openness making styles according to four domains: Vigilance, (Di Fabio and Busoni, 2006; Di Fabio and Palazzeschi, 2012; Hypervigilance, Buck-passing and Procrastination. Vigilance Rahaman, 2014), although Peter and Gurnáková (2014) found a refers to the way or style in which people seek objectives to make positive relationship between Hypervigilance and Openness. a decision by exploring alternatives, searching for rational and With respect to the negative relationship that Neuroticism has relevant information (e.g.,: I consider how best to carry out the with the Vigilance scale and the positive one it has with all the decision). It also involves the assimilation of the information in other MDMQ scales, research by Filipe et al. (2020) has shown an unbiased manner and the evaluation of different alternatives that people with a vigilant decision-making style tend to be more before making a decision. It results in a thorough information satisfied with life, show positive affect, and better decisional self- search, unbiased assimilation of new information, and other esteem, conversely the remaining decision-making scales were characteristics of high-quality decision making (Janis and Mann, associated with negative affect, lower satisfaction with life, and 1977). The Hypervigilance style entails the frantic pursuit of reduced decisional self-esteem (Filipe et al., 2020). Hence, the fact decisions to get out of the dilemma, so decisions are made the Vigilant and Neuroticism are negatively related is congruent in a flash to relieve tension quickly. Hypervigilance includes with the strong reverse association that has been observed emotional stress and limited perseverance (e.g.,: Even after I have between the Self-esteem and Neuroticism constructs (Judge et al., made a decision, I delay acting upon it.). Buck-passing includes 2002; Aluja et al., 2007). Moreover, the role that anxiety has in attribution of responsibility for one’s own decisions. Hesitation in making the actual choice process more difficult (Saka et al., 2008), decision-making is also related (e.g.,: I prefer that people who are also suggests that more neurotic individual should report less better informed decide for me.). Finally, Procrastination means vigilant decision making styles (Eysenck, 1992). deferring decisions for later by lowering priority (e.g.,: Whenever As has been summarized, the relationship between MDMQ I face a difficult decision, I feel pessimistic about finding a good and personality has been the focus of multiple research studies, solution.). Hypervigilance, Buck-passing and Procrastination are most of them involving the five-factor model. However, to non-vigilant styles of decision making. our knowledge, there are no studies examining the relation of these decision-making styles with Zuckerman’s personality model Decision-Making and Personality (Aluja et al., 2010). This Alternative Five Factor Personality The MDMQ Vigilance scale shows positive correlations Model (AFFPM) includes domains such as Activity, Aggression with the Five Factor Personality Model (FFPM) factors of and Sensation Seeking, whose relationship with decision-making Extraversion (Rahaman, 2014; Heidari and Arani, 2017), is currently unknown. As already detailed, people who score Agreeableness (Rahaman, 2014; Heidari and Arani, 2017), higher in Neuroticism and lower in Extraversion (which are Conscientiousness (Di Fabio and Busoni, 2006; Rahaman, 2014; also factors of the Zuckerman’s model) are expected to score Frontiers in Psychology | www.frontiersin.org 2 October 2021 | Volume 12 | Article 717705 Urieta et al. Decision-Making, Personality, Age, Sex, SP higher in Buck-passing, Procrastination, Hypervigilance and decision-making. People of low SP have poorer health than those lower in Vigilance. In fact, the strong relationships with Decision- with higher SP (Pamuk et al., 1998; Steenland et al., 2004). Making scales are expected to be found with Neuroticism. High SP is related to educational achievement, which provides Further, given its relation to the Conscientiousness factor of better occupational opportunities and higher potential, enabling the FFPM (García et al., 2012), Activity should be positively better nutrition, access to housing to health care resources associated with Vigilance and negatively associated with Buck- (Winkleby and Cubbin, 2003). Chronic stress related to perceived passing, Procrastination, and Hypervigilance. Aggressiveness is social position may also predispose people with lower SP to negatively related to the Agreeableness factor of the FFPM, illness (McEwen, 1998). Socioeconomic status has been related and, hence, should be positively associated with Buck-passing, to biological indicators of physical and mental health status, such Procrastination, and Hypervigilance. Sensation seekers are more as heart rate, drowsiness, cortisol habituation to stress, body fat attracted to risk, but tend to have less anxiety (García et al., distribution (Adler et al., 2000), as well as self-reported results, 2012). Nonetheless, Zuckerman’s model could provide some light such as depression (Demakakos et al., 2008) or perceived stress on individual differences in decision-making styles beyond that (Hamad et al., 2008). provided by the FFPM since Sensation Seeking (only considered Lower SP has also been related to poor decisions. People with as an Extroversion facet in the gold standard of the FFPM – lower income are more likely to be exposed to uncontrollable and NEO-PI-R) has previously been related to decision-making controllable negative life events and tend to make bad decisions behaviors (Reynolds et al., 2019), especially with respect to in economic reasoning (Bruine de Bruin et al., 2007). People with unplanned and risky behaviors that have negative consequences low social position tend to focus on immediate needs and make for the person and the group (Kovács et al., 2017; Ioannidis rational decisions in the proximate context of socioeconomic et al., 2019). Young people are greater sensation seekers threat. These changes in psychological processes can hinder than older people, but no differences were found between the achievement of long-term goals. Such people also struggle young and old people when making risky decisions, so it is with making optimal decisions regarding health and finances hard to hypothesize about the relationship between Sensation (Sheehy-Skeffington, 2020). Seeking and MDMQ. Aims of the Present Study Decision-Making, Sex and Age Age and sex have been related to decision-making, but no Differences in decision-making have been found due to both previous study separated age into ranges. Age ranges would allow age and sex, particularly with the MDMQ. Elderly people seems a better understanding of the distribution of the relationship to be more reliant on emotion compared to experience and with decision-making. Although SP and decision-making has are also better at facing the emotional aspects of a problem not received much study, there is evidence to suggest that (Löckenhoff, 2011; Filipe et al., 2020). Bouckenooghe et al. people of different social class have different instrumental and (2007) found that older people tend to score higher on Vigilance social values, which influence decision-making (Wang and Tang, and younger people on non-vigilant styles of decision making. 2019). Analyzing these variables together with personality traits Sproten et al. (2010) examined the effects of aging on decisions in is important, since they may confound the relationship between two domains of uncertainty: risk and ambiguity. No differences decision-making and personality (Starcke and Brand, 2012). were found between younger and older participants when they Hence, the main objective is to explore the relationship make risky decisions, but when ambiguous situations were between decision-making style and Zuckerman’s model of introduced, older subjects were less reluctant than the younger personality along with the examination of the role of age, sex ones. On another study, adults showed higher competence and and social position. From a practical point of view, locating problem-solving ability than young people (Blanchard-Fields the specific aspects of personality that contribute to difficulties et al., 2004), whereas with respect to the MDMQ, the latter have in decision-making processes is highly relevant to improving comparatively higher values in Hypervigilance, Buck-passing, such processes, and could help counselors and clinicians to and Procrastination (Kornilova et al., 2018). Young adults overcome such difficulties. It seems unlikely that difficulties will were less capable than older adults of managing stress when be resolved without intervention focusing on the more chronic making decisions, due to their higher levels of buck-passing, and dysfunctional personality antecedents of any decision- hypervigilance, and procrastination (Filipe et al., 2020). Sex making problems. differences have also been found. Females tended to score lower on Procrastination compared with males. Female and younger respondents scored higher on Hypervigilance compared with MATERIALS AND METHODS male and older respondents (Bouckenooghe et al., 2007). Participants and Procedure Decision-Making and Social Position The sample consisted of a total of 1,562 participants The social position (SP) of an individual together with the (Mage = 40.03, SD = 18.43; 54.3% females). Males reported social role determines the place of an individual in the social a slightly higher average age than females (42.16 vs. 39.06; t-test: environment and social organization. Low social position or 2.43; p < 0.025). 556 participants (Mage = 21.23; SD = 8.85) were socioeconomic status (SES) leads to problems and difficulties undergraduate students and 1,006 were community volunteers that affect health and generate social stress that can affect (Mage = 50.40; SD = 13.45). All participants were healthy Frontiers in Psychology | www.frontiersin.org 3 October 2021 | Volume 12 | Article 717705 Urieta et al. Decision-Making, Personality, Age, Sex, SP Caucasian adults aged 18–88 years old and were recruited performed comparing different groups of SPI and age, using in the cities of Madrid and Lleida (Spain) by undergraduate Scheffe’s post-tests. Since the total sample was gathered from students taking part in a university personality research and two populations, a separate factor analysis of the 22-item practice program. Students were asked to find one female and MDMQ using principal axis extraction and oblimin rotation one male participant in each of the following five age ranges: method was computed for subjects from the community and 18–30 (39.1%), 31–40 (8.8%), 40–50 (17.7%), 50–60 (22.4%), and university student populations. To test if the structure was over 60 (12%) years old. Participants in the general population stable across both samples, a Procrustes rotation and factorial reported their education and occupational levels on a 1–7-point congruence coefficients were performed. Goodness-of-fit indices scale in order to obtain the Hollingshead Social Position Index were calculated for the factorial structure of the whole sample. (SPI; Hollingshead, 1957); [SPI score = (Occupation score X Subsequently, the structure of the 20 facets of ZKA-PQ/SF 7) + (Education score X 4)]. For the purpose of analyzing SPI, and the 4 MDMQ domains were analyzed. To determine the only the cases that provided SPI data were included, which predictive ability of ZKA-PQ/SF on the 4 MDMQ domains, a constituted 64.4% of the total sample (Supplementary Table 1). multiple regression analysis was performed. The analysis was Note that the highest SPI values correspond to the lowest SP, and performed using the “enter” and “stepwise” methods over the that scores can be grouped into five SPI groups. All participants domains and facets, respectively. For the domains, the “enter” signed a standard informed consent document in accordance method was performed, but for the facets we applied the stepwise with the ethical guidelines of the university research committee. method with a more rigorous than usual criterion of PIN (probability of F to enter; p < 0.0001) and POUT (probability Measures of F to remove; p < 0.10). To graphically visualize the predictive Melbourne Decision-Making Questionnaire ability of the ZKA-PQ/SF, a single factor was extracted from the Melbourne Decision-Making Questionnaire (MDMQ; Mann MDMQ and a LOESS (locally estimated scatterplot smoothing) et al., 1997). The MDMQ is a 22-item questionnaire used regression was performed (Fox, 2000; O’Connor, 2005). This to assess decision-making style. It is a self-report inventory procedure is complementary to linear regression analyses and designed to measure the four main coping patterns identified in allows us to observe graphically how the personality domains (z- the conflict-theory model of decision-making (Janis and Mann, scores) are distributed across the general factor measured by the 1977): Vigilance (Vi), Hypervigilance (Hy), Buck-passing (Bp), MDMQ. Statistical analysis was carried out using SPSS 25 (SPSS and Procrastination (Pr). Participants indicated their agreement Corp., 2017) and Factor.exe (Ferrando and Lorenzo-Seva, 2017). with statements on a 3-point Likert-type scale. Each item consists Results files are available upon request from the first author. of three answers that are scored as follows: true (2), sometimes true (1) and not true (0). The Spanish version used in this research was validated by De Heredia et al. (2004). The 22 items RESULTS support a 4-factor structure. For the present sample, the reliability coefficients were 0.79 (Buck-passing), 0.78 (Procrastination), 0.70 Sociodemographic Variables, Test (Hypervigilance), and 0.74 (Vigilance). Descriptive and Reliability Zuckerman–Kuhlman-Aluja Personality Questionnaire The frequencies and percentages per sex of all the Shortened Form participants and the sociodemographic data of the community participants were calculated (Supplementary Table 1). Zuckerman–Kuhlman-Aluja Personality Questionnaire Means and standard deviations are also provided for age, shortened form (ZKA-PQ/SF; Aluja et al., 2018). The complete SPI, the domains of personality, and decision-making ZKA-PQ contains 200 items, with 10 items per facet (Aluja questionnaires (Table 1). The reliability of ZKA-PQ/SF et al., 2010). The short version has 80 items, 20-facets and 4 domains ranged from 0.81 to 0.90, and the reliability of items per facet measuring five traits (factors): Aggressiveness the MDMQ between 0.71 and 0.78. The SPI mean was (AG), Activity (AC), Extraversion (EX), Neuroticism (NE), 34.01 (SD = 18.64), which corresponds to an average social and Sensation Seeking (SS). The response format is a 4-point position rating (32–47 range) (Table 1 and Supplementary Likert-type scale ranging from 1 (strongly disagree) to 4 (strongly Table 1). agree). Validity and reliability evidence of the ZKA-PQ and ZKA-PQ/SF were presented in the original studies (Aluja et al., 2010, 2018) and in cross-cultural validations in various African, Melbourne Decision-Making American, Asian, and European cultures and languages (Rossier Questionnaire Factor Structure et al., 2016; Aluja et al., 2020). The ZKA-PQ/SF and scoring keys The main aim of the present paper is not to analyze the are included in the Appendix of Aluja et al. (2018). factor structure of the MDMQ. However, since total sample was gathered from two different samples (community and Data Analysis students), is important to test if the structure was replicated First, frequencies and percentages of sociodemographic and in both samples. From both factor matrices, 4 factors were descriptive variables, alpha internal consistency, and inter- extracted with oblique rotation with the eigenvalue criterion correlations were calculated. To study the relationship of one and Scree test. Parallel analysis also yielded 4 factors. The the MDMQ domains with SPI and age, an ANOVA was method to obtain the random correlation matrices was the Frontiers in Psychology | www.frontiersin.org 4 October 2021 | Volume 12 | Article 717705 Urieta et al. Decision-Making, Personality, Age, Sex, SP 1 M: Mean: SD: Standard deviation; SPI: Social Position Index. For correlations equal or higher ± 0.10 p-value < 0.001. Correlations equal or higher 0.20 in boldface (n = 1,562). SPI data correspond to 1,006 community permutation of the raw data (Buja and Eyuboglu, 1992). In both samples, all items were integrated into their corresponding theoretical factor. Both matrices were rotated to obtain a −0.06 2 third matrix using the Procrustes method that also allowed us to calculate the Tucker factor congruence coefficients for the items and the factors (Supplementary Table 2). 0.20 0.06 A value of congruence coefficients in the range [0.85 – 0.94] 3 means that the factors from each sample compared display a fair degree of similarity, and a value greater than 0.95 is −0.20 0.01 0.12 generally interpreted as the factors being practically identical 4 (Lorenzo-Seva and ten Berge, 2006). The overall congruence coefficient (0.98) indicates that both factor matrices were very similar. The factor congruence 0.07 0.04 0.05 0.03 5 of the factors ranged between 0.97 and 0.99, and that of the items between 0.83 and 1 (Supplementary Table 2). To ascertain the goodness-of-fit indices, a Robust Unweighted −0.15 −0.09 −0.14 0.07 0.24 6 Least Squares (RULS) analysis with robust Chi-square and Variance-scaled (Asparouhov and Muthen, 2010) and normalized direct oblimin rotation was performed. The Kaiser-Meyer-Olkin (KMO) test scored 0.89, and 4 −0.19 −0.04 −0.29 0.26 0.18 0.42 7 factors were also extracted. The goodness-of-fit indices were: Non-Normed Fit Index (NNFI) 0.99; Comparative Fit Index (CFI) 0.99; Schwarz’s Bayesian Information −0.42 −0.11 −0.10 0.18 0.18 0.26 0.03 Criterion (BIC) 1140.070; Root Mean Square Error of 8 Approximation (RMSEA) – 0.03 and Root Mean Square of Residuals (RMSR) – 0.02. −0.06 −0.18 −0.10 −0.08 −0.17 0.07 0.11 0.06 9 Decision-Making, Age, Sex and Social Position Age was significantly and negatively correlated with Buck-passing −0.01 −0.24 −0.10 0.21 0.18 0.23 0.57 0.07 −0.06 10 (−0.11; p < 0.001) and Procrastination (−0.15; p < 0.001). Sex (categorical variable scoring 1 for male and 2 for female) correlated with Neuroticism (0.26; p < 0.001) and Hypervigilance (0.21; p < 0.001). SPI also correlated negatively with Vigilance −0.11 −0.13 −0.22 −0.04 −0.15 0.10 0.20 0.11 0.38 0.41 11 TABLE 1 | Mean, standard deviation, reliability, inter-correlations and sex differences. (−0.17; p < 0.001) and positively with Hypervigilance (0.18; p < 0.001), Buck-passing (0.20; p < 0.001) and Procrastination (0.15; p < 0.001) (Table 1). We found moderate sex differences in age (t-test = −2.24; p < 0.03) and SPI (t-test = 0.19; p < 0.05), −0.15 −0.11 −0.21 −0.17 0.09 0.15 0.20 0.41 0.03 0.47 0.46 12 All subjects (n = 1,562) but with small effect sizes (Cohen, 1988). Males scored higher than females on Vigilance (t-test = −2.41; p < 0.02; d = −0.12) and females scored higher than males on Hypervigilance (t- 0.89 0.81 0.86 0.90 0.85 0.74 0.71 0.79 0.78 − − − α test = 8.48; p < 0.001), Buck-passing (t-test = 3.99; p < 0.001) and Procrastination (t-test = 3.60; p < 0.001) with a Cohen’s d of 0.44, 0.20, and 0.18, respectively. The main personality 8.82 7.29 7.85 9.65 8.83 2.20 2.34 2.67 2.34 18.43 18.64 SD − differences between sexes were in Neuroticism (37.79 vs. 32.86), Sensation Seeking (36.57 vs. 38.46) and Extraversion (49.19 vs. 48.06) with an effect size of 0.53, −0.22, and 0.14, 9.28 4.74 5.05 3.21 40.02 34.01 33.23 41.81 48.67 35.54 37.44 respectively (Table 2). M − Figures 1, 2 show MDMQ scores for each of the age and SPI ranks, respectively, separately for males and females. No significant interactions between sex and either age or SPI 8. Sensation Seeking 12. Procrastination 10. Hypervigilance 4. Aggressiveness 11. Buck-passing 3. SPI (n = 1,006) ranges were observed for any MDMQ scale. Results when subjects (italics). 5. Activity factor 6. Extraversion 7. Neuroticism sex is included as a factor (and excluding SPI) show that 9. Vigilance Vigilance presented an inverted U-shaped distribution across age (F (4 ,1) = 2.84; P = 0.023; ηp 2 = 0.007). Younger (under 1. Age 2. Sex 30) and older (> 60 years old) age groups scored higher, Frontiers in Psychology | www.frontiersin.org 5 October 2021 | Volume 12 | Article 717705 Urieta et al. Decision-Making, Personality, Age, Sex, SP TABLE 2 | Descriptive and sex differences. Female (n = 714) Male (n = 848) M SD M SD K S t-test p< d Age 39.06 18.70 41.16 18.05 −1.04 0.27 −2.24 0.03 −0.11 SPI (W = 504; M = 502)* 35.18 19.20 32.84 18.00 −0.58 0.59 −1,98 0.05 0.13 Aggressiveness 33.34 8.90 33.11 8.73 −0.34 0.35 0.52 0.60 0.03 Activity factor 42.07 7.33 41.50 7.22 −0.10 0.08 1.54 0.12 0.08 Extraversion 49.19 7.78 48.06 7.90 −0.14 −0.36 2.83 0.01 0.14 Neuroticism 37.79 9.50 32.86 9.13 −0.58 0.14 10.40 0.001 0.53 Sensation Seeking 36.57 9.00 38.46 8.52 −0.46 0.12 −4.24 0.001 −0.22 Vigilance 9.15 2.23 9.42 2.15 0.99 −0.94 −2.41 0.02 −0.12 Hypervigilance 5.19 2.31 4.21 2.26 −0.38 0.17 8.40 0.001 0.44 Buck-passing 5.30 2.69 4.76 2.61 −0.10 0.37 3.99 0.001 0.20 Procrastination 3.40 2.39 2.98 2.25 0.01 0.64 3.60 0.001 0.18 M: Mean; SD: Standard deviation; K: Kurtosis; S: Skewness; Cohen’s d:0.01: very small, 0.20: small, 0.50: medium, 0.80: large, 1.20: very large.∗ SPI is performed only form community subjects. FIGURE 1 | ANOVA mean co mparison of age ranges and MDMQ domains: 1: 30 years old and below; 2: 31–40 years old; 3: 41–50 years old; 4: 51–60 years old, and 5: more than 60 years old. Scheffe post-tests comparisons = p < 0.05. T-test sex comparisons * p < 0.05, ** p < 0.01, *** p < 0.001. but post hoc tests did not show significant differences between finally females scored higher in all age ranges in Hypervigilance. groups. In contrast, for Hypervigilance (F (4 ,1) = 5.99; P < 0.001; Apart from Vigilance, in both males and females there was ηp 2 = 0.015) and Buck-passing (F (4 ,1) = 13.05; P < 0.001; a U-shaped distribution, i.e., young people under 30 and ηp 2 = 0.033), a U-shaped distribution across age was observed, over 60 scored higher, while those in the intermediate ranges where young participants obtained significantly higher scores scored lower. than middle-aged ones, but not for old-aged ones. A U-shaped Similarly, with sex included as a factor, MDMQ Vigilance distribution across age for Procrastination (F (4 ,1) = 14.82; domain scores progressively dropped significantly with lower p < 0.001; ηp 2 = 0.037) was also observed. For this scale, social position (F (4 ,1) = 6.70; p < 0.001; ηp 2 = 0.026), unlike in young participants obtained significantly higher scores than the the other three domains, Hypervigilance (F (4 ,1) = 7.76; p < 0.001; other age groups. We observed that from the age of 40 onward, ηp 2 = 0.03), Buck-passing (F (4 ,1) = 10.59; p < 0.001; ηp 2 = 0.041) males scored higher in Vigilance, females from the age of 51 and Procrastination (F (4 ,1) = 8.41; p < 0.001; ηp 2 = 0.033). Scores onward scored higher in Buck-passing and Procrastination, and now increased progressively, and significantly, as SP decreased. Frontiers in Psychology | www.frontiersin.org 6 October 2021 | Volume 12 | Article 717705 Urieta et al. Decision-Making, Personality, Age, Sex, SP FIGURE 2 | ANOVA mean comparison of SPI ranges and MDMQ domains: 1: Upper; 2: Upper-Middle; 3: Middle; 4: Lower-Middle and 5: Lower. Scheffe post-tests comparisons = p < 0.05. T-test sex comparison * p < 0.05, *** p < 0.001. Age, sex and social position had an overall significant effect extreme groups on a single decision-making factor. For this on all four dimensions of the MDMQ (p < 0.001) with small purpose, we developed a variable with the factor loadings of and medium effects size (η2 = 0.038, 0.068, 0.050, and 0.031) the 22-item MDMQ obtained on a single non-rotated factor. for Vigilance, Hypervigilance, Buck-passing and Procrastination, Note that for this factor Vigilance items loaded negatively, so, respectively. Individually, age had a negligible or small effect this factor represents a non-vigilant decision-making style. Two on all four domains; sex had medium effect on Hypervigilance groups were subsequently formed according to the 30th and (η2 = 0.063 ) and SPI had a small effect for Buck-passing 70th percentile: (a) subjects who scored low, and (b) subjects (η2 = 0.048). [η2 < 0.0099 = negligible; η2 > 0.01: small; who scored high. The mean difference t-test was calculated η2 ≥ 0.0588 medium; η2 ≥ 0.1379: large effect size (Cohen, for the sociodemographic and personality variables. The results 1988, pp. 274–288)]. are shown in Figure 3. For visual comparison, scores were transformed into T-scores. The results indicated statistically Factor Convergence Between significant differences in all variables except Sensation Seeking. Participants with higher non-vigilant decision-making scores Decision-Making and Personality were young, mostly female, lower socially positioned, more To explore the relationship between the MDMQ domains aggressive, less active, more introverted, and highly neurotic and personality based on the Zuckerman’s model, we opted (p < 0.001). for a factor analysis of the 20 facets of the ZKA-PQ/SF together with the five MDMQ domains. We chose the principal Personality as a Predictor of axis extraction method with oblimin rotation. Five factors were extracted according to the structure of the ZKA-PQ/SF Decision-Making (Aluja et al., 2020). All facets of the ZKA-PQ/SF were Supplementary Table 3 shows the most predictive facets of each integrated into their corresponding theoretical factor. The of the 4 MDMQ domains, and the prediction of each of the 5 Vigilance domain of the MDMQ did not significantly load personality domains to the Decision-Making domains. Vigilance on any of the 5 personality factors. However, non-vigilant is predicted by Work Energy (AC4) and Verbal Aggression styles of decision-making. clearly loaded into the Neuroticism (−AG2) (R2 = 0.08). Hypervigilance is positively predicted by factor (Table 3). all 4 facets of Neuroticism and, to a lesser extent, by Thrill and Adventure Seeking (−SS1) (R2 = 0.24). Buck-passing is predicted by Low Self-esteem (NE4), Work Energy (−AC4), Personality Differences in Dependence (NE3) and Social Warmth (−EX2) (R2 = 0.18), Decision-Making Extreme Groups and Procrastination is predicted by Low Self-esteem (NE4), One way to study the relationships between sociodemographic Depression (NE2) and Work Energy (−AC4) (R2 = 0.18). variables and personality and decision-making is to compare The most predictive personality domains were –AG and AC Frontiers in Psychology | www.frontiersin.org 7 October 2021 | Volume 12 | Article 717705 Urieta et al. Decision-Making, Personality, Age, Sex, SP TABLE 3 | Factor analysis of ZKA-PQ/SF facets and MDMQ domains. They are present from birth and are observable in other species (Zuckerman, 2005). Both models include Neuroticism I II III IV V and Extraversion domains. The FFPM includes Agreeableness, AG1 Physical Aggression −0.56 0.13 −0.15 −0.11 0.01 Conscientiousness and Openness to Experience domains. The ZKA AFFPM does not consider Openness (or culture or intellect) as AG2 Verbal Aggression −0.73 0.01 0.00 0.14 −0.10 a personality domain but includes Activity (work compulsion ZKA and energy at work), Aggressiveness, and Sensation Seeking AG3 Anger ZKA −0.84 −0.16 0.15 −0.02 0.07 instead. Aggressiveness and Agreeableness dimensions have AG4 Hostility ZKA −0.70 −0.08 0.16 −0.09 0.01 shown a strong negative association, while Activity and SS1Thrill and Adventure −0.01 0.62 −0.23 −0.10 0.13 Conscientiousness have a positive correlation. Sensation Seeking Seeking ZKA is positively correlated with Extraversion and Openness but SS2 Experience Seeking 0.09 0.63 0.06 0.14 0.07 correlates negatively with Agreeableness and Conscientiousness ZKA (García et al., 2012). SS3 Disinhibition ZKA −0.05 0.73 0.13 0.26 −0.03 As expected, as for the results found with the FFPM, SS4 Boredom −0.04 0.64 0.03 −0.03 0.01 Neuroticism and Extraversion are very positively and negatively Suscep./Impulsivity ZKA associated with non-vigilant styles of decision-making. Note NE1 Anxiety ZKA −0.27 0.01 0.58 −0.04 0.24 that non-vigilant styles of decision-making were placed in NE2 Depression ZKA −0.13 −0.02 0.73 −0.03 0.00 the Neuroticism factor in the exploratory factor analysis NE3 Dependence ZKA −0.12 −0.07 0.73 0.13 0.08 involving both the factors of ZKA-PQ/SF and the MDMQ. NE4 Low Self-esteem ZKA 0.00 0.04 0.76 −0.09 −0.07 Aggressiveness is positively associated with Hypervigilance, Buck-passing, Procrastination, and negatively with Vigilance. EX1Positive Emotions ZKA 0.14 0.04 −0.23 0.53 0.13 Activity shows some low effect size correlations (around 0.10) EX2 Social Warmth ZKA 0.07 −0.08 −0.08 0.56 −0.08 positively with Vigilance, and negatively with, Buck-passing EX3 Exhibitionism ZKA −0.17 0.27 0.04 0.54 0.03 and Procrastination. In contrast, Sensation Seeking shows no EX4 Sociability ZKA 0.03 0.10 −0.02 0.78 0.05 relationship with the overall MDMQ single non-rotated factor AC1Work Compulsion ZKA 0.01 0.07 0.06 −0.07 0.45 scores and seems to have a unique pattern of correlations AC2 General Activity ZKA 0.03 0.10 −0.05 0.05 0.72 with four separate MDMQ domains. People high in Sensation AC3 Restlessness ZKA −0.25 0.20 0.07 0.05 0.55 Seeking are less sensitive to the negative consequences of AC4 Work Energy ZKA 0.08 −0.25 −0.16 0.18 0.47 their actions, make relatively riskier choices, and perform poorly on decision making tasks (Zuckerman and Kuhlman, Vigilance 0.18 −0.13 −0.03 0.03 0.27 Hypervigilance 0.02 0.12 0.70 −0.02 0.11 2000). On the other hand, people high in Neuroticism are Buck-passing 0.12 0.05 0.51 −0.07 −0.10 hypersensitive to punishment and are risk-resentful (Aluja and Procrastination 0.05 0.10 0.53 −0.07 −0.09 Blanch, 2011). The combination of high Neuroticism and low Extraversion has been related to people’s vulnerability to stress ZKA-PQ/SF: Zuckerman-Kuhlman-Aluja Personality Questionnaire shortened form; and proneness to low mood and low self-esteem (Eysenck and MDMQ: Melbourne Decision Making Questionnaire. Absolute value loadings equal or higher 0.30 in boldface. Eysenck, 1985). Therefore, these people will tend to exhibit MDMQ domains and loadings are in italics. individual characteristics associated with non-vigilant decision- making such as hesitation, vacillation, feelings of uncertainty, (Vigilance), NE (Hypervigilance), NE (Buck-passing), and NE and signs of emotional stress. Neuroticism and Extraversion (Procrastination). In Figure 4, the prediction of each of the are included in both personality models. Thus, our results five personality domains (z-score) can be seen graphically in are in line with the findings of other researchers using the a non-parametric LOESS regression as the score progresses on FFPM (Di Fabio and Busoni, 2006; Di Fabio and Palazzeschi, a single decision-making factor (T-score). The most predictive 2012; Peter and Gurnáková, 2014; Rahaman, 2014; Heidari and domains of higher factor scores were high Neuroticism (followed Arani, 2017). Moreover, Activity shows a similar pattern of by Aggressiveness) and low Extraversion (followed by Activity). correlations with the MDMQ as does Conscientiousness in the FFPM. Aggressiveness is positively related to Hypervigilance, Buck-passing, and Procrastination, although to a lesser extent DISCUSSION than Neuroticism. Age was moderately negatively related to Buck-passing and Our study is one of the first to investigate the relationship Procrastination. A more detailed analysis using five age ranges between decision-making and personality, using the AFFPM. between less than 30 years and more than 60 years reported that The differences are partly due to the fact that the FFPM people in the youngest range score higher than the other age and the AFFPM have different conceptual starting points. The ranges, except the group over 60 years (Hypervigilance, Buck- FFPM belongs to the lexical tradition and is a descriptive passing and Procrastination). The relationship between the age and inductively derived personality model, whereas the AFFPM ranges with the three non-vigilant decision-making styles was draws from the temperamental personality tradition, in which U-shaped, thus suggesting that young people, but also the oldest basic personality constructs have strong biological foundations. participants (to a lesser extent), tend to score higher in all three Frontiers in Psychology | www.frontiersin.org 8 October 2021 | Volume 12 | Article 717705 Urieta et al. Decision-Making, Personality, Age, Sex, SP FIGURE 3 | Age, Sex, SPI and personality t-test differences between low (30 percentile) and high (70 percentile) scores in MDMQ 1-factor. *** p < 0.001. L: Low and H: High. MDMQ 1 factor score. Another objective of this study was to examine the relationship between social position and decision-making. It was expected that people with a low social position, characterized by low educational level and occupation, would score lower on Vigilance and higher on Hypervigilance, Buck-passing and Procrastination. The results of the correlation analysis confirmed our expectations. Analysis of variance forming five categories with the SPI, clearly showed that people with better social position (lower SPI scores) scored higher on Vigilance and lower on non-vigilant styles of decision making, with relationship being clearly linear in this case. Females scored significantly higher than males in the Upper and Upper-Middle (Buck-passing), Middle and Lower-Middle (Procrastination), and in all Hypervigilance SPI categories. Note that people with a low social position were also more neurotic and less extraverted. Taking as a reference a general one-dimensional non-vigilant factor formed by the MDMQ items and considering only subjects with low and high scores on this factor, a personality profile including age and sex was obtained. According to this profile, people with high scores on this factor would tend to be young, female, low SP, aggressive, not very active, introverted, and neurotic. FIGURE 4 | LOESS plots for ZKA-PQ/SF (z-score) and MDMQ 1 factor solution (T-score). NE = Neuroticism; AG = Aggressiveness; SS = Sensation Seeking. LIMITATIONS AND FUTURE STUDIES This study has strengths and limitations. The main strength is the breadth of the sample, the age range, and the parity domains. This trend is found in both females and males, although between males and females. Another positive aspect is the good females tend to score higher in all age ranges and to obtain higher structural validity and reliability of the MDMQ and ZKA-PQ/SF overall mean scores than males in these three domains of the questionnaires. A limitation of this study is its cross-sectional MDMQ. This finding is particularly interesting and contributes design, which could compromise the validity of the results in to a better understanding of the relationship between age and other different contexts. A longitudinal design would have been decision-making. more suitable to produce causal conclusions. Data have been Frontiers in Psychology | www.frontiersin.org 9 October 2021 | Volume 12 | Article 717705 Urieta et al. Decision-Making, Personality, Age, Sex, SP collected using short self-reported questionnaires, and it would and Procrastination, and corresponding negative associations have been desirable to have interview data or parallel information with Extraversion. Aggression is negatively associated with on other characteristics of the sample such as psychopathological Vigilance and positively associated with Hypervigilance, Buck- trends, perception of stress or life satisfaction. Future studies passing and Procrastination. Activity is negatively associated with should examine the relationship between ZKA-PQ/SF with other Buck-passing and Hypervigilance, and positively with Vigilance. decision-making questionnaires such as the Rational Intuitive People with high scores on Hypervigilance, Buck-passing and Decision Style Scale (RI-DSS), the Proactive Decision-Making Procrastination tend to be younger and female in general, but an Questionnaire (PDMS) (Siebert and Kunz, 2016), and the General examination of five age ranges shows that those over 60 tend to Decision-Making Style (GDMS) (Scott and Bruce, 1995), among score comparably to those aged 30 and younger. Females score others. It would also be wise to study the role of intermediate lower in Vigilance and higher in non-vigilant styles of decision- variables such as intelligence and relationship of Zuckerman’s making. Low SP is associated with low scores in Vigilance and personality model, with behavioral problems involving high high scores in non-vigilant styles of decision-making. impulsivity and sensation seeking traits such as gambling, alcohol abuse and dependence, or driving behavior. In addition, future studies should examine the role of SP and SES, since this variable DATA AVAILABILITY STATEMENT has received little attention in relation to decision-making. Such a variable could also be assessed through more sophisticated multi- The original contributions presented in the study are included thematic indices than the Hollingshead Index of Social Position, in the article/Supplementary Material, further inquiries can be such as the Warner’s Index of Status Characteristics or the Census directed to the corresponding author. Bureau’s Index of Socioeconomic Status. On the other hand, the fact that both Social Position indicators are related to IQ would require a partialling out of IQ in the correlational analysis. ETHICS STATEMENT So, a future study should replicate those relationships between MDMQ, personality and Social Position controlling for IQ. The studies involving human participants were reviewed and approved by Comitè d’Ètica Hospital Universitari Arnau de Vilanova de Lleida (Spain). The patients/participants provided their written informed consent to participate in this study. PRACTICAL IMPLICATIONS In regard to practical implications, the present study confirms that personality traits and, specifically, the AFFPM, as measured AUTHOR CONTRIBUTIONS by the ZKA-PQ/SF, could provide useful information to help to All authors listed have made a substantial, direct and intellectual detect and avoid difficulties in decision making, and limitations contribution to the work, and approved it for publication. in an individual’s decision-making process. In practical and clinical contexts, therefore, personality instruments such as the ZKA-PQ/SF could be useful to support good decision-making FUNDING outcomes. For instance, counselors working with people with problems in their decision-making processes should actively This research was funded by a grant from the Spanish monitor their personality traits, with special attention to Ministry of Economy, Industry and Competitiveness (PID2019- neuroticism/anxiety. They should also take into account the role 103981RB-I00). of sociodemographic characteristics. SUPPLEMENTARY MATERIAL CONCLUSION The Supplementary Material for this article can be found Using the AFFPM, this study confirms a strong positive online at: https://www.frontiersin.org/articles/10.3389/fpsyg. association of Neuroticism with Hypervigilance, Buck-passing, 2021.717705/full#supplementary-material REFERENCES (SPSRQ–20). J. Personal. Assess. 93, 1–10. doi: 10.1080/00223891.2011.60 8760 Adler, N. E., Epel, E. S., Castellazzo, G., and Ickovics, J. R. Aluja, A., Kuhlman, M., and Zuckerman, M. (2010). Development of the (2000). Relationship of subjective and objective social status Zuckerman-Kuhlman-Aluja Personality Questionnaire (ZKA-PQ): A with psychological and physiological functioning: Preliminary factor/facet version of the Zuckerman-Kuhlman Personality Questionnaire data in healthy, White women. Health Psychol. 19, 586–592. (ZKPQ). J. Personal. 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All-cause and cause-specific Conflict of Interest: The authors declare that the research was conducted in the mortality by socioeconomic status among persons employed in 27 US absence of any commercial or financial relationships that could be construed as a states, 1984–1997. Am. J. Public Health 94, 1037–1042. doi: 10.2105/ajph.94. potential conflict of interest. 6.1037 Wang, P., and Tang, C. H. (2019). The Effects of Social Class on Individuals’ Publisher’s Note: All claims expressed in this article are solely those of the authors Decision-Making Tendencies in a Prestige-Money Game: Social Value or and do not necessarily represent those of their affiliated organizations, or those of Instrumental Value? J. Gambling Stud. 35, 1283–1302. doi: 10.1007/s10899-019- the publisher, the editors and the reviewers. Any product that may be evaluated in 09827-2 this article, or claim that may be made by its manufacturer, is not guaranteed or Winkleby, M. A., and Cubbin, C. (2003). Influence of individual and neighborhood endorsed by the publisher. socioeconomic status on mortality among black, Mexican-American, and white women and men in the United States. Psychol. Addict. Behav. 57, 444–452. Copyright © 2021 Urieta, Aluja, Garcia, Balada and Lacomba. This is an open-access doi: 10.1136/jech.57.6.444 article distributed under the terms of the Creative Commons Attribution License Zuckerman, M. (2005). Psychobiology of personality, 2nd Edn. Cambridge: (CC BY). The use, distribution or reproduction in other forums is permitted, provided University press. the original author(s) and the copyright owner(s) are credited and that the original Zuckerman, M., and Kuhlman, D. M. (2000). Personality and risk-taking: Common publication in this journal is cited, in accordance with accepted academic practice. No biosocial factors. J. Personal. 68, 999–1029. doi: 10.1111/1467-6494.00124 use, distribution or reproduction is permitted which does not comply with these terms. 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