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Decisive Personalities: Neuroticism and Perceptual Decision-Making Frank Alejandro Alvarez Perez

Bachelor scriptie

Begeleider: Leendert van maanen 30-06-2017

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Abstract

The current study addresses the relation between Neuroticism and perceptual decision-making. This relation was hypothesised to be linked to the relation between anxiety and impulsiveness and the rate of accumulation of evidence. The 45 participants partly filled out the NEO-PI-R (Costa & McCrae, 1992) and did a expanded jugdment task. To measure their decision-making process, the EZ-model was used. A multiple Linear regression model was set up to predict the rate of evidence accumulation by the facets of Neuroticism. The results were insignificant. The predicting variables: the facets of Neuroticism, did not predict the rate of evidence accumulation. This lead to the conclusion that the relation between Neuroticism and performance is possibly not linked to the relation between anxiety and impulsiveness and the rate of accumulation of evidence.

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Decisive Personalities: Neuroticism and Decision-Making

Decisions, in general, can be of any size and relevance. Many external factors, as well as internal ones, can influence the process of decision-making. The external factors could be anything that affects a person, as well as another. An external factor could be seen as an influencer on the individual from his environment. For example, the weather could affect whether decide to go running or not. On the contrary, an internal factor is a characteristic that differs between individuals. To clarify this, let's look at the scenario where two different people (A and B) are thinking of going for a run at the same moment. If there would be a difference in choice, besides any random or unsystematic explanation, like casual fatigue, personality could be a factor that explains why the choice of person A differs from the choice of person B. The present article aims at the relation between personality and decision-making. To give an insight of how personality is thought to be structured, a brief introduction to personality theory is given next.

Personality, as various as the imagination can think of, was reduced and

conceptualised by Costa and McCrae (1978). Their approach, best-known as the Big-Five approach of personality, states that personality can be seen as a set of five traits. In one way or another, these traits succeed to explain the characteristics that people share in terms of

personality. The five traits are Openness to experience, Agreeableness, Conscientiousness, Extraversion and Neuroticism. These traits have different facets. For example, sensation-seeking is one of the six facets of Extraversion, trust for Agreeableness, and competence for Conscientiousness. Neuroticism will be explained more extended because the main question within this study addresses the relation between Neuroticism and performance on perceptual decision-making.|

Neuroticism, one of the five documented personality traits, is often translated as the tendency to emotional instability. According to the Big Five approach, Neuroticism consists the following facets: hostility, anxiety, self-consciousness, impulsiveness and vulnerability to stress. Table 1 shows an overview of the five high-level traits and their facets. Bolded are the facets of impulsiveness and anxiety. Both will be explained in detail because the hypothesised relation between Neuroticism and performance on perceptual decision-making is thought to be linked to the relation between anxiety and impulsiveness on the decision-making process. High scores on anxiety reflect a tendency to be more nervous, quickly upset, tensed and also to worry more often, than low scores on anxiety. Furthermore, Anxiety is perhaps best known as an emotion, as it is often associated with fear (Costa & McCrae, 1992). However,

throughout this article, it is referred to anxiety as a trait. An emotion is rather a state. Impulsiveness, as stated in the Big Five description, is the incapability to reject temptations, suppress impulses and regulate feelings. High scores on impulsiveness reflect that the individual experiences such temptations, impulses or feelings to such an extent, that it becomes extremely hard, if not impossible, to not submit to those. It should be noted that impulsiveness does not refer to spontaneity, risk-taking or hasty decision-making. It remains nevertheless interesting to see if there is a relation between such a thing that is called

impulsiveness on the process of decision-making. More about this will be explained in the expectations section. The relation between personality and decision-making that is known so

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far, regards the kind of decision-making that extends over time. For instance, career-related choices, investments, etc. In the next section, we attempt to clarify what kind of relation there is found between several personality traits and this kind of decision-making.

Table 1. An overview of the five high-level traits and lower-level traits, as proposed by the Big Five approach.

Openness to Experience

Conscientiousness Extraversion Agreeableness Neuroticism

Fantasy Competence Warmth Trust Anxiety

Aesthetics Order Gregariousness Straightforwardness Hostility Feelings Dutifulness Assertiveness Altruism Depression Actions

Achievement-Striving

Activity Compliance

Self-consciousness Ideas Self-Discipline

Excitement-Seeking

Modesty Impulsiveness

Values Deliberation Positive Emotion

tendermindedness Vulnerability

Various Personality traits could be of relevance when it comes to decision-making. Knowing that personality can be seen as an entity with numerous traits, it is easier to see which specific trait influences behaviour, and more specifically, decision-making. For instance, extraversion was found to be associated with driving behaviour (Jonah, 1997). Similarily, Vollrath, Knoch and Cassano (1999) found that agreeableness and

conscientiousness are related to risky health behaviours. Regarding the relation between personality and decision-making, Lauriola and Levin (2001) found that different traits are good predictors for risky decision-making. According to their results, Openness to Experience was associated with more risky decision-making and Neuroticism was associated with less of that. Besides, Extraversion and Conscientiousness seem to influence career decision-making, however, mediated by the so-called life task dimensions (Shafer, 2000). In the same light, Leong and Chervinko (1996) found that negative personalities are positively related to indecision, regarding career-related decision-making. Such negative personality traits being fear of commitment, perfectionism and self-consciousness. These previous findings suggest that personality influences behaviour and decision-making. However, In this article, the ultimate question is whether Neuroticism has a convincing relation with decision-making. Taking a closer look at Neuroticism and decision-making might be clarifying. A brief review of previous studies shows the relation between Neuroticism and decision-making that is known so far.

Denburg and colleagues (2009) found that older participants had a worse performance on a decision-making test than the younger participants. The decrease in performance was related to elevated measurement in Neuroticism. This decision-making test was a so-called

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medical decision-making test, which focusses on gain and loss evaluation, general risk-taking and others. Similarly, Fuqua, Seaworth and Newman (1987) found that Neuroticism is related to career-related decision-making. Furthermore, Volrath and colleagues (1999) not only found that Agreeableness and Conscientiousness show a relation with risky decision-making, but also Neuroticism seemed to be related. Lauriola’s and Levin’s study (2001), that was mentioned before, also included Neuroticism. Neuroticism, as well as Openness to

Experience, was found to be related to risky decision-making. Having illustrated the relation between Neuroticism and decision-making it becomes salient that most of the literature is done in the light of risk-related behaviour or decision-making related to topics that are rather relevant in the long-term, such as career-related decisions or decisions that come with an investment. Little is known about the relation between personality and perceptual making, a kind of making more relevant in the short-term. What perceptual decision-making is, and how it could relate to Neuroticism, will become clear next.

Perceptual decision-making is often conceptualised as the accumulation of evidence. When enough evidence is accumulated, the choice is made. The sufficient amount of evidence is set by the individual. This threshold relates to response time (RT) in the way that higher a treshold result in slower RT if the rate of the evidence accumulation is fixed. This implicates that RT is also dependent on the evidence accumulation rate, resulting in a trade-off triad. higher rates lead to the same RT if the boundaries are set high, as lower rates will lead to the same RT if the boundaries are set low. In general, RT and accuracy-rate are often used to operationalize performance.

Taking in consideration the nature of perceptual decision-making, the question whether Neuroticism and perceptual decision-making are related may rise. In the light of this question Stelmack, Houlihan and McGarry-Roberts (1993) actually found that Neuroticism was related to the performance on perceptual decision-making. Neuroticism happened to be negatively related to RT. However, it remains unclear how such relation exists.

To clarify the relation between Neuroticism and performance on perceptual decision-making, that Stelmack and colleagues (1993) found, this study directed the focus to the relation between anxiety and impulsiveness, and the performance on perceptual decision-making. In the attempt to answer the main question, only impulsiveness and anxiety were included because these two facets were thought to have the strongest influence. Both are namely thought to be related to RT, however in a contrary way, due to their intuitional implications for the process of accumulating evidence. The implications will be further explained next.

The hypothesised relation between Neuroticism and performance of perceptual

decision-making can be explained through the effects of anxiety and impulsiveness on RT. On the one hand, Neuroticism would influence RT through anxiety. We hypothesise that anxiety could make the way that individuals use to handle the evidence ambiguous, resulting in poor consistency regarding the direction of the evidence accumulation. This effect of anxiety could be rooted in the overthinking nature of a neurotic individual. The overthinking element, may be the cause for the ambiguity in evidence handling. On the other hand, Neuroticism would influence RT through impulsiveness. A second hypothesis is that impulsiveness, irrespective of the item characteristics, would make the individual handle information as being

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information accumulation. In other words, they would accumulate the evidence on one outcome of the paradigma more recklessly, that is, without considering the other option. According to the Big Five approach, the kind of impulsiveness included in the theory does not regard the kind of impulsiveness that is related to hasty decision-making. However, if there is a different kind of impulsiveness for hasty decision-making than for impulse regulation, as stated by the Big Five, there could be an underpinning characteristic that connects them both. Resulting in the occurrence of both kinds in the same individual. Perhaps this characteristic is a general impulsiveness that is responsible for all kind of impulsiveness related behaviour. Therefore, it is believed that both paths contribute to the relation of Neuroticism and RT.

The next section will contain further explanation of the instrument that is used to measure Neuroticism, anxiety and impulsiveness: the NEO-PI-R questionary. It will also become clear how Diffusive Decision Model (DDM) will serve to approach this questions and how the two hypotheses are translated to terms of the model.

Methods Participants

The participants, 45 in total (27 females), were all native Dutch speakers with a mean age of 22.58 years (SD = 2.38). They were recruited via the website of the UvA psychology lab and, therefore, they happened to be all students. There was no other compensation than one research credit for taking part in research. Furthermore, the participants were only accepted if they were native in Dutch and had normal vision, or corrected to normal.

Material

The NEO-PI-R was used to measure Neuroticism, anxiety and impulsiveness. This revised version of the NEO Personality Inventory was published in 1992 by Paul and McCrae. The questionnaire consists of 240 questions related to the five hypothesised personality traits and the 30 facets. The questions could be answered on a five-point Likert scale. In the current study the Dutch version was used (Hoekstra, Ormel & De Fruyt, 1996), and only the items related to Neuroticism (6 items per facet, 48 total) were presented to the participants. Item 206 of the NEO-PI-R (Dutch) will serve as an example of a Neuroticism-related item: “Wanneer alles fout lijkt te gaan, kan ik toch nog goede beslissingen nemen”, which literally means: “When everything seems to go wrong, I can still make good decisions”. In this way, the predictors were measured: anxiety, impulsiveness and Neuroticism in general. How the dependent variable was measured will become clear next.

The DDM was used to measure the dependent variable: accumulation of evidence. DDM is often used to model perceptual decision-making, as it maps the cognitive processes involved in making a binary decision. Such choices should be of the single-stage type, so no multiple-staged choices, such as presented in reasoning tasks, were multiple factors should be considered and manipulated mentally. Moreover, the decision-time should be rather short. This means that RT is less than 1000 to 1500 ms (Ratcliff & McKoon, 2008). The DDM

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assumes that to make a decision, a process of evidence accumulation occurs. The decision is made when the evidence accumulates to the point where it reaches one of the response

criteria, or boundaries (a, 0). The rate that characterises the process of evidence accumulation is referred to as the drift rate (v), always starting at z, the starting point. When z= a/2, there is no bias. That means, there is no preference or probability of choosing one option over the other. The starting point is exactly in the middle. Figure 2 illustrates the model and its

parameters. Note that RT is dependent of v, and a and 0. Any changes in these two parameters result in different moments of decision. However, a simplification of this mode was used, the EZ-model (Wagenmakers, Van der Maas & Grasman, 2007). This model is a simplified DDM in the sense that it assumes that there is no bias (z=a/2). One of the convenient aspects of the model is that it distincts v from boundary separation (a, 0). In other words, the model permits extracting v from the decision-making process, and that is exactly what is aimed for. Also, the non-decision time (ter) can be modelled. Trials with RT in the non-decision time are trials that

are faster or slower than the correct/wrong responses, on average. Therefore, these trials are not considered normal trials, but rather trials that have been made carelessly (too fast or too slow, without thinking). Irrespective of this, all trials are of interest, because that is how the distribution of RT is shaped.

Figure 2. Illustration of DDM and its parameter. Drift rate is denoted as v, the boundaries as a and 0, and z is the starting point. RT refers to the reaction time. Note: retrieved from Ratcliff & McKoon (2008).

Software

The Software used during the entire experiment is called Psychopy. Psychopy is an open-source software meant to generate psychological tests. Mainly perceptual ones. Furthermore, RT was measured using the in-built detection function for response delay of Psychopy.

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Task

The task was an expanded judgement task. The participants were instructed to observe which of the two blinking squares appeared to blink more often on average. They were asked to look at a so-called fixation cross at the center of the screen, between the spots where the two squares would appear later, to draw back the attention of the participant to the center of the screen. The cross appeared on-screen during 0.30 seconds. The participants also were told to make the choice rather quick and accurate, by pressing the 'z' key to choose the left square or the 'm' key to choose the right square. After the decision was made, a short moment of feedback (1.00 second) documented whether the trial was correct or not, automatically followed by the next trial. If the participants did not make a choice before 10 seconds, then the trial ended and again an on-screen message appeared. This time to encourage quicker responses. The task consisted of a total amount of 200 trials.

Procedure

The participants were asked to come to the psychology laboratory of the University of Amsterdam. At their arrival, they were asked to fill in a consent form. The questionnaire, as well as the perceptual decision-making task, were presented on a computer. At the beginning of each block, the instruction was given on-screen to make sure they understood the

principles. The experiment finished after the last trial of the last block of the perceptual task and lasted about one hour. The experiment consisted of a general structure of four blocks. In the first block the participants had to answer 35 questions, and in the second block, 100 trials of the decision making task were presented. The third and the fourth block were identical to the previous two, except that the questions in the third block were different than the questions in block 2. Figure 3 visualises the design of the experiment.

Figure 3. Visualisation of the design. After the general instruction, the participants were prompted to fill in a questionnaire alternated with a task.

Analysis

For the analysis, a multiple linear regression model (MLRM) was used. In short, this model is an approach to studying the relation between two or more variables. The dependent variable is the one to be explained or predicted by the explanatory variables, or predictors. In

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this study the dependent variable is v and the explanatory variables are the six facets of Neuroticism. Such an expression would look like:

v ~ anxiety + hostility + depression + self-consciousness + impulsiveness + vulnerability. No interaction was expected to occur between the predictors, because the facets of Neuroticism, although they correlate with each other, were thought to acting independently in the decision-making process. In the following section, the result of the analysis will be

inspected and further explained in terms of the hypothesis.

Results

The data collecting provided us with information such as the scores on Neuroticism and all of its facets. Besides, the mean and variance of RT, as well as the proportion of correct answers, were used as input for the EZ-model, which gave the parameter estimation as the output: v, 0 and a and also Ter.

Before conducting the analysis, the data was checked for abnormalities. Any

problematic case was excluded. In fact, the data of two out of 45 participants were excluded for reasons of being corrupted. One file did simply not open and was, therefore, impossible to be inspected. The second case was the data of a participant that was suspected of not

following the instructions. Visualisation of the data illustrated extremely quick RT and

minimal variance. Besides all of these responses were made on the right key, there was no left key used in the sequence. This might be indicating to what we could call ‘button mashing’, the simple act of repeatedly pressing the key to rush through the trials. After the exclusion of these two participants, the analysis was done with the data of the remaining 43 participants.

Analysis

Before testing the hypotheses, a linear regression model was set up to predict the mean RT of each participant based on their score on Neuroticism. This was done in the light of previous research of Stelmack and colleagues (1993), who found that RT and Neuroticism were related. The regression analysis was not significant F(1, 41) = 0.0612, p = 0.8059, with an R2 of 0.00149. These finding, although contradicting with what Stelmack and colleagues found, could also be explained by the trade-off relation between RT, v and a. That means that the negative effect of a low v on RT, could be compensated by the positive effect of a high a on RT. For this reason, despite that no relation was found between RT and Neuroticism, we advanced to the hypotheses testing.

Expected was that anxiety and impulsiveness would predict v. It was thought,

specifically, that higher scores on anxiety would be associated with a lower v, and that higher scores on impulsiveness would be associated with higher v. An MLRM was calculated to predict v based on the six facets of Neuroticism. The regression analysis was not significant F(6, 36) = 0.286, p = 0.940, with an R2 of 0.046. No coefficient was significant either (table

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5). In other words, none of the independent variables were significant predictors for v. In the light of our hypotheses it should be emphasised that neither anxiety, nor impulsiveness, nor Neuroticism in general, were significant predictors. Thus, irrespective of the existance of a relation between Neuroticism and RT, there seem not be a relatin between anxiety and impulsiveness, and v. Despite that no significance was found for the model, other findings, although exploratory, were found to be striking and relevant to be mentioned for future analyses. These findings will be discussed next.

A crucial finding is that there was no correlation between the neuroticism-related components and any of the decision-making components. For the correlation tests, Pearson’s method was used. Table 4 shows a correlation matrix the columns. A possible cause and interpretation will be addressed in the discussion section.

Table 4. Correlation Matrix. Shows the correlation of all of the components of Neuroticism (1) and the decision-making relevant data(2). In bold: correlations between (1) and (2): none was significant.

A n x.

Host Depr Self-cons

Imp Vuln Mea n RT Acc Var RT v A Ter Anx. - .42 .70 .65 .45 .63 .02 -.11 -.16 -.08 -.09 .28 Host. - .61 .49 .35 .52 -.06 -.15 -.17 -.02 -.11 .17 Depr. - .63 .39 .52 -.01 -.19 -.13 -.12 -.09 .19 Self-cons. - .27 .59 .04 -.10 -.08 -.07 -.04 .20 Imp. - 0.29 -.14 -.02 -.15 .09 -.09 -.07 Vuln. - -.01 -.20 -.19 -.11 -.14 .33 Mean RT - .77 .87 -.45 .92 .18 Acc. - .66 .05 .76 .15 Var. RT - -.53 .95 -.29 v - -.56 .37 a - -.19 Ter -.

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Table 5. Unstandardized error, standardised error, t-value and the p-value of each coefficient.

Estimate Std. Error t-value p-value

Intercept 0.131 0.031 4.195 0.001 Anxiety 0 0.001 0.054 0.957 Hostility 0 0.001 0.41 0.684 Depression -0.001 0.001 -0.734 0.468 Self-Consciousness 0 0.002 0.11 0.913 Impulsiveness 0.001 0.001 0.832 0.411 Vulnerability -0.001 0.002 -0.533 0.598 Discussion

Already mentioned was the fact that the sample consisted of solely 43 participants, which is considerably small for correlational research. This shortcoming could possibly be the reason for the fact that no correlation was found between any component of Neuroticism and decision-making. Especially, because it contradicts previous studies that actually found Neuroticism and decision-making to be related. The perhaps too little sample could be biased and, thus, infer in the analysis. Therefore, it should not be ignored when evaluating the findings. A more sophisticated alternative is an explanation to the findings that has nothing to do with the sample size. It simply takes into account the differences between decision types.

In contrast to the previous studies, that focussed on multi-stage decisions (1) involving the future (e.g. investments), and involving more than two possibilities, this study put the focus on the perceptual and the single-stage type of decision-making (2), which is quick in terms of time-span (1000 to 1500 milliseconds, perhaps). The reason that this could be an explanation for the findings, is that the second type (2) of decision making does not allow personality, at least not Neuroticism, to infer with the decision-making progress, leaving no room for personality to influence such things as evidence accumulation and evidence

thresholds. This could explain why there is no relation between Neuroticism and performance on perceptual decision-making, at all. In the next section, the conclusions will be made considering the shortcomings and alternative explanations for the findings.

Conclusion

In this study, it was proposed that the relation between Neuroticism and performance could possibly be linked to the relation between anxiety and impulsiveness, and evidence

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accumulation. Principally, there was no relation found between Neuroticism and RT. This is contradicting to what Stelmack, Houlihan and McGarry-Roberts (1993) found. There was neither a relation between anxiety nor impulsiveness and evidence accumulation. More striking was that no relation was found between any of the components of Neuroticism and decision-making at all. Altogether, this evidence leads to the conclusion that if there was any relation between Neuroticism and performance, it is not linked to the relation between anxiety and impulsiveness, and evidence accumulation. A recommendation for future studies is that they take a larger sample of the population, consisting of an equal numbers of women and men. Decision-making remains an interesting topic to be researched and specially when it comes down to the different personalities and their relation, or perhaps, consequences on the decision-making process.

References

Costa, P. T., Jr., & McCrae, R. R. (1992). NEO PI-R professional manual. Odessa, FL: Psychological Assessment Resources, Inc.

Costa Jr, P. T., & McCrae, R. R. (1978). Objective personality assessment. The clinical psychology of aging (pp. 119-143). Springer US.

Denburg, N. L., Weller, J. A., Yamada, T. H., Shivapour, D. M., Kaup, A. R., LaLoggia, A., ... & Bechara, A. (2009). Poor decision making among older adults is related to elevated levels of neuroticism. Annals of Behavioral Medicine, 37(2), 164-172.

Fuqua, D. R., Seaworth, T. B., & Newman, J. L. (1987). The relationship of career indecision and anxiety: A multivariate examination. Journal of Vocational Behavior, 30, 175-186. Hoekstra, H. A., Ormel, J., & De Fruyt, F. (1996). NEO persoonlijkheids vragenlijsten:

NEO-PI-R: NEO-FFI. Swets Test Services (STS).

Johnson, J. E., & Powell, P. L. (1994). Decision making, risk and gender: Are managers different?. British Journal of Management, 5(2), 123-138.Jonah, B. A. (1997). Sensation seeking and risky driving: a review and synthesis of the literature. Accident Analysis & Prevention, 29(5), 651-665.

Lauriola, M., & Levin, I. P. (2001). Personality traits and risky decision-making in a controlled experimental task: An exploratory study. Personality and Individual Differences, 31(2), 215-226.

Leong, F. T. L., & Chervinko, S. (1996). Construct validity of career indecision: Negative personality traits as predictors of career indecision. Journal of Career Assessment, 4, 315-329.

Peirce JW (2009) Generating stimuli for neuroscience using PsychoPy. Front. Neuroinform. 2:10.

Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: theory and data for two-choice decision tasks. Neural computation, 20(4), 873-922.

Schubert, R., Brown, M., Gysler, M., & Brachinger, H. W. (1999). Financial decision-making: are women really more risk-averse?. The American economic review, 89(2),

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381-385.Shafer, A. B. (2000). Mediation of the Big Five's effect on career decision making by life task dimensions and on money attitudes by materialism. Personality and Individual Differences, 28(1), 93-109.

Stelmack, R. M., Houlihan, M., & McGarry-Roberts, P. A. (1993). Personality, reaction time, and event-related potentials. Journal of Personality and Social Psychology, 65(2), 399. Wagenmakers, E.-J., van der Maas, H. L. J., & Grasman, R. P. P. P. (2007). An EZ-diffusion

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