Personality

The bivariate analysis of the ‘Big Five’ dimensions of personality are included in the chapter on Background Characteristics because, while not at the center of inter-est for our research quinter-estions, they may have an association with the subjective

157

measures of economic vulnerability and therefore need to be controlled for. A point biserial correlation coefficients was used for those four dimensions of personality that follow a normal distribution and were treated as interval data: neuroticism, openness, extraversion and agreeableness (Appendix 13.11). The distribution of conscientiousness, which does not follow a normal distribution, was treated at the ordinal level (Appendix 13.12).

None of the five personality dimensions has more than just a weak effect on any of the three measures of economic vulnerability. The strongest and highly signifi-cant effect is between openness and obj_ev (rpb = −0.10, p < 0.001) meaning that low income is associated with a lower score on the openness scale. A weak positive and significant association exists between neuroticism and self-assessed economic vulnerability (rpb = 0.08, p = 0.002). The coefficient of determination is, however, very small (r²pb = 0.064), variation in the score of neuroticism explaining less than 1% of the variation in sa_ev. It would therefore be a mistake to conclude that the subjective measurement angle is per se influenced by personality. In fact, it is note-worthy that despite the wording of the survey item, based on the question ‘to what extent are you worried’, there is no statistically significant correlation between perc_ev and neuroticism (rpb = 0.06, p = 0.011). Furthermore, no association was detected between any of the measures and agreeableness, extraversion and conscientiousness.

These results signify that there exists a great diversity of psychological profiles for each vulnerable group as identified by the three measures. However, we cannot exclude that certain vulnerability types are associated with specific personality traits. It is for instance likely that the difference between types XXA and XXB can at least partly be explained by differentials in the levels of neuroticism and not only, as the vulnerability framework suggests, by differences in the successfulness of coping strategies and role strains (risk constellations 2a and 2b in Table 5.2). In order to be able to assess whether the neurotic personality type has an influence on the Perceived Measure in the case of specific risk constellations, we will test a series of specific hypotheses by comparing pairs of vulnerability types ending in either B or A.

We begin by conducting a Kruskal-Wallis test, a non-parametric omnibus test, in order to determine whether there is a statistically significant difference in the posi-tion (median) of neuroticism between at least two vulnerable populaposi-tion groups within the typology. After verifying the assumption that neuroticism follows the same distribution within each group of the Vulnerability Typology, we calculate the Kruskal-Wallis H, χ²(7) = 23.8, p = 0.001, based on which we reject the null hypoth-esis that all population groups have the same median score of neuroticism.

We proceed to examine the difference in medians of the specific population groups we are interested in. In each case, our null hypothesis is that there is no sta-tistically significant difference in the median scores of neuroticism between the two compared groups (H0 = n XXA = nXXB). For each test, we formulate the alternative hypothesis, that group XXA has a lower median score of neuroticism than group XXB. Table 13.1 (right column) shows the results of the Wilkoxon rank-sum test, which calculates the Mann-Whitney Test two sample statistic, an effect size

mea-13.6 Personality

sure that calculates the probability of an observation being in one group versus the other group (Goldstein 1997).

Two comparisons of population groups, Ha2 and Ha3, yielded significant results (p < 0.05): for Ha2, we see that for 40% of the pairs, the score of neuroticism is lower for ABA than for ABB or, put differently: the prevalence of neuroticism is higher in group ABA than in group ABB. This finding deviates from the expected effect we predicted by our theoretical model, but is compatible with previous findings on the multifaceted construct of neuroticism: it not only captures a propensity to emotional lability and worry, but also reflects an absence of optimism (Scheier et al. 1994).

Our results therefore suggest that in the case of economic vulnerability among Swiss pensioners, the ‘pessimism component’ of neuroticism is more clearly at work than the emotion-based components.

For Ha1 the result⁴ is non-significant but nonetheless interesting if we recall that type AAB is a type that we were not able to deduce logically from the risk constel-lations provided by the vulnerability framework (see Table 13.1). In fact, it seems illogical that someone who has no difficulties in making ends meet would still worry about not having enough money to cover current expenses. Differences in personal-ity seemed a plausible explanation to account for the existence of this – theoreti-cally – unlikely type but as we see, the personality trait neuroticism is not to be blamed for why respondents of type AAB are worried.

For Ha3, the effect goes in the expected direction: for 62% of the pairs, the score of neuroticism is lower for BAA than for BAB. This is the only type, where the Perceived Measure is significantly associated with higher scores of neuroticism, namely in the combination with objective vulnerability and a positive self-assessment.

In summary, we have found that the personality trait of neuroticism is the only personality dimension of theoretical relevance that is revealing a statistically signifi-cant relationship with economic vulnerability. Since it explains only a very small share of variance in the Vulnerability Typology, we conclude that this variable is of minor explanatory power and does therefore not need to be retained in the multivari-ate analysis.

Table 13.1 Wilkoxon rank-sum test for neuroticism and types of vulnerability Alternative hypothesis (median

group 1 < median group2) z

Prob >

|z| P{median(group1) < median(group2)}

Ha1 = nAAA < nAAB 1.51 0.132 0.54 Ha2 = nABA < nABB −2.11 0.035 0.40 H_a3 = nBAA < nBAB 1.99 0.047 0.62 H_a4 = nBBA < nBBB 1.43 0.154 0.59

4 The score (e.g. 0.54 for Ha1 = nAAA < nAAB) shows the proportion of ‘pairs’ for which the score of group 1 is smaller than the score of group 2. The number of pairs is defined by the number of people in the first group (e.g. AAA  =  1099) times the number of people in the second group (AAB = 129). For Ha1, among the 141,771 pairs, 54% were lower for AAA than for AAB, which is a non-significant result.

159

Appendices

Appendix 13.1: Sample Distribution by Sex and Measures