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Article

More of the Same? Comparing the Personalities of Ex-Spouse and New Partner after Divorce

by
Sascha Spikic
*,
Dimitri Mortelmans
and
Dries Van Gasse
Department of Sociology, Faculty of Social Sciences, University of Antwerp, 2000 Antwerp, Belgium
*
Author to whom correspondence should be addressed.
Soc. Sci. 2021, 10(11), 431; https://doi.org/10.3390/socsci10110431
Submission received: 20 September 2021 / Revised: 24 October 2021 / Accepted: 1 November 2021 / Published: 9 November 2021
(This article belongs to the Special Issue Divorce and Life Course)
Browse Figure
Versions Notes

Abstract

:
The similarity of the Big Five personality traits of ex-spouses and new partners was examined post-divorce. The notion that divorcees replicate their partner choice (fixed-type hypothesis) was tested against the hypotheses that they learn to select a new partner with more marriage-stabilizing personality traits than their former spouse (learning hypothesis), or are constrained by marriage market forces to repartner with someone who has less stabilizing personality traits (marriage market hypothesis). Data was derived from a Flemish study that sampled divorcees from the national register. The sample consisted of 700 triads of divorcees, their ex-spouses, and their new partners. The analysis results rejected the fixed-type hypothesis and instead supported both the learning hypothesis and the marriage market hypothesis, with higher order repartnering supporting the latter. Women also seemed to validate both hypotheses, as their partner comparison showed decreases in both stabilizing traits (conscientiousness and agreeableness) and destabilizing traits (neuroticism and extraversion). Overall, the results seem to suggest that divorcees do not repartner with someone of the same personality as their ex-spouse, and they are in some cases constrained by marriage market forces to repartner with less stabilizing personalities, while in other cases they are able to improve their partner selection.

1. Introduction

In contemporary society, serial monogamy is often assumed to be the norm. Since divorce and separation have become less stigmatized, more and more people leave dysfunctional relationships and pursue a future without their former partner (Bernardi et al. 2018). In many cases, the period of singleness is just a transitional time in between relationships (Koren 2016). However, those new relationships and remarriages have been demonstrated to be far less stable than first time marriages (Booth and Edwards 1992). Still, very little is known about the continuation of destabilizing factors into post-divorce relationships. The explanations for these trends can be very diverse and stem from multiple disciplines such as, among others, attachment theory (Bowlby 1969) or the parental gradient (Amato and DeBoer 2001). In this study, we focused on partner personality as a possible continuing destabilizer. Previous research demonstrated that certain personality traits can increase the risk of relationship dissolution (Karney and Bradbury 1995; Roberts et al. 2007), and because personality has been shown to be relatively stable (Roberts et al. 2006), these relationship instabilities are present throughout the adult life course. However, not much is known about how this translates into partner choice or if destabilizing personality matching replicates itself with each new relationship. Therefore, we aim to expand the existing literature by addressing the research question ‘Are the Big Five personality traits of one’s ex-spouse similar to those of his or her new partner?’. Thus far, there has not been any research addressing this personality transition to a post-divorce relationship. An additional contribution is provided by examining if post-divorce marriage market forces shape the evolution in personality traits across partners, or if divorcees are able to learn from past experiences and select more marriage-stabilizing personalities.

2. Background

Selecting a romantic partner is a complex process that entails a great deal of personal decision-making. This process only becomes more complicated after a divorce. That said, most divorcees tend to repartner relatively fast. Using Belgian register data, Pasteels and Mortelmans (2017) found the average time to repartner to be 2.24 years. Bernardi et al. (2018) demonstrated that in Belgium, even lone parents have a medium time to repartnering of only four years. When moving through life, we often look back and re-evaluate our partner choices. Although most partner features are easily comparable, such as educational attainment, physical attractiveness, income, and so on, the elements that are less noticeable are intrinsic attributes. One of these intrinsic attributes, on which we focus throughout this article, is personality.

2.1. The Big Five

The Big Five traits are a personality model that contains five core traits which reflect someone’s entire personality. These traits are neuroticism (e.g., anxious, depressed, emotionally unstable), extraversion (e.g., gregarious, energetic, talkative), conscientiousness (e.g., organized, self-regulating, high impulse control), agreeableness (e.g., kind, empathetic, trusting), and openness to experience (e.g., novelty seeking, curious, original).
People tend to have a universal preference for partners with certain scores on the Big Five traits. By examining 33 countries across six continents, Buss et al. (1990) found that the most desirable partner traits are linked to low scores on neuroticism and high scores on the other four traits. However, these desirable trait scores are not necessarily the most marriage-stabilizing. Extraversion and openness, both considered to be desirable traits, do not tend to decrease the risk of divorce (Roberts et al. 2007). Some studies found these two traits to actually increase the divorce risk (Bentler and Newcomb 1978; Solomon and Jackson 2014), Overall, empirical studies point towards agreeableness and conscientiousness as stabilizing traits and neuroticism as a destabilizer. Although openness and extraversion have received less empirical evidence, these traits also seem to be more likely to increase the risk of separation rather than decrease it (Bentler and Newcomb 1978; Roberts et al. 2007; Solomon and Jackson 2014; Spikic and Mortelmans 2021).

2.2. The Fixed-Type Hypothesis

Popular belief states that people have a fixed preference for certain qualities they value in a romantic partner, and thus, their partners often tend to be similar. This usually refers to sociodemographic variables, such as education, income, religion, and so on. Recently, some authors have questioned if similarity among someone’s romantic partners also includes more internal properties, namely personality traits. One possible explanation as to why individuals would choose their partner according to a fixed type could be found within the process of continued homogamy, where someone partners and repartners homogamously, leading to the new and ex-partner resembling each other because of the similar characteristics with their shared partner.
Empirical support for the existence of a fixed personality type is offered by Park and MacDonald (2019), who examined personality profile similarity among current and ex-partners in a German sample. Their study is the only one of its kind, involving self-reported personality measurements of both the new and ex-partner. Enough correspondence between personality profiles was found to conclude the presence of a fixed personality type, even after accounting for normative responses and similarity to the shared partner. In other words, the partners were uniquely similar, in a way that did not resemble their shared partner. In contrast to this person-centered approach of profile similarity, Štěrbová et al. (2019) investigated trait similarity among consecutive partners. The study, which was limited to mothers and their lifelong partners, also showed significant correspondence on the Big Five traits. However, the personality of the partners was reported by the shared partner and therefore influenced by the quality of the romantic relationship.
Hypothesis 1a.
The ex-spouse and new partner have similar Big Five personality traits (i.e., fixed type hypothesis).

2.3. The Learning Hypothesis

An alternative hypothesis to the fixed type hypothesis is the learning hypothesis. This notion is derived from Gelissen (2004), who coined the term when referring to the ability to achieve a more homogamous new relationship when repartnering. Gelissen (2004) therefore assumed that homogamy is a stabilizing force when he tested the learning hypothesis on sociodemographic variables such as education and social class. However, we argue that the same interpretation is unlikely to pertain to personality traits, because personality homogamy and personality matching in general have not been demonstrated to play a significant stabilizing role, at least not with regard to the Big Five traits (Solomon and Jackson 2014). In other words, there is not much to gain in learning to partner homogamously. Consequently, in this study, we interpret the learning hypothesis somewhat differently, namely as the ability to learn from past mistakes and increase the chances of marital stability by selecting a new partner who has more stabilizing personality traits. However, contrary to personality homogamy, which is often the result of a shared environment, the learning hypothesis is based on actively seeking a more marriage-stabilizing partner. Therefore, this hypothesis requires a somewhat unconstrained supply of potential partners. One could argue that because personality is an internal force, it is not as clustered into social groups as other sociodemographic variables are, and therefore, the pool of partner personalities is somewhat more evenly spread.
Hypothesis 1b.
The new partner is less neurotic, extraverted and open, and more agreeable and conscientious than the ex-spouse (i.e., learning hypothesis).

2.4. The Marriage Market Hypothesis

Although previous research offers some support for a fixed personality type, none of these studies has directly examined the Big Five personality traits. Furthermore, one can call into question the assumption of the fixed-type hypothesis and learning hypothesis, namely that partner choice is unconstrained in such a manner that one can easily find a new partner who resembles one’s ex-spouse or is more marriage-stabilizing than one’s ex-spouse. That freedom of partner choice and lack of restrictions might seem plausible in the first marriage market (FMM), but in contrast to the study of Park and MacDonald (2019), which overwhelmingly examined premarital relationships, the current study compares predivorce to post-divorce partners. We defined post-divorce partners broadly to also encompass nonmarital relationships that are formed after divorce. These post-divorce relationships or remarriages are formed in the post-divorce marriage market (PDMM), which differs from the FMM. Using a market perspective on relationship formation results in abstraction from the complexities of relationship formation. Nevertheless, using this perspective serves as a heuristic instrument unveiling the personality dynamics that are addressed in this study. In the PDMM, one has to choose between potential mates who were unable to find a partner in the FMM or who have separated from their partner or spouse. One could argue that the ex-spouse is, by definition, also a divorcee and therefore this distinction between the FMM and PDMM becomes irrelevant. However, it is unlikely that all divorcees possess equally destabilizing traits. More likely, there will be some individuals that possess highly destabilizing personalities, which forces them to reside in the PDMM for a longer period of time or to return to the PDMM multiple times. This discrepancy between the FMM and PDMM can have important implications. One should not simply extrapolate the similarity between partners in premarital relationships to the similarity between an ex-spouse and a post-divorce partner.
Consequently, unlike the fixed-type hypothesis and the learning hypothesis that assume an unlimited pool of partnership candidates, we propose a marriage market hypothesis that contests the idea of an unconstrained supply. It states that the likely constrained supply of potential mates with stabilizing personality traits in the PDMM results in a more complicated search for a new partner with a similar or higher level of stabilizing traits as the ex-spouse. With such a curtailed pool of potential partners, we hypothesize that the PDMM constrains divorcees to accept a decrease in marriage-stabilizing personality traits when repartnering. In line with this reasoning, the new partner is likely to be more neurotic, extraverted, and open, but also less agreeable and conscientious than the ex-spouse. As a result, we hypothesize that a divorcee will have less chance of repartnering with a similar or more marriage-stabilizing personality than his or her ex-spouse and instead will be restricted to less stabilizing personality traits.
Hypothesis 1c.
The new partner is more neurotic, extraverted and open, and less agreeable and conscientious than the ex-spouse (i.e., marriage market hypothesis).

2.5. Gender Differences

This limited supply ought not to be the same for every divorcee. Certain characteristics could affect the attractiveness and opportunities to repartner in such a way that the supply of potential partners significantly shrinks or grows. The most obvious of these potential moderators is gender. The supply of single men in the PDMM is smaller than in the FMM (Veevers 1988) and thus women have lower odds of repartnering than men (Kreidl and Hubatková 2017). Since divorced women have less men with marriage-stabilizing personalities to choose from, we hypothesize that these women experience more decline in consecutive partner personality than divorced men.
Hypothesis 2.
The marriage market hypothesis applies more to women than men (i.e., female marriage market hypothesis).
To explain women’s potentially disadvantaged position, we put forward three gender constraints. The first one is the difference in age preferences of men and women. In the favored dyad, men are somewhat older than their female partner (Buunk et al. 2001). Men’s preference for younger women results in women having more suitors in the FMM and less in the PDMM. When they enter the PDMM, women are usually somewhat older and thus face a shrunken supply of potential partners.
Hypothesis 3.
The marriage market hypothesis applies more to older women (i.e., female age penalty hypothesis).
A second gender constraint that disadvantages women is how the role of caretaker usually falls on mothers (Smart and Neale 1999 as cited by Anderson and Greene 2005). Having children, especially residential children, will lower a woman’s attractiveness on the marriage market, as new partners without children are less likely to take up a step-parent role (de Graaf and Kalmijn 2003; Vanassche et al. 2015). A new partner might feel less willing to help raise children he himself did not father (Goldscheider and Kaufman 2006). Therefore, we hypothesize that women who did not have children when entering the FMM, but were a single mother when active on the PDMM, will experience a more pronounced decline in the positive traits of their new partner compared to their ex-spouse.
Hypothesis 4a.
The marriage market hypothesis applies more to women who are a single parent at the start of the new relationship (i.e., single motherhood penalty hypothesis).
The third gender constraint features a socio-economic gradient to explain why women would experience less beneficial repartnering than men. Women tend to earn substantially less than men (Rubery et al. 2005), and even though the gender education gap has been reversed since the 1990’s, the income gap still persists (DiPrete and Buchmann 2013; Schofer and Meyer 2005). Consequently, the lower socio-economic position of women could give men the upper hand in terms of repartnering. Somewhat counterintuitively the lowest educated women actually have a higher rate of repartnering (Pasteels and Mortelmans 2017), but this is often due to financial needs. Consequently, one could argue that fast repartnering out of necessity does not result in an optimal partner choice. Therefore, we hypothesize that the lower socio-economic position of women compared to that of men contributes to a decline in marriage-stabilizing personality traits across partners. Considering that higher educated women are more likely to have a higher socio-economic status, low educated women ought to have a higher risk of such a decline.
Hypothesis 4b.
The marriage market hypothesis applies more to low educated women (i.e., female socio-economic penalty hypothesis).

2.6. Children

Starting from the marriage market hypothesis, we put forward three gender constraints that explained a possible disadvantaged position of women as compared to men: the female age penalty, parenthood, and education. However, based on the learning hypothesis, we could argue that one of these gender constraints, namely parenthood, could actually motivate women to improve their partner selection. Although empirical studies have found that resident children do indeed lower a woman‘s attractiveness in the PDMM (de Graaf and Kalmijn 2003), the element of choice is also present. The mother might choose to forgo a new relationship if the risk seems too high and her children provide enough companionship (Smart and Neale 1999 as cited by Anderson and Greene 2005). However, when she does repartner, she will likely do so with the best interests of her children in mind, and therefore select a partner whose personality offers the stability her family prefers. We therefore posit an alternative hypothesis, that being a parent when repartnering does not constrain women’s partner choice, but instead motivates women to select a more marriage-stabilizing partner than their ex-spouse. That being said, we acknowledge the intersectional position of lower educated single mothers who are more prone to financial poverty when taking up child custody. Consequently, a fast but suboptimal repartnering might be the only choice a lower educated single mother has, or, as Hübgen (2018) stated: since mothers with a lower socio-economic status are only a husband away from poverty in the PDMM.
Hypothesis 5.
The learning hypothesis applies more to women who are a single parent at the start of the new relationship (i.e., single motherhood learning hypothesis).

2.7. Own Personality

What about the personality of the shared partners themselves? Sodermans et al. (2016) indicated that neurotic and extraverted individuals would likely not repartner with someone who had more marriage-stabilizing personality traits than their ex-spouse. They found that neurotic divorcees remained mainly single or had multiple relationships. Extraverted divorcees were shown to repartner the fastest, which could lead to ill-considered decision making. The authors further found that a high level of conscientiousness is more likely to result in conventional repartnering, which refers to unmarried cohabitation followed by remarriage. Conscientious individuals do not tend to have multiple partnerships and thus are the most likely candidate to select a new partner with more marriage-stabilizing personality traits than their ex-spouse. These findings were supported by McCranie and Kahan (1986), who demonstrated that impulsive individuals and those high in stimulation seeking tend to have a higher likelihood of multiple divorces. These traits are associated with low conscientiousness, high extraversion, and high openness. One possible explanation is that impulsivity is associated with shorter courtships and therefore less thorough partner selection, resulting in a new partner with less stabilizing traits. Considering these findings, we hypothesize that neurotic, extraverted, open, and low conscientious divorcees will be more constrained by the marriage market forces to repartner with someone with less stabilizing personality traits than their ex-spouses.
Hypothesis 6.
The marriage market hypothesis applies more to neurotic, extraverted, open, and low conscientious individuals (i.e., own personality hypothesis).

3. Materials and Methods

3.1. Sample

The Divorce in Flanders survey (i.e., DiF) was used to compare the personalities of the ex-spouse and new partner (Mortelmans et al. 2012). Flanders, which constitutes the Dutch-speaking region of Belgium, noted a divorce rate in 2017 of 8.5 out of every 1000 couples (Corijn 2019). This is comparable to other western European countries. The DiF survey’s multiactor data was gathered in 2010 and consisted of heterosexual couples who married between 1971 and 2008, drawn from the Belgian National Register. Couples were selected based on the following criteria: were 18 to 40 years old at the time of marriage, were divorced only once, had Belgian nationality at birth, and were domiciled in the Flemish Region at the time of marriage and sampling (Mortelmans et al. 2012). For couples who separated, data on the new and ex-partners was available. We refer to the person who has had a relationship with both the new and ex-partner as the shared partner.
The final sample contained 700 shared partners with their own personality data, and that of their ex-spouse and new partner, resulting in a sample size of 2100 individuals. Shared partners were less likely to be female (i.e., 42.57%), but since both ex-spouse and new partner are from the opposite sex, the entire final sample included more women than men (i.e., 52.48%). Shared partners had a mean age of 46.73 years (SD = 7.43), while 38.14% of them had attained tertiary education and started their new relationships when they were on average 37.00 years old (SD = 7.15). Women’s new partners were slightly older than their ex-spouses (mean = 0.40; SD = 6.70), whereas men had younger partners than their ex-wives (mean = −2.27; SD = 6.73). In 78.43% of the cases, the new relationship was the first one since the end of the first marriage. Furthermore, 31.43% had no child when entering the first marriage but were a parent when entering the new relationship.
Lastly, the personality indicator scores from the respondents in the final sample differed less than 0.1 standard deviation from those of the full sample that included all respondents who participated in the personality measurement. This indicated that no selection bias is present for the personality indicators (i.e., Hedges’ g scores for the full and final sample on the personality indicators selected in the analysis were all between −0.1 and 0.1). The final sample did contain missing values on some of the personality items, which ranged from 0 to 5.63 percent missing. However, the MLR estimator is able to handle this type of missing values. The same does not apply to the other variables, of which three contained incomplete data (i.e., tertiary education = 0.26%; number of post-divorce relationships = 6.22%; age at the start of the new relationship = 9.54%). Consequently, listwise deletion was implemented, resulting in the final sample of 700 shared partners.

3.2. Measurements

The personality of the shared partner, ex-partner and new partner were reported by the individuals themselves. All three were measured during the same time period, which prevented period effects but not post-divorce personality changes. Personality was measured via the Big Five Inventory survey (i.e., BFI), which contained 44 items (John and Srivastava 1999). The indicators were made up of a 5-point Likert scale and treated as continuous variables (Bollen and Barb 1981). Responses ranged from 1 (disagree strongly) to 5 (agree strongly). The measurement models were constrained to guarantee scalar level measurement invariance across the shared partners, ex-spouses, and new partners. Similar to previous research regarding differences between two individuals’ Big Five scores, we ran separate analyses for each trait (Dyrenforth et al. 2010; McCrae et al. 2008). Appendix A Table A1 contains the item selection. Model fit could not be achieved when using the full range of BFI items. Lovik et al. (2017) had previously demonstrated that several of the 44 personality items do not fit the DiF data. Additionally, the items had a somewhat skewed distribution; therefore, we used the maximum likelihood estimator with robust standard errors (i.e., MLR in Mplus), which can handle nonnormal data (Muthén and Muthén 2017). Items were pre-selected based on explorative factor analyses. Different selections were then examined using confirmatory factor analyses, until an adequate model fit was achieved.
The predictor variables are the shared partner’s own personality traits and being female. The gender constraint variables include: the age at which the new relationship began, having attained tertiary education (i.e., ISCED-5 or higher), and if shared partners were parents in the PDMM as opposed to the FMM. This last variable referred to the situation where shared partners started their first marriage without children, but had children of their own before entering their new relationship. Two control variables were also included: the number of post-divorce relationships (i.e., continuous variable) and the age difference between the ex-spouse and new partner (i.e., positive values indicated that the new partner is older). The latter is needed because personality development continues during the adult lifespan, albeit less intense than during the early stages. A process of personality maturity can be present, where adults become more agreeable and conscientious, as well as less neurotic, with time (Roberts et al. 2008, p. 376). A large discrepancy between the ex-spouse’s age and that of the new partner might result in a significant personality difference.

3.3. Analyses

Based on the measurement models, we calculated the latent correlations between the personality traits of the ex-spouse and new partner. This enabled us to examine their similarity, which was questioned by the fix type hypothesis (i.e., Hypothesis 1a). Next, we addressed the marriage market hypothesis, by constraining the latent mean of the ex-spouse to zero the latent mean of the new partner expressed the mean difference between both. Consequently, the learning hypothesis (i.e., Hypothesis 1b) and marriage market hypothesis (i.e., Hypothesis 1c) could be tested via examining the mean difference scores. Negative values would indicate that the new partner possessed a lower personality score than the ex-spouse.
Afterwards, the measurement models were further developed into latent difference score models (see Figure 1 for this type of structural equation model). To examine the female marriage market hypothesis (i.e., Hypothesis 2), we investigated if women were more constrained than men by regressing the latent difference score onto the gender variable and the control variable regarding the number of relationships since the divorce. We then set these variables to zero, which resulted in the mean of the difference scores of either men or women.
Finally, we regressed the difference score onto gender, the two control variables, and the three gender constraint variables to further test Hypothesis 2, as well as the shared partner’s own personality (i.e., Hypothesis 6). Finally, we examined if the gender constraint variables explained the potential disadvantaged position of women in the PDMM by interacting the constraint variables with gender (i.e., Hypotheses 3–5).

4. Results

Table 1 contains information from multiple models. At the top, it shows the model fit indices of the measurement models. The chi-squared test is known to be biased when faced with large samples (Bentler and Bonett 1980), therefore we employed alternative indices that demonstrated adequate levels of model fit (i.e., RMSEA < 0.06, CFI > 0.90, SRMR < 0.06 (Hooper et al. 2008; Hu and Bentler 1999).
Situated below the fit indices in Table 1 are the latent correlations between the personality traits of the ex-spouse and new partner. These show little sign of similarity, as the latent correlations of extraversion (r = 0.10, p = 0.052), agreeableness (r = 0.02, p = 0.701), neuroticism (r = 0.07, p = 0.159), conscientiousness (r = 0.03, p = 0.664), and openness (r = 0.09, p = 0.093) all proved low in size and statistically insignificant. Consequently, the fixed type hypothesis (i.e., Hypothesis 1a) can be rejected.
Table 1 also captures the mean difference between the new and ex-partner on the Big Five personality traits. On conscientiousness (μ = −0.17; p = 0.000; 95% CI −0.22, −0.11), openness (μ = −0.22; p = 0.000; 95% CI −0.29, −0.05), and agreeableness (μ = −0.21; p = 0.000; 95% CI −0.28, −0.14), new partners showed lower scores than the ex-spouse, whereas on neuroticism (μ = 0.09; p = 0.019; 95% CI 0.02, 0.16), new partners scored higher. The finding that new partners are overall more neurotic, less conscientiousness, and less agreeable than ex-spouses seems to support the marriage market hypothesis (i.e., Hypothesis 1c). In contrast, the lower openness scores are a sign of more stability and thus point more towards the learning hypothesis (i.e., Hypothesis 1b).
However, these general mean difference score appear to hide several gender effects. When looking at the latent mean difference of those who had not repartnered before, differentiated between men and women, clear gender differences became noticeable, with women having new partners that scored lower on all traits, whereas for men this was only the case for openness (μ = −0.22; p = 0.004; 95% CI −0.37, −0.07), with some marginal significant decreases in conscientiousness across partners. In Table 2, the gender differences were measured more directly with regards to the effect on the difference score between partners, and they reaffirmed that, compared to men, women were more strongly marked by a decrease in their partner’s neuroticism (b = −0.32; p = 0.000) and agreeableness (b = −0.23; p = 0.000), while openness did not show any gender effects and conscientiousness was only marginally significant. In addition, extraversion across partners also tended to decline more for women (b = −0.34; p = 0.000), a finding that was less clear when comparing mean difference scores in Table 1. The tendency of women’s partners to decrease more in neuroticism and extraversion can be interpreted as a sign of women learning to select more marriage-stabilizing partners. In contrast, the decrease in partner’s agreeableness and the drop in conscientiousness can be regarded as a sign of the hypothesized disadvantaged position of women in the PDMM (i.e., Hypothesis 2). Thus, with regards to gender, both the learning hypothesis and the marriage market hypothesis were partially confirmed.
In terms of agreeableness and conscientiousness, the disadvantaged position of women over men could not be explained by any of the three gender constraint variables: age at which a new relationship was started (i.e., female ‘age-penalty’), parenthood which is mostly taken up by women, and educational attainment. Similarly, in terms of neuroticism and extraversion, the advantaged position of women over men could not be explained by single motherhood. None of the three gender constraint variables were found to interact with gender, and thus they did not seem to be more important to women than men in terms of constraining the supply in the PDMM (i.e., Hypotheses 3–5). In fact, the three hypothesized gender constraints also showed little main effects apart from those without higher education experiencing more decline in their partners’ openness (b = −0.13; p = 0.000)), and those who were a parent when entering the new relationship, but not when starting their marriage, being more likely to repartner with someone more conscientious than their ex-spouse (b = 0.09; p = 0.044).
Table 2 also contains the control variables and the second predictor variable. The latter appeared to be insignificant, as the shared partner’s own personality did not influence the mean difference score of the ex-spouse or new partner on any of the five traits (i.e., Hypothesis 6). The control variable that contained the age difference between both partners was also insignificant for all traits. In contrast, the second control variable showed that the more post-divorce relationships someone has had before the current relationship, the higher the likelihood of the new partner being more neurotic than the ex-spouse (b = 0.15; p = 0.004). In sum, the models explained a significant proportion of the variance in the mean difference between ex-spouse and new partner on neuroticism (R2 = 0.04; p = 0.004), extraversion (R2 = 0.03; p = 0.015), agreeableness (R2 = 0.03; p = 0.026), and openness (R2 = 0.02; p = 0.025), but not on conscientiousness.
Lastly, one could argue that testing five trait-models requires a correction for multiple testing and the increased risk of Type 1 errors. When a Bonferroni correction is applied (i.e., 0.05/5 = 0.01), most results remain statistically significant, except for three effects. Two of these effects are less relevant to the hypotheses tested compared to other effects that remained statistically significant. The same cannot be said about the finding pertaining to those who were a parent when entering the new relationship, but not when starting their marriage. After applying the Bonferroni correction, these individuals no longer seem to be likely to repartner with someone more conscientious than their ex-spouse.

5. Discussion

5.1. No Fixed Type

The current study examined the Big Five personality trait correspondence between the ex-spouse and new partner after divorce. To succeed in this aim, we looked to answer the following research question: ‘How do the Big Five personality traits of an ex-spouse compare to those of the new partner?’ The results show that the level of partner similarity (i.e., Hypothesis 1a) found in previous research on profile similarity between consecutive romantic partners cannot be extrapolated to trait similarities between an ex-spouse and new partner (Park and MacDonald 2019). As a consequence, the notion of continued homogamy, where consecutive partners share such a large degree of similarity with their shared partner, that these partners resemble each other, seems equally unlikely. How can we then explain the previous findings by Park and MacDonald (2019), who demonstrated the existence of a fixed type when examining personality profile similarity? The answer might be found in the work of McCrae et al. (2008) who used data from four different countries to demonstrate that the Big Five traits themselves show less homogamy than their lower level facets. Personality indicators, which are situated at an even lower level than facets on the Big Five hierarchical order, might therefore also show more homogamy. Since correlating the indicators themselves achieves profile similarity, this could explain the significant levels of homogamy resulting from this type of similarity measurement, as opposed to trait similarity itself, which is centered on capturing the latent Big Five factors.

5.2. Alternative Hypotheses

In the absence of a fixed type of partner, we examined if the new partner had either more marriage-stabilizing personality traits than the ex-spouse (i.e., Hypothesis 1b: learning hypothesis) or less stabilizing traits (i.e., Hypothesis 1c: marriage market hypothesis). The latter was seen as more likely given the constrained pool of potential partners in the PDMM as opposed to the FMM. The results mostly confirmed the marriage market hypothesis, with the new partner appearing more neurotic, less agreeable, and less conscientious than the ex-spouse. The sizeable gender effect also supported the marriage market hypothesis. Due to their disadvantaged position in the PDMM, women seem to have faced a steeper drop in agreeableness and somewhat in conscientiousness. Finally, we found that the more the shared partner had to repartner, the more neurotic their new partner appeared to be, which further supports the marriage market hypothesis. Consequently, one could say repartnering multiple times seems to lead to less and less stabilizing partners.
However, the learning hypothesis also found support, namely in the general decrease in openness when repartnering and the drop in neuroticism and extraversion that women seem to experience in their new partner, as compared to men. In addition, the aforementioned increase in conscientiousness concerning parents also appears to serve as evidence for the learning hypothesis. However, this finding was not very strong and disappeared after applying a correction for multiple testing. Consequently, it remains unclear if parents purposely search for new partners who are more conscientious than their former spouse, because this trait is associated with stability and would therefore benefit their children.

5.3. Needs, Attractiveness, and Opportunities

According to de Graaf and Kalmijn (2003), the general reasons to start a long-term relationship are threefold: needs, attractiveness, and opportunities. Needs refer to the demand side of a marriage market. Personality needs are likely to be the same in both the PDMM and FMM. The preferences for these personality traits are likely to remain as people grow older, thus their attractive strength should be the same in the PDMM as in the FMM. However, supporting evidence of the learning hypothesis suggests that for women the needs are somewhat different, as women tend to choose new partners with less destabilizing traits.
Secondly, there exists a level of general attractiveness regarding the supply of potential partners. The supply of the PDMM is mostly made up of individuals who were romantically less successful, i.e., divorcees and long-term singles. The potential partners in the PDMM therefore likely rank lower in overall marriage-stabilizing personality traits than those in the FMM, because the FMM also includes personalities that go on to have long lasting marriages, whereas the PDMM likely contains more individuals with highly destabilizing personality traits.
Although the quality of the supply is important, its quantity might be even more decisive. The quantity of the partner supply is associated with the opportunity to partner, which is more restricted in PDMM due to the smaller number of potential partners. Divorcees also tend to visit traditional marriage market hotspots less often, which further lowers the opportunity to start a new relationship (de Graaf and Kalmijn 2003; Gelissen 2004).
The differing attractiveness and opportunity in the FMM and PDMM explain the support for the marriage market hypothesis in our findings, which indicates that while women ‘learn’ to decrease marriage-destabilizing traits in their partners, they are simultaneously constrained to accept a decrease in the stabilizing traits. Likewise, higher order repartnering also seems to lead to higher levels of the marriage-destabilizing trait of neuroticism in the new partners.

5.4. Gender

The discrepancy in women’s and men’s partner correspondence could not be explained by the caretaker role after divorce, or by the cultural norms for preferred partner age that favor older men over older women. The discrepancy also did not appear to be a result of the accumulated intersectionality in gender lines, as women are often more prone to poverty and have a more urgent need for a second earning partner in the household (Budig et al. 2012; Hübgen 2018).
The gender constraint of an age penalty did not seem to be more strongly present for women; in fact, it appeared absent for both sexes. One possible explanation is the decreasing likelihood to repartner as divorcees become older (Sodermans et al. 2016). The second gender constraint of parenthood also did not show any difference between men and women. Lastly, the socio-economic gender constraint was operationalized using educational attainment and was ultimately incapable of explaining women’s drop in agreeableness and conscientiousness when repartnering. The absence of an effect could be the result of the complicated multifactor-influenced context surrounding this type of constraint, which includes the presence of educational homogamy and the reversal of gender inequality in education (Grow and Van Bavel 2015; Shafer 2013; Theunis et al. 2015), as well as the association between education, intelligence, and the personality trait of openness (Van Eijck and De Graaf 2004; Goldberg et al. 1998; Lundberg 2013).

5.5. Limitations

The current study has some important limitations that need to be acknowledged. First, it is problematic to measure personality after divorce because previous research has shown that divorce can change personality (Specht et al. 2011). In addition, partners’ personalities may converge the longer they are together (Rammstedt et al. 2013). Therefore, it is possible that the personality of the ex-partners resembled the personality of the shared partner more when they were still married. This implies that if we measure the personality of the ex-spouse and new partner at different times, namely when both are in a relationship with the shared partner, then their personalities could be more similar. However, the change in age and contextual variables that accompany different interview moments could also increase discrepancies between partners. Still, measuring the ex-spouse personality after the marriage cannot explain why the new partner consistently ranks as being less attractive with regards to the Big Five personality traits. The explanation could very well be hidden because of a more severe limitation inherent to this study, namely the lack of information on those divorcees that do not repartner. Without knowing which personalities stay single after divorce, we cannot adequately examine the reason as to why the new partner has less attractive personality traits than the ex-spouse, and why this is especially true for women. This can explain why the shared partners’ own personality did not have an effect on the difference between the new and ex-partner. It is possible that those with highly destabilizing traits do not repartner at all, and thus are omitted from the sample.
Despite these limitations, the findings of this study demonstrate that divorcees do not appear to repartner with someone that resembles the personality of their ex-spouse, but rather the marriage market constraints and a need for more stability moderate their choice for repartnering with someone who is more marriage-stabilizing in some traits and more destabilizing in others.

Author Contributions

Conceptualization, S.S., D.V.G.; Methodology, S.S.; Software, S.S.; Formal analysis, S.S.; Writing—Original Draft, S.S.; Writing—Review & Editing, S.S., D.M.; Resources, S.S.; Writing - Review & Editing, D.M., D.V.G.; Supervision, D.M.; Project administration, D.M.; Funding acquisition, D.M., D.V.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the University of Antwerp, grant number 42/FA040100/FFB150348.

Data Availability Statement

The data and materials used in the research are available and can be obtained via email.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table
Table A1. Personality indicator selection.
Table A1. Personality indicator selection.
Big Five TraitIndicator
NeuroticismIs relaxed, handles stress well (R)
Can be tense
Worries a lot
Gets nervous easily
ExtraversionIs talkative
Is reserved (R)
Tends to be quiet (R)
Is outgoing, sociable
ConscientiousnessDoes a thorough job
Perseveres until the task is finished
Does things efficiently
AgreeablenessHas a forgiving nature
Is considerate and kind to almost everyone
Likes to co-operate with others
OpennessIs original, comes up with new ideas
Is curious about many different things
Is a deep thinker
Has an active imagination
Is inventive
Likes to reflect, play with ideas
Note: (R) = reversed coded item.

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Socsci 10 00431 g001 550
Figure 1. Multiple indicator latent difference score models (McArdle 2009), measured separately for each of the Big Five traits. Scalar measurement invariance was imposed. The latent difference score between the ex-spouse’s and new partner’s personality were regressed onto the personality of the shared partner (i.e., self) and the socio-demographic characteristics of the self and control variates (i.e., cov). Mean structures are not illustrated.
Figure 1. Multiple indicator latent difference score models (McArdle 2009), measured separately for each of the Big Five traits. Scalar measurement invariance was imposed. The latent difference score between the ex-spouse’s and new partner’s personality were regressed onto the personality of the shared partner (i.e., self) and the socio-demographic characteristics of the self and control variates (i.e., cov). Mean structures are not illustrated.
Socsci 10 00431 g001
Table
Table 1. Measurement model fit, latent correlations and latent difference scores. Positive mean difference scores indicate that the new partner outscores the ex-partner.
Table 1. Measurement model fit, latent correlations and latent difference scores. Positive mean difference scores indicate that the new partner outscores the ex-partner.
NECAO
Measurement model fit:
χ2112.66181.2071.2485.40299.27
(df)(65)(65)(34)(35)(154)
p(0.000)(0.000)(0.000)(0.000)(0.000)
RMSEA0.030.050.040.050.037
CFI0.970.920.950.900.926
SRMR0.040.040.050.050.048
Latent correlation0.070.100.030.020.09
(0.159)(0.052)(0.664)(0.701)(0.093)
Mean difference: general0.09 *−0.05−0.17 ***−0.21 ***−0.22 ***
(0.019)(0.268)(0.000)(0.000)(0.000)
95% CI0.02; 0.16−0.14; 0.04−0.22; −0.11−0.28; −0.14−0.29; −0.15
Latent variance:0.89 ***1.12 ***0.39 ***0.49 ***0.79 ***
general(0.000)(0.000)(0.000)(0.000)(0.000)
Mean difference: women first PD rel.−0.27 **−0.21 *−0.16 **−0.31 ***−0.20 **
(0.001)(0.046)(0.006)(0.000)(0.009)
95% CI−0.42; −0.11−0.42; −0.00−0.28; −0.05−0.45; −0.17−0.35; −0.05
Mean difference:0.030.13−0.10−0.08−0.22 **
men first PD rel.(0.673)(0.207)(0.084)(0.209)(0.004)
95% CI−0.12; 0.19−0.07; 0.32−0.21; 0.01−0.21; 0.05−0.37; −0.07
Note: N = 700 triads; df and p-value between brackets; * = p < 0.05; ** = p < 0.01; *** = p < 0.001; unstandardized means and coefficients; PD rel. = post-divorce relationship.
Table
Table 2. Latent difference score models, including predictors. Positive mean difference scores indicate that the new partner outscores the ex-partner.
Table 2. Latent difference score models, including predictors. Positive mean difference scores indicate that the new partner outscores the ex-partner.
NECAO
Model fit:
χ2274.99274.86112.87128.73449.92
(df)(130)(130)(81)(81)(255)
RMSEA0.040.040.020.030.03
CFI0.920.910.960.920.91
SRMR0.050.040.030.040.05
Intercept0.080.230.03−0.17−0.24
(0.649)(0.269)(0.831) (0.267)(0.144)
Control var.:
# post-divorce rel.0.15 **−0.02−0.02−0.030.00
(0.004)(0.778) (0.510) (0.507) (0.949)
∆age ex and new−0.000.00−0.000.000.04
(0.783)(0.794)(0.533) (0.701) (0.241)
Predictors:
Big Five trait0.070.05−0.02−0.030.02
(0.351)(0.520) (0.823)(0.769)(0.634)
female−0.32 ***−0.34 ***−0.09−0.23 ***0.01
(0.000)(0.000)(0.053) (0.000) (0.704)
Gender C/M:
pre-new rel. child0.04−0.050.09 *0.03−0.03
(0.555)(0.560)(0.044) (0.603) (0.404)
age start new rel. −0.00−0.00−0.000.00 0.04
(0.691)(0.820)(0.345) (0.645) (0.262)
no tertiary educ.0.02−0.10−0.060.04−0.13 ***
(0.702)(0.184)(0.186)(0.457) (0.000)
age start new rel.
* female
pre-new rel. child
* female
tertiary education
* female
R2 mean difference0.04 **0.03 *0.010.03 *0.02 *
(0.004)(0.015)(0.135)(0.026)(0.025)
Note: N = 700 triads; unstandardized means and coefficients; interaction terms are not significant and therefore not included in the models; p-value in brackets; * = p < 0.05; ** = p < 0.01; *** = p < 0.001; C/M = constraint/motivation; Big Five trait = Big Five trait of the shared partner; rel. = relationship; educ. = education; var. = variable; pre-new rel. child = not being a parent when starting the marriage, but being one when starting the post-divorce relationship.
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Spikic, S.; Mortelmans, D.; Van Gasse, D. More of the Same? Comparing the Personalities of Ex-Spouse and New Partner after Divorce. Soc. Sci. 2021, 10, 431. https://doi.org/10.3390/socsci10110431

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Spikic S, Mortelmans D, Van Gasse D. More of the Same? Comparing the Personalities of Ex-Spouse and New Partner after Divorce. Social Sciences. 2021; 10(11):431. https://doi.org/10.3390/socsci10110431

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Spikic, Sascha, Dimitri Mortelmans, and Dries Van Gasse. 2021. "More of the Same? Comparing the Personalities of Ex-Spouse and New Partner after Divorce" Social Sciences 10, no. 11: 431. https://doi.org/10.3390/socsci10110431

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