Abstract
Evolutionary Psychology has considered a Fast Life History Strategy (FLHS), denoting an individual's tendency to invest more resources in proliferation than in child-rearing, to be responsible for the emergence of aversive traits. Empirical evidence for this notion has been inconsistent, however. Herein, we tested whether FLHS is an adequate representation of the underlying disposition of aversive traits (N = 869). To this end, we considered twelve specific aversive traits, and additionally measured and modeled the common core of these traits. We found only weak correlations of FLHS with individual aversive traits as well as with their common core. In sum, the results suggest that the common core of aversive traits is only marginally reflected in FLHS.
Key Insights
FLHS was only weakly related to some aversive traits. FLHS shared little variance with common core of aversive traits. FLHS was correlated most strongly with self-reported selfishness. Relevant aspects of aversive traits are hardly represented in FLHS. FLHS does not represent underlying disposition of aversive traits.
Relevance Statement
Although a Fast Life History Strategy (FLHS) is related to some aversive traits to some extent, this study suggests that FLHS lacks relevant aspects of what is common to all aversive traits and thus does not adequately represent their underlying disposition.
Over the last decades, research in personality psychology has increasingly directed attention to personality traits linked to socially aversive and ethically questionable attitudes and behaviors, often denoted as
Specifically, one recurring theme invoked to account for the common basis of aversive traits is Life History Theory (LHT). Jonason et al. (2012), for instance, concluded that the “Dark Triad may indicate a fast life strategy based on immediate rewards and gratification” (p. 193). LHT is a framework originating in evolutionary biology which classifies organisms by how they spend their finite resources to enhance their reproductive fitness. Specifically, LHT locates organisms on a continuum from
Even though LHT originally referred to differences between species, it has been adapted by evolutionary psychologists to explain individual differences among humans (Figueredo et al., 2005; Nettle & Frankenhuis, 2020). Like most mammals, humans are generally highly
Although impulsivity and behaviors directed at instant gratification do represent aspects of some aversive traits, most notably of Psychopathy (Hart et al., 1992; Paulhus & Williams, 2002), these attributes are neither sufficient nor necessary to explain aversive behavior in general. First, whereas impulsivity and the pursuit of immediate rewards may in some cases incur externalities or interfere with others’ needs and may thus be perceived as aversive, they are not socially or ethically aversive attributes per se. For example, impulsively buying an item at the grocery store that was not on the shopping list rarely causes anybody harm and can thus hardly be considered socially aversive. Second, impulsivity and a focus on instant gratification are not universally featured in aversive traits. In fact, short-term thinking is conceptually unrelated to traits such as Sadism (deriving pleasure from the suffering of others; O'Meara et al., 2011) or Moral Disengagement (dismissing ethical standards for oneself; Moore et al., 2012), and is even partially incompatible with Machiavellianism (
Indeed, the empirical picture does not unanimously support a link between a Fast Life History Strategy and single specific aversive traits and outcomes. On the one hand, a link between aversive traits and Life History traits has been demonstrated by positive correlations between the Dark Triad components and measures of short-term mating (.22 <
The present study sought to provide more direct and conclusive evidence on this question, that is, whether a Fast Life History Strategy adequately represents the common dispositional basis of aversive traits. To this end, we considered not only a wide range of (twelve) specific aversive traits, but additionally measured and modeled the common core of these traits and related them to a measure of life history strategy. Specifically, we first approximated the common core of the measured aversive traits via bifactor modeling in which the general factor captures the commonalities among all items used to measure aversive traits (Reise, 2012; see also Moshagen et al., 2018). Secondly, we measured the common core of dark traits directly through a corresponding item set designed specifically to operationalize the underlying dispositional tendency of which all aversive traits are specific manifestations (Bader, Hartung, et al., 2021; Moshagen, Zettler, & Hilbig, 2020). If a Fast Life History Strategy indeed represents the underlying disposition of aversive traits, it must be substantially related to most, if not all, specific aversive traits and—arguably even more strongly so—to their common core, both when modeled via the single specific aversive traits and when operationalized via an item set designed to measure the common core of these traits directly.
Method
The study was not preregistered. Data and analysis scripts are available in the Supplementary Materials. The study was run based on approval by the ethics committee of the University of Koblenz-Landau (#154_2018).
Measures
Fast Life History Strategy was assessed using the German translation of the Mini-K (Hammerl, 2017). The 20-item scale covers six dimensions of Life History Strategy (insight, planning, and control; mother/father relationship quality; friend social contact/support; family social contact/support; harm avoidance; community involvement; Figueredo et al., 2006), with lower scores indicating a faster Life History Strategy. Additionally, we measured a total of twelve aversive traits as summarized in Table 1.
1
Although there is no consensus on which traits ought to be considered ‘aversive’, we relied on these twelve traits because they arguably represent a comprehensive array of aversive traits (as compared to the so-called Dark Triad or Dark Tetrad most commonly considered in this context) and have been shown to load on a common aversive core (Moshagen, Zettler, & Hilbig, 2020).
Overview of Included Aversive Traits and Corresponding Inventories
aAn ad-hoc translation was used.
Participants and Procedures
Data for this study were collected as part of the Prosocial Personality Project (PPP), a large-scale web-based study involving six measurement occasions for the base project and several follow-up assessments.
2
Besides the D70, the data reported herein have not been published before. For other publications that were based on data from the PPP, please see the project's documentation on the OSF at https://osf.io/m2abp/.
D70 was assessed at T1; Greed, Machiavellianism, Narcissism, Psychopathy, and Sadism, were assessed at T3 (61 days after T1 on average) of the base project. Life History Strategy (Mini-K), in turn, was assessed at follow-up 2020-05a (171 days after T1 on average); Crudelia, Frustralia, Egoism, Moral Disengagement, Psychological Entitlement, Self-Centeredness, and Spitefulness were assessed at follow-up 2020-05b (167 days after T1 on average). The order of scales was randomized within each measurement occasion. Moreover, at each measurement occasion, two attention check items were embedded within the scales (e.g., “Please select ‘strongly disagree’ here. This serves to check your attention.”).
The final sample for this study consisted of 869 participants (46% female, aged 18 to 66 years,
Descriptive Statistics, Reliabilities and Correlations Between K and All Measures Included
Analyses and Results
Hypotheses were tested estimating confirmatory factor analyses with the
Following the commonly used approach, Life History Strategy was modeled by specifying a higher-order structure (Richardson et al., 2017). More precisely, we specified six lower-order factors representing the six dimensions of the Mini-K from the respective items. Additionally, we specified a higher-order factor representing K, on which the six lower-order factors loaded. Each factor was assigned a scale by fixing its variance to 1 (which also applies for all other factors). The model fit the data well (according to conventional guidelines; Browne & Cudeck, 1992), χ2(164) = 497, A single-factor model fit the data considerably worse, χ2(170) = 2,304,
To estimate the bivariate correlations between Life History Strategy and the individual aversive traits, we specified separate models containing a factor for one of the aversive traits along with the latent K-factor. The reliabilities of all aversive traits were acceptable to high both in terms of Cronbach's alpha (.73 < α < .89) and unidimensional omega (.72 < ωU < .89; see Table 1). As can be seen in Table 2, the correlations of single aversive traits with K varied greatly, yielding a medium-sized effect on average (median |
To further test whether K can approximate the latent common core of all aversive traits, we specified a bifactor model with all aversive trait indicators loading on a general factor and on a specific factor for the individual aversive trait. The general factor in a bifactor model captures the variance shared among all items and thus represents their common core, whereas the specific factors capture the remaining variance shared among the items of a given trait that is not shared with the other traits. In this case, the general factor captures the aversive content shared by the trait indicators and can thus be interpreted as the latent disposition that accounts for individual differences in aversive traits and behavioral tendencies. By contrast, the specific factors capture only the remaining, non-aversive characteristics of the respective traits. As a consequence, they do not represent the original constructs anymore and will hence not be further considered substantively. For identification purposes, the general and specific factors were constrained to mutual orthogonality, which also reflects the fact that they account for non-overlapping portions of variance. This model structure fit the data well, χ2(7,018) = 14,368,
Finally, we considered the association between the K-factor and D as a direct measure of the common core of aversive traits. Following Bader, Hartung, et al. (2021), D was also modeled by specifying a bifactor structure such that all items loaded both on the general factor representing D (i.e., the shared variance among all items) and on one of five specific factors or themes (representing the shared variance among subsets of items that is independent from D). Again, the general and specific factors were constrained to mutual orthogonality. The bifactor model yielded a good fit to the data, χ2(2,275) = 5,907, The latent correlation between D and the general factor estimated across the aversive traits was
Discussion
Recent research in personality psychology has come to agree that socially aversive traits share a common dispositional core (Jonason et al., 2017; Moshagen et al., 2018; Muris et al., 2017; Schreiber & Marcus, 2020; Vize et al., 2020). Among other suggestions, it has been presumed that aversive traits signify a Fast Life History Strategy (Buss, 2009; Jonason et al., 2012). According to Life History Theory (LHT), this strategy describes species that maximize their reproductive fitness by high proliferation and little parental efforts (Pianka, 1970). In explaining individual differences within the human species, such a strategy is thought to reflect in the general preference for immediate rewards over long-term benefits or, more broadly speaking, impulsivity, in turn leading to exploitative and otherwise aversive behavior (Buss, 2009; Jonason et al., 2012). Empirical evidence, however, has been inconsistent on the potential link between a Fast Life History Strategy and socially aversive traits, let alone their common core. Thus, the present study strictly tested whether a Fast Life History Strategy indeed reflects aversive traits and strongly represents their common core.
In a large, heterogeneous sample, we found that K was related only to some individual aversive traits, with a maximum of only 22% shared variance (with Crudelia) and a median of 7% across all aversive traits, which is notably less than the shared variance among the latter (median 34%, see Table A1 in the Supplementary Materials). Similarly, shared variance between K and the common core of all aversive traits—both modelled via the individual aversive traits and measured directly—only amounted to around 10%. Thus, whereas individuals characterized by a faster Life History Strategy also tend to be higher on some aversive traits, this association is arguably too weak for K to be an adequate representation of the common underlying disposition of all aversive traits.
5
We also verified our results by modeling K—analogously to the common aversive core—as a bifactor structure. The analysis script and results are provided in the Supplementary Materials. In short, although single correlations between K and aversive traits slightly differed from those reported herein, the correlations with both the aversive traits (median | Likewise, basic personality dimensions such as Honesty-Humility and Agreeableness have been shown to share substantially more overlap with and thus outperform Life History Strategy in accounting for the commonalities of aversive traits (Hodson et al., 2018; Horsten et al., 2021; Moshagen, Zettler, Horsten, et al., 2020; Vize et al., 2020).
K shared the smallest portion of variance with Narcissism, Moral Disengagement, and Psychological Entitlement, and the largest with Crudelia and Egoism. Although Crudelia is supposed to manifest in sadistic, brutal, and destructive behaviors (Vukosavljevic-Gvozden, Opacic, & Perunicic-Mladenovic, 2015), the items of the respective scale arguably also reflect egoistic as opposed to big-hearted tendencies. Thus, whereas the relation of a Fast Life History Strategy with socially aversive behavior seems to be largely driven by selfishness, other relevant aspects of aversive traits are poorly represented. Most notably, individuals with a faster Life History Strategy neither seem to be driven by convictions regarding their superiority and privileges as motives for exploitative behaviors (as reflected in Psychological Entitlement and Narcissism), nor do they derive utility from the disutility of others (as reflected in Sadism and Spitefulness). Indeed, it is entirely plausible that a Fast Life History Strategy cannot represent these aversive traits, as they are neither driven by impulsiveness—which is suggested to be the main aspect linking Fast Life History Strategy to aversive behaviors—, nor is there an obvious evolutionary advantage to hurting others for mere enjoyment.
Taken together, the findings are compatible with the fact that LHT primarily predicts how a species maximizes its reproductive fitness in light of evolutionary trade-offs. According to this theory, individuals characterized by a Fast Life History Strategy exhibit various behaviors which are not commonly regarded as “dark” in the sense of ethically or morally aversive (e.g., early sexual intercourse, non-use of birth control, having multiple sexual partners or being an absent parent) and would thus be beyond the scope of a common aversive core. Moreover, to explain why a faster Life History Strategy would lead to aversive personality traits and behaviors, auxiliary assumptions about co-occurring traits are necessary (e.g., that a behavioral strategy optimized for short-term relations—for instance, cheating—is caused by absent parents; Gladden et al., 2009).
It should be noted that our conclusions are limited by the specific operationalization of LHT which is purely psychometric in nature and does not assess actual life history traits or the timing of life history events (Copping et al., 2014, 2017; Sear, 2020). As has been argued before, however, organisms are “adaptation executers”, not “fitness maximizers”, meaning that the execution of predicted adaptations (e.g., amount of resources invested in child rearing or own survival) is deemed at least as or even more indicative of a Fast or Slow Life History Strategy than their outcomes (e.g., number of sexual partners and offspring, life expectancy), which are not only influenced by Life History Strategy, but also by environmental conditions (Figueredo et al., 2014). The Mini-K has been shown to assess such adaptation executions in terms of patterns of resource investment in the major psychosocial areas associated with a slower Life History Strategy (Figueredo et al., 2017).
A further limitation pertaining to the operationalization of Life History Strategy is that the Mini-K (containing 20 items) is a short-form of the much longer 199-item Arizona Life History Battery (ALHB; Figueredo, 2007). The Mini-K might thus not fully represent the full breadth of Life History Strategy. However, the items of the Mini-K were designed to summarize the content covered by all six dimensions of the ALHB (Figueredo et al., 2006) and it has been shown to closely converge with the ALHB (
Nonetheless, it has been suggested that the assessment of Life History Strategy should not solely rely on a psychometric approach but also take into account biodemographic data (Black et al., 2017; Nettle & Frankenhuis, 2020; Sear, 2020). Thus, future research may need to be grounded on a combination of psychometric and biometric data for more conclusive insights on the link between a Fast Life History Strategy and aversive traits and behaviors.
In sum, whereas a Fast Life History Strategy (as measured by the Mini-K) is to some extent related to and thus may constitute a distal antecedent of at least a few specific aversive traits—most likely Crudelia and Egoism—it is a relatively poor proxy for most aversive traits. Correspondingly, it shares only limited variance with the common core of these traits and does not, per se, represent the underlying disposition of all aversive traits.
Footnotes
This research was funded by grants 2277, Research Training Group „Statistical Modeling in Psychology“ (SMiP) and HI 1600/1-2 by the German Research Foundation (DFG).
Isabel Thielmann is an editorial board member of the journal.
Data Availability
For this article, data is freely available (for access, see Index of Supplementary Materials below).
Supplementary Materials
For this article the following Supplementary Materials are available via the PsychArchives repository (for access see Index of Supplementary Materials below):
The authors have no additional (i.e., non-financial) support to report.
Ethics Approval
The study was approved by the local ethics committee of the University of Koblenz-Landau (#154_2018).
