Abstract
Autistic-like traits (ALTs) have been widely examined, including in romantic relationships, yet few studies have approached them from an evolutionary perspective. Mate retention tactics are associated with different types of life history strategies. Because we hypothesize that individuals with ALTs prefer a fast life history strategy, we also assume that they use specific types of mate retention tactics. This study investigated the associations between ALTs and mate retention tactics, considering reproductive strategies and attachment styles as mediators. Structural equation modeling on a sample of 796 individuals (52% female) showed that individuals with ALTs are less likely to engage in cost-inflicting tactics. No significant link between ALTs and benefit-provisioning mate retention tactics was found in this study. ALTs were more strongly linked to attachment styles—both fearful and avoidant—than to reproductive strategies. Contrary to expectations, ALTs did not negatively predict a slow reproductive strategy (parental effort) or positively predict a fast strategy (mating effort), though additional regression analyses suggested a potential link with mating effort. Participants’ sex did not moderate these relationships, while age was associated with decreased attachment anxiety, mating effort, and mate retention behaviors, alongside increased parental effort. A key limitation is the weak predictive power of ALTs for reproductive strategies, highlighting the need for alternative measurement approaches in future research.
Keywords: reproductive strategies, autistic-like traits (ALTs), life history theory, attachment styles, mate retention tactics
Introduction
Contemporary literature offers several different conceptualizations of autistic traits (cf. Płatos et al., 2023). The medical approach, focused on an individual's deficits and difficulties, diagnoses autism spectrum disorder (ASD) as a set of neurodevelopmental conditions characterized by some specific common traits listed in classification systems such as the DSM-5 (American Psychiatric Association, 2013) and ICD-11 (WHO, 2019). These traits primarily include deficits in the ability to initiate and sustain social interactions and social communication, as well as limited, repetitive, and inflexible patterns of behavior, interests, or activities that are atypical or excessive given the individual's age and sociocultural context.
Nearly two decades ago, the term autistic-like traits (ALTs) was introduced as a new conceptual framework and has since become a topic of growing research interest. ALTs are defined as personality traits, patterns of social functioning, and cognitive processes with continuous distribution across the general population (Maldonado Moscosoet et al., 2022; Pomè et al., 2022). In medical terms, their extreme levels present as dysfunctions within the domain of ASD (Baron-Cohen et al., 2001; Constantino & Todd, 2003; Del Giudice et al., 2010; Hoekstra et al., 2007; Lundström et al., 2012; Omelańczuk & Pisula, 2020).
From an evolutionary psychology perspective, personality and its dimensions or traits are viewed as the product of long-term (in an evolutionary sense) interactions between environmental pressures and the human mind, which arose in response to the social adaptive problems recurrently faced by our ancestors (Michalski & Shackelford, 2010). These psychological mechanisms enhance various evolutionary advantages, such as increasing the likelihood of being selected as a romantic partner, fostering trust in others, and facilitating coalition formation (see Sefcek et al., 2015). Personality traits are also associated with reproductive behaviors (Michalski & Shackelford, 2010). For instance, research on the Tsimane, semi-sedentary forager-horticulturalists of Amazonian Bolivia, indicates that men exhibiting higher levels of extraversion, openness, and conscientiousness, coupled with lower levels of neuroticism, tend to have greater fertility and more surviving offspring (Gurven et al., 2014). Personality traits can also be understood as manifestations of life history strategies (Burtăverde et al., 2023)—“allocations of limited resources to the competing needs of survival, development, or reproduction” (Stott et al., 2024, p. 830).
In evolutionary psychology, there are also hypotheses explaining the adaptive potential of ASD and ALTs (see reviews by Del Giudice et al., 2010; Ploeger & Galis, 2011). For example, it has been suggested that ASD may be the result of an extreme male brain (Baron-Cohen, 2002) and can manifest itself in the ability to systematize (noting regularities and rules), which could have been important in developing tools and weapons, hunting, tracking, and trading (Ploeger & Galis, 2011), providing certain evolutionary advantages for individuals with such skills, for example, higher social status.
Another concept (Crespi & Badcock, 2008a) postulates a continuum with two extremes: psychosis and autism. The starting point for this hypothesis is the observation that both autism and psychotic disorders impair human social functioning. According to Crespi and Badcock (2008a), Badcock (2011), Crespi (2008), and Crespi and Badcock (2008b), psychosis and autism may result from a genetic mechanism—genomic imprinting—a specific tug-of-war between parental genes, that is, maternally biased expression of genes and reduced expression of paternally active ones involved in brain development (psychosis) or vice versa (autism).
The hypothesis of sexual selection of autistic-like and schizotypal traits correlates with the “imprinted brain” hypothesis of autism and psychosis, but it also refers to the extreme male brain hypothesis (Del Giudice et al., 2010). The authors assume the involvement of a genomic imprinting mechanism and additionally refer to sexual selection, that is, the choice of a partner for mating or relationships by one sex based on criteria “imposed” by the other sex. The idea of sexual selection was introduced by Darwin (1871) to explain the evolution of exaggerated physical traits, such as ornaments present in only one sex (e.g., brighter or more extensive plumage, such as in peacocks, serves as a visual signal to attract mates), which cannot be explained as adaptation to the ecological conditions of the species.
Individuals with high levels of ALTs are less motivated and have fewer opportunities for short-term sexual relationships with multiple partners. Their limited social networks, along with lower levels of extraversion and openness to experience, diminish both their curiosity for novelty, including sexual experiences, and the frequency of interactions with a potential mate (Del Giudice et al., 2010). In evolutionary psychology, ALTs are considered traits that predispose individuals to a particular reproductive strategy, that is, the optimal allocation of personal resources, including psychological ones, among various competing developmental tasks (Del Giudice et al., 2010).
An important pillar of the stability of romantic ties is the use of mate retention tactics (Barbaro et al., 2016). From an evolutionary perspective, the latter evolved to address the adaptive problem of potential infidelity (Buss, 1988a, 1988b; Buss & Shackelford, 1997). Furthermore, research on interpersonal behavior has shown that during the COVID-19 pandemic, cognitive, emotional, and behavioral jealousy in women was positively associated with a wide range of mate retention tactics, suggesting that jealousy may drive the use of a greater number of mate retention tactics (Degiuli et al., 2023). However, such strategies can be conceptualized not only as mechanisms to prevent infidelity but more broadly as behaviors aimed at maintaining and strengthening romantic relationships (Barbaro et al., 2016; Pazhouhi et al., 2024).
The use of specific tactics is predicted by one's attachment orientation (Barbaro et al., 2016, 2019; Nascimento et al., 2022), that is, the unique ways in which an individual forms and experiences emotional bonds with a partner in a romantic relationship (Simpson & Rholes, 2019). In turn, attachment orientation is linked to an individual's reproductive strategy (Belsky et al., 1991; Chisholm, 1996; Del Giudice, 2009; Schmitt, 2005; Szepsenwol & Simpson, 2019).
To the best of our knowledge, an evolutionary model of the relationship between ALTs and mate retention tactics—accounting for mediating variables—has not yet been tested. Therefore, the aim of the present study was to explore the association between ALTs and mate retention tactics, considering mediators relevant from the perspective of evolutionary theory: attachment style and reproductive strategy.
Studies have shown (Del Giudice et al., 2010; see also Del Giudice et al., 2014) that ALTs are linked to the so-called slow reproductive strategy: a stronger commitment to long-term relationships and an increased investment of time and resources in one's romantic partner. However, findings on the relationships between ALTs and other psychological variables paint a different picture. For example, it has been found that, in adults, a higher level of ALTs is associated with insecure attachment styles, that is, anxious and avoidant (e.g., Ameli et al., 2019; Sörnyei et al., 2024), and that insecure attachment styles are more typical of a fast reproductive strategy rather than of a slow one (Belsky et al., 1991; Guo et al., 2025). Moreover, studies on individuals with ASD indicate that they often experience parenting difficulties (Dissanayake et al., 2020; Saito et al., 2022), which suggests that this may limit parental effort—one of the key indicators of a slow reproductive strategy. For these reasons, the aim of the present study is also to test an alternative theoretical model in which ALTs are assumed to be predictors of a fast reproductive strategy.
The study also controlled for sex, which, from an evolutionary standpoint, is an important factor shaping relationships between various psychosocial variables. For instance, men and women differ in their criteria for selecting romantic partners (Buss, 1989; Walter et al., 2020), as well as in their preferences for reproductive strategies associated with life history (see Luoto et al., 2019). Moreover, previous research points to sex differences in the levels of ALTs (Hoekstra et al., 2007) and in attachment styles (Del Giudice, 2011).
Autistic-Like Traits—General Characteristics
ALTs are sometimes described as mild forms of ASD (Arenella et al., 2022) or as the broad autism phenotype (BAP) (De Groot & Van Strien, 2017; Hartley et al., 2019). Studies using the Autism Spectrum Quotient (AQ)—a questionnaire designed to measure autistic traits (Baron-Cohen et al., 2001)—indicate the existence of an ALT–ASD dimension, which has been corroborated by genetic research (Arenella et al., 2022; Bralten et al., 2018; Lundström et al., 2012). These findings also suggest that ASD and ALTs are etiologically related. Furthermore, research has shown that autistic traits measured in the general population tend to be more pronounced in men than in women (Hoekstra et al., 2007; Reed et al., 2016).
The term “broad autism phenotype” was first proposed on the basis of studies indicating that the relatives of individuals with an ASD diagnosis tend to exhibit mild autistic traits (Bolton et al., 1994). In most cases, the term BAP sensu stricto is still used in reference to subclinical differences in these traits among individuals related to those with ASD (e.g., Baron-Cohen, 2008; Crowell et al., 2019; Rubenstein et al., 2019), rather than in reference to individuals from the general population. In contrast, ALTs found in the general population are given more liberal criteria in terms of their definition and selection for research (Sucksmith et al., 2011). This is the meaning we will adopt for the term in this paper.
Research on ALTs covers a wide range of psychological issues, including sensory processing (Robertson & Simmons, 2013), cognitive flexibility (Gökçen et al., 2014), prosocial behavior (Jameel et al., 2015), empathy, sensory symptoms of alexithymia (Riccio et al., 2020), as well as functioning in friendships (e.g., Jobe & Williams White, 2007) and romantic relationships (e.g., Gallitto & Leth-Steensen, 2015). The latter area serves as a direct inspiration for the present study.
ASD has a strong genetic component. In a Swedish twin cohort, the heritability of ASD was estimated at 0.83 (Sandin et al., 2017), while a meta-analysis of twin studies reported estimates ranging from 64% to 91% (Kiddle [née Tick] et al., 2015). Research has also examined the heritability of autistic traits in the general population. For example, in a meta-analysis, Ronald and Hoekstra (2011) found that heritability typically ranges from 60% to 90% for parent- and teacher-rated autistic traits in middle childhood and beyond, whereas self-report measures tend to yield more moderate heritability estimates (36%–57%). These findings support the rationale for investigating the genetic underpinnings of both ASD and ALTs. In fact, genetic studies indicate that ASD and ALTs are influenced by the same genetic risk factors, with ASD representing the extreme end of the population distribution of autistic traits (Arenella et al., 2022; Bralten et al., 2018; Lundström et al., 2012).
Nevertheless, apart from any genetic factors associated with ASD, a range of additional etiological mechanisms have been proposed. These include neurobiological processes (Lamanna & Meldolesi, 2024), epigenetic modifications (e.g., DNA methylation), and prenatal exposure to viral infections (Yoon et al., 2020). Physiological mechanisms have also been implicated, such as immune dysregulation, chronic inflammation, oxidative stress, mitochondrial dysfunction, and alterations in the gut microbiota and its metabolites (Zhuang et al., 2024).
Autistic characteristics measured by the AQ are not strongly associated with age (Lodi-Smith et al., 2021). The same applies to ALT scores. For instance, a study that assessed AQ scores in a sample collected through the UK Channel 4 television website following the broadcast of a medical education program showed that age was not meaningfully correlated with AQ (Ruzich et al., 2015).
One of the problematic issues related to ASD and ALTs is connected with the “diametrical model” (Badcock, 2011; Crespi, 2008; Crespi & Badcock, 2008a, 2008b), which assumes a continuum between autistic traits and the psychosis spectrum.
According to Crespi and Badcock (2008a), schizophrenia, bipolar disorder, and major depression exhibit substantial phenotypic overlap and are conceptualized as part of a broader psychotic spectrum that includes schizotypy. Psychotic conditions involve negative symptoms such as social withdrawal, apathy, perseveration, and flat affect, which have also been linked to autistic-like features. Psychiatry describes the negative dimensions of schizotypy as social withdrawal, anxiety, and reduced emotional expression (see Del Giudice et al., 2010), and negative schizotypy partially overlaps with ALTs, particularly in terms of social isolation, affective flattening, and communication difficulties (Crespi & Badcock, 2008a; Del Giudice et al., 2010). This may reflect common functional mechanisms or phenotypic similarity (Del Giudice et al., 2010).
The continuum between autistic traits and the psychosis spectrum corresponds to a continuum between two opposing modes of cognition. Autism is associated with high levels of mechanistic cognition (visuospatial abilities, cause–effect inference) and low levels of mentalistic cognition (communication deficits, reduced empathy, and limited social understanding). In the psychosis spectrum, the reverse is true, with high mentalistic but low mechanistic abilities (Del Giudice et al., 2014).
However, principal component analyses suggest a two-dimensional relationship between ASD and psychosis, with one axis capturing shared social difficulties and anxiety, and a second, bipolar axis contrasting positive schizotypy (the tendency to experience unusual cognitive and perceptual phenomena) with autistic traits, supporting a diametrical continuum (Dinsdale et al., 2013; see also Del Giudice et al., 2014). Accordingly, a meta-analysis found that negative schizotypal traits are positively correlated with autistic deficits, while positive schizotypy shows an inverse relationship, further supporting this model (Zhou et al., 2019).
The intricate relationship between autism measures, and especially the AQ, and psychotic traits has raised concerns about the reliability of the AQ (Baron-Cohen et al., 2001) as a valid measure of autistic characteristics (Del Giudice, 2018). This issue will be revisited in the Limitations section of the present article.
Life History Theory and Autistic-Like Traits
Originally, life history theory (LHT) was developed in evolutionary biology to describe and compare the species-level strategies organisms use to maximize fitness under ecological constraints (Gadgil & Bossert, 1970; Stearns, 1992). In evolutionary psychology, LHT explains the development of reproductive strategies at the individual level. In general, LHT posits that individuals’ reproductive strategies are linked to the allocation of the organism's bioenergetic resources, which is shaped by specific environmental cues reflecting the quality of one's environment (Belsky et al., 2012; Chang, 2018; Del Giudice et al., 2015; Figueredo et al., 2005; Kavanagh & Kahl, 2018; see also Kim & Choi, 2025). In terms of resource allocation, there is competition over which of the organism's functions should receive the most resources at a given time (Ellis et al., 2009). The principle of allocation, which involves directing an organism's resources toward one function at the expense of another (trade-off), plays a central role in the biological–ecological LHT (Stearns, 1989) and has also been adopted by psychological LHT (see discussion in Nettle & Frankenhuis, 2020).
The two main directions of resource allocation are somatic effort and reproductive effort (Cabeza de Baca & Ellis, 2017; Chua et al., 2017; Del Giudice, 2009; Del Giudice & Belsky, 2010; Ellis et al., 2009; Lu et al., 2022; Łukasik et al., 2021). The former is responsible for maintaining the organism's vital functions, growth, and development. The latter concerns one's ability to produce offspring. Reproductive effort can manifest as effort directed toward a mate (i.e., selecting and retaining a mate) and as parental effort, which involves the allocation of physiological resources (e.g., breastfeeding; Milne & Judge, 2012) as well as material and emotional resources to ensure the child's optimal development.
The so-called fast strategy prioritizes reproductive over somatic effort and mating over parental effort, whereas the slow strategy does the opposite (Figueredo et al., 2012). The slow strategy forms early in life in environments characterized by low levels of unpredictability and harshness (i.e., low risk of morbidity and mortality). In contrast, the fast strategy emerges under conditions of ecological stress and unpredictable environmental changes (i.e., high risk of morbidity and mortality) (Ellis et al., 2009; Gladden & Cleator, 2018; Griskevicius et al., 2013). When survival chances are low, it becomes more advantageous to adopt a “live fast, die young” strategy—that is, to have as many offspring as possible in a short period of time (Gladden & Cleator, 2018).
The fast strategy is characterized by a cluster of psychosocial traits, such as early sexual maturation and sexual debut, a higher number of sexual partners, short-term romantic relationships, limited parental investment, sexual and emotional infidelity, and a preference for diverse sexual behaviors. In contrast, the slow strategy is associated with later maturation and onset of sexual activity, long-term romantic relationships, greater parental investment, and fewer sexual partners (Belsky et al., 1991; Ellis et al., 2009; Figueredo et al., 2013; Griskevicius et al., 2013; Mell et al., 2018; Simpson et al., 2012). LHT research points to sex differences in the use of life history reproductive strategies: women tend to adopt a slow strategy, while men are more likely to adopt a fast one (Figueredo et al., 2005; see also Luoto et al., 2019).
According to LHT, the trade-off between mating and parental effort varies with age. Mating effort is concentrated during peak reproductive readiness, while parental effort typically follows the arrival of offspring. Women's fertility declines from the late 20s, with marked decreases by the late 30s, and men also show reduced fertility by this stage, though less sharply (Dunson et al., 2002). In women, estrogen—central to reproductive functioning (Tang et al., 2019)—peaks in the mid-to-late 20s and declines thereafter (Lephart, 2018), with an average loss of about 80% in the first year after menopause (Horstman et al., 2012).
In men, testosterone functions as an indicator of mating versus parental effort: it rises from early adolescence, peaks around age 19, and gradually declines after about 40, paralleling patterns of reproductive capacity (de la Rochebrochard, 2001; Kelsey et al., 2014). Higher testosterone is positively associated with cumulative mating success (Peters et al., 2008), whereas lower testosterone has been observed among men investing heavily in parental care, suggesting a physiological shift toward parenting effort (Alvergne et al., 2009).
As hypothesized by Marco Del Giudice et al. (2010) and based on sexual selection through mate choice and genomic imprinting, ALTs do not favor a fast strategy, but instead are conducive to reproductive benefits through a strategy focused on parental effort, that is, a slow strategy. Structural equation modeling (SEM) of this hypothesis (Del Giudice et al., 2010; see also Del Giudice et al., 2014) showed that ALTs predict restricted sociosexuality, fewer sexual partners (see also Ponzi et al., 2016), stronger commitment to long-term relationships, and increased investment of time and resources in one's romantic partner.
The impacts of poor social functioning in ASD individuals are reflected in social loneliness (Ee et al., 2019). Compared to nonautistic couples, autistic/nonautistic couples have also reported lower satisfaction with affective communication (Yew et al., 2023), reported fewer opportunities to meet potential new partners, had shorter relationship duration, and experienced greater anxiety when meeting a potential partner (Hancock et al., 2020). Individuals with higher levels of ALT's reported higher levels of same-sex attraction (Qualls et al., 2018).
The phenomenon studied in the context of interpersonal relationships among individuals on the autism spectrum is assortative mating. Assortative mating—the tendency to choose similar partners (Luo, 2017)—is evident among individuals on the autism spectrum, who are more likely to form relationships with similar others (Feng et al., 2026; Jackson et al., 2022). Similarity often involves traits such as systemizing, emotion recognition, spatial skills (Richards et al., 2022), and theory of mind (Jackson et al., 2022). Although assortative mating is typically linked to slow life history strategies and stable environments (Figueredo & Wolf, 2009), individuals on the ALT–ASD spectrum often experience unstable early environments (Berg et al., 2016; Takeda et al., 2024), which predict a faster life history strategy (Csathó & Birkás, 2018).
Thus, assortative mating in this group may instead function as an escape to safer, more predictable social contexts. Individuals with ASD show elevated anxiety (Kent & Simonoff, 2017), including social anxiety related to difficulties in understanding social cues, and unpredictability in social settings often heightens anxiety levels in ASD individuals, making them avoid such situations (Montaser et al., 2023); similar patterns are observed in subjects with ALTs (Freeth et al., 2013; Shi & Hirai, 2024). Notably, high anxiety has been associated with earlier and increased reproduction (Jacobson & Roche, 2018), a pattern characteristic of a fast life history strategy.
Analyses of reproductive strategies in present-day societies suggest that LHT effectively explains the observed patterns. Data from over 200 countries (Brandt & Maner, 2024) show that lower mortality risk is associated with slower reproduction. A study of nearly 33,000 individuals from the Czech Republic found that higher education correlates with fewer children and a later age at first childbirth (Sýkorová & Flegr, 2021).
Improvements in living standards, medicine, and food security have increased life expectancy, making slower life history strategies more advantageous in developed societies (Sýkorová & Flegr, 2021). Although the rise of agriculture in human evolution was linked to poorer health and faster strategies, recent improvements in living conditions and public health have enabled a shift back toward slower reproductive strategies (Sýkorová & Flegr, 2021).
Attachment Theory, Romantic Relationships, and Autistic-Like Traits
According to the theory advanced by John Bowlby (1969, 1973, 1988), the attachment system serves as a mechanism ensuring offspring survival. Mary Ainsworth (1979), who further developed attachment theory, identified three attachment styles: secure, insecure-avoidant, and insecure-ambivalent.
Hazan and Shaver (1987), who applied attachment theory in the study of romantic relationships, proposed the concept of romantic love as an attachment process. Brennan et al. (1998) identified two dimensions of attachment in adult romantic relationships: anxious and avoidant. The former describes individuals with a low sense of security, a strong need for closeness, and frequent worry about their relationship. The latter describes individuals who avoid closeness, are self-reliant, and are less invested in relationships.
Attachment styles are significant predictors of relationship quality (Kaźmierczak & Błażek, 2015; Li & Chan, 2012; Sisi et al., 2021). People who are securely attached in their romantic relationships report greater relationship satisfaction than those with other attachment styles (Gleeson & Fitzgerald, 2014; Hammond & Fletcher, 1991; Li & Chan, 2012; Sisi et al., 2021; Vollmann et al., 2019; Wongpakaran et al., 2012). A meta-analysis of 73 studies (Li & Chan, 2012) found that both anxious and avoidant styles are correlated with lower levels of positive relationship indicators and higher levels of negative indicators. Overall, the secure attachment style is associated with better romantic relationship quality, whereas the insecure ones are linked to poorer quality.
In their pioneering research, Hazan and Shaver (1987) demonstrated that attachment styles are also correlated with different experiences of parental bonding quality in childhood. This finding was corroborated by later studies (Feeney & Noller, 1990; Gleeson & Fitzgerald, 2014): individuals with a secure attachment style tend to retrospectively view their parents more positively than those with insecure attachment styles, and especially those classified as fearful-avoidant (Gleeson & Fitzgerald, 2014). These reports are consistent with predictions from LHT (Szepsenwol & Simpson, 2019) and psychosocial acceleration theory (PAT; Belsky et al., 1991), both of which suggest that the quality of the family environment, including early childhood attachment, has a bearing on future reproductive strategies.
Sex differences in attachment styles have also been reported. A meta-analysis of attachment styles (Del Giudice, 2011), which encompassed 100 studies using samples from various regions of the world and questionnaires based on the two-dimensional model of attachment, found that men predominantly exhibit an avoidant style, whereas women are more likely to exhibit an anxious style (see Scharfe, 2016).
Attachment styles show dynamic changes across the lifespan. Chopik et al. (2019) found that attachment anxiety declines with age, particularly during middle and older adulthood. Avoidance also decreases, but in a more linear fashion with age. Van Assche et al. (2013) likewise reported in a review paper a significant decline in attachment anxiety, but not in avoidant attachment. In turn, Bogaert and Sadava (2002) reported a negative correlation between age and attachment anxiety (in women). Another study (Segal et al., 2009) showed that older adults score lower than younger adults on the ambivalent–worry attachment scale and the preoccupied attachment scale (characterized by craving closeness and intimacy while simultaneously fearing abandonment or rejection), whereas no age differences were found for secure, avoidant, or dismissing attachment. In sum, the cited research indicates a consistent effect for attachment anxiety—namely, its decline with age—whereas the findings concerning attachment avoidance appear more complex.
Many studies have examined the relationship between the degree of ALTs and attachment styles. It has been found that in adults a higher level of ALTs is associated with insecure attachment styles, that is, anxious and avoidant (Ameli et al., 2019; Brennan et al., 1998; Gallitto & Leth-Steensen, 2015; Lamport & Turner, 2014; Pollmann et al., 2010; Sörnyei et al., 2024), and that insecure attachment styles mediate the relationship between higher ALT scores and lower satisfaction in close relationships (Beffel et al., 2021).
One of the factors that can be associated with insecure attachment among individuals with ALTs and ASD is mentalizing impairment. Such impairments—difficulties in attributing mental states to oneself and others—are associated with insecure attachment in individuals with ALTs and ASD, as these abilities develop within early relationships that shape internal working models (Sörnyei et al., 2024). Depending on relationship quality, these models can either support or hinder mentalizing and attachment security. Moreover, such impairments—possibly linked to atypical amygdala–prefrontal functioning—mediate the relationship between ALTs and anxious–avoidant attachment (Sörnyei et al., 2024).
Attachment Orientation and Mate Retention Tactics
Nineteen specific strategies have been identified (Buss et al., 2008), which can be hierarchically grouped into five broader categories: Direct Guarding (e.g., Concealment of Mate, Monopolization of Mate's Time), Intersexual Negative Inducements (e.g., Punishing Mate's Infidelity Threat, Emotional Manipulation), Positive Inducements (e.g., Sexual Inducements, Appearance Enhancement), Public Signals of Possession (e.g., Verbal and Physical Possession Signals), and Intrasexual Negative Inducements (e.g., Derogation of Mate, Violence Against Rivals).
According to another classification (Miner et al., 2009), mate retention tactics fall into two main categories. The first one includes cost-inflicting behaviors aiming to lower the partner's self-esteem—making them feel unworthy of the current relationship—or to instill fear and social isolation, which may increase the likelihood of staying in the relationship. The second category consists of benefit-provisioning behaviors, which increase the partner's satisfaction and strengthen relationship bonds (Albert & Arnocky, 2016).
Research on the relationships between attachment styles and mate retention tactics has been conducted mainly with a focus on avoidant and anxious attachment styles. This is due to the widespread use of the Experiences in Close Relationships (ECR) Scale (Brennan et al., 1998) to measure attachment. Studies that take into account the secure attachment style are—according to the authors’ knowledge—virtually nonexistent. The only study known to us, Nascimento et al. (2022), found no significant correlation between these variables.
Cross-sectional studies (Barbaro et al., 2019; Nascimento et al., 2022; see also Altgelt & Meltzer, 2019) have shown that individuals with avoidant attachment styles tend to use both cost-inflicting and benefit-provisioning tactics less frequently. In contrast, individuals with anxious attachment styles are more likely to use such strategies. These differences stem from distinct ways of interpreting cues related to the threat of infidelity or relationship dissolution and from the differing dynamics of the attachment system: downplaying threat cues and deactivation of the attachment system in avoidantly attached individuals versus hypervigilance and hyperactivation in anxiously attached individuals (Barbaro et al., 2019; see also Kruger et al., 2013; Mikulincer & Shaver, 2015).
Men use the benevolent mate retention strategy more frequently than women (they often engage in benefit-provisioning behaviors but infrequently in cost-inflicting ones) and also more often employ the exhaustive strategy (engaging in both cost-inflicting and benefit-provisioning behaviors). Women, on the other hand, more frequently use a disengaged mate retention strategy (they rarely engage in either benefit-provisioning or cost-inflicting mate retention behaviors) (Lopes & Shackelford, 2019). In an Iranian sample (Babaeizad et al., 2022), men reported significantly higher scores than women on both cost-inflicting and benefit-provisioning tactics. In turn, age is negatively associated with both types of mate retention tactics (Atari et al., 2017; Degiuli et al., 2023; de Miguel & Buss, 2011).
Attachment Orientation and Reproductive Strategies
LHT posits that the attachment system mediates the relationship between the environmental conditions of early childhood and the development of life history strategies in adulthood (Chisholm, 1996; Szepsenwol & Simpson, 2019; Young et al., 2017). The first predictions on this topic were formulated in socialization theory, which later served as the foundation for PAT (Belsky et al., 1991; see critique of PAT in the Limitations section). The latter theory emphasizes that early exposure to family related stressors (e.g., marital conflict, single parenting, unstable employment) leads to suboptimal parenting, which in turn results in insecure attachment, accelerated maturation, an earlier onset of sexual activity, short-term pair bonds, and limited parental investment (Belsky et al., 1991). The attachment system is sensitive to environmental signals (safe vs. harsh) and responds with adaptive emotional, cognitive, and behavioral reactions (Szepsenwol & Simpson, 2019), which collectively form a life history strategy optimal for such conditions.
Importantly, theoretical analyses suggest that attachment orientation mediates life history effects. For example, individuals with secure attachment typically adopt a slow reproductive strategy, whereas those with insecure attachment are more likely to pursue a fast strategy (Belsky et al., 1991; Chisholm, 1996; Del Giudice, 2009; Guo et al., 2025; Schmitt, 2005; Szepsenwol & Simpson, 2019).
The relationship between attachment style and reproductive strategy is supported primarily by indirect evidence, such as the age at first sexual intercourse and the number of sexual partners—both of which are key indicators of reproductive strategies (e.g., Simpson et al., 2012). In adults, a secure attachment style is associated with a later onset of sexual activity (Bogaert & Sadava, 2002). On the other hand, so-called unrestricted orientation—the tendency to engage in sex outside of a committed relationship—is positively correlated with insecure attachment styles (Brennan & Shaver, 1995). Among adults of both sexes, the anxious attachment style has been linked to earlier sexual activity and a higher number of sexual partners (Bogaert & Sadava, 2002) and stronger intentions to engage in sex without contraception (French et al., 2020).
Research on the relationship between avoidant attachment style and indicators of reproductive strategies is less conclusive. Studies involving college students suggest that the avoidant style is associated with greater promiscuity (Brennan & Shaver, 1995; Chen, 2017), but French et al. (2020) found no correlation between this attachment style and engagement in unprotected sexual activity, which the authors explain by suggesting that those who value emotional independence may be less likely to engage in intimacy-promoting behaviors, such as unprotected sex.
In summary, these findings point to a link between secure and anxious attachment styles and reproductive strategies, but a less obvious relationship between avoidant attachment and reproductive strategies.
To the best of our knowledge, there are few studies examining the relationship between attachment styles and reproductive strategies in the context of LHT. Kruger (2017) demonstrated that avoidant attachment is positively correlated with mating effort and negatively with parental effort (correlations with the anxious style were statistically insignificant). Dunkel et al. (2016) showed that individuals with a slow reproductive strategy tend to exhibit a secure attachment style, whereas those with a fast strategy tend to exhibit insecure styles. Međedović et al. (2022) found that both anxious and avoidant attachment are negatively related to long-term mating, and avoidance is negatively associated with parenthood motivation. In summary, based on theoretical analyses and the available research, it can be assumed that insecure attachment styles are positively correlated with a fast reproductive strategy and negatively with a slow reproductive strategy.
Life History Reproductive Strategies and Mate Retention Tactics
According to analyses by Buss et al. (2008), different mate retention tactics correlate in various ways with measures of controlling behavior, violence, and coercion, including sexual coercion. In general, tactics classified under Positive Motivation (e.g., Resource Display, Sexual Inducements, Love and Care, Verbal Possession Signals, Submission and Devaluation) either do not correlate at all or show only a low positive correlation with such measures. All of these tactics fall under the category of benefit-provisioning strategies (Miner et al., 2009) and can therefore be considered mutualistic. All the remaining tactics correlate positively with measures of control and violence (e.g., Vigilance, Derogation of Mate, Concealment of Mate, Intrasexual Threats). These tactics fall under the categories of Direct Guarding, Intersexual Negative Inducement, and Intrasexual Negative Inducement (Buss, 1988a, 1988b); they are cost-inflicting (Miner et al., 2009) and may be considered antagonistic.
There are few studies examining relationships between reproductive strategies and mate retention tactics. Gladden et al. (2013) showed that an antagonistic strategy characterized by exploitative acquisition of resources in social and sexual relationships is typical of individuals with a fast life history reproductive strategy. In contrast, a mutualistic strategy, marked by cooperation and sensitivity to the needs of others, characterizes individuals with a slow reproductive strategy. Research by Reynolds and McCrea (2015) also confirms that people employing a fast reproductive strategy tend to use exploitative strategies in interpersonal relationships, aiming to increase their own resources at the expense of others. According to other research (Kiire, 2019), a fast reproductive strategy is associated with violence toward one's mate, which is categorized as a cost-inflicting tactic.
In romantic relationships, self-esteem plays an important role. For example, individuals with lower self-esteem report lower satisfaction and commitment in their relationships than individuals with higher self-esteem (Robinson & Cameron, 2012). Self-esteem is correlated with mate value, and studies have shown that individuals with higher mate value tend to adopt a slower reproductive strategy (Dillon et al., 2013; McDowell & Starratt, 2020). However, individuals with ASD (van der Cruijsen & Boyer, 2021), similarly to individuals with ALTs (Pollmann et al., 2010), tend to have lower self-esteem, which suggests that autistic traits may be associated with lower mate value. This, in turn, may indicate a tendency toward a faster reproductive strategy and a greater inclination to use cost-inflicting tactics.
The use of these tactics is also associated with the threat of infidelity (Buss & Shackelford, 1997). As Jones et al. (2007) demonstrated, individuals higher in mating effort (which may be treated as a proxy for a fast life history strategy) exhibit stronger aversive emotional responses to situations linked to infidelity. They are also more likely to use punitive (i.e., cost-inflicting) responses designed to prevent infidelity (Jones et al., 2007). Furthermore, individuals who perceive themselves as less desirable report higher levels of suspicious jealousy (Zeigler-Hill et al., 2025).
Perceived risk of infidelity is also positively associated with preferences for both cost-inflicting and benefit-provisioning behaviors (Barbaro et al., 2019). In situations signaling infidelity, people experience jealousy and display a wide range of behaviors aimed at protecting their relationships (Degiuli et al., 2023). Research (Arnocky & Locke, 2020; Arnocky et al., 2024; Davis et al., 2018; Degiuli et al., 2023) consistently shows that jealousy positively predicts both cost-inflicting and benefit-provisioning behaviors.
Research conducted on nonclinical samples suggests that men who report more autistic traits often feel that they lack intimacy or cannot trust their partner. This may be a consequence of lower self-esteem and lower mate value, and it may also explain why individuals with ALTs experience a greater threat of infidelity and higher levels of jealousy, as well as a stronger tendency to use both cost-inflicting and benefit-provisioning tactics.
In sum, we predict that individuals with ALTs prefer to use both cost-inflicting and benefit-provisioning tactics.
In turn, slow strategists more often use benefit-provisioning tactics and do not show any associations with cost-inflicting tactics (Pazhouhi et al., 2024), although there are socioeconomic and educational factors significantly impacting these behaviors. Other research indicates that a slow strategy is associated with decreased levels of sexually coercive behaviors and intimate partner aggression (see Gladden et al., 2013), which are usually costly for partners.
The Current Study
The conducted review of the relevant literature will serve as a basis for formulating hypotheses related to the general patterns observed between variables (e.g., the relationship between ALTs and attachment orientations). In addition, we have formulated specific assumptions that pertain exclusively to ALTs.
Assumption 1: ALTs Predict Lower Parental Effort
According to Del Giudice’s (2014) model and previous research (Del Giudice et al., 2010; see also Del Giudice et al., 2014), individuals with ALTs tend to favor parental investment and are considered slow strategists. However, the question of parental effort among individuals with autistic traits is more complex. Studies on parenting in individuals with ASD indicate that they often experience parenting difficulties (Dissanayake et al., 2020; Saito et al., 2022) as well as reduced parental efficacy (Lau et al., 2016). For instance, in a Japanese sample (Sakakihara et al., 2024), fathers with autistic traits were significantly less likely to prepare meals for their children, help them eat, or assist them in changing clothes. Parenting difficulties among individuals with ASD are thought to be associated, among other factors, with attention-switching challenges and communication barriers (Saito et al., 2022).
Research on the BAP, a constellation of subclinical social, communication, and behavioral differences in family members—and thus potentially analogous to ALTs—has also revealed associations with a history of language and literacy problems (Bishop et al., 2004; see also O’Connor et al., 2025). Such difficulties may hinder communication with children and contribute to less effective parenting outcomes. Furthermore, evidence suggests that specific BAP traits in the caregivers of autistic children are linked to distinct parenting behaviors: aloofness is associated with less positive parenting, pragmatic language difficulties with lower emotion coaching and higher levels of poor monitoring, and rigidity with emotion dismissing (DeLucia et al., 2022).
In research concerning ALTs (non-ASD), Ponzi et al. (2016) reported that participants scoring higher on the AQ had lower short-term mating orientation, but there was no significant correlation between the AQ and long-term mating orientation. These results suggest that individuals with ALTs do not necessarily prefer long-term relationships. There is a statistically significant difference between the duration of relationships among ASD and non-ASD individuals. Relationship duration is significantly shorter in the case of individuals with ASD (Hancock et al., 2020; Yew et al., 2023).
Taken together, these findings lead us to hypothesize that individuals with ALTs will score lower on parental effort.
Assumption 2: Individuals with ALTs Prefer Mating Effort
Building upon the preceding assumption, we propose that ALTs may be associated with mating effort, reflecting a fast life history strategy. Naturally, an alternative scenario is also conceivable, in which ALTs are linked to both parental and mating effort. However, for the purposes of the present study, we chose to clearly contrast the assumptions concerning the relationship between ALTs and reproductive strategies, treating this hypothetical dual-association scenario as a potential endpoint rather than a starting point.
This hypothesis is grounded in the theoretical review presented earlier, which examined the relationships between ALTs, attachment styles, reproductive strategies, and mate retention tactics. Specifically, ALTs are positively associated with both anxious and avoidant attachment styles, which are also positively predicted by a fast reproductive strategy (linked to both kinds of mate retention tactics). Thus, we hypothesize that individuals with ALTs may prefer mating effort and tend to employ both cost-inflicting and benefit-provisioning mate retention tactics.
Predictions
The first objective of this study was to test the model of relationships between ALTs and mate retention tactics considering the variables of attachment style and reproductive strategy. Based on a literature review and additional specific assumptions concerning ALTs, the model assumes the following relationships:
ALTs are a positive predictor of cost-inflicting and benefit-provisioning tactics.
ALTs are a positive predictor of anxious and avoidant attachment.
Anxious and avoidant attachment are negative predictors of a slow reproductive strategy (parental effort) and positive predictors of a fast reproductive strategy (mating effort).
Anxious and avoidant attachment styles mediate the relationship between ALTs and mate retention tactics in that individuals with a greater degree of ALTs exhibit higher levels of anxious and avoidant attachment. Anxious attachment is a positive predictor of both types of tactics, while avoidant attachment is a negative predictor of them.
Assuming that ALTs are a negative predictor of a slow reproductive strategy, we hypothesize that a “weaker” (i.e., less pronounced) slow reproductive strategy is associated with less frequent use of benefit-provisioning tactics. Additionally, we predict that a faster reproductive strategy is associated with more frequent use of both cost-inflicting and benefit-provisioning tactics.
The second objective of the study was to determine whether the relationships described in the tested model are moderated by sex. This question was motivated by the results of studies presented in the theoretical section, which suggest that sex differentiates outcomes in terms of ALTs, life history reproductive strategies, attachment styles, and some of the relationships between these variables.
Methods
Participants
All participants were Polish and were recruited from the Podkarpacie region. The study included 811 individuals who had been in a romantic relationship for at least 3 months. Data from 15 participants were removed due to substantial missing responses (over 20%). Ultimately, responses from 796 participants (52% women) were included in the analysis. The average age of the participants was 36.4 years, with a standard deviation of 13.5. The educational attainment of the participants was as follows: primary 3.8%, vocational 16.8%, secondary 38.4%, and tertiary 38.4%; 20 participants did not provide that information (2.5%). Furthermore, 47.4% of the participants were from rural areas, 21% from towns with fewer than 50,000 inhabitants, 10.4% from towns with 50,000–100,000 inhabitants, 14% from cities with 100,000–250,000 inhabitants, and 7% from cities with over 250,000 inhabitants. These data were missing from two participants. Finally, 67.6% of the participants were professionally active, 7.2% were unemployed, 16.1% were students, 6.4% were retirees/pensioners, 2.4% belonged to other categories, and three participants did not provide a response to this question.
Procedure
The study was conducted by 10 interviewers, comprising volunteers and fourth-year pedagogy students, who interacted directly with the participants. The interviewers did not know the objectives of the study or the detailed characteristics of the tools. Prior to data collection, interviewers underwent a 30-min training course covering study procedures, participant anonymity, the right to withdraw, and questionnaire administration. Any questions raised during the training were clarified, and interviewers were not compensated for their involvement in the study.
The study was conducted using a set of questionnaires. The participants received oral instructions, which were also provided in writing and attached to the first page of the questionnaire set. The participants placed completed questionnaire sets anonymously into envelopes. The time for completing the tests was unlimited but did not exceed 40 min. The participants did not receive any rewards. The study was approved by the Bioethics Committee at the University of Rzeszów. All participants provided written informed consent in accordance with the Declaration of Helsinki.
Statistical Procedure
Statistical analyses were performed using SPSS 21 and AMOS 28. Examinations of missing values indicated that item-level missingness across all questionnaires ranged from 0.1% to 1.4%. To assess the pattern of missing data, Little's missing completely at random (MCAR) test was conducted; its results, χ2(9,738) = 11,037.80, p < .001, suggest that the data were not MCAR. However, an exploratory analysis of the missing data patterns indicated that the data were missing at random (MAR), as the occurrence of missingness was associated with the participants’ gender: specifically, men were overrepresented among cases with missing data in the AQ, ECR-R (Experience in Close Relationships-Revised, Short Form), and MRI-SF (Mate Retention Inventory-Short Form), whereas women were overrepresented among cases with missing data in the Brief Self-Report Scales Assessing Life History Dimensions of Mating and Parenting Effort.
Missing data were replaced using multiple imputation with five iterations using multiple imputation by fully conditional specification (FCS MI), which is a powerful and statistically valid method for creating imputations based on the assumption of MAR (Liu & De, 2015). The skewness of the variables was <2 (the highest value was obtained for Intrasexual Negative Inducements at 1.56); kurtosis was <3, and although only the variable Intrasexual Negative Inducements had a kurtosis of 3.02, the nonparametric correlation coefficient Spearman's rho was used in the calculations. The significance of differences was tested with the Mann–Whitney U test. Collinearity was tested separately for cost-inflicting and benefit-provisioning tactics and was found not to pose a problem, with the highest variance inflance factor (VIF) value being 1.38, well below the threshold of VIF >10.0 (Kline, 2016) or the more restrictive VIF >3.3 (Kock, 2015). The obtained indicators also showed that the verified relationships model is free of common method bias (Kock, 2015).
The relationships posited in the hypotheses were tested using SEM. The sample size (N = 796) was sufficient for such analysis, as it exceeded the recommended minimum sample size N for the number of estimated parameters p (N × p): 20 participants × 24 parameters in the model = 480 (Kline, 2016). Reported standardized regression coefficients for the structural pathways were estimated using maximum likelihood. For the tested model of paths between the variables, bootstrap analysis with 200 bootstrap samples was also performed, which indicated that the sample distribution reflected the basic shape of the population distribution and enabled the establishment of confidence intervals (Kline, 2016). Additional regression analyses were also conducted using Hayes’ PROCESS macro (Models 6 and 4; Hayes, 2013).
Measures
The AQ questionnaire (Baron-Cohen et al., 2001; in a Polish adaptation by Pisula et al., 2013). The AQ is a self-administered measure that provides a quantitative assessment of the degree to which an adult individual exhibits autistic traits. This instrument evaluates five areas of functioning: social skills, communication, attention switching, imagination, and attention to local details.
The AQ consists of 50 items, each rated by participants on a 4-point Likert scale, ranging from 1 (definitely agree) to 4 (definitely disagree). Approximately half of the items are phrased to elicit a “disagree” response, and the other half to elicit an “agree” response. For example, the items I prefer to do things with others rather than on my own and I prefer to do things the same way over and over again are scored first, whereas items such as If I try to imagine something, I find it very easy to create a picture in my mind and When I’m reading a story, I can easily imagine what the characters might look like are scored second.
The participants’ responses were scored according to the key provided by Baron-Cohen et al. (2001). A score of 1 was assigned to definitely agree or slightly agree responses on Items 1, 2, 4–7, 9, 12–13, 16, 18–23, 26, 33, 35, 39, 41–43, and 45–46, and to definitely disagree or slightly disagree responses on Items 3, 8, 10–11, 14–15, 17, 24–25, 27–32, 34, 36–38, 40, 44, and 47–50. A higher score indicates a greater intensity of autistic traits. In the present study, Cronbach's alpha for the entire AQ scale was .75.
Brief Self-Report Scales Assessing Life History Dimensions of Mating and Parenting Effort (Kruger, 2017, own translation). Each scale contains four self-assessment items in the areas of mating and parental effort. For example: Has slept with a large number of partners over the course of their life (mating effort), Use most of your money to support your family (parental effort). Respondents indicate their answers on a 7-point Likert scale, ranging from 1 (strongly disagree) to 7 (strongly agree). Higher scores on the scales correspond to higher levels of parental or mating effort, respectively. Parental effort was treated as a proxy for a slow life history reproductive strategy, whereas mating effort was treated as a proxy for a fast life history strategy. This approach was based on the correlations obtained by Kruger (2017) with various measures of life history strategies, which generally point to the existence of a resource allocation trade-off mechanism and associations typical of the slow–fast reproductive strategy continuum. In the present study, Cronbach's alpha was .79 for parental effort and .88 for mating effort.
ECR-R (Brennan et al., 1998; Fraley et al., 2000; in Polish adaptation by Lubiewska et al., 2016). It is a self-report scale designed for testing individual differences in terms of attachment orientation. The ECR-R SF is an abbreviated version of the ECR-R and consists of 18 items, of which half (9) are indicative of anxious attachment, while the other half are indicative of avoidant attachment (Lubiewska et al., 2016). Examples include: I often worry that my partner will not want to stay with me; I prefer not to be too close to romantic partners. Some items need to be recoded, for example: When I share my private thoughts and feelings with someone close to me, I feel good. Respondents rate the items on a 7-point Likert scale from 1 (strongly disagree) to 7 (strongly agree). High scores on one or both dimensions indicate an insecure attachment orientation. Conversely, individuals with low levels of attachment-related anxiety or avoidance may be perceived as exhibiting a secure attachment orientation (Brennan et al., 1998). In the present study, Cronbach's alpha was .92 for anxiety, .85 for avoidance, and .77 for the overall measure.
MRI-SF (Buss et al., 2008; in a Polish adaptation by Marzec et al., 2014). The inventory is an instrument designed to identify behaviors used to retain one's partner in a relationship. The short version contains 38 items linked to 19 specific tactics. Sample items include Called to make sure my partner was where she said she would be; Pleaded that I could not live without my partner; Bought my partner an expensive gift; Asked my partner to wear my ring. The 19 specific tactics may be subsumed under two categories (Miner et al., 2009): cost-inflicting and benefit-provisioning behaviors. The participants rated the items on a scale from 0 (never) to 3 (often). In the presented study, Cronbach's alpha for MRI-SF was .94, and Cronbach's alpha was .91 for cost-inflicting tactics and .92 for benefit-provisioning tactics.
Results
Preliminary Analysis
Research data are available at https://doi.org/10.23668/psycharchives.16425. Before analyzing the results of testing the presented model, descriptive statistics and correlations between the key variables were examined (see Table 1).
Table 1.
Descriptive Statistics and Correlations Between the Variables Included in the Study.
| Variable | M | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
|---|---|---|---|---|---|---|---|---|---|---|
| 1. AQ | 18.9 | 5.6 | – | |||||||
| 2. Anxiety | 27.2 | 10.2 | 0.28*** | – | ||||||
| 3. Avoidance | 21.3 | 7.4 | 0.33*** | 0.30*** | – | |||||
| 4. Parental effort | 21.8 | 4.5 | −0.09** | −0.28*** | −0.43*** | – | ||||
| 5. Mating effort | 10.5 | 5.3 | 0.18*** | 0.30*** | 0.30*** | −0.44*** | – | |||
| 6. Cost tactics | 35.9 | 10.8 | 0.17*** | 0.44*** | 0.10** | −0.16*** | 0.31*** | – | ||
| 7. Benefit tactics | 35.8 | 10.8 | −0.11** | 0.20*** | −0.20*** | 0.01 | 0.07 | 0.66*** | – | |
| 8. Age | 36.4 | 13.5 | 0.08* | −0.25** | −0.03 | 0.41** | −0.27** | −0.19** | −0.20** | – |
Note. AQ = overall score for AQ; anxiety = anxious attachment; avoidance = avoidant attachment; parental effort = an empirical proxy for a slow reproduction strategy; mating effort = an empirical proxy for a fast reproduction strategy; cost tactics = tactics inflicting costs on the partner; benefit tactics = tactics benefitting the partner; AQ = autism spectrum quotient.
*p < .05, **p < .01, ***p < .001.
As shown in Table 1, the AQ is positively correlated with attachment anxiety and attachment avoidance. The AQ is weakly and negatively correlated with parental effort and positively (and more strongly) correlated with mating effort. In the case of the AQ, a positive correlation was found with cost-inflicting tactics, and a negative correlation with benefit-provisioning ones. This suggests that individuals with higher ALT levels tend to use benefit-provisioning tactics less often, and cost-inflicting tactics more often.
Negative correlations were found between both anxious and avoidant attachment and parental effort, and positive correlations between both of these attachment styles and mating effort. Attachment anxiety is positively correlated with both cost-inflicting and benefit-provisioning tactics. In turn, attachment avoidance is positively correlated with cost-inflicting tactics and negatively with benefit-provisioning tactics.
Parental effort was negatively correlated with cost-inflicting tactics; conversely, mating effort showed a positive correlation with them. This indicates that a slow reproductive strategy is associated with less frequent use of cost-inflicting mate retention tactics, whereas a fast strategy is linked to their more frequent use. A positive correlation was found between cost-inflicting and benefit-provisioning tactics.
With respect to age, it was found that with increasing age, attachment anxiety decreases, parental effort increases, mating effort diminishes, and the frequency of using both types of mate retention tactics declines.
In the next step, we analyzed sex differences in terms of the key variables (see Table 2).
Table 2.
Summary of Differences Between Women and Men in the Mann–Whitney U Test.
| Women (n = 411) | Men (n = 385) | Z Value | |
|---|---|---|---|
| Mean Rank | Mean Rank | ||
| AQ | 374.47 | 424.15 | 3.05** |
| Anxiety | 393.94 | 403.36 | 0.58 |
| Avoidance | 356.12 | 443.74 | 5.378*** |
| Mating effort | 437.83 | 356.51 | −5.00*** |
| Partner effort | 362.43 | 437.00 | 4.59*** |
| Cost tactics | 381.07 | 417.11 | 2.21* |
| Benefit tactics | 366.18 | 433.00 | 4.01*** |
| Age | 386.7 | 403.89 | 1.06 |
Note. AQ = overall score for AQ; anxiety = anxious attachment; avoidance = avoidant attachment; parental effort = an empirical proxy for a slow reproduction strategy; mating effort = an empirical proxy for a fast reproduction strategy; cost tactics = tactics inflicting costs on the partner; benefit tactics = tactics benefitting the partner; AQ = autism spectrum quotient.
*p < .05, **p < .01, ***p < .001.
Men scored higher on the AQ than women and used mate retention tactics more often. Men also showed a significantly higher level of attachment avoidance than women. Women scored higher on parental effort, whereas men—on mating effort. No significant differences were found regarding age.
SEM Model
In the next step, we tested the theoretical model of relationships between variables using SEM (see Figure 1), applying the maximum likelihood estimation method. We evaluated the accuracy of the model using the following indicators: a nonsignificant p-value in the chi-square test, a root mean square error of approximation (RMSEA) < .08, and a comparative fit index (CFI) > .90. The theoretical model was modified to achieve a good fit to the data. To this end, we removed three statistically nonsignificant paths. The final structural model (see Figure 1) demonstrated a very good fit to the data: χ2(4) = 4.40, p = .35, CFI = 1, RMSEA [90% CL] = .01 [0.0, .06], PCLOSE = .91. Table 3 presents the results of bootstrap analysis.
Figure 1.
Model of relations between variables obtained through SEM analysis. Note. Estimations between variables are given as standardized effects. AQ = overall score for AQ; anxiety = anxious attachment; avoidance = avoidant attachment; parental effort = an empirical proxy for a slow reproduction strategy; mating effort = an empirical proxy for a fast reproduction strategy; cost tactics = tactics inflicting costs on the partner; benefit tactics = tactics benefitting the partner; ns. = nonsignificant effect; SEM = structural equation modeling; AQ = autism spectrum quotient.
Table 3.
Results of Bootstrap Analysis for Paths (Direct Effects) in the Tested Model, Including Unstandardized and Standardized Regression Coefficients.
| Path | B | SE | C.R. | p | β | 95% CL | p | |||
|---|---|---|---|---|---|---|---|---|---|---|
| LL | UL | |||||||||
| Anxiety | ← | AQ | 0.51 | 0.06 | 8.14 | *** | 0.28 | 0.21 | 0.36 | .007 |
| Avoidance | ← | AQ | 0.42 | 0.05 | 9.42 | *** | 0.32 | 0.25 | 0.37 | .009 |
| Mating effort | ← | AQ | 0.07 | 0.03 | 2.12 | .03 | 0.08 | −0.01 | 0.15 | .111 |
| Mating effort | ← | Avoidance | 0.13 | 0.03 | 5.21 | *** | 0.18 | 0.12 | 0.27 | .009 |
| Mating effort | ← | Anxiety | 0.12 | 0.02 | 6.44 | *** | 0.23 | 0.15 | 0.32 | .006 |
| Parental effort | ← | Anxiety | −0.07 | 0.02 | −4.61 | *** | −0.16 | −0.23 | −0.09 | .005 |
| Benefit tactics | ← | Avoidance | −0.33 | 0.04 | −8.47 | *** | −0.23 | −0.27 | −0.18 | .009 |
| Cost tactics | ← | Anxiety | 0.40 | 0.03 | 11.44 | *** | 0.37 | 0.31 | 0.43 | .013 |
| Parental effort | ← | AQ | 0.06 | 0.03 | 2.17 | .03 | 0.08 | 0.02 | 0.16 | .01 |
| Parental effort | ← | Avoidance | −0.24 | 0.02 | −11.52 | *** | −0.39 | −0.47 | −0.30 | .009 |
| Benefit tactics | ← | Mating effort | 0.16 | 0.07 | 2.15 | .03 | 0.08 | −0.005 | 0.16 | .054 ns |
| Benefit tactics | ← | AQ | −0.30 | 0.05 | −5.9 | *** | −0.16 | −0.20 | −0.11 | .011 |
| Benefit tactics | ← | Anxiety | 0.29 | 0.04 | 7.76 | *** | 0.28 | 0.22 | 0.34 | .008 |
| Cost tactics | ← | Mating effort | 0.47 | 0.07 | 7.24 | *** | 0.23 | 0.16 | 0.32 | .007 |
Note. B = unstandardized regression coefficients; β = standardized regression coefficients. C.R. = critical ratio. 95% confidence intervals (bias-corrected percentile method). LL = lower limit; UL = upper limit; AQ = overall score for AQ; anxiety = anxious attachment; avoidance = avoidant attachment; parental effort = an empirical proxy for a slow reproduction strategy; mating effort = an empirical proxy for a fast reproduction strategy; cost tactics = tactics inflicting costs on the partner; benefit tactics = tactics benefitting the partner; ns = nonsignificant effect; AQ = autism spectrum quotient. ***p < .001.
The results (Table 3) show that the AQ is a negative predictor of benefit-provisioning tactics and a positive predictor of anxious and avoidant attachment; it is also a positive predictor of parental effort (but see the mediation described below).
Furthermore, it was found that anxious attachment is a negative predictor of parental effort and a positive predictor of mating effort, as well as a positive predictor of both cost-inflicting and benefit-provisioning tactics. Avoidant attachment is, in turn, a negative predictor of parental effort and a positive predictor of mating effort, as well as a negative predictor of benefit-provisioning tactics.
No relationship was identified between parental effort and either of the two mate retention tactics. This indicates that in the tested model, parental effort is not a predictor of such tactics.
An analysis revealed the following mediations (Table 4). The relationship between the AQ and parental effort was shown to be mediated by both anxious (total effect = −0.093, 95% CL [−0.157, −0.028], p = .023; indirect effect = −0.168, 95% CL [−0.216, −0.136], p = .004) and avoidant attachment (total effect = −0.093, 95% CL [−0.157, −0.028], p = .023; indirect effect = −0.168, 95% CL [−0.216, −0.136], p = .004): higher AQ scores are associated with higher scores on both attachment styles, which, in turn, are accompanied by lower scores on parental effort.
Table 4.
The Result of the Mediation Analysis in the Tested Model.
| Paths | Estimate | 95% CL | p | |
|---|---|---|---|---|
| LL | UL | |||
| AQ–Anxiety–Parental effort | −0.168 | −0.216, | −0.136 | .004 |
| AQ–Anxiety–Benefit tactics | 0.020 | −0.017 | 0.048 | .277 |
| ns | ||||
| AQ–Avoidance–Mating effort | 0.121 | 0.088 | 0.162 | .008 |
| AQ–Avoidance–Parental effort | −0.168 | −0.216 | −0.136 | .004 |
| AQ–Mating effort–Benefit tactics | 0.020 | −0.017 | 0.048 | .277 |
| ns | ||||
| AQ–Avoidance–Mating effort–Benefit tactics | 0.020 | −0.017 | 0.048 | .277 |
| ns | ||||
Note. 95% confidence intervals (bias-corrected percentile method). LL = lower limit; UL = upper limit; AQ = overall score for AQ; anxiety = anxious attachment; avoidance = avoidant attachment; parental effort = an empirical proxy for a slow reproduction strategy; mating effort = an empirical proxy for a fast reproduction strategy; benefit tactics = tactics benefitting the partner; ns = nonsignificant effect; AQ = autism spectrum quotient.
The relationship between the AQ and mating effort is also mediated by both anxious (total effect = 0.197, 95% CL [0.104, 0.256], p = .008; indirect effect = 0.121, 95% CL [0.088, 0.162], p = .008) and avoidant attachment (total effect = 0.197, 95% CL [0.104, 0.256], p = .039; indirect effect = 0.121, 95% CL [0.088, 0.162], p = .008): higher AQ scores are correlated with higher levels of both attachment styles, and these, in turn, are associated with higher mating effort scores.
The tested model explains 10% of the variance in avoidant attachment, 8% of the variance in anxious attachment, 13% of the variance in mating effort, 19% of the variance in parental effort, 12% of the variance in benefit-provisioning tactics, and 24% of the variance in cost-inflicting tactics.
To answer whether sex is a moderator in the tested model of relationships between variables, we conducted multigroup analysis within the SEM framework to test and compare the effects of each structural path between different groups (Memon et al., 2019). The analysis results did not indicate that sex moderates the tested relationships (in the unconstrained model): χ2(8) = 7.486, p = .49 (detailed regression analysis results for individual paths in the model; Table S1, Supplemental materials).
Additional Regression Analysis
The SEM analysis indicating a positive relationship between the AQ and parental effort is inconsistent with the negative correlation observed between these variables (Table 1), which is β = 0.08, rho = −0.09, p < .01, but both parameters are weak. Since, for the verified hypotheses, the relationship between the AQ and parental effort is crucial for determining the links between parental effort and mate retention tactics, separate regression analyses were conducted using Hayes’ PROCESS macro (Hayes, 2013, Model 6) for benefit-provisioning tactics (Model BENEFIT) and cost-inflicting tactics (Model COST).
An analysis of the BENEFIT model (Table S2, Supplemental materials; Figure 2) revealed that the AQ is a positive predictor of parental effort (β = 0.09, B = 0.06, 95% CL [0.006, 0.116], p = .031). However, an additional mediation analysis using Hayes’ PROCESS macro (Hayes, 2013, Model 4) showed that the relationship between the AQ and parental effort is statistically nonsignificant (B = −0.026, 95% CL [−0.083, 0.032], p = .380), but indirect (mediatory) effect still exists (B = −0.05, 95% BootCL [−0.071, −0.030]). It can therefore be assumed that the positive relationship between the AQ and parental effort obtained in the SEM model arises from a suppression effect. It may be deemed a case of so-called reciprocal suppression, which involves cases in which two predictors correlate oppositely with one criterion but are positively related to one another (Watson et al., 2013). Consequently, there is probably no direct relationship between the AQ and parental effort, and the relationship between these variables is fully mediated by anxious attachment.
Figure 2.
BENEFIT model of relations between variables obtained through regression analysis using Hayes’ PROCESS macro (Model 4). Note. Estimations between variables are given as standardized effects, AQ = overall score for AQ; anxiety = anxious attachment; avoidance = avoidant attachment; parental effort = an empirical proxy for a slow reproduction strategy; mating effort = an empirical proxy for a fast reproduction strategy; benefit tactics = tactics benefitting the partner; ns. = nonsignificant effect; AQ = autism spectrum quotient.
Regression analysis further indicated that the AQ is a negative predictor of benefit-provisioning tactics (β = −0.11, B = −0.22, 95% CL [−0.356, −0.078], p = .002). Statistically significant mediations were also obtained (Table S2, Supplemental materials). Regression analyses indicated significant primary mediation through the pathway from the AQ to anxiety to benefit-provisioning tactics, with an indirect effect of B = 0.14, SE = 0.025, and a 95% bootstrap confidence interval of [0.098, 0.197]. Compared to the SEM results, previously established relationships among the variables were confirmed, with two notable differences.
First, the relationship between avoidant attachment and mating effort was found to be statistically nonsignificant (B = 0.04, 95% CL [−0.014, 0.090], p = .149), indicating that avoidant attachment does not mediate the association between the AQ and mating effort and that the relationship between the AQ and mating effort is direct (β = 0.13, B = 0.10, 95% CL [0.033, 0.160], p = .003). In addition, a more detailed regression analysis focusing on the AQ, avoidant attachment, and mating effort using Hayes’ PROCESS macro (Hayes, 2013, Model 4) revealed a significant direct effect of the AQ on mating effort (B = 0.12, 95% CL [0.053, 0.188], p = .0005), as well as a significant mediating effect of avoidant attachment (indirect effect = 0.07, 95% BootCL [0.042, 0.096]).
Second, the relationship between mating effort and benefit-provisioning tactics—nonsignificant in the SEM—proved to be significant in regression analysis, with mating effort positively predicting the use of benefit-provisioning tactics (β = 0.07, B = 0.16, 95% CL [0.007, 0.309], p = .04).
The tested model explains 13% of the variance in avoidant attachment, 8% in anxious attachment, 22% in mating effort, 19% in parental effort, and 11% in benefit-provisioning tactics.
Since the age variable differentiates the dynamics of reproductive strategies, attachment style, and mate retention tactics, and because there are correlations between this variable and other variables included in the present study (see Table 1), age was introduced as a covariate in regression analyses controlling for other variables. With age, the levels of anxious attachment (B = −0.18, p < .001), reproductive effort (B = −0.04, p = .002), benefit-provisioning tactics (B = −0.12, p < .001), and cost-inflicting tactics (B = −0.08, p = .005) decrease, whereas parental effort increases (B = 0.11, p < .001). Age is unrelated to avoidant attachment (B = −0.01, p = .577). Two mediation paths remain significant after adjusting for age, but attachment dimensions create competing indirect effects: anxiety increases the frequency of benefit-provisioning tactics (B = 0.25, p < .001), whereas avoidance decreases it (B = −0.30, p < .001), leading to overall neutral mediation due to the suppression effect.
In the COST model, regression analysis confirmed most of the relationships obtained in the SEM model except for the relationship between avoidant attachment and mating effort, which is statistically nonsignificant (Table S3, Supplemental materials; Figure 3). Furthermore, only a positive trend was found between the AQ and cost-inflicting tactics (B = 0.11, 95% CL [−0.001, 0.243], p = .08). However, it is worth noting that the relationship between mating effort and cost-inflicting tactics was stronger than in the SEM model (β = 0.37, B = 0.48, 95% CL [0.342, 0.623], p < .001). Regression analyses (Table S3, Supplemental materials) indicated a significant primary mediation through the pathway from the AQ to anxiety to cost-inflicting tactics, with an indirect effect of B = 0.19, BootSE = 0.03, and a 95% bootstrap confidence interval of [0.139, 0.255].
Figure 3.
COST model of relations between variables obtained through regression analysis using Hayes’ PROCESS macro (Model 4). Note. Estimations between variables are given as standardized effects. AQ = overall score for AQ; anxiety = anxious attachment; avoidance = avoidant attachment; parental effort = an empirical proxy for a slow reproduction strategy; mating effort = an empirical proxy for a fast reproduction strategy; cost tactics = tactics inflicting costs on the partner; ns. = nonsignificant effect; AQ = autism spectrum quotient.
The tested model explains 13% of the variance in avoidant attachment, 8% in anxious attachment, 22% in mating effort, 19% in parental effort, and 24% in cost-inflicting tactics.
Age was again included as a covariate, controlling for other variables. Controlling for all other predictors, older participants report lower cost-inflicting scores (B = −0.08, p = .005). With increasing age, the levels of anxious attachment (B = −0.18, p < .001), reproductive effort (B = −0.04, p = .002), and benefit-provisioning tactics (B = −0.12, p = .001) decrease, whereas parental effort increases (B = 0.11, p < .001). Age is unrelated to avoidant attachment (B = −0.01, p = .577). All mediation paths remain significant after adjusting for age, implying that the mechanisms linking the AQ to cost-inflicting tactics are age-independent.
However, it should be emphasized that including age as a covariate revealed a previously nonsignificant positive relationship between the AQ and cost-inflicting tactics (B = 0.14, p = .035) in the SEM and COST models, which had earlier been observed in the correlation analysis (rho = 0.17, p < .001, Table 1). Age appears to function as a suppressor variable: it is positively associated with the AQ (Table 1) but negatively with cost-inflicting tactics, which may have masked the true positive effect of the AQ on cost-inflicting tactics in the SEM and COST models. This is a case of cooperative suppression (Watson et al., 2013): the AQ is positively linked to cost-inflicting tactics, and age is negatively linked to cost-inflicting tactics, while the AQ and age are positively correlated.
Discussion
A diverse body of research points to the existence of an ALT–ASD dimension (Arenella et al., 2022; Lundström et al., 2012). From the perspective of evolutionary psychology, and in particular LHT, ALTs are considered traits that predispose individuals to adopt specific reproductive strategies (Del Giudice et al., 2010). On the other hand, reproductive strategies are associated with specific mate retention tactics (Gladden et al., 2013) or mate acquisition strategies aimed at securing a sexual resource (Reynolds & McCrea, 2015). The main aim of the present study was to test a model that incorporates additional variables between ALTs and mate retention tactics, namely attachment styles and reproductive strategies, both of which are emphasized in LHT.
Hypothesis 1 regarding the relationship between ALTs (measured through the AQ questionnaire) and mate retention tactics was not confirmed. In the SEM-tested model, it was not found that individuals with higher ALTs use both kinds of tactics. Instead, it was shown that such individuals are less likely to engage in cost-inflicting tactics and do not prefer benefit-provisioning tactics. The obtained results suggest that individuals with higher levels of ALTs do not necessarily use tactics inflicting costs on their partners, but they do not seek to reward them, either (however, see the subsection Age as a Covariate below).
On the one hand, this may result from a fear of abandonment due to the costs of the relationship: it has been shown, for example, that individuals with higher ALT levels are more sensitive to rejection (Lin et al., 2022). On the other hand, this may stem from difficulties with attaining the closeness implied in benefit-provisioning tactics (e.g., Love and Care—Displayed greater affection for my partner, public signals of possession—Put my arm around my partner in front of others). Moreover, individuals reporting more ALTs also report a lower degree of emotional closeness toward their romantic partners (Gallitto & Leth-Steensen, 2015).
Additional regression analysis (BENEFIT model) indicated that ALTs are a negative predictor of benefit-provisioning tactics and that there is a positive trend between ALTs and cost-inflicting tactics (COST model). These results suggest that besides a tendency to use cost-inflicting tactics, individuals with ALTs may avoid benefit-provisioning tactics. However, because these findings were obtained using a simpler statistical method as compared to SEM, they are only a working hypothesis for further investigation.
In line with Hypothesis 2, ALTs emerged as strong positive predictors of both avoidant and anxious attachment styles. These results replicate findings from other studies (Ameli et al., 2019; Lamport & Turner, 2014; Sonfelianu et al., 2025; Sörnyei et al., 2024) and can be linked to difficulties in mentalizing in people with autistic traits, that is, the ability to attribute different mental states to oneself and others (Sörnyei et al., 2024).
Thus, as suggested by some longitudinal research on the stability of attachment styles from childhood to adulthood (Pinquart et al., 2013; Waters et al., 2000), insecure attachment styles developed in children experiencing negative situations (e.g., abuse, parental divorce, or low socioeconomic status) are more likely to persist in later periods of life than secure attachment styles. According to LHT, this may be attributable to environmental conditions generally characterized by unpredictability and adversity (Ellis et al., 2009). Among these, family factors such as insensitive and inconsistent parenting are important (e.g., Belsky et al., 1991).
Recent studies suggest that the childhood environment can be challenging for children with ASD. Interactions within mother–child dyads (for 3- to 7-year-olds) are indicative of difficulties in maintaining positive emotional states because the emotional states of children with ASD tend to change very rapidly (Guo et al., 2017). Similarly, Berg et al. (2016) documented a link between ASD and the occurrence of adverse childhood experiences, showing higher rates of income deprivation, parental divorce/separation, exposure to neighborhood violence, and household mental illness among individuals with ASD compared to control groups. Autistic children also had more parent-reported total adverse events (Ebert et al., 2026). As Takeda et al. (2024) suggest, adverse childhood experiences, such as abuse, can modify the expression of some genes in an epigenetic manner and result in inferior mental health and overall well-being in individuals with ASD. These factors linked to adverse childhood experiences are precisely those identified by LHT as cues for the development of a fast reproductive strategy (see Gao et al., 2024).
According to Hypothesis 3, anxious and avoidant attachment are negative predictors of a slow reproductive strategy (parental effort) and positive predictors of a fast reproductive strategy (mating effort). This hypothesis has been supported through SEM analysis: individuals with higher levels of anxious and avoidant attachment tend to follow a fast reproductive strategy, whereas those with lower levels of these attachment styles tend to follow a slow strategy. This finding is consistent with theoretical analyses suggesting that attachment orientation mediates life history effects, with securely attached individuals exhibiting a slow reproductive strategy, and those with insecure attachment styles exhibiting a fast strategy (Belsky et al., 1991; Chisholm, 1996; Del Giudice, 2009; Schmitt, 2005; Szepsenwol & Simpson, 2019). This is also in line with previous reports (Dunkel et al., 2016; Kruger, 2017), although, in contrast to Kruger's study (2017), we did find a relationship between the anxious attachment style and reproductive strategies. The result is also in contrast to the recent study by Kwiek et al. (2025), in which mating effort was not predicted by attachment styles, and parenting effort was predicted only by higher attachment avoidance but not by attachment anxiety.
According to Hypothesis 4, anxious and avoidant attachment styles mediate the relationship between ALTs and mate retention tactics in that individuals with higher ALT scores show higher levels of both anxious and avoidant attachment. In turn, anxious attachment is a positive predictor of both types of tactics, whereas avoidant attachment is a negative predictor of them. This hypothesis was partly confirmed in the SEM model for anxious attachment and both types of tactics and for avoidant attachment with benefit-provisioning tactics. Analogous results were obtained in the BENEFIT and COST regression models. These results are largely consistent with findings from other studies (Barbaro et al., 2019). As the authors explain, anxiously attached individuals may use benefit-provisioning retention tactics to strengthen their emotional and psychological connection with romantic partners, and the use of cost-inflicting tactics may be the effect of overperception of the risk of infidelity. In turn, the unwillingness of avoidantly attached individuals to use benefit-provisioning tactics allows them to avoid closeness in relationships (Barbaro et al., 2019).
Hypothesis 5, which proposed that ALTs would negatively predict a slow reproductive strategy (parental effort) and positively predict a fast reproductive strategy (mating effort), was not supported by the SEM-tested model. Positive associations were observed for parental effort, while the direct effect for mating effort was nonsignificant. However, it is worth noting that the observed relationship between ALTs and parental effort was weak (direct effect = 0.08, p = .01), and therefore this finding should be interpreted with caution. A positive association between the AQ and parental effort also emerged in both the BENEFIT and COST regression models, although it was similarly weak (direct effect = 0.06, p = .03).
Hypothesis 5 also predicted that a slower reproductive strategy (parental effort) would negatively predict benefit-provisioning tactics, whereas a faster reproductive strategy (mating effort) would positively predict both cost-inflicting and benefit-provisioning tactics. This hypothesis was not supported in the SEM-tested model. The resulting model showed no relationship between a slow reproductive strategy and mate retention tactics. The result is contrary to the study by Pazhouhi et al. (2024), which found that slow strategists more often use benefit-provisioning tactics and did not reveal any associations between this strategy and cost-inflicting tactics.
In the case of the fast strategy, there was a preference for cost-inflicting tactics. This result is consistent with findings from other studies (Reynolds & McCrea, 2015; see also Kiire, 2019), which have shown that a fast strategy is associated with exploitative behavior (such as coercion for sexual resources, retaliatory violence, deception, and manipulation), all of which are forms of cost infliction.
The positive relationship between the fast strategy and cost-inflicting tactics was also supported by the COST regression model. However, the BENEFIT regression model revealed that this strategy was also positively linked to benefit-provisioning tactics, which is in line with our hypothesis that the fast strategy is related not only to cost-inflicting but also to benefit-provisioning tactics. Nevertheless, this result is inconsistent not only with the finding obtained in the SEM-tested model, where only a positive relationship between the fast strategy and cost-inflicting tactics was observed, but also with the correlation analysis (Table 1), which did not indicate any significant correlation between the fast strategy (mating effort) and benefit-provisioning tactics. Thus, overall, it seems that the fast strategy is positively associated only with cost-inflicting tactics.
This finding may be important for LHT. Research on jealousy—whose higher intensity is linked to a fast strategy—has not provided a clear answer as to which types of mate retention tactics are correlated with it. For example, Davis et al. (2018) found that jealousy positively predicted cost-inflicting mate retention, whereas Degiuli et al. (2023) (see also Arnocky et al., 2024) found that all three dimensions of jealousy (cognitive, emotional, and behavioral) positively predicted both cost-inflicting and benefit-provisioning mate retention behaviors. The present findings seem to support the view that the fast strategy (mating effort) is associated only with cost-inflicting tactics.
Sex as a Moderator
The present study did not show that sex moderates relationships within the tested model. The only effect that differed by sex was that the association between ALTs and mating effort was positive and statistically significant for women, but statistically insignificant for men. Since, to the best of our knowledge, there is virtually no research directly addressing these issues, it is currently difficult to offer a comprehensive interpretation. In contrast to Del Giudice's (2011) findings, no statistically significant sex differences were found in attachment anxiety, although some other studies (e.g., Dunkel et al., 2016; Fernandez et al., 2019) have also reported no sex differences in this attachment orientation.
Age as a Covariate
In the COST and BENEFIT regression models, age was introduced as a covariate. Importantly, in the COST model, the inclusion of age revealed the AQ to be a positive predictor of cost-inflicting tactics. The absence of this relationship in the SEM model and the uncontrolled COST model was likely due to suppression and a masked relationship caused by the age variable. In turn, in the BENEFIT regression model, the AQ is still negatively associated with benefit-provisioning tactics. These results may suggest that individuals with high levels of ALTs not only use benefit-provisioning tactics less frequently but also tend to employ cost-inflicting tactics. However, this matter requires further research.
Moreover, age turned out to be a significant covariate: with increasing age, levels of attachment anxiety, mating effort, and the frequency of both benefit-provisioning and cost-inflicting tactics decrease, whereas parental effort increases. Age is not related to ALTs or to changes in avoidant attachment.
The finding that age is not related to avoidant attachment is in line with a review of romantic attachment orientation and age by Van Assche et al. (2013). Age is also negatively associated with mate retention tactics, which is consistent with previous reports (Atari et al., 2017; Degiuli et al., 2023; de Miguel & Buss, 2011), and these relationships can be interpreted as a shift toward parental investment: once a relationship is established, stabilized, and offspring appear, individuals tend to focus on their children's well-being and upbringing, which corresponds to parental effort (at the expense of mating effort).
A decline in attachment anxiety with age is well documented. In a sample of over 86,000 Internet respondents aged 18 to 70, Chopik et al. (2013) found that attachment anxiety was highest among younger adults and lowest among middle-aged and older adults. It has been suggested that attachment anxiety can be reduced through experiences that foster a secure model of the self in daily life (Chopik et al., 2024).
Replicate Findings from Previous Research
The present study replicates many findings from previous research pointing to the existence of correlations between variables. The positive correlation of the AQ with attachment anxiety and attachment avoidance is consistent with findings from other studies (Ameli et al., 2019; Lamport & Turner, 2014). The positive association between anxious and avoidant attachment is also in line with previous studies (Međedović et al., 2022). The negative intercorrelation between mating effort and parental effort is consistent with Kruger (2017). Attachment anxiety is positively correlated with both cost-inflicting and benefit-provisioning tactics. In turn, attachment avoidance is positively correlated with cost-inflicting tactics and negatively with benefit-provisioning tactics. Similar findings have been reported from previous research (Altgelt & Meltzer, 2019; Barbaro et al., 2016; Nascimento et al., 2022). A positive correlation was found between cost-inflicting and benefit-provisioning tactics. Such a positive association between both types of mate retention tactics has also been reported from other studies (Altgelt & Meltzer, 2019; Barbaro et al., 2019).
This also applies to sex differences: for instance, men score higher on the AQ than women (Hoekstra et al., 2007; Reed et al., 2016) and use mate retention tactics more frequently (Babaeizad et al., 2022; Marzec et al., 2014). In this study, men scored higher than women on both cost-inflicting and benefit-provisioning tactics, similar to findings reported by Babaeizad et al. (2022). Lopes and Shackelford (2019) refer to this combined strategy of using both types of tactics as an exhaustive strategy and note that men are more likely than women to use it. Men also exhibit significantly higher levels of attachment avoidance than women (Del Giudice, 2011, 2019). Women scored higher on parental effort, whereas men scored higher on mating effort. These are typical sex differences in reproductive strategies (e.g., Tarka et al., 2018).
Limitations
The first limitation is theoretical in nature and concerns criticism (Volk, 2025) of PAT (Belsky et al., 1991) and the assumptions derived from it regarding reproductive strategies in the context of LHT (Ellis, 2004; Ellis et al., 2009). Volk (2025) highlights a key theoretical limitation of PAT and LHT, questioning their core assumptions based on evidence from anthropology, biology, genetics, and developmental psychology. He argues that LHT more effectively explains interspecific and between-population patterns than within-population data in fast–slow frameworks (see also Zietsch & Sidari, 2020), and that PAT may not fully account for the complexity of human life history (see also Koehler & Rutherford, 2026). Furthermore, animal analogies are often misleading, as human patterns of parenting, reproduction, and mortality differ substantially from those of other species. Humans also possess considerable capacity to mitigate extrinsic mortality, a major factor influencing reproductive strategies, which can favor the development of slow rather than fast life history strategies. For example, mothers can adjust the frequency of their lactation, significantly enhancing juveniles’ ability to withstand immediate famine and store energy for future scarcity (Butte & King, 2005; Volk, 2025, p. 5).
It is worth emphasizing, however, that it is not only psychological LHT that suffers from various weaknesses. Stott et al. (2024) point out that similar problems also concern biological–ecological LHT, from which psychological LHT originates: life history studies support the fast–slow continuum as the dominant but not unique axis structuring life history variation. There are, in fact, examples in nature of life history strategies that fall outside LHT predictions. The authors propose retaining the fast–slow continuum in LHT as the main structural axis describing life history diversity but complementing it with additional axes reflecting the variation found in the natural world. There is therefore a need to move away from the classical fast–slow model toward a more complex one. In our opinion, in evolutionary psychology, such a role may be fulfilled by Del Giudice's (2018) aforementioned proposal, which introduces additional profiles on the fast and slow sides of the strategy, understood as a trade-off between mating effort and parental effort.
The second limitation relates to theoretical and methodological issues associated with the AQ. While the AQ is commonly used to study ALTs, Del Giudice (2018) emphasizes that it is not a pure measure of ALTs. He points out a significant overlap between the AQ and negative schizotypy (social isolation and anxiety, reduced emotional expression), which is particularly evident for items describing interpersonal difficulties, such as isolation, social anxiety, and communication problems (Del Giudice, 2018; Del Giudice et al., 2010, 2014). According to Del Giudice (2018), all correlates of ALTs should therefore be interpreted with caution.
Nevertheless, there is evidence supporting the usefulness of the AQ. For example, total AQ scores can distinguish male juveniles with ASD from those without ASD but with severe behavioral problems, despite overlapping symptoms, particularly in terms of empathy deficits (Rutten et al., 2023). The validation of the Polish children's version (Mage ∼ 7) showed that children with autism scored significantly higher than their neurotypical peers on the total score and the subscales of Social Skills, Communication, and Imagination (Omelańczuk & Pisula, 2025).
A meta-analysis (Westwood et al., 2016) also found that individuals with anorexia nervosa scored higher on both the full AQ and AQ-10 (Allison et al., 2012) than healthy controls, indicating greater difficulties in social skills, communication, and cognitive flexibility, which are characteristic of autistic traits. These results are consistent with earlier findings showing a higher prevalence of ASD among individuals with anorexia nervosa (22.9%) compared to the general population (1.1%) in the United Kingdom (Mills & Kenyon, 2013). Receiver operating characteristic analysis (see, e.g., Nahm, 2022) has further demonstrated that total AQ can differentiate between adults with autism, schizophrenia, and neurotypical individuals with moderate to high accuracy (Wouters & Spek, 2011). Similar results were obtained for the children's version (Omelańczuk & Pisula, 2025). It is important to emphasize that these studies do not contradict Del Giudice's findings. Rather, they suggest that, despite its imperfections, the AQ can still be a useful tool in ALT research.
The second theoretical and methodological problem is that the AQ does not have a uniform factor structure. Instead of the five subscales proposed by Simon Baron-Cohen et al. (2001), three factors were identified—Social Skill, Patterns/Details, and Communication/Mindreading—which were found to be the best way of examining specific types of autistic traits in the AQ (English et al., 2020). Zhu et al. (2022) found six factors: (1) social anhedonia; (2) interest in details/patterns; (3) imagination ability; (4) desire for predictability/routine; (5) social cognition; and (6) social discourse convention.
In another study (Hoekstra et al., 2008), the full AQ showed that a hierarchical structure provides the best fit, with two main dimensions: social interaction and attention to detail, the former of which is further subdivided into four additional dimensions. Moreover, some AQ items appear to measure different constructs in individuals with ASD and those without ASD, including items formulated in a negative way (Lundqvist & Lindner, 2017; Rentergem et al., 2019). However, Murray et al. (2016) suggest that while the AQ is not an appropriate tool for clinical assessment, it measures moderately low to moderately high levels of the general autistic trait with good precision.
The next limitation of the present study is the use of SEM to test the developed model and determine cause-and-effect relationships. Establishing causality by means of SEM is controversial and widely debated (see, e.g., Bollen and Pearl, 2013), and it is generally accepted that SEM alone cannot be used to make definitive claims about causal relationships (Babalola & Nwanzu, 2021). However, as noted by Bullock et al. (1994, p. 262), “potential is the key word when discussing SEM.” This means that the tested model, grounded in theory and previous research, can to some extent approximate potential causal relationships. Nevertheless, these should be interpreted with great caution, and rather as a starting point for further research, such as longitudinal studies. In addition, all data used in the study were collected through self-report questionnaires. Therefore, the results may be distorted by social desirability bias (Caputo, 2017).
An important limitation is that ALTs (measured with the AQ) were found to be weak predictors of reproductive strategies. However, it should be noted that previous studies (e.g., Del Giudice et al., 2010), using a different tool to measure mating and parenting effort, did not identify strong associations, either. In the cited study (Del Giudice et al., 2010), the AQ was split into two factors: AQ-detail, corresponding to the attention to detail scale, and AQ-interpersonal, encompassing the remaining scales. SEM analysis showed that AQ-detail and AQ-interpersonal were relatively weak or moderate predictors of mating effort, with coefficients of −0.03 and −0.23, respectively. The same was true of long-term investment, which is a proxy for parenting effort (Del Giudice et al., 2010).
The relationship between the AQ and reproductive strategies is further complicated by the results of more detailed regression analyses, which indicate that these relationships vary depending on the statistical approach used (SEM model vs. regression analysis) and the number of variables included in the model. For example, in the case of the AQ → anxious attachment → parental effort pathway, regression analysis (Hayes, 2013, Model 4) indicates only a mediation effect (i.e., no direct AQ → parental effort effect). Therefore, the issue of the relationships between ALTs and reproductive strategies remains open for future investigation.
Conclusions
There has been relatively little research on ALTs from an evolutionary perspective. The aim of the present study was to place ALTs within the context of evolutionary LHT and the psychological variables associated with it. The results showed that ALTs are less strongly associated with evolutionary reproductive strategies and more strongly linked to attachment styles in romantic relationships—both anxious and avoidant. Attachment styles—and especially anxious attachment—were found to be significant mediators between ALTs and reproductive strategies, which is consistent with other research indicating that attachment orientation mediates life history-related effects.
An important aim of the study was to verify the hypothesis that ALTs negatively predict a slow reproductive strategy (i.e., parental effort) and positively predict a fast reproductive strategy (i.e., mating effort). This hypothesis was not supported by the SEM-tested model. The results indicate that ALTs are positively, although weakly, associated with parental effort. However, an additional and more detailed regression analysis suggests a potential association between ALTs and mating effort, which warrants further investigation.
Another key aim of the study was to examine whether ALTs are related to mate retention tactics. The results of the SEM-tested model suggest that individuals with elevated ALTs do not tend to use benefit-provisioning tactics.
Age turned out to be a significant covariate: with increasing age, levels of attachment anxiety, mating effort, and the frequency of both benefit-provisioning and cost-inflicting tactics decrease, whereas parental effort increases.
A significant limitation of the present study is that ALTs were found to be weak predictors of life history reproductive strategies, which contributed to the lack of clear and consistent results. This issue requires particular attention in future research and calls for the application of alternative methods of measuring such strategies.
Supplemental Material
Supplemental material, sj-docx-1-evp-10.1177_14747049261473640 for Autistic-Like Traits in Members of the General Population and Mate Retention Tactics: The Mediation of Attachment Styles and Reproductive Strategies by Andrzej Łukasik and Agnieszka Łaba-Hornecka in Evolutionary Psychology
Footnotes
ORCID iDs: Andrzej Łukasik https://orcid.org/0000-0002-5338-2570
Agnieszka Łaba-Hornecka https://orcid.org/0000-0002-6441-0717
Ethical Considerations: All procedures performed in studies involving human participants were in accordance with the ethical standards of the IRB and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study.
Funding: The authors received no financial support for the research, authorship, and/or publication of this article.
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Supplemental Material: Supplemental material for this article is available online.
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Supplemental material, sj-docx-1-evp-10.1177_14747049261473640 for Autistic-Like Traits in Members of the General Population and Mate Retention Tactics: The Mediation of Attachment Styles and Reproductive Strategies by Andrzej Łukasik and Agnieszka Łaba-Hornecka in Evolutionary Psychology