The concept of harsh environments describes external factors capable of causing disability and death for individuals of various ages within a population, and this concept is also addressed by life-history theory (Belsky et al., 2012). Harshness is an environmental condition capable of shaping LH trajectories in response to the environmental conditions experienced throughout development (Ellis, 2004; Chang and Lu, 2017). This is because in harsher environments, with higher mortality rates, having a late start to reproduction may mean not reproducing at all. Therefore, exposure to resource uncertainty and harsh conditions favors the expression of a fast LH trajectory and can be observed through reproductive milestones (Ellis et al., 2009). For example, individuals with a fast LH strategy exhibit earlier sexual debut, early parenthood initiation, a higher number of children by the end of reproductive life, as well as lower parental investment, greater mating effort, and higher risk propensity (Del Giudice et al., 2015). On the other hand, living in more predictable and less harsh environments favors the accumulation of resources for later competition, favoring the strategy of individuals with slow LH trajectories. They achieve reproductive milestones later and display greater parental investment, higher concern for partner retention, and lower risk propensity (Del Giudice et al., 2015). In Western societies, harshness is commonly assessed through socioeconomic status (SES) as lower SES levels are consistently associated with increased rates of morbidity and mortality across various domains (Chen et al., 2002; Ellis et al., 2009; Simpson et al., 2012).

The life-history strategy directly impacts levels of parental investment. This is because one of the expected trade-offs within the LH concerns investing in mating effort or parental effort as an increase in the number of offspring reduces the time and energy available to allocate to each of them (Kruger, 2021). Individuals adopting a fast LH strategy will primarily invest in seeking mates, thereby increasing their reproductive potential; conversely, those following a slow LH strategy will focus their efforts on mate retention and parental care (Del Giudice and Belsky, 2011; Lu et al., 2017). These behavioral expressions align with the theoretical expectations outlined in the parental investment theory (Trivers, 1972), where it is anticipated that men will exhibit more elements of a fast LH when compared to women. This is due to differences in reproductive potential between the sexes, with men increasing their reproductive success by mating with more women, while women increase their reproductive success by being more selective with their mates (Trivers, 1972; Salas-Rodríguez et al., 2021). However, there is an important peculiarity to highlight in the human species: men also contribute to parental care and, therefore, also exhibit aspects of partner selectivity in long-term relationships (Arnocky and Vaillancourt, 2017), resulting in individual differences within each sex. Thus, environmental conditions play a fundamental role in calibrating individuals' LH strategies (Pepper and Nettle, 2017). Therefore, factors such as harshness can lead an individual to adopt a life history different from what is theoretically expected based on sex differences, due to the significant behavioral plasticity found in our species.

Unpredictability is also an environmental condition capable of shaping LH trajectories (Ellis, 2004). Following a similar logic, more unpredictable environments signify higher chances of resource scarcity. Therefore, it is evolutionarily advantageous to anticipate reproduction rather than investing more time and energy in maturation or resource accumulation (Lu et al., 2017). Thus, in more stable environments, organisms have a better chance to accumulate resources for competition, favoring the adoption of a slower LH strategy compared to unpredictable contexts, which, in turn, favors faster strategies (Chang et al., 2019a).

The cues of unpredictability that most influence LH trajectories are experienced during childhood (Stearns, 1992; Ellis et al., 2022). The family unpredictability experienced in childhood is the result of inconsistent parental behaviors in meeting the basic needs of children (Howat-Rodrigues and Tokumaru, 2014). According to Hill et al. (2008), this construct derives from attachment theory (e.g., Bowlby, 1969) and life-history theory (e.g., Hill et al., 1997). The mental model of unpredictability is supported by inconsistent family patterns regarding emotional support, financial resources, and mealtime schedules in the early stages of development (Howat-Rodrigues and Tokumaru, 2014). Thus, family unpredictability seems to be the primary cue perceived by the infant, aiding in the calibration of their LH strategy.

During childhood, parenting plays a crucial role. In predictable environments, caregivers have more availability to invest energy and care in their offspring, resulting in higher returns in terms of survival and future reproductive success for their children (Chisholm et al., 1993; Lu et al., 2023). Furthermore, this predictability is transmitted from caregiver to offspring. The opposite occurs in unpredictable environments, where caregivers have less availability for their offspring, resulting in fewer resources and care, contributing to children perceiving greater environmental unpredictability. Therefore, for individuals in their early life stages, the levels of unpredictability experienced in the family environment play a fundamental role in shaping their LH strategies.

Thus, both harshness and family unpredictability contribute to the development of fast LH strategies. This means that, in adulthood, these individuals are inclined to exhibit behaviors consistent with this strategy. For example, these patterns predispose adult individuals to a preference for immediate benefits over future benefits (Hill et al., 2008). Therefore, exposure to inconsistent patterns of family behavior and harsh environments in childhood predicts a higher risk propensity in adulthood (Andrade-Silva et al., 2016), as well as an increased focus on seeking reproductive partners and lower levels of parental care (Neel et al., 2016).

Our ancestors faced a range of recurrent challenges, including the need to prevent diseases, avoid physical harm, gain and maintain status, find mates for reproduction, and care for kin. Kenrick et al. (2010a) developed the concept of fundamental social motives (or simply, fundamental motives), which suggests that humans possess seven distinct motivational systems: self-protection, disease avoidance, affiliation, status pursuit, mate acquisition, mate retention, and parental care (Kenrick et al., 2010a; Neuberg et al., 2011). Each of these systems was shaped over the course of evolution in response to specific challenges encountered by our ancestors, and they are activated by specific environmental cues that lead to physiological and behavioral responses. This theory assumes that in modern times, these fundamental motives still play a central role in our decision-making and social interactions.

The framework of fundamental motives allows for quantifying reproductive and risk-taking behavior. Factors such as age, sex, and exposure to different environmental cues lead to variations in the expression of these motives among individuals (e.g., Kenrick et al., 2010b; Neel et al., 2016). Some of these environmental cues also help explain an individual's LH, as previously mentioned, such as unpredictability and harshness in childhood. Both childhood unpredictability and exposure to harsh environments (Belsky et al., 2012; Simpson et al., 2012) influence the expression of motives related to self-protection, disease avoidance, and reproductive domains in adults (Neel et al., 2016).

Self-protection and disease avoidance are among the first motives to emerge during development. The former is linked to maintaining the individual's physical integrity, while the latter pertains to the behavioral immune system (Neuberg et al., 2011). Although they frequently occur concurrently, both are distinct motivational systems activated by feelings of fear and disgust, respectively (Neel et al., 2016). Based on the previously discussed variables influencing the LH strategy adopted, individuals who experienced greater family unpredictability in childhood (Ross and Hill, 2002) and were exposed to harsh environments (Belsky et al., 2012) tend to exhibit a higher inclination toward risk-taking behaviors in adulthood. Higher levels of childhood unpredictability have also been associated with higher levels of risk-taking in health-related aspects as individuals tend to prioritize other social motives above their long-term health (Martinez et al., 2022). We observe that these indicators, which underlie a fast LH strategy, tend to inhibit the activation of these more fundamental motives associated with an individual's physical integrity and health in adulthood.

As we move toward the end of an individual's development, we have the manifestation of reproductive (mate seeking and mate retention) and caregiving motives. The mate seeking motive is linked to the pursuit of sexual partners, mate retention pertains to maintaining romantic relationships, and parental care relates to caring for children and family (Pick et al., 2022a). Similarly, the variables influencing the LH strategy also impact the expression of motives related to reproduction and caregiving in adulthood. For instance, individuals who have experienced greater family unpredictability and harshness tend to adopt a faster strategy and exhibit higher levels of mate seeking compared to mate retention and parental care (Chang et al., 2019b). Conversely, those who have encountered lower levels of unpredictability and harshness tend to adopt a slower strategy, demonstrating higher levels of mate retention and parental care compared to mate seeking (Chang et al., 2019b). Therefore, throughout an individual's development, the mentioned LH indicators can influence the expression of motives related to the reproductive domain.

Despite being primarily transmitted through respiratory means and by asymptomatic individuals, information disseminated through the media has turned coughs and sneezes into stigmas of the disease, even in cases of false positives (Bouayed, 2022). Thus, although the behavioral immune system may not have been as effective in identifying disease signs, given that many individuals were asymptomatic (Ackerman et al., 2021), the study by Keller et al. (2022) demonstrated that watching videos of people sneezing or coughing elicited disgust and fear responses capable of activating the immune system as well, through the production of secretory immunoglobulin A. Therefore, it is expected that witnessing sneezes and coughs generated disgust responses and, thus, activated motives related to disease avoidance. On the other hand, the relationship between self-protection and cues of contagious diseases is indirect. This relationship occurs because the impending threat of contagion can evoke feelings of fear (Galoni et al., 2020), which stem from the establishment of a state of uncertainty and lack of individual control (Lerner and Keltner, 2000, 2001; Galoni et al., 2020). Thus, the pandemic context may have highlighted contagion cues that elicited feelings of disgust and fear, triggering motives of self-protection and disease avoidance.

The fundamental motives related to the reproductive domain were also impacted by the pandemic. The social distancing measures imposed during the pandemic may lead to individuals encountering difficulties in mate seeking as these measures aimed to avoid social contact as a means of reducing the risk of contagion (Pick et al., 2022b). Additionally, confinement led many couples to focus on retaining their partners and caring for their children and/or family members (Ko et al., 2020; Pick et al., 2022b). Therefore, the restrictions imposed by the pandemic affected both individuals who intended to seek partners and those involved in maintaining their relationships and caring for their children.

During the pandemic, there was variation in adherence to preventive measures (Faasse and Newby, 2020), and those who did not follow these guidelines increased their susceptibility to the risk of infection. Risk propensity refers to the tendency to make decisions that may cause physical or psychological harm that threatens survival (Boyer, 2006). In the case of motives related to disease avoidance and self-protection, disregarding interactions with individuals who appear ill can be considered risky behavior. Similarly, continuing to seek partners and disregarding social distancing guidelines can also be seen as risky behavior. Conversely, maintaining one's partner and caring for their offspring may be considered low-risk behavior, especially for cohabiting families. The propensity for risky behaviors varies among individuals and is influenced by LH indicators such as family unpredictability experienced (Ross and Hill, 2002) and exposure to harsh environments (Belsky et al., 2012) in childhood. Thus, it is possible that understanding these LH indicators can increase the explanatory power of why variations were observed in these motivated behaviors among adults during the pandemic.

In this study, we focus on the expression of fundamental motives related to self-protection, disease avoidance, mate seeking, mate retention, and parental/familial care. It is an exploratory study aiming to investigate whether exposure to different levels of family unpredictability during childhood is associated with reproductive milestones and can explain differences in the expression of motives related to contagion risk and aspects of reproductive behavior during the pandemic. To achieve this, participants were initially grouped based on the similarity of their experiences related to family unpredictability during childhood. Following this procedure, the groups were described and compared in terms of reproductive milestones and the expression of motives related to self-protection, disease avoidance, and reproductive domains. We hypothesize that (a) groups of individuals with different experiences of unpredictability during childhood will exhibit distinct reproductive milestones, and (b) these groups will show differences in the expression of motives related to self-protection, disease avoidance, and reproductive domains.

This study was not preregistered. All data and analysis code have been made publicly available at the Open Science Framework and can be accessed at https://osf.io/4qvu6/?view_only=b98e70d2d2454b88b688cef016b3896b. The study adhered to the JARS guideline (Kazak, 2018) and the principles outlined in The Code of Ethics of the World Medical Association (Declaration of Helsinki) regarding experiments involving humans.

All participants were recruited exclusively through social networks, where the survey was introduced, and a link was provided. The survey was promoted on researchers' personal profiles, university laboratory profiles, and institutional emails. The sample was a convenience sample. The intended sample size (N = 252) was calculated using GPower 3.1 software (Mayr et al., 2007) with the following parameters: alpha value of 5%, expected power of 95%, and an effect measure (f ) of 0.25. There were 16 participants who failed to fully complete all questionnaires and were thus excluded from the analyses. The achieved sample size was N = 438. Data collection took place online using the Google Forms platform from November 2021 to May 2022. All participants volunteered and did not receive any payment. This research was submitted and approved by the local Human Research Ethics Committee with opinion number: 45297521.6.0000.5537. All participants provided their consent for participation and publication of research data through the free and informed consent form (FICF).

A total of 438 individuals (280 women) over 18 years of age, of both sexes, and residing in Brazil participated in the study. The exclusion criteria were being under 18 years of age, not residing in Brazil at the time of the survey, and not having fully completed all the questionnaires. The mean age of participants was 31.66 years (SD = 10.93). In terms of education, 62.33% reported having completed higher education, 37.44% had completed secondary education, and 0,23% had completed high school. Based on the Brazilian Economic Classification Criteria (Associação Brasileira de Empresas de Pesquisa, 2021), 15.75% of the participants belonged to class A, 56.85% belonged to class B, 24.43% to class C, and 2.97% to class D and E. Class A participants have a higher level of economic power, while individuals from classes D and E have a lower level of economic power.

In this research, sociodemographic data, perceived unpredictability in childhood, and levels of activation of fundamental motives were collected. Below, we briefly describe the instruments used.

The Sociodemographic Measures consisted of two parts: one focused on sociodemographic characteristics and the other on reproductive milestones in life history. In the first part, questions referred to consumption items and the subject's level of education, which resulted in the categorization of the person's socioeconomic status according to the Brazil Criterion (Associação Brasileira de Empresas de Pesquisa, 2021). The second part contained variables considered relevant in the literature for analyzing the individual's life-history trajectory, such as number of children, age at first sex, age at first child, and menarche.

The Scale of Family Unpredictability during Childhood, developed and validated by Howat-Rodrigues and Tokumaru (2014), was used. The questionnaire is divided into three dimensions: Nurturance, Money, and Meals. The components of the Nurturance dimension were associated with parental inconsistency in fulfilling emotional needs and providing help in dealing with challenging circumstances, which we refer to as “family support”. The components comprising the Money factor were associated with uncertainty about the availability of financial resources to cover expenses and purchase goods, which we refer to as “uncertainty of financial resources”. The items included in the Meals factor were associated with uncertainty about mealtime schedules and the individuals who would take part in them, which we refer to as “family mealtime routine”. The scale is a 5-point Likert scale, where 1 corresponds to “strongly disagree” and 5 corresponds to “strongly agree”. The first dimension contained questions such as “I was sure that my family would take care of me”, the second dimension was “In my house, we didn't know if there would be food for daily meals”, and the third dimension was “In my house, I knew who would be present at mealtime”. The internal consistency of the scale measured by Cronbach's alpha was α = 0.858.

The Fundamental Social Motives Inventory by Neel et al. (2016) was used to measure motivations related to individual self-protection, disease avoidance, mating effort, and family care. The inventory was translated into Brazilian Portuguese by a group of researchers from Brazil in collaboration with the original instrument researchers. The questionnaire is a 7-point Likert scale, ranging from “strongly disagree” to “strongly agree”. The scales used were self-protection (“I think a lot about how to stay safe from dangerous people”), disease avoidance (“I avoid places and people that might carry diseases”), mate seeking (“I spend a lot of time thinking about ways to meet possible dating partners”), mate retention (“It is important to me that my partner is sexually loyal to me”), kin care—family (“Caring for family members is important to me”), and kin care—children (“I help take care of my children”). Each motive is composed of six questions, and the minimum and maximum possible score is 6 and 36, respectively. The internal consistency of the scale measured by Cronbach's alpha was α = 0.788.

The participants were the unit of investigation in this study. Data collection was conducted through an online questionnaire using the Google Forms platform. All participants were recruited via social networks or institutional emails, where a brief introduction to the survey and an access link were provided. Upon reading the FICF and agreeing to participate, participants were directed to a tab containing the instruments to be completed. Once they finished the questionnaire, participants were thanked and dismissed.

We conducted a cluster analysis to group participants based on the similarities in experiences related to family unpredictability during childhood, using the items from the Scale of Family Unpredictability during Childhood (Howat-Rodrigues and Tokumaru, 2014). In this procedure, the ideal number of clusters was determined by grouping participants (cases) according to their questionnaire responses using the method of linkage between groups with squared Euclidean distance. The number of clusters was based on the greatest distance between clustered coefficients in the agglomeration scheme. We conducted a general linear model (GLM) using the clusters to test both of our hypotheses: (a) examining the impact of different patterns of family unpredictability experienced during childhood and sex (independent variables) on reproductive milestones (dependent variables) and (b) investigating the influence of different patterns of family unpredictability experienced during childhood (independent variable) on the participants' scores of the fundamental motives disease avoidance, self-protection, mate seeking, mate retention, kin care (family), and kin care (children) (dependent variables). Statistical significance was set at a level of 5% for all analyses. All data were analyzed using IBM SPSS Statistics, Version 26.

The model that best fits the sample identified three clusters. Cluster 1 consisted of participants with the highest means of family support and family mealtime routine, as well as the lowest uncertainty of financial resources, and was therefore labeled as “low unpredictability”. Both Cluster 2 and Cluster 3 comprised individuals with higher means of uncertainty of financial resources and lower means of family mealtime routine. The distinguishing factor between these two clusters was that Cluster 2 had higher means of family support compared to Cluster 3, resulting in Cluster 2 being labeled as “unpredictability with family support” while Cluster 3 was labeled as “unpredictability without family support”. The means for each cluster are presented in the table below (Table 1).

Significant differences were observed in the number of children, age at first sex, and age at first reproduction based on clusters, sex, and the interaction between them. It is important to note that the groups did not differ in terms of age. Regarding the number of children, a significant difference was found between clusters, between sexes, and in the interaction between them. In terms of clusters, the “unpredictability without family support” group had a higher mean number of children (M_{Unpredic Without Support} = 2.54, 95% CI: 1.99–3.10, p < 0.05) compared to the other two groups (M_{Low Unpredictability} = 1.77, 95% CI: 1.50–2.04; M_{Unpredic With Support} = 1.58, 95% CI: 1.19–1.98). In terms of sex, men had a higher mean number of children (M = 2.24, 95% CI: 1.84–2.65, p = 0.026) compared to women (M = 1.69, 95% CI: 1.41–1.96). Regarding the interaction, male individuals in the “unpredictability without family support” group had a higher mean number of children (M = 3.40, 95% CI: 2.45–4.34, p < 0.05) compared to all others. The variable “age at first sex” showed a significant difference between clusters and in relation to sex. Among the clusters, the “unpredictability without family support” group had an earlier age at first sex (M_{Unpredic Without Support} = 16.93, 95% CI: 16.14–17.27, p =0.007) compared to the “low unpredictability” group (M_{Low Unpredictability} = 18.41, 95% CI: 17.88–18.93), while the “unpredictability with family support” group did not differ from either of the other two groups (M_{Unpredic Witht Support} = 18.03, 95% CI: 17.37–18.69). In terms of sex, men had an earlier age at first sex (M = 17.17, 95% CI: 16.55–17.80, p =0.002) compared to women (M = 18.41, 95% CI: 17.95–18.86). The variable “age at first reproduction” showed a difference between sexes, with men having their first child at a later age (M = 29.60, 95% CI: 27.18–32.02, p =0.001) compared to women (M = 24.41, 95% CI: 22.73–26.08). No significant differences were found in the variable menarche. The main results described in this subsection can be seen in the table below (Table 2).

The GLM tests showed differences among the clusters in relation to the fundamental domains of “mate retention” and “kin care (family)” (Table 3). Bonferroni's post-hoc test revealed that the “unpredictability without family support” group exhibited fewer scores related to both “mate retention” and “kin care (family)” motivations. The “low unpredictability” group and the “unpredictability with family support” group did not differ from each other in terms of both motivations.