Lower emotional stability predicted higher probability of moving due to neighborhood, housing, & family, while higher agreeableness was associated with lower probability due to neighborhood & education

Personality traits and reasons for residential mobility: Longitudinal data from United Kingdom, Germany, and Australia. Markus Jokela. Personality and Individual Differences, Volume 180, October 2021, 110978. https://doi.org/10.1016/j.paid.2021.110978

Abstract: Personality traits have been associated with differences in residential mobility, but details are lacking on the types of residential moves associated with personality differences. The present study pooled data from four prospective cohort studies from the United Kingdom (UK Household Longitudinal Survey, and British Household Panel Survey), Germany (Socioeconomic Panel Study), and Australia (Household, Income, and Labour Dynamics in Australia) to assess whether personality traits of the Five Factor Model are differently related to residential moves motivated by different reasons to move: employment, education, family, housing, and neighborhood (total n = 86,073). Openness to experience was associated with all moves but particularly with moves due to employment and education. Extraversion was associated with higher overall mobility, except for moves motivated by employment and education. Lower emotional stability predicted higher probability of moving due to neighborhood, housing, and family, while higher agreeableness was associated with lower probability of moving due to neighborhood and education. Adjusting for education, household income, marital status, employment status, number of children in the household, and housing tenure did not substantially change the associations. These results suggest that different personality traits may motivate different types of residential moves.

Keywords: PersonalityMigrationMobilityDemographyGeographical psychology

4. Discussion

The current results from four prospective cohort studies suggest that personality differences are related to people's motivations to move. Openness to experience was associated with higher overall mobility but especially with mobility due to education and employment. Extraversion was also related to higher overall mobility, except moves driven by employment or education. Higher emotional stability and higher agreeableness were associated with lower residential mobility: emotional stability due to neighborhood, housing, and family, and agreeableness due to neighborhood and education. Conscientiousness was not related to residential mobility.

In Western developed countries, between 10% and 25% of households change residence every two years (Sánchez & Andrews, 2011). Economic and demographic perspectives emphasize the practical determinants of residential mobility: people move after jobs, they move to larger or smaller homes as family size changes, or they try to move away from neighborhoods they dislike (Findlay et al., 2015; Kley, 2011). The present results demonstrate that personality is not competing with sociodemographic factors as an explanation for residential mobility. Instead, people's personality traits determine, in part, how strongly their residential mobility is determined by different mobility motivations. The role of personality is thus not restricted to only predicting moves that are unrelated to sociodemographic drivers of mobility (e.g., employment or housing) but can be observed across multiple reasons for moving.

Openness to experience and extraversion are the two personality traits that have been most consistently associated with residential mobility in previous studies (Campbell, 2019; Ciani & Capiluppi, 2011; Jokela, 2009, Jokela, 2020), and the current findings provide further support for their role in residential mobility. Openness to experience was a particularly strong predictor of moves related to employment and education. Openness to experience was related to educational achievement, and sociodemographic covariates accounted for about half of its associations with mobility related to employment and education. Beyond the socioeconomic correlates, individuals with high openness to experience may be more curious and willing to explore new places (Silvia & Christensen, 2020), which increases the likelihood of moving after opportunities of higher education and employment, and moving for other reasons as well. Extraversion was also related to higher overall mobility rates. Individuals with high extraversion are energetic, active, assertive, and sensitive to rewarding experiences (Smillie, 2013). These characteristics may increase the probability of planning to move and taking action to move, and also to perceive the move to a new location as an opportunity rather than a risk.

Lower emotional stability was associated with higher mobility rates, mainly due to neighborhood, housing, and family. Individuals with low emotional stability are sensitive to negative emotions and distress (Jeronimus et al., 2016). It is therefore plausible that any dissatisfaction with the neighborhood or housing conditions is experienced more strongly by individuals with low compared to high emotional stability (Jokela, 2009), and the heightened dissatisfaction with neighborhoods or housing conditions may explain the association between low emotional stability and mobility. Higher agreeableness, in turn, was related to lower mobility due to neighborhood and education. This may be related to highly agreeable people's stronger commitment and integration with their local communities (Lounsbury et al., 2003), which could help to explain why they are less eager to move.

Conscientiousness was not related to residential mobility. Studies from the United States (Jokela, 2009) and Australia (with the same HILDA data as used here; Campbell, 2019) have also reported no significant associations with conscientiousness. However, conscientiousness may influence more specific forms of residential mobility. In HILDA, higher conscientiousness predicted higher probability of rural-to-urban migration but was not associated with urban-to-rural migration (Jokela, 2020), suggesting that conscientiousness may be associated with selective residential mobility to specific locations. And in a previous study with the BHPS, higher conscientiousness predicted higher migration probability among those participants who intended or desired to move but lower migration probability among those who did not intend or desire to move (Jokela, 2014). This suggests that the influence of conscientiousness on residential mobility depends on the person's mobility intentions, so that highly conscientious individuals are more likely to stick to their plans of either moving or not moving. A previous analysis with HILDA (Campbell, 2019) also observed that conscientiousness was related to how migration intentions aligned with migration outcomes among those who migrated. The current study did not assess mobility intentions, so such associations could not be assessed here.

The findings indicate that sociodemographic and personality explanations for residential mobility are not competing or mutually exclusive. Nevertheless, it is worth noting that moves related to employment and education were predicted only by one personality trait (openness to experience) whereas neighborhood-related moves were predicted by four personality traits (all traits except conscientiousness). Housing-related moves were also predicted by only one personality trait (emotional stability) and family-related moves by two traits (extraversion and emotional stability). Together these patterns suggest that personality may have the broadest influence on residential mobility via neighborhood preferences. Except for the two strongest associations of openness to experience, the magnitudes of the personality associations were mostly modest, so the role of personality in determining residential mobility patterns should not be overemphasized. However, even modest associations may accumulate into important population-level differences over 20–30 years (Jokela, 2020).

The study has some limitations that could be addressed in future studies. First, the study focused on reason-specific moves but did not consider moving distances that can be related to reasons to move (Thomas, 2019). Some of the personality associations with reason-specific moves may thus overlap with willingness to move over longer distances. Second, the current analysis considered only personality of individuals but did not consider possible family dynamics in which the personality associations depend on the personality traits, or other characteristics, of the spouse, because the decision to move concerns the whole family. Third, the analysis did not consider other contextualized associations that may arise over the life course (Findlay et al., 2015; Kley, 2011). For example, some personality traits may become particularly important for work-related mobility for individuals who become unemployed, or for family-related and housing-related mobility when individuals become parents. Fourth, it must be emphasized that the present results are based on meta-analytic results across three countries. The study-specific associations suggested considerable similarities between countries (see supplementary material), but it is also possible that some of the associations between personality and residential mobility vary by country or region, because different locations are characterized by different residential mobility patterns. Fifth, it would also be informative to study people's self-reported reasons for staying in their current neighborhood instead of moving away.

In sum, the present findings provide contextualized data on how different personality traits predict residential mobility due to different reasons to move. Neighborhood characteristics and sociodemographic factors associated with different life stages are important drivers of residential mobility. However, personality does not need to be considered as competing with sociodemographic explanations of residential mobility. Rather, personality traits appear to influence the relative weight of different motivating factors in guiding people's mobility decisions.

As the level of family politicization & consistency increases, the influence of genes decreases; we take this to imply that family socialization can compensate for (genetic) individual differences & foster increased political engagement

Rasmussen, Stig H. R., Aaron Weinschenk, Chris Dawes, Jacob v. Hjelmborg, and Robert Klemmensen. 2021. “Parental Transmission and the Importance of the (non-causal) Effects of Education on Political Engagement: Missing the Forest for the Trees.” PsyArXiv. June 7. doi:10.31234/osf.io/agn8t

Abstract: By most accounts, an important prerequisite for a well-functioning democracy is engaged citizens. A very prominent explanation of variation in political engagement suggests that parental transmission through socialization accounts for individual-level differences in political engagement. In this paper, we show that classic formulations of parental transmission theory can be supplemented by findings from the bio-politics literature, allowing us to disentangle when heritable factors are important and when socialization factors are important predictors of political engagement. The paper demonstrates that the effect of education on various measures of political engagement is confounded by both genes and parental socialization; no previous study has documented the importance of both of these confounders. We then go on to show that as the level of family politicization and consistency increases, the influence of genes decreases. We take this to imply that family socialization can compensate for (genetic) individual differences and foster increased political engagement. By only focusing on the “causal” effect of education, we are missing the forest for the trees.

Robust associations between fear of missing out and both social networking sites use & Problematic SNS use

Fear of missing out and social networking sites use and abuse: A meta-analysis. Giulia Fioravanti et al. Computers in Human Behavior, Volume 122, September 2021, 106839. https://doi.org/10.1016/j.chb.2021.106839

Highlights

• A meta-analysis on the relationship between FoMO levels and SNS use and problematic SNS use (PSNSU) was conducted.

• The effect sizes indicate robust associations between FoMO and both SNS use and PSNUS.

• Age, sex, and geographic area did not moderate the associations.

• FoMO should be employed as a relevant dimension in the evaluation and treatment of PSNUS.

Abstract: A growing body of research has examined the potential effects of the Fear of Missing Out (FoMO) on Social Networking Site (SNS) use and Problematic SNS use (PSNSU). The aim of the current meta-analysis is to summarize findings on the relationship between FoMO levels and (i) SNS use and (ii) PSNSU. Furthermore, we meta-analyzed results on the associations between FoMO and some individual characteristics. The sample included 33 independent samples with a total of 21,473 participants. The results of the random-effects meta-analysis show a positive correlation between FoMO and SNS use and between FoMO and PSNSU, with effect sizes indicating robust associations. Age, sex, and geographic area of the samples did not moderate the associations. FoMO was positively correlated with depression, anxiety, and neuroticism and negatively correlated with consciousness. These results give robustness to the construct validity of FoMO itself, as this concept was introduced to explain why some people might be especially attracted to social media. Moreover, concerns that others might be having rewarding experiences that one is absent from seem to be a trigger for a compulsive use of social platforms, driven by the need to get in touch with others, or as tool to develop social competence.

Keywords: 

Fear of missing outMeta-analysisProblematic social networking sites useSocial media addictionSocial networking site use

Facial shape provides a valid cue to sociosexuality in men but not women

Facial shape provides a valid cue to sociosexuality in men but not women. Joseph C. AntaraIan, D. Stephen. Evolution and Human Behavior, Volume 42, Issue 4, July 2021, Pages 361-370. https://doi.org/10.1016/j.evolhumbehav.2021.02.001

Abstract: Existing work suggests that observers' perceptions of sociosexuality from strangers' faces are positively associated with individuals' self-reported sociosexuality. However it is not clear what cues observers use to form these judgements. Over two studies we examined whether sociosexuality is reflected in faces, which cues contain information about sociosexuality, and whether observers' perceptions of sociosexuality from faces are positively associated with individuals' self-reported sociosexuality. In Study One, Geometric Morphometric Modelling (GMM) analysis of 103 Caucasian participants revealed that self-reported sociosexuality was predicted by facial morphology in male but not female faces. In Study Two, 65 Caucasian participants judged the sociosexuality of opposite sex faces (faces from Study One) at zero acquaintance. Perceived sociosexuality predicted self-reported sociosexuality for men, but not women. Participants were also presented with composites of faces of individuals with more unrestricted sociosexuality paired with composites of faces of individuals with more restricted sociosexuality and asked to indicate which was more unrestricted. Participants selected the more unrestricted sociosexuality male, but not female, facial composites at rates significantly above chance. GMM analyses also found that facial morphology statistically significantly predicted perceived sociosexuality in women's and, to a greater extent, in men's faces. Finally, facial shape mediated the relationship between perceived sociosexuality and self-reported sociosexuality in men's but not women's faces. Our results suggest that facial shape acts as a valid cue to sociosexuality in men's but not women's faces.

Keywords: Face perceptionSociosexualityValid cues

Although increasing evidence highlights genetic contributions to male sexual orientation, our current understanding of contributory loci is still limited, consistent with the complexity of the trait

Genome-Wide Linkage Study Meta-Analysis of Male Sexual Orientation. Alan R. Sanders, Gary W. Beecham, Shengru Guo, Judith A. Badner, Sven Bocklandt, Brian S. Mustanski, Dean H. Hamer & Eden R. Marti. Archives of Sexual Behavior, Jun 2 2021. https://link.springer.com/article/10.1007%2Fs10508-021-02035-3

Abstract: Male sexual orientation is a scientifically and socially important trait shown by family and twin studies to be influenced by environmental and complex genetic factors. Individual genome-wide linkage studies (GWLS) have been conducted, but not jointly analyzed. Two main datasets account for > 90% of the published GWLS concordant sibling pairs on the trait and are jointly analyzed here: MGSOSO (Molecular Genetic Study of Sexual Orientation; 409 concordant sibling pairs in 384 families, Sanders et al. (2015)) and Hamer (155 concordant sibling pairs in 145 families, Mustanski et al. (2005)). We conducted multipoint linkage analyses with Merlin on the datasets separately since they were genotyped differently, integrated genetic marker positions, and combined the resultant LOD (logarithm of the odds) scores at each 1 cM grid position. We continue to find the strongest linkage support at pericentromeric chromosome 8 and chromosome Xq28. We also incorporated the remaining published GWLS dataset (on 55 families) by using meta-analytic approaches on published summary statistics. The meta-analysis has maximized the positional information from GWLS of currently available family resources and can help prioritize findings from genome-wide association studies (GWAS) and other approaches. Although increasing evidence highlights genetic contributions to male sexual orientation, our current understanding of contributory loci is still limited, consistent with the complexity of the trait. Further increasing genetic knowledge about male sexual orientation, especially via large GWAS, should help advance our understanding of the biology of this important trait.

Discussion

Our primary analysis for this investigation was the joint analysis of multipoint linkage from the Hamer and MGSOSO datasets (Mustanski et al., 2005; Sanders et al., 2015), to which each dataset contributed some peaks (Fig. 1, Supplementary Figs. 1 and 2). Overall, the maximum multipoint peaks increased little in height, though the pericentromeric chromosome 8 peak was broadened (Fig. 2). Chromosomes 8 and X retained the highest multipoint peaks genome-wide, mostly arising from the larger (MGSOSO) dataset (Fig. 2). The joint analysis gives a more comprehensive picture of shared and heterogeneous linkage regions (e.g., at pericentromeric chromosome 8), the studies share overlapping peaks (possibly suggesting heterogeneity, perhaps with different genes involved in the different datasets), and the evidence broadens the search. The secondary analyses on summary statistics using MSP and GSMA to incorporate all three (Hamer, MGSOSO, Canadian) GWLS datasets showed no genome-wide significant results though suggestive findings remained present. The joint analysis of multipoint linkage (Fig. 1) extracted the available positional information from collaborating GWLS, though previous GWLS findings were not much further strengthened in these analyses. Nevertheless, this provides information to complement other approaches, such as helping prioritize findings from GWAS. Linkage and association studies measure different genetic properties (i.e., segregation of a region within families, vs. correlation of alleles in a population), both of which provide clues about underlying trait genetics. Thus, since GWLS are different from GWAS, we were unable to directly combine any GWAS (e.g., Ganna et al., 2019) with the studied GWLS in our GWLS meta-analysis. Limitations include those inherent to linkage (as opposed to GWAS) of traits with complex genetics (e.g., their limited utility for phenotypes with contributions from more than one or a few genes); on the other hand, linkage retains some advantages over association approaches, such as being robust to allelic heterogeneity (Lipner & Greenberg, 2018). Accumulating genetic studies of the trait such as by much enlarged GWAS (e.g., Ganna et al., 2019) will be especially useful, given its successful application in the study of other phenotypes manifesting complex genetics (e.g., Fig. 3b in Sullivan et al. (2018)).

Relational turbulence (external changes to the relational environment compel romantic partners to navigate transitions by establishing new daily routines as interdependent couples) in COVID-19

Relational turbulence from the COVID-19 pandemic: Within-subjects mediation by romantic partner interdependence. Alan K. Goodboy et al. Journal of Social and Personal Relationships, March 17, 2021. https://doi.org/10.1177/02654075211000135

Abstract: Relational turbulence theory posits that external changes to the relational environment compel romantic partners to navigate transitions by establishing new daily routines as interdependent couples. The COVID-19 pandemic is an unprecedented transition fraught with difficult changes that have the potential to be especially disruptive to romantic partners’ daily routines as couples alter their patterns of interdependence and adapt their everyday lives. To study the pandemic’s effect as a relational transition, college students in romantic relationships (N = 314) completed measures of partner facilitation and interference, negative emotions, and relational turbulence as they recalled what their relationships were like prior to the pandemic (January, 2020) and then reported on their relationships during the peak of the first wave of the pandemic in the U.S. (April, 2020). On average, negative emotions (i.e., anger, fear, sadness) toward interacting with partners and relational turbulence both increased from before to during the pandemic, and partner interference was positively correlated, whereas facilitation was inversely correlated, with negative emotions during the pandemic. Results of a within-subjects mediation model revealed that changes in relational turbulence were explained, in part, by a decrease in partner interdependence due to the pandemic. A direct effect of the pandemic on increases in relational turbulence was also discovered.

Keywords: COVID-19, interdependence, negative emotions, relational turbulence model, relational turbulence theory

Discussion

In an effort to better understand how dating relationships are affected by the COVID-19 pandemic, this study provided tests consistent with the RTM/RTT and demonstrated that this pandemic affected college students’ interdependence in their romantic relationships, their experience of negative emotions in those relationships, and ultimately the stability of those relationships. Specifically, compared to how romantic relationships were recalled before the pandemic, during the pandemic, on average, interference and facilitation from a partner in everyday routines declined, negative emotions toward the partner were amplified, and relational turbulence became more prevalent. Collectively, these results confirm RTT’s claim that transitions create changes to relational environments that modify patterns of interdependence, which ultimately give rise to more chaotic relational states (Solomon et al., 2016).

The decrease in partner interdependence might be explained by college students’ restrictions for contact during the pandemic. That is, their partner’s ability to facilitate or interfere with daily routines becomes less influential if their overall contact and time spent together has decreased due to pandemic-related constraints. Put simply, romantic partners might see each other less, providing fewer opportunities to interfere or facilitate. A post-hoc analysis provided evidence for this explanation of decreased interdependence; on average, partners saw each other 4.400 times a week before the pandemic (SD = 2.199), which decreased to an average of 3.220 times a week during the pandemic (SD = 2.496); t(300) = 7.305, p < .001, d = .420. This limited contact explanation could explain the decreases in interdependence from before to during the pandemic. For instance, some students might have moved back home and now live with a parent or parents after college campuses discontinued in-person educational offerings and switched to online instruction (Sahu, 2020). Post-hoc descriptive statistics revealed additional evidence for this limited contact explanation as partners reported increases in geographical separation after the pandemic started. Prior to the pandemic, 50.2% of partners were geographically within 15 minutes of their partner (n = 158), whereas during the pandemic, only 28.3% of partners remained within a 15-minute travel proximity (n = 89). From these post-hoc contact explorations revealing decreased weekly contact with and increased geographical distance from partners, we believe that partner interdependence declined because of new living situations that were required as romantic partners moved from college campuses and were no longer enrolled in on-campus courses or experiencing an on-campus college life.

The within-subjects mediation model revealed parallel indirect effects for partner interdependence (both interference and facilitation) on relational turbulence, as well as a direct effect of the pandemic itself on relational turbulence. With regard to the former, increases in relational turbulence were explained in part by decreases in facilitation and interference. That is, slightly less relational turbulence was experienced to the extent that partners interfered less with daily routines during the pandemic, but at the same time, relational turbulence increased more to the extent that partners did not facilitate as much with daily routines either. These opposite indirect effects are in line with the wealth of research demonstrating that interference creates turbulence whereas facilitation diminishes it (e.g., McLaren et al., 2011, 2012; Solomon & Priem, 2016). However, a direct effect revealed that, controlling for changes in partner facilitation and interference, the pandemic itself was associated with a change in more relational turbulence above and beyond partners’ decreases in interdependence. Pandemic stressors, independent of partner interdependence, appear to disrupt the stability of romantic relationships. Although relational research on the pandemic is limited as of this writing, preliminary findings suggest that stressors from the pandemic, including social isolation, financial strain, and perceived stress, are associated with lower romantic relationship quality (Balzarini et al., 2020).

During the pandemic, college students reported an increase in negative emotions toward communicating with their romantic partners including more anger, fear, and sadness. This increase in negative emotions might be indicative of partners’ daily emotional welfare being compromised as a byproduct of the pandemic. Lades et al. (2020) found when individuals stayed home during the pandemic and did not pursue outside activities, they experienced more negative affect. However, partner interference was strongly associated with these negative emotions, which is in line with previous research in other transitional contexts (Brisini & Solomon, 2019; Knobloch et al., 2007; Knobloch & Theiss, 2010; Solomon & Brisini, 2019). From a discrete emotions perspective, such negative affect may result because partner interference behaviors are perceived as threatening, uncontrollable attempts to impede one’s goals (Nabi, 2002). Axiom 2 of RTT received support as individuals felt more anger, fear, and sadness when interacting with their partner when routines were interrupted by them during the pandemic.

The findings from this investigation extend the purview of RTT to the novel context of a global health emergency and demonstrate support for the theory’s utility in the specific context of a pandemic. This research furthers a line of relatively recent scholarship which applies and tests the mechanisms of RTT when romantic partners are experiencing situations that are out of the ordinary, further illustrating RTT’s efficacy in explaining both normative and nonnormative relational experiences (e.g., Tian & Solomon, 2020). With regard to the latter, some findings emerged here which appear to be unique to the particular context under study. For example, although transitions typically evoke increased interference and attendant negative emotions from a partner (see Solomon et al., 2010), here we found that both forms of partner interdependence decreased from before to during the pandemic. It seems clear (and others have concluded) that interference is complex and unique to the transition in question (Harvey-Knowles & Faw, 2016), as some transitions naturally lend themselves to more—or in this case, less—partner interdependence, given the stringent social distancing guidelines that have characterized the pandemic in the U.S. Although partner interference is a negatively valenced construct in RTT, and thereby the reduction of interference should lead to concomitant reductions in the experience of relational turbulence, here that effect appears to have been offset by the concurrent experience of decreased partner facilitation (again, likely due to the inherent social distancing constraints of the pandemic for the college student daters in this sample, most of whom were geographically distant). In this investigation, we observed an increase in relational turbulence, which was indirectly affected by decreased partner facilitation and directly exacerbated by the nature of the pandemic itself.

Further, the findings from this study highlight the complex role of interdependence processes within RTT, and provide some evidence for the ways in which partner interference and facilitation work together (or in this case, work against each other) to impact the experience of relational turbulence in college student dating relationships. From RTT’s perspective, the least amount of turbulence should result when partner facilitation is high while partner interference is low. Here, partner interference decreased, yet so did partner facilitation. Thus, although RTT suggests that partner facilitation may at times serve a sort of buffering function against interference or the effect of transitions, this buffering effect could not be realized (despite the decrease in partner interference) because the pandemic constrained the ability to facilitate (and to interfere with) a partner’s daily routines. Perhaps because of this, the findings from this study suggested that the pandemic itself as compared to interdependence processes had the strongest impact on the experience of relational turbulence. It is important to note that the nuances of these findings regarding interdependence processes are expected to be context-dependent, as the majority of college student daters who comprised this sample were geographically distant during the pandemic. It is likely that a different pattern of results would emerge for married or cohabitating couples with regard to interdependence processes, for whom it is unlikely that both partner facilitation and interference would decrease during this extended time of social distancing, working remotely, homeschooling children, etc. For married and cohabitating couples, interdependence processes are expected to play a stronger role in the experience of relational turbulence during a pandemic (Knoster et al., 2020).

The collective results reveal several practical implications for romantic relationships of all types, including marital relationships, during the pandemic. First, it is important to recognize that transitions are times rife with relational turbulence for couples as changes to external environments produce chaotic relational states (Solomon et al., 2010). Life, in general, has been chaotic since the pandemic began and has created stressors external to interdependent relationships that carry over into it and naturally affect its quality (Balzarini et al., 2020). It is important for partners to recognize that their romantic relationships may be strained from the pandemic, and they might expect negative affect and tumultuous sensitivities for their relationships as these are processes theorized to result from the experience of transitions (Solomon & Knobloch, 2004). Second, in order to more successfully navigate the pandemic, and to navigate extreme or nonnormative relational episodes more generally, it is important for relational partners to adapt to the “new normal” by establishing neoteric patterns of interdependence that encourage relational stability. This could include establishing new daily routines and/or maintain existing ones for psychosocial benefits (WHO, 2020). These daily routines are not all instrumental or occupational; they include hobbies as well, which have been identified as particularly important for maintaining emotional well-being during the pandemic (Lades et al., 2020).

Third, in order to more effectively manage intense relational experiences, romantic partners should put in extra efforts to facilitate their partners’ daily routines, and actively try not to interfere with them. It is possible that only so much facilitation can be reasonably and safely enacted during the pandemic (and further, some research with the RTT in the context of intense relational episodes suggests that facilitation does not always lead to positive outcomes; Tian & Solomon, 2020), so college student partners in particular—as opposed to spouses, for example—might acknowledge they have less overall influence on their partners’ daily routines since the pandemic commenced. Fourth, romantic partners should realize that their reactivity during the pandemic and other extreme relational experiences is likely to be exacerbated, and this reactivity may manifest in the form of more extreme or perhaps even volatile emotions, cognitions, and communicative behaviors (Solomon et al., 2010, 2016). Such extreme reactions have implications for a variety of relational processes, including seeking/providing social support and engaging in conflict. As such, romantic partners should be cognizant of the far-reaching impact of intense experiences such as the current global health pandemic on everyday functioning in the relationship. Being aware of the potential for such reactivity may encourage partners to pause and reassess rather than overreact and engage in communication or other behaviors that could possibly damage the relationship.

Although important insights about the pandemic’s impact on the stability of romantic relationships emerged from this investigation, the findings must be interpreted in light of the limitations that were present. The primary limitation of this research was the reliance on recollections of the romantic relationship pre-pandemic (January, 2020) with a data collection that took place during the pandemic (April, 2020). Partners reported on what their relationship was like 4 months prior and then reported on how their relationship was currently during the peak of the pandemic. This method of reporting on the relationship during a previous time and at the time of the survey has been used by previous relational turbulence scholars (Brisini et al., 2018). However, asking participants to report on “then and now” repeated measurements in the same survey presents recall limitations for modeling within-participant “change.” Yet, to design a study with two time points, we would have needed prior knowledge that a global pandemic was imminent to have collected data before it began. Thus, our repeated measurements in the same survey are a proxy for change, but cannot actually measure true changes over time, and there is a chance that recall bias was an issue (i.e., a particular fondness for “before times”). Another limitation is the college student sample which might have derived different effects due to physical separation from college campuses. As such, future researchers should examine pandemic effects in marriages and test RTT within cohabitating contexts, which might offer different conclusions from more established patterns of interdependence in shared living arrangements.

Future researchers should also continue to study major transitions as opportunities to model relational turbulence. Although transitions are not a scope condition for testing RTT because partner influence can and does occur at any point in a close relationship (Berscheid, 2002), transitions are periods of discontinuity where interdependence will change as the relational environment is affected (Solomon et al., 2016). Future researchers might also examine how the COVID-19 pandemic has created relational uncertainty, and in turn, resulted in biased cognitions as purported by RTT. To keep our survey brief with repeated measures, we only examined half of the relationship parameters in RTT. Relational uncertainty is at the core of RTT and deserves empirical attention as the pandemic continues. Finally, scholars should examine processes of relational turbulence in both dating and married samples to compare effects for generalizability (Brisini & Solomon, 2019). Although these two types of relationships have produced similar effect sizes in the relational turbulence literature (Goodboy et al., 2020), nonetheless, it remains important to continue studying both types of relationships.

This study explored changes in some of the relational processes proposed by RTT that were experienced by dating partners before the COVID-19 pandemic began to the peak of the first wave of the pandemic in the U.S. The findings revealed pandemic-related relational impacts in the form of decreased partner interdependence, increased experience of negative affect, and heightened relational turbulence (explained both by decreased partner interdependence and by the impact of the pandemic itself). These results provide continued support for RTT’s predictive and explanatory utility, and importantly, suggest practical mitigation strategies for couples who are coping with the ongoing global health crisis. This work provides support for Solomon and Brisini’s (2019) assertion that “RTT may have the greatest value when it illuminates the challenges that confront couples coping with significant life transitions, especially those that impose economic, health, or emotional burdens” (p. 2432).