COVID-19 in 18 countries, 6 languages: We observed an early strong upsurge of anxiety-related terms, which was stronger in countries with stronger increases in cases; positive emotions remained relatively stable

Metzler, Hannah, Bernard Rimé, Max Pellert, Thomas Niederkrotenthaler, Anna Di Natale, and David Garcia. 2021. “Collective Emotions During the COVID-19 Outbreak.” PsyArXiv. June 8. doi:10.31234/osf.io/qejxv

Abstract: The COVID-19 pandemic has exposed the world's population to sudden challenges that elicited strong emotional reactions. Although investigations of responses to tragic one-off events exist, studies on the evolution of collective emotions during a pandemic are missing. We analyzed the digital traces of emotional expressions in tweets during five weeks after the start of outbreaks in 18 countries and six different languages. We observed an early strong upsurge of anxiety-related terms in all countries, which was stronger in countries with stronger increases in cases. Sadness terms rose and anger terms decreased around two weeks later, as social distancing measures were implemented. Positive emotions remained relatively stable. All emotions changed together with an increase in the stringency of measures during certain weeks of the outbreak. Our results show some of the most enduring changes in emotional expression observed in long periods of social media data. Words that frequently occurred in tweets suggest a shift in topics of conversation across all emotions, from political ones in 2019, to pandemic related issues during the outbreak, including everyday life changes, other people, and health. This kind of time-sensitive analyses of large-scale samples of emotional expression have the potential to inform mental health support and risk communication.

The absence of pessimism was more strongly related to positive health outcomes than was the presence of optimism

Scheier, M. F., Swanson, J. D., Barlow, M. A., Greenhouse, J. B., Wrosch, C., & Tindle, H. A. (2021). Optimism versus pessimism as predictors of physical health: A comprehensive reanalysis of dispositional optimism research. American Psychologist, 76(3), 529–548. Jun 2021. https://doi.org/10.1037/amp0000666

Abstract: Prior research has related dispositional optimism to physical health. Traditionally, dispositional optimism is treated as a bipolar construct, anchored at one end by optimism and the other by pessimism. Optimism and pessimism, however, may not be diametrically opposed, but rather may reflect 2 independent, but related dimensions. This article reports a reanalysis of data from previously published studies on dispositional optimism. The reanalysis was designed to evaluate whether the presence of optimism or the absence of pessimism predicted positive physical health more strongly. Relevant literatures were screened for studies relating dispositional optimism to physical health. Authors of relevant studies were asked to join a consortium, the purpose of which was to reanalyze previously published data sets separating optimism and pessimism into distinguishable components. Ultimately, data were received from 61 separate samples (N = 221,133). Meta-analytic analysis of data in which optimism and pessimism were combined into an overall index (the typical procedure) revealed a significant positive association with an aggregated measure of physical health outcomes (r = .026, p < .001), as did meta-analytic analyses with the absence of pessimism (r = .029, p < .001) and the presence of optimism (r = .011, p < .018) separately. The effect size for pessimism was significantly larger than the effect size for optimism (Z = −2.403, p < .02). Thus, the absence of pessimism was more strongly related to positive health outcomes than was the presence of optimism. Implications of the findings for future research and clinical interventions are discussed.

Discussion

The results of the present reanalyses confirm the findings from earlier quantitative and qualitative reviews. The presence of optimism combined with the absence of pessimism (as assessed by the overall/combined scale) is a reliable predictor of physical health. This was true for an analysis that pooled all of the outcomes together and also true for the majority of analyses that examined subgroups of outcomes separately. This replication of prior findings is noteworthy inasmuch as over 80 percent of the studies included in the present reanalyses were not included in the previous meta-analysis (Rasmussen et al., 2009). The novel findings concern the relative strength of optimism and pessimism in contributing to associations with health. Although each was a significant predictor of physical health, the Optimism, Pessimism, and Health 19 effect sizes associated with the absence of pessimism were generally greater in size than those associated with the presence of optimism. The magnitude of these differences was great enough to be significantly different for the analysis aggregating across outcomes, as well as for several of the analyses that investigated subgroups of outcomes separately. Adjustment of the findings for publication bias did little to alter the basic nature of the primary findings. Moderator analyses were conducted on the effect sizes from the overall/combined scale, as well as the two subscales. These analyses failed to identify any significant moderator. It is of interest that there were no significant differences in effect sizes as a function of the type of study employed. Cross-sectional studies are open to a number of methodological criticisms, most notably the issue of reverse causality. Longitudinal studies examine associations across time, but without provisions for equating the health of participants at baseline. As such, longitudinal studies are subject to many of the same criticisms as are cross-sectional studies. Prospective studies provide the gold standard, in that they offer an assessment of the change in the outcome variable overtime (or otherwise start with participants who can be assumed to be equivalent in health at baseline). Given these considerations, it is especially striking that the moderator analyses revealed that study design did not significantly impact the magnitude of the effect sizes that were obtained. The foregoing discussion speaks to the statistical reliability of the effects that emerged. A few words also need to be said about the magnitude of the effects that emerged. The effects sizes reported here appear small. Several considerations should be borne in mind, however, when evaluating the effect sizes obtained. First, as just noted, the effect sizes reported are adjusted for a host of factors, including those related to demographics, study design, and other confounding psychosocial factors. Thus, the effect sizes reported are unique to optimism and pessimism. It is not surprising that the effect sizes are somewhat small, especially so inasmuch as shared variance with related psychosocial factors had been removed. The second point to make is that statistical effects, even small ones, can be quite meaningful when applied to large numbers of people. Take for example, the effect size Optimism, Pessimism, and Health 20 characterizing the association between the pessimism subscale and mortality. The corresponding adjusted odds ratio for this effect in the present reanalysis is 1.074 [95% CI (1.024, 1.126)]. In terms of the number of people who lived and died in the United States in 2016 (the year the most recent study in these reanalyses was published), this odds ratio implies that a 1-point change in the pessimism direction of the pessimism subscale corresponds to an increase in 97,914 deaths from all causes [95% CI (32,540, 162,641)]. Finally, it is worth mentioning that the size of the effects obtained using the present metaanalytic techniques are quite comparable to effects reported in other meta-analyses of psychosocial factors and physical health when the studies are put on this same metric [see, e.g., Richardson et al. (2012) for a meta-analysis of perceived stress and incident coronary heart disease and Kivimäki et al., 2012 for a meta-analysis of job strain and coronary heart disease]. Taken together, these considerations suggest that from a public health standpoint the magnitude of the effects obtained in the present analysis are nontrivial and quite comparable to other findings in the literature. The present set of reanalyses has several potential limitations that should be highlighted. First, search terms for the present analysis relied heavily on the framework used by Rasmussen et al. (2009). The scheme used here is only one of many that could be adopted. Different search terms could yield a different corpus of studies, and the findings obtained using those different studies could be somewhat different. Second, the yield rate for relevant studies was 32%. It is difficult to evaluate this yield rate compared to other meta-analytic studies. This is the case because the data required for the present study could not be extracted from published studies. Rather, the analysis was contingent on authors of those published studies reanalyzing their data and forwarding on the results of those re-analyses. It is likely that this extra requirement lowered the yield rate to some extent. The third limitation concerns the homogeneous nature of the gender and racial composition of the participants. Although these factors differed somewhat from study to study, over 90% of the overall sample were white and women. Additionally, over 90% of the studies were conducted Optimism, Pessimism, and Health 21 in the United States. More studies are clearly needed to determine if the effects reported here are replicable in more diverse populations. Fourth, the conduct of the present research was a group effort. The analyses could not have been done if consortium members had not conducted the needed analyses and forwarded their findings to the primary authors for further meta-analytic processing. On the positive side, the project represents one of the best examples of collaborative science in the truest sense of the term. On the negative side, the more people involved, the more potential there is for error. This concern is mitigated by the fact that the researchers involved had already published peer reviewed papers with these same data, and as such had already demonstrated significant capability with these analyses. Finally, the outcomes examined in the present study all involved physical health. It is unclear if similar findings would obtain if mental health outcomes were examined. Perhaps optimism and pessimism would be equally robust as predictors of psychological well-being. Perhaps optimism would be stronger. It is important not to extrapolate the findings obtained with the present set of outcomes to possible findings involving other outcomes. Future research on psychological well-being should report results for the optimism and pessimism subscales separately, in order to evaluate the relative strength of the two dimensions in predicting outcomes in that domain. There is a more nuanced point to be made here than simply to acknowledge that the differential impact of optimism and pessimism on psychological well-being needs to be explored. That is, stress has been identified as one potentially important factor that might mediate the impact of optimism (and pessimism) on physical health (Scheier & Carver, 2018). How? The idea is that stress (and stress-related emotions) might modulate downstream biological systems that underlie health and disease. Optimists cope with and psychologically react to adversity in a different way than do pessimists (Segerstrom et al., 2017). It would be interesting to see within this context if the presence or absence of optimism and the presence or absence of pessimism relate differentially Optimism, Pessimism, and Health 22 to the various emotions that arise in reaction to stressful circumstances. It would further be interesting to see if these potentially different emotions (that characterize the reactions of optimists and pessimists to stress) might themselves be more or less strongly related to physical health outcomes. Answering questions such as these could further in a significant way our understanding of why it might be that the absence of pessimism is more strongly related to physical health outcomes than is the presence of optimism. Limitations aside, the present findings have at least three implications. First, future research should, as a matter of course, provide effect size information for the overall/combined scale and the two subscales separately—a suggestion that has been made previously (Scheier et al., 1994). Such a practice is even more important now that quantitative data exist documenting the differential associations of the two subscales with physical health. With the complete complement of effect sizes reported, future research could continue to evaluate the importance of the separate contributions of optimism versus pessimism without the need to establish consortiums. The present findings also hold important implications for positive psychology (Peterson & Park, 2003; Seligman & Csikszentmihalyi, 2000). Positive psychology emphasizes those characteristics that enable people to experience full, industrious, and resilient lives. As such, it stands in contrast to traditional views that tend to focus on negative attributes, such as depression, anxiety, and other characteristics which undermine successful living. Dispositional optimism is often described as a good example of a variable falling within the positive psychology domain (e.g., Dunn, 2018). As the present data make clear, however, the presence of optimism does not provide the whole story. Optimism is important, but it does not appear to be as important as the absence of pessimism in predicting physical health. In the future, researchers in positive psychology might benefit from taking these findings into account when planning and conducting research. Researchers should examine more closely the predictor variables they are using to see if negative and positive characteristics might be intermingled in the measures employed. If so, an effort should be made to tease apart the positive Optimism, Pessimism, and Health 23 and negative components of the measures to determine what is in fact responsible for doing the predicting. Ultimately, it may turn out that it is the positive aspects of the measures that are important, but it also possible that the negative features are the ones driving the observed associations. Only by explicitly evaluating these possibilities will we know for sure. The final implication concerns interventions. Future efforts to design and adapt interventions to promote better health should keep in mind the differential links between optimism, pessimism, and physical health. In this regard, it is interesting that some cognitive behavior therapies seem to put a greater emphasis on lessening pessimism than they do on promoting optimism. One example of such an intervention concerns cognitive restructuring (Leahy & Rego, 2012), in which participants are trained to challenge the automatic thoughts, beliefs, and expectancies underlying negative feelings. Participants confront their automatic, negative thinking by systematically, and explicitly monitoring their moods and assessing in a more objective fashion the information in the ongoing context that either supports or challenges their negative thoughts. Perhaps existing interventions that focus more on lessening pessimism such as those involving cognitive restructuring will be more successful in promoting better health than will those that place a greater weight on promoting optimism, or even those that place an equal weight on both components. Note that it is not a matter of causing harm, but more a matter of targeting the component that offers the most gain. It is also possible, however, that things are more complicated. Perhaps what works best will depend on the nature of the outcome of interest (e.g., health behaviors versus biological pathways). Intervention efforts with respect to optimism, pessimism, and physical health are still in their infancy. As research in the intervention domain continues to evolve, it would seem prudent to keep the distinction between optimism and pessimism in mind. Doing so may prove profitable both practically and theoretically.

Canadians who feel disgust towards sitting on the toilet seat of a public bathroom are in general more socially conservative, tend to vote for conservatives, & favor conservative policies on issues like gay rights & immigration

The political phenotype of the disgust sensitive: Correlates of a new abbreviated measure of disgust sensitivity. Patrick Fourniera, Michael Bang Petersen, Stuart Sorok. Electoral Studies, Volume 72, August 2021, 102347. https://doi.org/10.1016/j.electstud.2021.102347

Abstract: The fields of political psychology and election studies often live separate lives. One reason has been the difficulty of including long psychological question batteries in the high-quality, representative samples that are the hallmark of election studies. In this study, we examine a novel one-item measure of psychological differences in sensitivity to one particular emotion: disgust. We demonstrate that disgust sensitivity serves as a foundational political difference that colors a very large range of social and political attitudes and behaviors: including ideology, political engagement, reactions towards outgroups, support for government intervention, behavior during a pandemic, and vote choice.

Keywords: Disgust sensitivityElection studyIdeologyVote choicePolicy attitudesGroup ratings

Eveningness, a preference for later sleep and rise times, is significatively linked to Major Depressive Disorder (MDD), but the effect is small

Diurnal preference and depressive symptomatology: a meta-analysis. Ray Norbury. Scientific Reports volume 11, Article number: 12003. Jun 7 2021. https://www.nature.com/articles/s41598-021-91205-3

Abstract: Eveningness, a preference for later sleep and rise times, has been associated with a number of negative outcomes in terms of both physical and mental health. A large body of evidence links eveningness to Major Depressive Disorder (MDD). However, to date, evidence quantifying this association is limited. The current meta-analysis included 43 effect sizes from a total 27,996 participants. Using a random-effects model it was demonstrated that eveningness is associated with a small effect size (Fisher’s Z = − 2.4, 95% CI [− 0.27. − 0.21], p < 0.001). Substantial heterogeneity between studies was observed, with meta-regression analyses demonstrating a significant effect of mean age on the association between diurnal preference and depression. There was also evidence of potential publication bias as assessed by visual inspection of funnel plots and Egger’s test. The association between diurnal preference and depression is small in magnitude and heterogenous. A better understanding of the mechanistic underpinnings linking diurnal preference to depression and suitably powered prospective studies that allow causal inference are required.

Discussion

The current findings demonstrate a small but significant association between diurnal preference and depressive symptomatology. All of the reported studies indicated a positive association between eveningness and depression, ranging between − 0.52 and − 0.03. The summary effect size for the random effects model was − 0.24 which is largely consistent with an earlier meta-analysis30 that reported an effect size of − 0.2 and together these data suggest a small but reliable association between eveningness and depression. Contrary to the findings of Au and Reece, in the current analysis evidence of a potential publication bias (i.e. statistically significant or favourable results being more likely to be published than studies with non-significant or unfavourable results) was observed. The adjusted effect size (Fishers Z = − 0.21), however, remained significant. Subgroup analyses demonstrated no moderating effect of sample characteristics, eveningness or depression measure, or studies published in 2020 vs. any other year. Meta-regression showed a significant effect of age on the association between eveningness and depression symptomatology, but no evidence for a moderating effect of sample size, gender ratio, or year of publication.

A long-standing question in the literature is one of directionality; does eveningness cause depression or is eveningness a consequence of the disorder? The cross-sectional studies quantified here cannot speak directly to this question. However, the current results demonstrated no significant difference between clinical and non-clinical samples, a finding consistent with Au and Reece30. Eveningness may therefore represent a risk-factor for depression rather than a consequence of the depressed state. The vulnerability-stress hypothesis of depression96,97 proposes that depression emerges through an interaction between psychological vulnerability factors (e.g., negative biases/preferential processing of negative material) and an environmental stressor (e.g., bereavement, financial insecurity). Importantly, previous work suggests that eveningness is associated with aspects of negative thinking (i.e. psychological vulnerability factors) in never-depressed individuals. For example, eveningness has been associated with greater recall for negative personality trait words, greater recognition of sad facial expressions63,98 and maladaptive emotion regulation strategies93,99. Similarly, high neuroticism (i.e. individuals who are emotionally reactive and tend to experience more negative emotions and depression) has also been associated with eveningness100. Converging evidence, therefore, suggests that in healthy, never-depressed individuals, eveningness is associated with depressogenic personality types, negative biases in emotional processing and impaired emotion regulation which, if combined with adversity, may lead to depression. These findings also suggest modifiable markers that could be therapeutically targeted to prevent the onset of depression in evening type individuals.

Of the moderators tested here only age was significantly associated with effect size. This contrasts with the findings of Au and Reece (2017) who did not observe a similar relationship. The mean age range in the current study was 19–70, which is broader than included by Au and Reece (19–55, MDD sample only) which may account for the discrepancy. Although it should be noted that for the majority of studies included here (~ 50%) the mean age was less than 30 years of age. Of note, Kim et al. recently reported no difference in prevalence rates for depression in late chronotypes vs. neither types in a population of Korean adults stratified by age (19–40, 41–59 and 60–80 years). However, although the total sample size was large (N = 6382) the number of participants in the older 60–80 years group classified as evening-type was small (N = 22) which may limit interoperability101. Counter to this, eveningness has been associated with increased odds for reporting depression in a large sample of older adults (age range 40–70 years) taken from the UK Biobank102. Similarly, here increasing age was associated with increased depressive symptomatology but the factors underpinning this effect remain to be elucidated. Older individuals that remain more evening-type may gradually lose friendship networks and group allegiances as peers gravitate to a social schedule in synchrony with their changing circadian typology, potentially leaving evening-prone individuals more isolated and potentially more prone to depression. This notion, however, is purely speculative and requires further investigation with suitably powered, prospective studies to determine the potential impact of age on the association between eveningness and depression.

There are several limitations associated with this work which should be considered when interpreting the results. A general limitation of meta-analyses is that by creating a summary of outcomes, important between-study differences are ignored. To formally address this here study inclusion was restricted to adults, for clinical samples mood disorders other than MDD were excluded and only studies that used validated instruments to measure depressive symptomatology and diurnal preference were included. In addition, moderator analysis and meta-regression were employed to explore study heterogeneity. More specifically, the current analysis was unable to account for important factors that may impact the results. Sleep duration and/or sleep quality, for example, were not taking into consideration (zero-order correlations or unadjusted odds-ratios/mean differences were reported). Similarly, social jet-lag, the difference between internal rhythm and external demands (e.g. work or university), which may be more pronounced in evening-types and is associated with increased likelihood of reporting depressive symptoms103,104 was not included in this meta-analysis. The current report, therefore, cannot directly assess the potential impact of social jetlag on the association between eveningness and depressive symptoms. Further, the terms chronotype and diurnal preference are frequently used interchangeably in the literature but reflect different aspects of the same phenomenon. Here, the focus was diurnal preference and the questionnaires included limited to the MEQ, rMEQ and CSM which determine morningness/eveningness preferences based on self-reported preferences for times of activity and rest. These measures, therefore, reflect a personality trait. By contrast, instruments such as the Munich Chronotype Questionnaire (MCTQ)105 measure behaviour (mid-point of sleep on free days) which can be viewed as an indicator of state106. The focus of the current report was unipolar depression, but increasing evidence links eveningness with other affective disorders such as bipolar disorder107 and Major Depressive Disorder with Seasonal Pattern108 and anxiety109. Future meta-analyses that review and synthesise the recent literature related to these disorders is warranted. Finally, it should also be noted that all phases of this review and analyses were conducted solely by the author.

In summary, the current meta-analysis demonstrated that eveningness is associated with depressive symptoms. These data are largely consistent with a previous meta-analysis30 and the extant literature. The underlying causes that lead to depression are likely multifactorial and progress in understanding the links between diurnal preference and depression is predicated on a better understanding of the mechanistic underpinnings and suitably powered prospective studies that allow causal inference.

Most non-human species are cognitively constrained to show only simple forms of reputation-based cooperation

Manrique, Hector, Henriette Zeidler, Gilbert Roberts, Pat Barclay, Flora Samu, Andrea Fariña, Redouan Bshary, et al. 2021. “The Psychological Foundations of Reputation-based Cooperation.” PsyArXiv. June 2. doi:10.1098/rstb.2020.0287

Abstract: Humans care about having a positive reputation, which may prompt them to help in scenarios where the return benefits are not obvious. Various game-theoretical models support the hypothesis that concern for reputation may stabilize cooperation beyond kin, pairs or small groups. However, such models are not explicit about the underlying psychological mechanisms that support reputation-based cooperation. These models therefore cannot account for the apparent rarity of reputation-based cooperation in other species. Here we identify the cognitive mechanisms that may support reputation-based cooperation in the absence of language. We argue that a large working memory enhances the ability to delay gratification, to understand others' mental states (which allows for perspective-taking and attribution of intentions), and to create and follow norms, which are key building blocks for increasingly complex reputation-based cooperation. We review the existing evidence for the appearance of these processes during human ontogeny as well as their presence in non-human apes and other vertebrates. Based on this review, we predict that most non-human species are cognitively constrained to show only simple forms of reputation-based cooperation.

Less educated citizens in democracies are considerably less trustful of science than their counterparts in non-democracies, not due to stronger religiosity or lower science literacy, but for a shift in the mode of legitimation

Jiang, Junyan and Wan, Kin-Man, Democracy and Mass Skepticism of Science (June 3, 2021). SSRN: http://dx.doi.org/10.2139/ssrn.3845857

Abstract: Ever since the Age of Enlightenment, democracy and science have been seen as two aspects of modernity that mutually reinforce each other. This article highlights a tension between the two by arguing that certain aspects of contemporary democracy may aggravate the anti-intellectual tendency of the mass public and potentially hinder scientific progress. Analyzing a new global survey of public opinion on science with empirical strategies that exploit cross-country and cross-cohort variations in experience with democracy, we show that less educated citizens in democracies are considerably less trustful of science than their counterparts in non-democracies. Further analyses suggest that, instead of being the result of stronger religiosity or lower science literacy, the increase in skepticism in democracies is mainly driven by a shift in the mode of legitimation, which reduces states' ability and willingness to act as key public advocates for science. These findings help shed light on the institutional sources of "science-bashing" behaviors in many long-standing democracies.

Keywords: science, democracy, institution, anti-intellectualism, constitution, legitimacy

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[democracies are significantly less likely to make references to science in their constitutions, and award a smaller share of high state honors to scientists.]

Poorly educated individuals with highest trust in science: Korea, China, Kazakhstan, Spain, Tanzania, Gambia, Tajikistan, Myanmar, UAE, and Uzbekistan. For college degree+, the highest trust countries are the Philippines, India, Belgium, Denmark, Norway, Ireland, Finland, Spain, Tajikistan, and Czech Republic.

Over the course of the pandemic, we observed that the genetic predisposition to life satisfaction had an increasing influence on perceived quality of life

Warmerdam, Robert, Henry H. Wiersma, Pauline Lanting, Marjolein X. Dijkema, Judith M. Vonk, Marike H. Boezen, Patrick Deelen, et al. 2021. “Increased Genetic Contribution to Wellbeing During the COVID-19 Pandemic.” PsyArXiv. June 7. doi:10.31234/osf.io/uksxt

Abstract: Physical and mental health are determined by an interplay between nature, i.e. genetics, and nurture, which encompasses experiences and exposures that can be short or long-lasting. Depressive episodes, for example, are partly the result of an interaction between stressful life-events and a genetic predisposition to depression The COVID-19 pandemic represents a unique situation in which whole communities were suddenly and simultaneously exposed to both the virus and the societal changes required to combat the virus. We studied 27,537 population-based biobank participants for whom we have genetic data and extensive longitudinal data collected via 19 questionnaires over 10 months, starting in March 2020. This allowed us to explore the interaction between genetics and the impact of the COVID-19 pandemic on individuals’ wellbeing over time. We observe that genetics affected many aspects of well-being, but also that its impact on several phenotypes changed over time. Over the course of the pandemic, we observed that the genetic predisposition to life satisfaction had an increasing influence on perceived quality of life. These results suggest that people’s genetic constitution manifested more prominently over time, potentially due to social isolation driven by strict COVID-19 containment measures. Overall, our findings demonstrate that the contribution of genetic variation to complex phenotypes is dynamic rather than static.

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).