A synthesis of evidence for policy from behavioural science during COVID-19.

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

The social media discourse of engaged partisans is toxic even when politics are irrelevant.

Prevailing theories of partisan incivility on social media suggest that it derives from disagreement about political issues or from status competition between groups. This study-which analyzes the commenting behavior of Reddit users across diverse cultural contexts (subreddits)-tests the alternative hypothesis that such incivility derives in large part from a selection effect: Toxic people are especially likely to opt into discourse in partisan contexts. First, we examined commenting behavior across over 9,000 unique cultural contexts (subreddits) and confirmed that discourse is indeed more toxic in partisan (e.g. r/progressive, r/conservatives) than in nonpartisan contexts (e.g. r/movies, r/programming). Next, we analyzed hundreds of millions of comments from over 6.3 million users and found robust evidence that: (i) the discourse of people whose behavior is especially toxic in partisan contexts is also especially toxic in nonpartisan contexts (i.e. people are not politics-only toxicity specialists); and (ii) when considering only nonpartisan contexts, the discourse of people who also comment in partisan contexts is more toxic than the discourse of people who do not. These effects were not driven by socialization processes whereby people overgeneralized toxic behavioral norms they had learned in partisan contexts. In contrast to speculation about the need for partisans to engage beyond their echo chambers, toxicity in nonpartisan contexts was higher among people who also comment in both left-wing and right-wing contexts (bilaterally engaged users) than among people who also comment in only left-wing or right-wing contexts (unilaterally engaged users). The discussion considers implications for democratic functioning and theories of polarization.

"Mostly White, heterosexual couples": Examining demographic diversity and reporting practices in relationship science research samples.

Social and personality psychologists aim to "understand individuals in their social contexts for the benefit of all people" (Society for Personality and Social Psychology, n.d.). Though this mission is admirable, value statements do little, on their own, to create an inclusive, high-quality science that benefits humanity broadly. In this research, we evaluate relationship science, a major subfield of social-personality psychology, illustrating both the unique diversity-relevant challenges faced by particular subfields and the barriers to inclusive and diverse research that are shared across research areas. Specifically, we examine the sample diversity and reporting practices of 1,762 studies published in eight mainstream psychology and relationships journals at two time points-(a) 1996-2000 and (b) 2016-2020-and center our analysis around five focal sample characteristics: gender, sexual orientation, regional context, socioeconomic status (SES), and race. We find that reporting practices and representation have not improved for some core demographic characteristics (e.g., socioeconomic status) and that even in domains for which reporting practices have improved (e.g., sexual orientation), reporting remains limited. Further, we find that reporting practices in relationship science frequently center Whiteness (e.g., "participants were mostly White"), obscure or overlook potential sexual orientation diversity (e.g., implying that individuals in man-woman dyads are "heterosexual"), and treat the United States as the contextual default (e.g., participants came from a "large Southeastern university"). In light of these findings, we offer recommendations that we hope will cultivate a more representative and inclusive discipline. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Mate evaluation theory.

There are two unresolved puzzles in the literature examining how people evaluate mates (i.e., prospective or current romantic/sexual partners). First, compatibility is theoretically crucial, but attempts to explain why certain perceivers are compatible with certain targets have revealed small effects. Second, features of partners (e.g., personality, consensually rated attributes) affect perceivers' evaluations strongly in initial-attraction contexts but weakly in established relationships. Mate Evaluation Theory (MET) addresses these puzzles, beginning with the Social Relations Model postulate that all evaluative constructs (e.g., attraction, relationship satisfaction) consist of target, perceiver, and relationship variance. MET then explains how people draw evaluations from mates' attributes using four information sources: (a) shared evolved mechanisms and cultural scripts (common lens, which produces target variance); (b) individual differences that affect how a perceiver views all targets (perceiver lens, which produces perceiver variance); (c) individual differences that affect how a perceiver views some targets, depending on the targets' features (feature lens, which produces some relationship variance); and (d) narratives about and idiosyncratic reactions to one particular target (target-specific lens, which produces most relationship variance). These two distinct sources of relationship variance (i.e., feature vs. target-specific) address Puzzle #1: Previous attempts to explain compatibility used feature lens information, but relationship variance likely derives primarily from the (understudied) target-specific lens. MET also addresses Puzzle #2 by suggesting that repeated interaction causes the target-specific lens to expand, which reduces perceivers' use of the common lens. We conclude with new predictions and implications at the intersection of the human-mating and person-perception literatures. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Initial impressions of compatibility and mate value predict later dating and romantic interest.

Romantic first impressions seem to linger, but why? Few studies have investigated how romantic desire during initial interactions predicts later relational outcomes (e.g., later romantic interest, contact attempts) using a design that can tease apart different possible mechanisms (e.g., mate value, selectivity, compatibility). Across three speed-dating studies (n = 559) with longitudinal follow-ups (including college and community samples, and a sample of men who date men), we investigated whether different components of initial romantic impressions predicted later romantic outcomes and relationship initiation. Using the social relations model, we partitioned initial desire at speed dating (determined from 6,600+ total dates) into partner effects (a date's consensual desirability, e.g., mate value), actor effects (a participant's general desirousness, e.g., selectivity), and relationship effects (a participant's unique liking for a date over and beyond partner and actor effects, e.g., compatibility) to predict later evaluations (romantic interest, physical attraction, and desire to know better) and behaviors (direct messaging and going on dates). Meta-analyses across the three studies showed that, across 6,100+ follow-up reports, partner and relationship effects were especially strong predictors of relationship initiation variables. Consistent with evolutionary models of human pair bonding, these findings suggest that both consensually desirable traits and unique impressions of compatibility have lingering effects on relationship development, even from the moment that two potential partners meet.

Interventions to reduce partisan animosity.

Rising partisan animosity is associated with a reduction in support for democracy and an increase in support for political violence. Here we provide a multi-level review of interventions designed to reduce partisan animosity, which we define as negative thoughts, feelings and behaviours towards a political outgroup. We introduce the TRI framework to capture three levels of intervention-thoughts (correcting misconceptions and highlighting commonalities), relationships (building dialogue skills and fostering positive contact) and institutions (changing public discourse and transforming political structures)-and connect these levels by highlighting the importance of motivation and mobilization. Our review encompasses both interventions conducted as part of academic research projects and real-world interventions led by practitioners in non-profit organizations. We also explore the challenges of durability and scalability, examine self-fulfilling polarization and interventions that backfire, and discuss future directions for reducing partisan animosity.

Connect or protect? Social class and self-protection in romantic relationships.

Lower SES (socioeconomic status) couples tend to face particular challenges in their relationships. Relative to higher SES couples, they are less likely to marry and more likely to divorce-but they do not value their romantic relationships any less. Drawing on risk regulation theory and theories of social class as culture, we suggest that lower SES individuals adapt to their more chronically precarious environments by prioritizing self-protection more than higher SES individuals do, but that the need to self-protect may undermine relationship satisfaction. We investigate these ideas across 3 studies, using cross-sectional, longitudinal, and daily-diary methods. Lower SES individuals were more self-protective, both in their thoughts about their relationship (Studies 2-3), and in the judgments they made about their partner's commitment level over 2 years (Study 1) and 2 weeks (Study 3). Self-protection, in turn, was associated with lower relationship satisfaction (Studies 2-3). However, lower SES individuals were only self-protective when feeling vulnerable in their relationships (Study 3). Taken together, these studies identify psychological mechanisms to explain why the structural challenges that lower SES individuals experience can make it more difficult to achieve satisfying relationships. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

A Multisite Preregistered Paradigmatic Test of the Ego-Depletion Effect.

We conducted a preregistered multilaboratory project (k = 36; N = 3,531) to assess the size and robustness of ego-depletion effects using a novel replication method, termed the paradigmatic replication approach. Each laboratory implemented one of two procedures that was intended to manipulate self-control and tested performance on a subsequent measure of self-control. Confirmatory tests found a nonsignificant result (d = 0.06). Confirmatory Bayesian meta-analyses using an informed-prior hypothesis (δ = 0.30, SD = 0.15) found that the data were 4 times more likely under the null than the alternative hypothesis. Hence, preregistered analyses did not find evidence for a depletion effect. Exploratory analyses on the full sample (i.e., ignoring exclusion criteria) found a statistically significant effect (d = 0.08); Bayesian analyses showed that the data were about equally likely under the null and informed-prior hypotheses. Exploratory moderator tests suggested that the depletion effect was larger for participants who reported more fatigue but was not moderated by trait self-control, willpower beliefs, or action orientation.

Who are "We"? Couple Identity Clarity and Romantic Relationship Commitment.

This research introduces the construct of couple identity clarity-the extent to which an individual, as one of two partners in a romantic relationship, believes that the two of them know who they are as a couple. Cross-sectional (Studies 1-2), experimental (Study 3), and longitudinal (Study 4) studies supported the hypothesis that couple identity clarity is associated with higher commitment. Moreover, higher couple identity clarity, although related to actual agreement between partners on their identity as a couple, predicted commitment above and beyond agreement (Study 2)-as well as predicted reduced likelihood of relationship dissolution over a 9-month period (Study 4). Exploratory analyses revealed that successful conflict resolution may enhance couple identity clarity, in turn predicting commitment (Study 4). These studies highlight the importance of people's understanding of who they are as a couple and how this understanding shapes relationship persistence.

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies.

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner's ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person's own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships.

Using social and behavioural science to support COVID-19 pandemic response.

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.

Creativity and romantic passion.

Romantic passion typically declines over time, but a downward trajectory is not inevitable. Across 3 studies (1 of which encompassed 2 substudies), we investigated whether creativity helps bolster romantic passion in established relationships. Studies 1A and 1B revealed that people with highly creative personalities report not only greater overall passion but also an attenuation in the tendency for passion to decline as relationship duration increases. Studies 2 and 3 explored positive illusions about the partner's physical attractiveness as a possible mediator of the effect of creativity on passion. Cross-lagged panel analyses in Study 2 indicated that being creative is linked to a tendency to view the partner as especially attractive, even relative to the partner's own self-assessment. Path analyses in Study 3 provided longitudinal evidence consistent with the hypothesis that positive illusions about the partner's attractiveness (participant's assessments, controlling for objective coding of the partner's attractiveness) mediate the link between creativity and changes in passion over time. Study 3 also provided longitudinal evidence of the buffering effect of creativity on passion trajectories over time, an effect that emerged not only for self-reported passion but also for objectively coded passion during a laboratory-based physical intimacy task 9 months later. A meta-analytic summary across studies revealed a significant overall main effect of creativity on passion, as well as a significant moderation effect of creativity on risks of passion decline (e.g., relationship length). (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Best Practices for Testing the Predictive Validity of Ideal Partner Preference-Matching.

Many psychological hypotheses require testing whether the similarity between two variables predicts important outcomes. For example, the ideal standards model posits that the match between (A) a participant's ideal partner preferences, and (B) the traits of a current/potential partner, predicts (C) evaluative outcomes (e.g., the decision to date someone, relationship satisfaction, breakup); tests of the predictive validity of ideal-matching require A × B → C analytic strategies. However, recent articles have incorrectly suggested that documenting a positive samplewide correlation between a participant's ideals and a current partner's traits (an A-B correlation) implies that participants pursued, selected, or desired partners with traits that matched their ideals. There are at least six alternative explanations for the emergence of a samplewide A-B correlation; A-B correlations do not provide evidence that ideals guide the selection/evaluation of specific partners. We review appropriately rigorous A × B → C tests that can aid scholars in identifying the circumstances in which ideal-matching exhibits predictive validity.

Can you get the magic back? The moderating effect of passion decay beliefs on relationship commitment.

The present research introduces the construct of a decay theory of passion-a lay belief that romantic passion decline is irreversible-and investigates how this construct interacts with existing levels of passion for one's romantic partner to predict lower relationship commitment and greater pursuit of romantic alternatives. Across three studies employing experimental and nonexperimental procedures-and a set of meta-analytic syntheses including additional studies-results generally supported the hypotheses that, although low passion is linked to lower commitment and greater pursuit of romantic alternatives, such effects are stronger when adherence to decay beliefs is high rather than low. These effects tended to be independent of effects of destiny and growth theories (Knee, 1998), a related set of lay theories in the domain of relationships. Mediated moderation analyses revealed that the moderating effect of decay theories on relationship commitment mediates the moderating effect of decay theories on the link between low passion and the pursuit of romantic alternatives. Discussion addresses the possibility that changing one's beliefs surrounding the nature of romantic passion may be an important, but previously overlooked, means for preventing one from prematurely abandoning an otherwise satisfying relationship. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

You Can't See the Real Me: Attachment Avoidance, Self-Verification, and Self-Concept Clarity.

Attachment shapes people's experiences in their close relationships and their self-views. Although attachment avoidance and anxiety both undermine relationships, past research has primarily emphasized detrimental effects of anxiety on the self-concept. However, as partners can help people maintain stable self-views, avoidant individuals' negative views of others might place them at risk for self-concept confusion. We hypothesized that avoidance would predict lower self-concept clarity and that less self-verification from partners would mediate this association. Attachment avoidance was associated with lower self-concept clarity (Studies 1-5), an effect that was mediated by low self-verification (Studies 2-3). The association between avoidance and self-verification was mediated by less self-disclosure and less trust in partner feedback (Study 4). Longitudinally, avoidance predicted changes in self-verification, which in turn predicted changes in self-concept clarity (Study 5). Thus, avoidant individuals' reluctance to trust or become too close to others may result in hidden costs to the self-concept.

The I3 Model: a metatheoretical framework for understanding aggression.

The I3 Model is a general-purpose metatheory. It posits that three orthogonal processes influence the likelihood and intensity of a given behavior, including aggressive behavior. Instigation encompasses immediate environmental stimuli (e.g., provocation) that normatively afford an aggressive response. Impellance encompasses situational or dispositional qualities (e.g., trait aggressiveness) that influence how strongly the instigator produces a proclivity to enact that response. Inhibition encompasses situational or dispositional qualities (e.g., alcohol intoxication) that influence how strongly the proclivity is overridden rather than manifesting in aggressive behavior. Extant evidence supports Perfect Storm Theory-a theoretical perspective derived from the I3 Model-which posits that aggression is especially likely, and especially intense, to the extent that instigation and impellance are strong and inhibition is weak.

"You've Changed": Low Self-Concept Clarity Predicts Lack of Support for Partner Change.

People often pursue self-change, and having a romantic partner who supports these changes increases relationship satisfaction. However, most existing research focuses only on the experience of the person who is changing. What predicts whether people support their partner's change? People with low self-concept clarity resist self-change, so we hypothesized that they would be unsupportive of their partner's changes. People with low self-concept clarity did not support their partner's change (Study 1a), because they thought they would have to change, too (Study 1b). Low self-concept clarity predicted failing to support a partner's change, but not vice versa (Studies 2 and 3), and only for larger changes (Study 3). Not supporting a partner's change predicted decreases in relationship quality for both members of the couple (Studies 2 and 3). This research underscores the role of partners in self-change, suggesting that failing to support a partner's change may stem from self-concept confusion.

Is Romantic Desire Predictable? Machine Learning Applied to Initial Romantic Attraction.

Matchmaking companies and theoretical perspectives on close relationships suggest that initial attraction is, to some extent, a product of two people's self-reported traits and preferences. We used machine learning to test how well such measures predict people's overall tendencies to romantically desire other people (actor variance) and to be desired by other people (partner variance), as well as people's desire for specific partners above and beyond actor and partner variance (relationship variance). In two speed-dating studies, romantically unattached individuals completed more than 100 self-report measures about traits and preferences that past researchers have identified as being relevant to mate selection. Each participant met each opposite-sex participant attending a speed-dating event for a 4-min speed date. Random forests models predicted 4% to 18% of actor variance and 7% to 27% of partner variance; crucially, however, they were unable to predict relationship variance using any combination of traits and preferences reported before the dates. These results suggest that compatibility elements of human mating are challenging to predict before two people meet.