Smart-Dating in Speed-Dating: How a Simple Search Model Can Explain Matching Decisions

How do people in a romantic matching situation choose a potential partner? We study this question in a new model of matching under search frictions, which we estimate using data from an existing speed dating experiment. We find that attraction is mostly in the eye of the beholder and that the attraction between two potential partners has a tendency to be mutual. These results are supported by a direct measure of subjective attraction. We also simulate the estimated model, and it predicts rejection patterns, matching rates, and sorting outcomes that fit the data very well. Our results are consistent with the hypothesis that people in a dating environment act strategically and have at least an implicit understanding of the nature of the frictions and of the strategic equilibrium

Trust and biased memory of transgressions in romantic relationships.

Relative to people with low trust in their romantic partner, people with high trust tend to expect that their partner will act in accordance with their interests. Consequently, we suggest, they have the luxury of remembering the past in a way that prioritizes relationship dependence over self-protection. In particular, they tend to exhibit relationship-promoting memory biases regarding transgressions the partner had enacted in the past. In contrast, at the other end of the spectrum, people with low trust in their partner tend to be uncertain about whether their partner will act in accordance with their interests. Consequently, we suggest, they feel compelled to remember the past in a way that prioritizes self-protection over relationship dependence. In particular, they tend to exhibit self-protective memory biases regarding transgressions the partner had enacted in the past. Four longitudinal studies of participants involved in established dating relationships or fledgling romantic relationships demonstrated that the greater a person's trust in their partner, the more positively they tend to remember the number, severity, and consequentiality of their partner's past transgressions—controlling for their initial reports. Such trust-inspired memory bias was partner-specific; it was more reliably evident for recall of the partner's transgressions and forgiveness than for recall of one's own transgressions and forgiveness. Furthermore, neither trust-inspired memory bias nor its partner-specific nature was attributable to potential confounds such as relationship commitment, relationship satisfaction, self-esteem, or attachment orientations. (PsycINFO Database Record (c) 2016 APA, all rights reserved

Personality and social relationships: What do we know and where do we go

Personality and social relationships influence each other in multiple and consequential ways. To understand how people differ from each other in their personality and social behavior, how these differences develop, and how this affects further life outcomes, we need to better understand the interplay of personality and social relationships. Here, we provide an integrative overview on personality-relationship research across relationship types (everyday encounters, friendships, romantic, and family relationships), and personality characteristics. We summarize the state of research on (a) how much relationship aspects vary across actors, partners, and actor-partner relations, (b) which personality characteristics predict these variance components (i.e. actor, partner, and relationship effects), and (c) how social relationships work as contexts for personality development. Following an integrative process framework, key open questions are discussed concerning the processes that underlie personality-relationship and relationship-personality effects. We conclude with a call for conceptual integration, methodological expansion, and collaborative action.Personality and relationships influence each other in manifold ways; they cannot be understood in isolation. This paper summarizes the state of the art, provides a common framework for the future of science of personality and social relationships. Emotional Stability, Communion, and Self-Control relate to getting along. Agency and Sociability predict getting ahead. Relationship variance is the largest but least understood variance component. Evidence for effects of relationships on personality development is mixed. More comprehensive and integrative research on underlying processes needed

Explaining illness with evil::Pathogen prevalence fosters moral vitalism

Pathogens represent a significant threat to human health leading to the emergence of strategies designed to help manage their negative impact. We examined how spiritual beliefs developed to explain and predict the devastating effects of pathogens and spread of infectious disease. Analysis of existing data in studies 1 and 2 suggests that moral vitalism (beliefs about spiritual forces of evil) is higher in geographical regions characterized by historical higher levels of pathogens. Furthermore, drawing on a sample of 3140 participants from 28 countries in study 3, we found that historical higher levels of pathogens were associated with stronger endorsement of moral vitalistic beliefs. Furthermore, endorsement of moral vitalistic beliefs statistically mediated the previously reported relationship between pathogen prevalence and conservative ideologies, suggesting these beliefs reinforce behavioural strategies which function to prevent infection. We conclude that moral vitalism may be adaptive: by emphasizing concerns over contagion, it provided an explanatory model that enabled human groups to reduce rates of contagious disease.</p

Measurement invariance of the moral vitalism scale across 28 cultural groups

Moral vitalism refers to a tendency to view good and evil as actual forces that can influence people and events. The Moral Vitalism Scale had been designed to assess moral vitalism in a brief survey form. Previous studies established the reliability and validity of the scale in US-American and Australian samples. In this study, the cross-cultural comparability of the scale was tested across 28 different cultural groups worldwide through measurement invariance tests. A series of exact invariance tests marginally supported partial metric invariance, however, an approximate invariance approach provided evidence of partial scalar invariance for a 5-item measure. The established level of measurement invariance allows for comparisons of latent means across cultures. We conclude that the brief measure of moral vitalism is invariant across 28 cultures and can be used to estimate levels of moral vitalism with the same precision across very different cultural settings.Peer reviewe

Explaining illness with evil: pathogen prevalence fosters moral vitalism

Pathogens represent a significant threat to human health leading to the emergence of strategies designed to help manage their negative impact. We examined how spiritual beliefs developed to explain and predict the devastating effects of pathogens and spread of infectious disease. Analysis of existing data in studies 1 and 2 suggests that moral vitalism (beliefs about spiritual forces of evil) is higher in geographical regions characterized by historical higher levels of pathogens. Furthermore, drawing on a sample of 3140 participants from 28 countries in study 3, we found that historical higher levels of pathogens were associated with stronger endorsement of moral vitalis- tic beliefs. Furthermore, endorsement of moral vitalistic beliefs statistically mediated the previously reported relationship between pathogen prevalence and conser- vative ideologies, suggesting these beliefs reinforce behavioural strategies which function to prevent infection. We conclude that moral vitalism may be adaptive: by emphasizing concerns over contagion, it provided an explanatory model that enabled human groups to reduce rates of contagious disease

A Worldwide Test of the Predictive Validity of Ideal Partner Preference-Matching

©American Psychological Association, [2024]. This paper is not the copy of record and may not exactly replicate the authoritative document published in the APA journal. The final article is available, upon publication, at: [ARTICLE DOI]”Ideal partner preferences (i.e., ratings of the desirability of attributes like attractiveness or intelligence) are the source of numerous foundational findings in the interdisciplinary literature on human mating. Recently, research on the predictive validity of ideal partner preference-matching (i.e., do people positively evaluate partners who match versus mismatch their ideals?) has become mired in several problems. First, articles exhibit discrepant analytic and reporting practices. Second, different findings emerge across laboratories worldwide, perhaps because they sample different relationship contexts and/or populations. This registered report—partnered with the Psychological Science Accelerator—uses a highly powered design (N=10,358) across 43 countries and 22 languages to estimate preference-matching effect sizes. The most rigorous tests revealed significant preference-matching effects in the whole sample and for partnered and single participants separately. The “corrected pattern metric” that collapses across 35 traits revealed a zero-order effect of β=.19 and an effect of β=.11 when included alongside a normative preference-matching metric. Specific traits in the “level metric” (interaction) tests revealed very small (average β=.04) effects. Effect sizes were similar for partnered participants who reported ideals before entering a relationship, and there was no consistent evidence that individual differences moderated any effects. Comparisons between stated and revealed preferences shed light on gender differences and similarities: For attractiveness, men’s and (especially) women’s stated preferences underestimated revealed preferences (i.e., they thought attractiveness was less important than it actually was). For earning potential, men’s stated preferences underestimated—and women’s stated preferences overestimated—revealed preferences. Implications for the literature on human mating are discussed.Unfunde

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