How Do Invested Partners Become Invested? A Prospective Investigation of Fledgling Relationship Development

Investment-the feeling that one has put considerable resources into a relationship-is theorized to play a key role in relationship persistence. Yet, the development of investment is not well-understood. We recruited 256 individuals in new dating relationships and surveyed them each week for up to 25 weeks. This design allows us to test underlying theoretical assumptions about how people become invested in new dating partners. Some assumptions, such as the idea that investment increases over time, were confirmed. Other assumptions were not supported: Feelings of investment were quite high after only a few weeks of dating and were not strongly shaped by concrete relationship milestones. Rather, feelings of investment were strongly linked to other subjective indicators of relationship development, such as feeling attached to the partner and believing that the relationship had a good future. We discuss the implications of these findings for existing models of investment.

We're Not That Choosy: Emerging Evidence of a Progression Bias in Romantic Relationships

Dating is widely thought of as a test phase for romantic relationships, during which new romantic partners carefully evaluate each other for long-term fit. However, this cultural narrative assumes that people are well equipped to reject poorly suited partners. In this article, we argue that humans are biased toward pro-relationship decisions-decisions that favor the initiation, advancement, and maintenance of romantic relationships. We first review evidence for a progression bias in the context of relationship initiation, investment, and breakup decisions. We next consider possible theoretical underpinnings-both evolutionary and cultural-that may explain why getting into a relationship is often easier than getting out of one, and why being in a less desirable relationship is often preferred over being in no relationship at all. We discuss potential boundary conditions that the phenomenon may have, as well as its implications for existing theoretical models of mate selection and relationship development.

Psychological Science in the Wake of COVID-19: Social, Methodological, and Metascientific Considerations

The COVID-19 pandemic has extensively changed the state of psychological science from what research questions psychologists can ask to which methodologies psychologists can use to investigate them. In this article, we offer a perspective on how to optimize new research in the pandemic's wake. Because this pandemic is inherently a social phenomenon-an event that hinges on human-to-human contact-we focus on socially relevant subfields of psychology. We highlight specific psychological phenomena that have likely shifted as a result of the pandemic and discuss theoretical, methodological, and practical considerations of conducting research on these phenomena. After this discussion, we evaluate metascientific issues that have been amplified by the pandemic. We aim to demonstrate how theoretically grounded views on the COVID-19 pandemic can help make psychological science stronger-not weaker-in its wake.

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.