Singlehood, defined as not being in a romantic relationship, is becoming increasingly common worldwide. Despite this, research on singlehood has not received remotely equivalent research attention as romantic relationships. Well-being research that has explicitly included singles has focused on whether coupled versus single people are more satisfied with their lives. However, these between-group comparisons have not attended to within-group variability among singles that can point to when and for whom singlehood is associated with thriving. In this review, we document findings from the emerging field of singlehood studies to highlight what is and is not known about factors that are associated with the well-being of single individuals from a within-group perspective. Our review examines (a) intrapersonal factors (characteristics of the individual), (b) interpersonal experiences (qualities of ones social relationships and experiences), and (c) societal influences (features related to ones broader social or cultural context) related to well-being in singlehood. We conclude by offering future directions for the conceptualization of and research on singlehood with the goal of promoting a thorough and inclusive perspective.

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.