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.
This study examined the long-term consequences of idealization in marriage, using both daily diary and questionnaire data collected from a sample of 168 newlywed couples who participated in a 4-wave, 13-year longitudinal study of marriage. Idealization was operationalized as the tendency for people to perceive their partner as more agreeable than would be expected based on their reports of their partner's agreeable and disagreeable behaviors. Spouses who idealized one another were more in love with each other as newlyweds. Longitudinal analyses suggested that spouses were less likely to suffer declines in love when they idealized one another as newlyweds. Newlywed levels of idealization did not predict divorce.
The purpose of this research was to understand in greater detail, using 2 samples (Study 1 N = 4,881 heterosexual couples; Study 2 N = 335 heterosexual couples who completed the Relationship Evaluation Questionnaire), how partner or self-enhancement patterns differentially influence relationship outcomes. A multivariate analysis of covariance was conducted comparing 4 outcome measures for different couple types in which individuals rated the partner higher, the same, or lower than they rated themselves on affability. Couples in which both individuals perceived themselves as more affable than the partner experienced poorer results on the relationship outcome measures, whereas couples in which both individuals perceived the partner's personality as more affable than their own experienced more positive relationship outcomes. Additional analyses with structural equation models demonstrated the consistent influence of enhancement measures on relationship outcomes for cross-sectional and longitudinal samples.Scholars have been studying the influence of different patterns in self-and partner ratings on relationship outcomes for a few decades
This article summarizes research that challenges conventional wisdom about the early roots of marital distress and divorce. We abstract results from a 13-year study that focused on the extent to which long-term marital satisfaction and stability could be forecast from newlywed and early marital data. We explore the usefulness of three models-emergent distress, enduring dynamics, and disillusionment-designed to explain why some marriages thrive and others fail. The dominant paradigm, the emergent-distress model, sees newlyweds as homogeneously blissful and posits that distress develops as disagreements and negativity escalate, ultimately leading some couples to divorce. The results we summarize run counter to this model and suggest instead that (a) newlyweds differ considerably in the intensity of both their romance and the negativity of their behavior toward one another and, for those who remain married, these early dynamics persist over time; and (b) for couples who divorce, romance seems to deteriorate differently depending on how long the marriage lasts. Soon after their wedding, "early exiters" seem to lose hope of improving an unpromising relationship; "delayed-action divorcers" begin marriage on a particularly high note, yet quickly show signs of disillusionment. These delayed-action
We review the literature on partner idealization (also known as positive illusions) in the field of close relationships. Our review assesses the soundness of idealization research from conceptual, theoretical, methodological, and evidentiary perspectives. In addition, we explore the potential linkage of idealization to the newer and seemingly related construct of disillusionment. Given the apparent role of disillusionment in relationship dissolution, explication of the role of idealization in disillusionment would benefit the field. To this end, we present an initial model of mechanisms that may govern relations between idealization and disillusionment to guide future research.
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