What fuels passion? An integrative review of competing theories of romantic passion

In an integrative review, we examine four theories and models of romantic passion to determine what causes feelings of romantic passion. Although a growing consensus has emerged for the definition of romantic passion, we suggest that this is largely not the case for the source of romantic passion. We outline how four different perspectives—Limerence Theory, the Rate of Change in Intimacy Model, the Self-Expansion Model, and the Triangular Theory of Love—propose four different potential sources of romantic passion and review empirical support in favor and against each. For each of these perspectives, we additionally outline the predicted trajectory of passion that follows from each theorized source of passion, as well as each perspective's view on the ability for passion to be controlled and up-regulated. In identifying ways in which these theories and models offer conflicting predictions about the source of romantic passion, this review points to ways in which a more comprehensive model may be developed that integrates across these four perspectives

Creativity and romantic passion.

Romantic passion typically declines over time, but a downward trajectory is not inevitable. Across three studies (one of which encompassed two sub-studies), 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 nine 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)

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. </jats:p

“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. </jats:p

Predicting Romantic Interest during Early Relationship Development: A Preregistered Investigation using Machine Learning

There are massive literatures on initial romantic attraction and established, “official” relationships. But there is a gap in our knowledge about early relationship development: the interstitial stretch of time in which people experience rising and falling romantic interest for partners who have the potential to—but often do not—become sexual or dating partners. In the current study, 208 single participants reported on 1,065 potential romantic partners across 7,179 data points over seven months. In stage 1 of the analyses, we used machine learning (specifically, Random Forests) to extract estimates of the extent to which different classes of predictors (e.g., individual differences vs. target-specific constructs) accounted for participants’ romantic interest in these potential partners (12% vs. 36%, respectively). Also, the machine learning analyses offered little support for perceiver × target moderation accounts of compatibility: the meta-theoretical perspective that some types of perceivers are likely to experience greater romantic interest for some types of targets. In stage 2, we used traditional multilevel-modeling approaches to depict growth-curve analyses for each predictor retained by the machine learning models; robust (positive) main effects emerged for many variables, including sociosexuality, gender, the potential partner’s positive attributes (e.g., attractive, exciting), attachment features (e.g., proximity seeking, separation distress), and perceived interest. We also directly tested (and found no support for) ideal partner preference-matching effects on romantic interest, which is one popular perceiver × target moderation account of compatibility. We close by discussing the need for new models and perspectives to explain how people assess romantic compatibility