Finding meaning in us: The role of meaning in life in romantic relationships

Abstract

The present research tested a model of relationship functioning that incorporates meaning in life (MIL), proposing that MIL plays an important role in individuals’ motivations and perceived quality of romantic relationships. Study 1 employed a weekly diary methodology (N = 121 individuals in romantic relationships) and found that both within- and between-person relationship MIL are associated with internalized motivational states (i.e. intrinsic motivation, harmonious passion) and relationship quality (i.e. satisfaction, commitment). Study 2 was a dyadic study that examined both members of romantic couples (N = 238 dyads). Results found that both one’s own and one’s partner’s MIL predict motivation and relationship quality. Further, we also found evidence of a hierarchical model of MIL, such that relationship-specific experiences of MIL mediate associations between general MIL and relationship motivation and quality. Taken together, this research provides consistent and compelling evidence regarding the importance of MIL in romantic relationships.

Keywords:

• Meaning
• motivation
• relationships
• romantic partners
• self-determination

Notes

1. Although these models treat relationship quality and motivation as outcomes, according to the hierarchical model presented they can also be conceived of as predictors. They are treated as outcomes in these models largely for convenience. Additionally, theoretical and empirical work has established that other basic needs such as autonomy, competence, and relatedness (assessed in Study 1) are fundamental ingredients in relationship functioning and motivation. As such, we framed our analyses around these theoretical principles rather than the reverse.

2. Standardized coefficients in multilevel modeling are controversial due to the nested nature of the data and different sources of variance. Level 1 (within-person) predictors can only explain level 1 variance and level 2 (between-person) predictors can only explain level 2 variance. In the present analyses, level 1 and level 2 predictors were standardized for their respective levels. Outcomes were standardized across all observations, predictors were standardized across all observations at their respective levels. Thus, standardized coefficients reflect the amount of total variance explained.