Associations between language style matching and relationship commitment and satisfaction: An integrative data analysis. (August 2020) - Bierstetel, Sabrina J.; Farrell, Allison K.; Briskin, Julia L.; Harvey, Michael W.; Gable, Shelly L.; Ha, Thao; Ickes, William; Lin, Wei-Fang; Orina, Minda M.; Saxbe, Darby; Simpson, Jeffry A.; Ta, Vivian P.; et al.
Language style matching (LSM) refers to similarity in function word use between two people during a conversation. Previous research has shown that LSM predicts romantic relationship stability, but it remains unknown why LSM is associated with stability. Across five studies from five different labs, we aimed to identify links between LSM and two relationship perceptions strongly associated with stability: commitment and satisfaction. Based on prior work, we hypothesized that LSM would be associated with commitment but not satisfaction. This hypothesis was supported in Study 1 ( N = 82) but was not supported in Study 2 ( N = 158). Preregistered analyses of three additional data sets ( N = 198, 190, 138) were then conducted to attempt to replicate the effect between commitment and LSM. The predicted associations between LSM and commitment/satisfaction, measured concurrently and longitudinally, were not observed in Studies 3–5. Moreover, a meta-analysis across all 766 individuals ( N = 383 couples) revealed that although the association between LSM and satisfaction was marginal ( M r = .10, Z = 1.92, p = .05, confidence interval (CI) = −.002, .203), there was no link between LSM and commitment ( M r = .05, Z = 0.97, p = .33, CI = −.052, .154). Across conflict discussions (i.e., in Studies 1 and 3–5), there were no associations between conflict LSM and satisfaction ( M r = .09, Z = 1.49, p = .14, CI = −.028, .203) or commitment ( M r = .03, Z = 0.50, p = .62, CI = −.087, .145). These findings suggest that if true associations between LSM and commitment and satisfaction exist, they are very small effects. They also emphasize the importance of replicating one's own findings and illustrate a fruitful approach to replicating findings from high-investment studies through collaborating with researchers with similar data sets to increase statistical power and, in turn, reproducibility.