This work complements existing research regarding the forgiveness process by highlighting the role of commitment in motivating forgiveness. On the basis of an interdependence-theoretic analysis, the authors suggest that (a) victims' self-oriented reactions to betrayal are antithetical to forgiveness, favoring impulses such as grudge and vengeance, and (b) forgiveness rests on prorelationship motivation, one cause of which is strong commitment. A priming experiment, a cross-sectional survey study, and an interaction record study revealed evidence of associations (or causal effects) of commitment with forgiveness. The commitment-forgiveness association appearred to rest on intent to persist rather than long-term orientation or psychological attachment. In addition, the commitment-forgiveness association was mediated by cognitive interpretations of betrayal incidents; evidence for mediation by emotional reactions was inconsistent.

Five studies established that normal narcissism is correlated with good psychological health. Specifically, narcissism is (a) inversely related to daily sadness and dispositional depression, (b) inversely related to daily and dispositional loneliness, (c) positively related to daily and dispositional subjective well-being as well as couple well-being, (d) inversely related to daily anxiety, and (e) inversely related to dispositional neuroticism. More important, self-esteem fully accounted for the relation between narcissism and psychological health. Thus, narcissism is beneficial for psychological health only insofar as it is associated with high self-esteem. Explanations of the main and mediational findings in terms of response or social desirability biases (e.g., defensiveness, repression, impression management) were ruled out. Supplementary analysis showed that the links among narcissism, self-esteem, and psychological health were preponderantly linear.

We propose the Attachment Security Enhancement Model (ASEM) to suggest how romantic relationships can promote chronic attachment security. One part of the ASEM examines partner responses that protect relationships from the erosive effects of immediate insecurity, but such responses may not necessarily address underlying insecurities in a person’s mental models. Therefore, a second part of the ASEM examines relationship situations that foster more secure mental models. Both parts may work in tandem. We posit that attachment anxiety should decline most in situations that foster greater personal confidence and more secure mental models of the self. In contrast, attachment avoidance should decline most in situations that involve positive dependence and foster more secure models of close others. The ASEM integrates research and theory, suggests novel directions for future research, and has practical implications, all of which center on the idea that adult attachment orientations are an emergent property of close relationships.

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 investigated the fluctuations of autonomic nervous activities during the menstrual cycle. Twenty college females were tested for cardiovascular reactivity to mental challenge during both follicular and luteal phases across two menstrual cycles. Power spectral analysis of heart rate variability (HRV) was used to examine the autonomic nervous activities. At baseline, although heart rate and blood pressure did not differ across the menstrual cycle, the low-frequency (LF) component in the HRV was higher and the high-frequency (HF) component in the HRV was lower during the luteal phase than during the follicular phase. The LF/HF ratio was also significantly greater in the luteal phase. These data suggest that sympathetic nervous activities are predominant in the luteal phase as compared with follicular phase. In addition, the power spectral analysis of HRV has more sensitivity than heart rate or blood pressure in assessing the slight fluctuations of autonomic nervous activities during the menstrual cycle.