(PS2-D88) Psychometric Validation of an Everyday Exercise Satisfaction Scale

Previous research with the Intimate Partner Anger Scale (IPAS) found that it predicts marital dissatisfaction and aggression between partners significantly better than a general measure of anger. This scale has two factors representing anger-in and anger-out. The present study extends the scale's validity to predicting cyber aggression within romantic partners. Further, this study tested the incremental validity of the IPAS in predicting cyber aggression over and above the predictions by a measure of general dysfunctional anger (e.g., Anger Disorders Scale – Short Form (ADS-SF). The ADS-SF includes items representing provocations, affect arousal, cognitions, motives, and angry behaviors. Presently it is more common for people to express their anger digitally, and we have no estimates of the relationship between anger at one’s romantic partner and the extent and type of cyber aggression. This study administered the IPAS and the Cyber Psychological Abuse Scale (CPAS) to more than 600 subjects online through social media outlets. The RPAS includes 20 items, ten that load on the anger in a factor and ten on the anger-out factor. It has excellent support for the factor structure, internal consistency, and validity. The CPAS is a 9-item scale that yields a total score and two subscales, minor cyber abuse and severe cyber abuse. Participants take the scale twice, once regarding their role as a perpetrator and once regarding their role as a victim of cyber aggression yielding 18 items total. Using hierarchical regression, we regressed the total scores of the IPAS onto the CPAS to see the total amount of cyber-aggression in the relationship. Age and gender were initially added as predictors to the model, followed by the Dyadic Adjustment Scale (DAS) and ADS-SF. The DAS and ADS-SF were added to assess the degree to which relationship satisfaction and more general dysfunctional anger predict more cyber aggression in romantic partnerships.

The regression revealed that the predictors, age, gender, and DAS contributed significantly to the regression model F(1,339) = 16.828, p < .001). Finally, introducing ADS-SF, the regression model explained an additional 16.2% of the variation in total IPAS, and this change in R² square was also significant, F(1,338) = 69.374, p < .001. These results support our hypothesis that the RPAS has incremental validity as it predicts cyber aggression better than general satisfaction with the relationship and general dysfunctional anger. Further, when we control for DAS and ADS-SF on the relationship between IPAS and CPAS, we find the following partial correlations (r= -.057, p < .02; r = .415, p < .001). This demonstrates that the IPAS has a significant unique variance in predicting cyberaggression over and above the shared variance of Relationship satisfaction and general dysfunctional anger.