Measuring Emotional Contagion: An Examination of the Responsive Distress Scale

Contact Information: Shane Westfall, PhD student, c/o Department of Psychology, University of Nevada, Las Vegas. Email: [email protected] Abstract This study examined the psychometric qualities of the Responsive Distress Scale, a measure of emotional contagion experienced by individuals. Participants (n = 149) completed the Responsive Distress Scale, in addition to several other measures. We then analyzed the psychometric qualities of internal consistency, convergent validity, individual item analyses, and conducted both exploratory and confirmatory factor analysis. Convergent validity was high and internal consistency was acceptable. After conducting item analyses it became apparent that three items were problematic for the scale. Through factor analyses, we extracted two factors and identified these two factors as Negative Emotional Responsiveness and Event Responsiveness. We determined that the measure taps into two distinct constructs, rather than one. Future research might profitably divide this scale into two distinct subscales or focus entirely upon items that explicitly mention responses to other people’s distress. Introduction A fascinating aspect of human interaction is the capacity to influence the subjective experiences of others. Behaviors, attitudes and emotions are all subject to changes from the surrounding social environment. One key aspect of this phenomenon is responsive distress. Responsive distress is defined as “the tendency to feel negative emotions when in the presence of others who are feeling negative emotions” (Barchard, 2001, p. 15). Responsive distress can be measured utilizing the Responsive Distress Scale (Barchard, 2001). The current study aims to examine the Responsive Distress Scale (RDS), specifically to (1) examine its internal consistency, (2) examine its validity, (3) conduct an item analysis in order to determine how the internal consistency and validity of this measure could be improved and (4) conduct an item-level factor analysis.