Everyday Emotions: Naturalistic Observation Of Specific Positive Emotions In Daily Family Life

With technological advances rapidly expanding our ability to collect continuous streams of passive recordings, new techniques for processing and analyzing data of this type are needed. This article presents a feasible, reliable, and valid language-based methodology for scanning large quantities of naturalistic recordings to study specific positive emotions in families. Detailing a keyword approach to identifying and coding verbal expressions of compassion, gratitude, pride, and amusement in video transcripts, this study demonstrates one way of locating phenomena, such as emotion, that arise across many different situations in family life. Transcripts of over 350 hr of video recordings obtained from 32 families interacting in their homes and communities were coded to describe the rates per hour at which mothers, fathers, and school-age children verbally expressed 4 positive emotions. Parents expressed compassion, gratitude, and pride more often than children did, but they expressed amusement at similar rates. Gender comparisons revealed that mothers expressed compassion and gratitude more frequently than fathers, and girls expressed these emotions more often than boys. The specific emotion approach allowed us to probe the association between parental and child-expressed positivity: Mothers' expressions of compassion were the most powerful predictor, explaining over half the variance in children's expressions of positive emotion. This study describes a promising approach to analyzing large volumes of passive data; the results show how families differ with respect to the landscape of 4 specific positive emotions and suggest how and why these emotions should be differentiated in studies of daily family life.