Clarifying the Measurement of a Self-Structural Process Variable: The Case of Self-Complexity

Despite the importance of self-structural variables to understand self-processes, research in this area has been hampered by measurement problems. The current study seeks to clarify this situation by examining the interrelationships among six self-structural measures of trait-sorting data of 252 Chinese college students: the H statistic of self-complexity, the hierarchical attribute class number, the number of self-aspects, the overlap among self-aspects in terms of traits describing them, the average inter-aspect correlation, and the self-concept compartmentalization Phi. It was found that H was highly correlated with the hierarchical attribute class number, and overlap was highly correlated with the average inter-aspect correlation. Both H and the hierarchical attribute class number were highly correlated with the number of self-aspects; although both the former measures were positively correlated with overlap and the average inter-aspect correlation in general, the relationships were like an inverted U curve. Self-concept compartmentalization was negatively correlated with both overlap and the average inter-aspect correlation. Four main implications of these findings lead to recommendations being made for future studies of self-structural variables, such as self-complexity, self-concept fragmentation, and self-concept compartmentalization and their relationship to well-being.