The Dynamic Identity Fusion Index: A New Continuous Measure of Identity Fusion for Web-Based Questionnaires

摘要

We introduce a computer-based measure of identity fusion, a form of group alignment characterized by a visceral feeling of oneness with a group. Past measures of identity fusion (a single pictorial item and a 7-item verbal scale) have demonstrated a unique capacity to predict willingness to engage in extreme pro-group behaviors (e.g., fighting and dying for one's group). The Dynamic Identity Fusion Index (DIFI) combines the simplicity of the single pictorial item with the higher fidelity afforded by a continuous scale. The DIFI runs on a script written in JavaScript and works on both traditional computers and modern touch-pad devices. It allows for simultaneous assessment of self-group distance and overlap, two conceptually distinct components of group alignment. Study 1 assessed the criterion validity of the two components of the DIFI and discovered that the overlap metric was a better indicator of identity fusion than the distance metric. Four more studies demonstrated DIFI's temporal stability (Study 2), convergent and discriminant validity (Study 3), and predictive validity, specifically endorsement of pro-group behaviors (Study 4). We discuss implications of the DIFI for future research on identity fusion and recommend when it should be used.