The Functional Self-Discrimination Measure (FSDM) is a method of coding a speaker's verbal discrimination of their own behavior based on Relational Frame Theory (RFT) that predicts wellbeing 6 and 12 months later (Atkins & Styles, 2016). In this study, we replicated our original findings with a new sample, and expanded the coding scheme to include verbal discriminations of the ‘other’. In addition to Value Oriented Self-Rules and Self-as-Context, we show Other-as-Context also predicts long-term wellbeing. Further, we show that the ratio of coded to total utterances predicts psychological wellbeing. This approach provides researchers and clinicians with an additional tool for understanding and measuring the ways people discriminate their own and others behavior in natural language that is a reliable determinant of wellbeing over extended periods.