Axel Mayer

States are increasingly important in personality theory and research. Yet, the assessment of personality states usually relies on ad hoc measures whose development and evaluation are largely separated from theoretical considerations. To enable theory-guided development and evaluation of personality state measures, we introduce a framework based on the revised latent state-trait (LST-R) theory. The theory defines latent states as the expectation of an observed measure given a person in a specific situation, which can be decomposed into latent traits and latent situation-specific state residuals. Consequently, items and scales can be evaluated for their reliability due to latent traits (consistency) and situation-specific influences (specificity). We propose that specificity, in particular, is an appealing property for instruments designed to assess personality states. We illustrate this framework with experience sampling data on personality states. Our framework has implications for both the conceptualisation and the assessment of personality states. On the theoretical side, we provide a formal definition of personality states, which enables integration between trait-, process-, and development-focused theories. On the practical side, we show how using LST-R models allows researchers to develop and evaluate state measures on their own terms rather than applying criteria for trait measures to assess the qualities of state measures.