Work

Decisions About Expressing Subjective States Generalise Across Psychological Domain

Year: 2026
Type: preprint
Abstract: People routinely make decisions about how to express their internal psychological states to theoutside world. These communication choices can systematically influence the meaning observersextract about the internal states of others. In psychological science, this is frequently observed inthe way people respond to self-report surveys. Quantitative cognitive models of thesecommunication choices, such as the Latent State and Response Style (LASARS) model, translatecontinuous psychological states into Likert-type responses. In doing so, the model can separateinternal experiences (latent states) from preferences for (or against) certain response options inself-report scenarios. A key assumption of the LASARS model is that response style reflects astable individual characteristic that generalises across contexts. The present study tested thisassumption by examining whether response styles remain consistent across theoretically distinctpsychological domains. A sample of 145 adults completed four survey instruments assessingsensation seeking, thinking styles, dark personality traits, and perceived control. We compared amodel in which response style parameters were estimated separately for each instrument with amore parsimonious model in which response style was assumed to be identical across allinstruments. Response style parameters exhibited strong cross-instrument correlations, exceedingthe magnitude of correlations observed among latent states. Furthermore, constraining responsestyle to be shared across instruments produced virtually identical predictions of observed scoresand latent state estimates while reducing model complexity substantially. These findings providestrong evidence that response style is a stable, domain-general characteristic. They also supportthe conclusion that people use similar decision strategies to express their internal psychologicalstates across the different constructs they may wish or be asked to communicate.
Language: English
Open Access status: green
OpenAlex ID: W7225647538
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