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The call for personalized approaches in psychopathology is growing, as group-level analyses fail to capture the person-specific patterns. This study used an idiographic network approach to model the daily dynamics of loneliness, paranoia, affect, and social motivation in seven individuals with psychosis. We applied Group Iterative Multiple Model Estimation (GIMME) to intensive longitudinal data collected using the Experience sampling method. Results revealed substantial inter-individual heterogeneity, particularly in social motivation pathways and the role of paranoia in affective changes. Specifically, the relationship between social avoidance and approach was positive for one participant and negative for another. Furthermore, a unique temporal effect of paranoia predicting subsequent negative affect was identified in one case. These findings highlight the critical relevance of idiographic methods for moving beyond generalized models and identifying precise, actionable targets for developing tailored interventions in psychosis.
Januška et al. (Wed,) studied this question.