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In this article, a data-driven approach was adopted to demonstrate how real-life diary techniques [ie, the experience sampling method (ESM)] could be deployed for assessment purposes in patients with psychotic disorder, delivering individualized and clinically relevant information. The dataset included patients in an acute phase of psychosis and the focus was on paranoia as one of the main psychotic symptoms (30 patients with high levels of paranoia and 34 with low levels of paranoia). Based on individual cases, it was demonstrated how (1) symptom and mood patterns, (2) patterns of social interactions or activities, (3) contextual risk profiles (eg, is being among strangers, as opposed to family, associated with higher paranoia severity?), and (4) temporal dynamics between mood states and paranoia (eg, does anxiety precipitate or follow the onset of increased paranoia severity?) substantially differ within individual patients and across the high vs low paranoid patient group. Most striking, it was shown that individual findings are different from what is found on overall group levels. Some people stay anxious after a paranoid thought came to mind. For others, paranoia is followed by a state of relaxation. It is discussed how ESM, surfacing the patient's implicit knowledge about symptom patterns, may provide an excellent starting point for person-tailored psychoeducation and for choosing the most applicable therapeutic intervention.

Mobile Assessment in Schizophrenia: A Data-Driven Momentary Approach