Capturing Individual Sleep, Mood, and Psychotic Symptom Dynamics over Time: A Case Illustration of Novel Ideographic Modeling and Visualization Strategies - Abstract
Emerging psychotic disorders are complex mental health conditions with widely heterogeneous clinical presentations. Advances in ideographic analyses may facilitate understanding of this complexity and inform personalized medicine approaches to psychosis treatment. Ideographic analysis included a case example from an experience sampling method (ESM) study of affect and psychosis in 35 individuals aged 15-25 diagnosed as at clinical high risk for psychosis (CHR) or with recent-onset psychosis (early psychosis, EP). Participants received 6 prompts per day within an individualized 12-hour window for 21 days using a smartphone application. They rated experiences of positive affect, negative affect, and psychotic symptoms and recorded daily sleep onset and offset times. The case example was one of a subset (n=9) of participants who provided an additional 21-days of ESM data either 6 or 12-months after initial participation. Line graphs and ribbon plots provide visualizations of the case example’s moment- and day-level symptom data, respectively. Symptom networks were
estimated using group iterative multiple model estimation (GIMME). Line graphs illustrate momentary affective and psychotic symptoms over two data collection periods of three-weeks separated by 6 or 12 months. Ribbon plots depict covariation of day-level symptom data, including sleep data. Symptom network plots depict uni- and bi-directional connections between day-level symptom data and sleep variables. Ideographic modeling and visualization of symptoms over different temporal periods offer unique perspectives for understanding changing symptom patterns and relations in emerging psychotic disorders. Ideographic analyses have the potential to enhance individualized, hypothesis-driven assessment and selection of treatment priorities.