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While evidence shows that people with early psychosis are flexible in using different emotion regulation (ER) strategies to manage the varying contextual demands, no studies have examined the effectiveness of such regulatory flexibility in this population. We addressed this issue by investigating whether and how ER flexibility relate to different dynamic aspects (variability, instability, inertia, and recovery) of negative affect (NA) in a combined early psychosis sample, consisting of both individuals at high clinical risk for psychosis and those diagnosed with first-episode psychosis.
Methods
Participants were 148 individuals from the INTERACT project, a multi-center randomized controlled trial on the efficacy of acceptance and commitment therapy in early psychosis. We utilized data from the baseline assessment, during which all participants completed six days of experience sampling assessment of momentary NA, as well as end-of-day assessments of ER strategy use.
Results
Multilevel models of within-person associations showed that greater ER flexibility was associated with more stable NA, and quicker recovery of NA from stressors during the day. Linear regression analyses of between-person associations showed that people who had more variable and unstable NA reported greater ER flexibility generally. No evidence was found for associations with NA inertia.
Conclusions
The current study identified unique within-person and between-person links between ER flexibility and dynamics of NA in early psychosis. These findings further provide evidence for ER flexibility in early psychosis, emphasizing the adaptive nature of regulatory flexibility in relation to reduced instability in NA and faster recovery from NA in everyday life.
The behaviors, thoughts, and feelings related to psychopathology are often not of a static nature, but rather change and fluctuate over time in response to changes in daily life situations. Therefore, clinical psychology research can benefit from focusing on how psychopathological features behave over time, as this can provide new perspectives and insights concerning the phenomenology and mechanisms underlying psychopathology. The collection of intensive longitudinal data, consisting of many repeated measurements from single participants, allows for the investigation of several dynamic properties of single or multiple symptoms (and their interrelations). This chapter presents an overview of some major dynamic properties that can be studied with intensive longitudinal data. First, it focuses on several univariate approaches, allowing the examination of one single feature over time. Then it discusses some methods and models to further examine the dynamic relationships between two or more symptoms. For each approach, information is provided on how to calculate simple indices on a more descriptive level, as well as how to model the dynamic features using more complex models.
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