Abstract
Theoretical views and a growing body of empirical evidence suggest that psychiatric relapses in schizophrenia-spectrum disorders (SSDs) have measurable warning signs. However, because they are time- and resource-intensive, existing assessment approaches are not well-suited to detect these warning signs in a timely, scalable fashion. Mobile technologies deploying frequent measurements—i.e., ecological momentary assessment—could be leveraged to detect increases in symptoms that may precede relapses. The present study examined EMA measurements with growth curve models in the 100 days preceding and following 27 relapses (among n = 20 individuals with SSDs) to identify (1) what symptoms changed in the periods gradually preceding, following, and right as relapses occur, (2) how large were these changes, and (3) on what time scale did they occur. Results demonstrated that, on average, participants reported elevations in negative mood (d = 0.34), anxiety (d =0.49), persecutory ideation (d =0.35), and hallucinations (d =0.34) on relapse days relative to their average during the study. These increases emerged gradually on average from significant and steady increases (d = 0.05 per week) in persecutory ideation and hallucinations over the 100-day period preceding relapse. This suggests that brief (i.e., 1–2 item) assessments of psychotic symptoms may detect meaningful signals that precede psychiatric relapses long before they occur. These assessments could increase opportunities for relapse prevention as remote measurement-based care management platforms develop.
Highlights
Relapses in schizophrenia-spectrum disorders (SSDs) are devastating
Results demonstrated that a brief mobile Ecological Momentary Assessment (EMA) system detected changes in self-reported mood and psychotic symptoms that occurred in the period preceding relapse, both gradually over time before the relapse and immediately as psychiatric relapses occur
A series of growth curve models suggested that there were elevations in negative mood (d = 0.34), anxiety (d = 0.49), persecutory ideation (d = 0.35), and hallucinations (d = 0.34) on relapse days relative to average, and steady increases in persecutory ideation and hallucinations were evident in the 100-day period preceding relapse
Summary
Relapses in schizophrenia-spectrum disorders (SSDs) are devastating. In addition to disrupting the lives of individuals experiencing them, each relapse event cumulatively increases the likelihood of subsequent relapses [1], dysfunction [2], poor treatment response [3, 4], and suicide [5]. Mobile devices can be used to deploy a series of brief, selfreport measures administered during patients’ day-to-day lives [i.e., ecological momentary assessment or EMA; [17]] using mobile technologies that many people with SSDs already have [18] These approaches have the potential to improve detection of relapse risk and to characterize changes that occur in the post-relapse period as well, and to establish trajectory models. Ben-Zeev and colleagues deployed a multi-modal mobile assessment system—CrossCheck—in a sample of individuals with schizophrenia for 12 months [28,29,30] This system administered EMA scales up to three times per week over this period. The present study aims to determine whether a brief report of individual symptoms assessed via EMA detects changes occurring before, during, and after psychiatric relapses. We operationalize this approach by examining [1] whether and to what degree EMA responses assessing symptoms change before relapse, [2] whether mean values predicted by those models on the day of relapse differ from participant averages throughout the study period, and [3] whether and to what degree responses change following relapse
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