Critical Fluctuations as an Early-Warning Signal for Sudden Gains and Losses in Patients Receiving Psychotherapy for Mood Disorders

Abstract

Whereas sudden gains and losses (large shifts in symptom severity) in patients receiving psychotherapy appear abrupt and hence may seem unexpected, hypotheses from complex-systems theory suggest that sudden gains and losses are actually preceded by certain early-warning signals (EWSs). We tested whether EWSs in patients’ daily self-ratings of the psychotherapeutic process predicted future sudden gains and losses. Data were collected from 328 patients receiving psychotherapy for mood disorders who completed daily self-ratings about their therapeutic process using the Therapy Process Questionnaire (TPQ). Sudden gains and losses were classified from the Problem Intensity scale of the TPQ. The other items of the TPQ were used to compute the EWSs. EWSs predicted an increased probability for sudden gains and losses in a 4-day predictive window. These results show that EWSs can be used for real-time prediction of sudden gains and losses in clinical practice.

Early warning signals in psychopathology: what do they tell?

“…Shifts between these equilibria, marking the onset or remittance of symptoms, may occur in an abrupt, stepwise fashion rather than gradually [6,7]. The likelihood of such shifts depends on the system's stability [8]. In a stable system, temporary departures from equilibrium caused by small environmental perturbations are met with regulatory processes that quickly restore the equilibrium.…”

“…Empirical support for complex systems principles in psychopathology was provided by studies that confirmed that markers of instability-specifically, critical fluctuations-indeed predict symptom shifts [11][12][13]. The present paper does not discuss critical fluctuations [8,11,[14][15][16], but rather focuses on critical slowing down as a marker of instability. Critical slowing down refers to an increasingly slowed return to equilibrium [10,17].…”

Studying Complex Adaptive Systems With Internal States: A Recurrence Network Approach to the Analysis of Multivariate Time-Series Data Representing Self-Reports of Human Experience

“…Graphical representations of recurrence networks often use layouts that emphasize certain structural properties (e.g., "spring" layouts) and discard information about the temporal order, the vertex sequence. However, in a clinical setting, e.g., if multivariate time-series data are used to detect imminent regime shifts, such as sudden gains and losses in symptom severity [39,40], it is important to retain temporal information. Here, we present a simple layout for recurrence networks based on the spiral.…”

Depression – ein komplexes dynamisches System

“…In einer Studie an 328 Patient*innen mit affektiven Störungen (einem Spektrum von rezidivierenden und chronischen Depressionen sowie zyklothymen Störungen) konnte eine Zunahme der dynamischen Komplexität im Sinne eines Frühwarnindikators vor einem Sprung in der Dynamik festgestellt werden (Olthof et al, 2019a). Die Patient*innen wurden stationär behandelt und ihre Verläufe mit dem Therapie-Prozessbogen täglich erfasst (die Daten stammen aus dem Grossdatensatz zur SNSbasierten Prozess-und Outcome-Forschung).…”

“…B. sudden gains) auftreten, sondern auch vor suizidalen Krisen. Wenngleich nach Stand des Wissens eine Langfristvorhersage suizidaler Krisen unmöglich erscheint, so ist immerhin eine kurzfristige Vorhersage möglich (Fartacek et al, 2016 Olthof et al, 2019a).…”