TY - JOUR
T1 - An investigation of the potential clinical utility of critical slowing down as an early warning sign for recurrence of depression
AU - Tonge, Natasha A.
AU - Miller, J. Philip
AU - Kharasch, Evan D.
AU - Lenze, Eric J.
AU - Rodebaugh, Thomas L.
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2024/3
Y1 - 2024/3
N2 - Background and objectives: Much of the burden of depressive illness is due to relapses that occur after treatment into remission. Prediction of an individual's imminent depressive relapse could lead to just-in-time interventions to prevent relapse, reducing depression's substantial burden of disability, costs, and suicide risk. Increasingly strong relationships in the form of autocorrelations between depressive symptoms, a signal of a phenomenon described as critical slowing down (CSD), have been proposed as a means of predicting relapse. Methods: In the current study, four participants in remission from depression, one of whom relapsed, responded to daily smartphone surveys with depression symptoms. We used p-technique factor analysis to identify depression factors from over 100 survey responses. We then tested for the presence of CSD using time-varying vector autoregression and detrended fluctuation analysis. Results: We found evidence that CSD provided an early warning sign for depression in the participant who relapsed, but we also detected false positive indications of CSD in participants who did not relapse. Results from time-varying vector autoregression and detrended fluctuation analysis were not in agreement. Limitations: Limitations include use of secondary data and a small number of participants with daily responding to a subset of depression symptoms. Conclusions: CSD provides a compelling framework for predicting depressive relapse and future research should focus on improving detection of early warning signs reliably. Improving early detection methods for depression is clinically significant, as it would allow for the development of just-in-time interventions.
AB - Background and objectives: Much of the burden of depressive illness is due to relapses that occur after treatment into remission. Prediction of an individual's imminent depressive relapse could lead to just-in-time interventions to prevent relapse, reducing depression's substantial burden of disability, costs, and suicide risk. Increasingly strong relationships in the form of autocorrelations between depressive symptoms, a signal of a phenomenon described as critical slowing down (CSD), have been proposed as a means of predicting relapse. Methods: In the current study, four participants in remission from depression, one of whom relapsed, responded to daily smartphone surveys with depression symptoms. We used p-technique factor analysis to identify depression factors from over 100 survey responses. We then tested for the presence of CSD using time-varying vector autoregression and detrended fluctuation analysis. Results: We found evidence that CSD provided an early warning sign for depression in the participant who relapsed, but we also detected false positive indications of CSD in participants who did not relapse. Results from time-varying vector autoregression and detrended fluctuation analysis were not in agreement. Limitations: Limitations include use of secondary data and a small number of participants with daily responding to a subset of depression symptoms. Conclusions: CSD provides a compelling framework for predicting depressive relapse and future research should focus on improving detection of early warning signs reliably. Improving early detection methods for depression is clinically significant, as it would allow for the development of just-in-time interventions.
KW - Complex dynamic systems
KW - Critical slowing down
KW - Depression
KW - Early warning signs
KW - Ecological momentary assessment
KW - Relapse
UR - http://www.scopus.com/inward/record.url?scp=85176238813&partnerID=8YFLogxK
U2 - 10.1016/j.jbtep.2023.101922
DO - 10.1016/j.jbtep.2023.101922
M3 - Article
C2 - 37956479
AN - SCOPUS:85176238813
SN - 0005-7916
VL - 82
JO - Journal of Behavior Therapy and Experimental Psychiatry
JF - Journal of Behavior Therapy and Experimental Psychiatry
M1 - 101922
ER -