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An investigation of the potential clinical utility of critical slowing down as an early warning sign for recurrence of depression.
Tonge, Natasha A; Miller, J Philip; Kharasch, Evan D; Lenze, Eric J; Rodebaugh, Thomas L.
Afiliación
  • Tonge NA; Department of Psychology & Brain Sciences, Washington University in St. Louis, St. Louis, Missouri, USA. Electronic address: ntonge@gmu.edu.
  • Miller JP; Division of Biostatistics, Washington University in St. Louis, St. Louis, Missouri, USA.
  • Kharasch ED; Department of Anesthesiology, Duke University School of Medicine, Durham, NC, USA.
  • Lenze EJ; Department of Psychiatry, Washington University in St. Louis, School of Medicine, St. Louis, Missouri, USA.
  • Rodebaugh TL; Department of Psychology & Brain Sciences, Washington University in St. Louis, St. Louis, Missouri, USA.
J Behav Ther Exp Psychiatry ; 82: 101922, 2024 03.
Article en En | MEDLINE | ID: mdl-37956479
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Depresión Límite: Humans Idioma: En Revista: J Behav Ther Exp Psychiatry Año: 2024 Tipo del documento: Article Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Depresión Límite: Humans Idioma: En Revista: J Behav Ther Exp Psychiatry Año: 2024 Tipo del documento: Article Pais de publicación: Países Bajos