Critical slowing down as early warning for the onset and termination of depression

TLDR

Complex systems such as climate or ecosystems exhibit critical slowing down as they approach tipping points. Time‑series analysis of self‑reported mood shows that critical‑slowing indicators predict impending depressive episodes, with slower mood dynamics and increased inter‑aspect correlations, supporting mood‑system tipping points and enabling smartphone‑based early warning.

Abstract

Significance As complex systems such as the climate or ecosystems approach a tipping point, their dynamics tend to become dominated by a phenomenon known as critical slowing down. Using time series of autorecorded mood, we show that indicators of slowing down are also predictive of future transitions in depression. Specifically, in persons who are more likely to have a future transition, mood dynamics are slower and different aspects of mood are more correlated. This supports the view that the mood system may have tipping points where reinforcing feedbacks among a web of symptoms can propagate a person into a disorder. Our findings suggest the possibility of early warning systems for psychiatric disorders, using smartphone-based mood monitoring.