- Bibtex: @vandelempuut2014
- Bibliography: van de Leemput, I. A., Wichers, M., Cramer, A. O. J., Borsboom, D., Tuerlinckx, F., Kuppens, P., van Nes, E. H., Viechtbauer, W., Giltay, E. J., Aggen, S. H., Derom, C., Jacobs, N., Kendler, K. S., van der Maas, H. L. J., Neale, M. C., Peeters, F., Thiery, E., Zachar, P., & Scheffer, M. (2014). Critical slowing down as early warning for the onset and termination of depression. Proceedings of the National Academy of Sciences, 111(1), 87–92. https://doi.org/10.1073/pnas.1312114110
Example citation
Key takeaways
- Autorecorded mood
- Mood dynamics are slower and aspects of mood are more correlated in individuals that are likely to have a transition to/from depression.
- Four sources of evidence for the network structure of depression
- Within-individual correlation between symptoms
- Symptoms have specific responses to stressors
- Clinicians think about depressive symptoms as related
- Patients as well
- I couldn’t follow the methods and modelling at all..
Negative chronic conditions (bad situation at work) can reduce resilience in the system and may trigger initial symptoms (insomnia), eventually reaching a tipping point.
Some signs that an individual is near a tipping point: higher variance in each emotion and both higher within- and between-emotion correlation (between is negatively correlated but stronger).
It’s very hard to precisely model complex systems, which would be needed to have perfect accuracy in tipping points etc. So the alternative is to look for generic markers or characteristics that may indicate that the system is near a tipping point. One such phenomenon is Critical slowing down. The recovery from small stressors to the system is slower than usual.
…elevated variance and correlation may be used as indicators of critical slowing down and therefore as early warning signals that may reveal the loss of resilience in the proximity of a tipping point.