Abstract
Complexity science methods offer new opportunities for prognosis and treatment in healthcare and clinical psychology because of the increasing need for integration of the detailed knowledge of physiological and psychological subsystems and the increasing prevalence of multiple disease conditions in our aging societies. This chapter explains how the frequently occurring acute transitions and related tipping points in physical and mental processes in these populations can be monitored with time series and dynamical indicators of resilience. The authors introduce slowing down of recovery, increase in variance and autocorrelation, and increasing cross-correlation between subsystem time series as valid predictors of the proximity of tipping points in diseases such as depression, heart failure and syncope. Using wearable devices, together with these complex systems analyses, yields new methods of forecasting and may improve resilience of individual persons and their mental or physical (organ) subsystems
| Original language | English |
|---|---|
| Title of host publication | Complex Systems and Population Health |
| Editors | Yorghos Apostolopoulos, Michael K. Lemke, Kristen Hassmiller Lich |
| Publisher | Oxford University Press |
| Pages | 59-72 |
| ISBN (Print) | 9780190880743 |
| DOIs | |
| Publication status | Published - 29 May 2020 |