The challenges of forecasting resilience
Chang, L. J., Reddan, M., Ashar, Y. K., Eisenbarth, H., & Wager, T. D.
In one sentence. Argued, as a peer commentary on a proposed neurobiological resilience framework, that forecasting individual resilience trajectories will require large-scale longitudinal datasets with dense intraindividual sampling and innovative computational and analytic methods.
Abstract
Developing prospective models of resilience using the translational and transdiagnostic framework proposed in the target article is a challenging endeavor and will require large-scale data sets with dense intraindividual temporal sampling and innovative analytic methods.
Citation: Chang, L. J., Reddan, M., Ashar, Y. K., Eisenbarth, H., & Wager, T. D. (2015). The challenges of forecasting resilience. Behavioral and Brain Sciences, 38. https://doi.org/10.1017/s0140525x14001496