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The challenges of forecasting resilience

Published online by Cambridge University Press:  02 September 2015

Luke J. Chang ,
Marianne Reddan ,
Yoni K. Ashar ,
Hedwig Eisenbarth  and
Tor D. Wager
Luke J. Chang
Affiliation:
Department of Psychology & Neuroscience, University of Colorado, Boulder, CO 80309. [email protected]@[email protected]@[email protected]://cosanlab.comhttp://wagerlab.colorado.edu
Marianne Reddan
Affiliation:
Department of Psychology & Neuroscience, University of Colorado, Boulder, CO 80309. [email protected]@[email protected]@[email protected]://cosanlab.comhttp://wagerlab.colorado.edu
Yoni K. Ashar
Affiliation:
Department of Psychology & Neuroscience, University of Colorado, Boulder, CO 80309. [email protected]@[email protected]@[email protected]://cosanlab.comhttp://wagerlab.colorado.edu
Hedwig Eisenbarth
Affiliation:
Department of Psychology & Neuroscience, University of Colorado, Boulder, CO 80309. [email protected]@[email protected]@[email protected]://cosanlab.comhttp://wagerlab.colorado.edu
Tor D. Wager
Affiliation:
Department of Psychology & Neuroscience, University of Colorado, Boulder, CO 80309. [email protected]@[email protected]@[email protected]://cosanlab.comhttp://wagerlab.colorado.edu
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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.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 38 , 2015 , e98
Copyright
Copyright © Cambridge University Press 2015 

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