Computational modeling can help us formalize how choice behaviors can be optimally adapted to different situations and investigate the ways in which individuals deviate from optimal behavior. Both anxious and depressed individuals report difficulties with decision-making; these difficulties have consequences for social interactions and occupational function. Understanding whether anxiety and depression are associated with common or unique deficits in decision-making has been hampered by studies focusing on either anxiety or depression alone and overlooking issues of comorbidity. This is important to address to better identify which aspects of decision-making should be targets for intervention in different patient groups. The separate investigation of anxiety- and depression-related deficits in decision-making has also led to a lack of equivalence of tasks and limited use of both reward-related and aversive outcomes within the same study. In the proposed research, we will conduct bifactor analysis of item-level responses to anxiety and depression questionnaires and use participant scores on the dimensions obtained to interrogate whether deficits in decision- making under second-order uncertainty are common to both anxiety and depression or unique to one or the other. We focus upon second-order uncertainty as this characterizes many of the situations we encounter in every-day life but there has been limited investigation of whether anxiety or depression are linked to deficits in adjusting decision-making to second-order uncertainty. Second-order uncertainty arises both when the probability of our actions resulting in certain outcomes changes across time (volatility) and when information needed to estimate how likely a given action is to lead to a given outcome is not fully available (ambiguity). In the proposed studies, we will use volatility and ambiguity manipulations to examine whether deficits in decision-making under second-order uncertainty are common to both anxiety and depression or unique to one or other and whether such deficits are domain general or domain specific (vary by outcome type: aversive, reward gain or reward loss). On-line studies will be used to conduct replication work and to examine if impaired decision-making under second-order uncertainty is primarily linked to internalizing symptomatology or common to a broader range of psychopathology. These online studies will also enable us to test exploratory hypotheses pertaining to other dimensions of psychopathology. Understanding the extent to which alterations in decision- making under second order uncertainty are unique to anxiety or depression, common to both anxiety and depression (i.e. a transdiagnostic marker of Internalizing psychopathology), or associated with psychopathology more broadly is important to clarify so that we can better tailor cognitive and psycho- educational interventions to different patient groups. It may also help clarify whether existing interventions developed in relation to anxiety (e.g. CBT focusing on ambiguity aversion) might valuably be applied to other forms of psychopathology.

Public Health Relevance

Our personal and work relationships are frequently characterized by changing dynamics and insufficient information to precisely calculate our actions? probability of success. The proposed studies investigate whether difficulties making decisions under these forms of uncertainty are common to both anxiety and depression and potentially also to other forms of psychopathology. Better understanding these difficulties will facilitate development of new psychoeducational and cognitive interventions targeted at remediating difficulties in decision-making under these forms of uncertainty and hopefully aid in better identifying patient groups that might benefit from such interventions.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
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Cognition and Perception Study Section (CP)
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Ferrante, Michele
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University of California Berkeley
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United States
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