Covid Admin. Supp. to Elucidating the relationship between decision-making under second-order uncertainty and dimensions of negative affect using computational modeling:

Project Abstract – no change from original proposal
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
psychoeducational 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.

Grant Number: 3R01MH122558-05S1
NIH Institute/Center: NIH
Principal Investigator: Sonia Bishop