Consider the following static single-agent choice problem under uncertainty.
Let $V$ be the state of the world with support $\mathcal{V}$ and probability distribution $P_V\in \Delta(\mathcal{V})$. First, let nature draw a realisation $v$ of $V$ from $P_V$. Then, let the decision maker (DM) choose an action $y\in \mathcal{Y}$, with $\mathcal{Y}$ finite, without observing $v$. Upon the decision has been made, the DM gets a payoff $u(y,v)$.
An optimal strategy of the decision problem above is $P_Y\in \Delta(\mathcal{Y})$ such that, $\forall y\in \mathcal{Y}$ such that $P_Y(y)>0$ and $\forall \tilde{y}\neq y$, we have that $$ \sum_{v\in \mathcal{V}} u_i(y,v)P_V(v)\geq \sum_{v\in \mathcal{V}} u_i(\tilde{y},v)P_V(v) $$
Additionally, one can imagine that the DM can process some information structure $S$ to update her prior before choosing an action. In such case, we can use the notion of one-player BCE in Bergemann and Morris (2013,2016) to characterise the set of probability distributions of $(Y,V)$ that are predicted by the model while remaining agnostic about $S$.
Question:
Does the narrative above (and, hence, also the Bergemann and Morris framework) assume that the DM is risk neutral? Can it be reformulated also for the case in which the DM is risk averse?