A cluster randomized controlled trial of a modified vaccination clinical reminder for primary care providers.

Objective: Adult vaccination rates in the United States fall short of national goals, and rates are particularly low for Black Americans. We tested a provider-focused vaccination uptake intervention: a modified electronic health record clinical reminder that bundled together three adult vaccination reminders, presented patient vaccination history, and included talking points for providers to address vaccine hesitancy.

Method: Primary care teams at the Atlanta Veterans Affairs Medical Center, who saw 28,941 patients during this period, were randomly assigned to receive either the modified clinical reminder ( = 44 teams) or the status quo ( = 40 teams).

Effects of Causal Structure on Decisions About Where to Intervene on Causal Systems.

We investigated how people design interventions to affect the outcomes of causal systems. We propose that the abstract structural properties of a causal system, in addition to people's content and mechanism knowledge, influence decisions about how to intervene. In Experiment 1, participants preferred to intervene at specific locations (immediate causes, root causes) in a causal chain regardless of which content variables occupied those positions.

Ideal is typical.

A well-established finding in research on concepts and categories is that some members are rated as better or more typical examples than others. It is generally thought that typicality reflects centrality, that is, that typical examples are those that are similar to many other members of the category. This interpretation of typicality is based on studies in which participants had little knowledge about the relevant categories.

Feature inference and the causal structure of categories.

The purpose of this article was to establish how theoretical category knowledge-specifically, knowledge of the causal relations that link the features of categories-supports the ability to infer the presence of unobserved features. Our experiments were designed to test proposals that causal knowledge is represented psychologically as Bayesian networks. In five experiments we found that Bayes' nets generally predicted participants' feature inferences quite well.