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 (N = 44 teams) or the status quo (N = 40 teams). RESULTS: Uptake of influenza and other adult vaccinations was 1.6 percentage points higher in the intervention group, which was not statistically significant (confidence interval, CI [-1.3, 4.4], p = .28). The intervention had similar effects on Black and White patients and did not reduce the disparity in vaccination rates between these groups. CONCLUSION: Provider-focused interventions are a promising way to address vaccine hesitancy, but they may need to be more intensive than a modified clinical reminder to have appreciable effects on vaccination uptake. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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. In Experiment 2, participants were more likely to intervene on root causes versus immediate causes when they were presented with a long-term goal versus a short-term goal. These results show that the structural properties of a causal system can guide the design of interventions.

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. In the present study, experienced fishermen were asked to give goodness-of-example ratings to familiar freshwater fish. These fishermen were of two cultural groups with somewhat different goals and ideals. Typicality was well predicted by fishes' desirability and poorly predicted by their centrality. Further, the two cultural groups differed in their typicality ratings in ways that corresponded to their different goals and ideals. For knowledgeable reasoners typicality in natural taxonomic categories appears based on ideals rather than on centrality.

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. However, we also observed a pervasive violation of one of the defining principles of Bayes' nets-the causal Markov condition-because the presence of characteristic features invariably led participants to infer yet another characteristic feature. We argue that this effect arises from a domain-general bias to assume the presence of underlying mechanisms associated with the category. Specifically, people take an exemplar to be a "well functioning" category member when it has most or all of the category's characteristic features, and thus are likely to infer a characteristic value on an unobserved dimension.