Objective Previous research suggests people with social anhedonia (SocAnh) exhibit deficits in anticipated pleasure for social stimuli relative to controls. However, previous research has relied on hypothetical social stimuli and has focused on anticipated pleasure without examining negative affect. Method Participants were informed that they would complete an “enjoyable” sharing task with a peer and were asked to forecast positive and negative affect during the interaction. After the interaction, participants reported their experienced emotions. Results We found SocAnh and controls anticipated and experienced similar levels of positive affect and that both groups underpredicted positive affect. The SocAnh group anticipated and experienced more negative affect than controls and was more accurate in forecasting negative affect. Conclusion This is the first study to show that SocAnh is associated with the heightened anticipation of negative affect and that experiencing heightened negative affect during social interactions could drive reduced motivation and desire to engage in future social interaction.

There is a norm in psychological research to use causally ambiguous statistical language, rather than straightforward causal language, when describing methods and results of nonexperimental studies. We hypothesized that this norm leads to higher ratings of study quality and greater acceptance of policy recommendations that rely on causal interpretations of the results. In a preregistered experiment, we presented psychology faculty, postdocs, and doctoral students (n=142) with abstracts from hypothetical studies. Abstracts described studies’ results using either straightforward causal or causally ambiguous statistical language, but all concluded with policy recommendations relying on causal interpretations of the results. As hypothesized, participants rated studies with causally ambiguous statistical language as of higher quality (by .48-.59 SD) and as similarly or more supportive (by .16-.26 SD) of policy recommendations. Thus, causally ambiguous statistical language may allow psychologists to communicate causal interpretations to readers without being punished for violating the norm against straightforward causal language.

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