Lifestyle versus social determinants of health in the Dutch parliament: An automated analysis of debate transcripts.

Although public health scholars increasingly recognize the importance of the social determinants of health (SDOH), health policy outputs tend to emphasize downstream lifestyle factors instead. We use an automated corpus research approach to analyse fourteen years of health policy debate in the Dutch House of Representatives' Health Committee, testing three potential causes of the lack of attention for SDOH: political ideology, by which members of parliament (MPs) from some political orientations may prioritize lifestyle factors over SDOH; lifestyle drift, by which early attention for SDOH during problem analysis is replaced by a lifestyle focus in the development of solutions as the challenges in addressing SDOH become clear; and focusing events, by which political or societal chance events, known to the public and political elites simultaneously, bolster the lifestyle perspective on health. Our analysis shows that overall, the committee spent most of its time discussing neither SDOH nor lifestyle: healthcare financing and service delivery dominated instead. When SDOH or lifestyle were referenced, left-leaning MPs referred significantly more to SDOH and right-leaning MPs significantly more to lifestyle. Temporal effects related to election cycles yielded inconsistent evidence. Finally, peak attention for both lifestyle and SDOH coincided with ongoing political debate instead of exogenous, unforeseen focusing events, and these peaks were rendered relatively insignificant by the larger and more consistent attention for health care. This paper provides a first step toward automated analysis of policy debates at scale, opening up new avenues for the empirical study of health political discourse.

Uncertainty aversion predicts the neural expansion of semantic representations.

Correctly identifying the meaning of a stimulus requires activating the appropriate semantic representation among many alternatives. One way to reduce this uncertainty is to differentiate semantic representations from each other, thereby expanding the semantic space. Here, in four experiments, we test this semantic-expansion hypothesis, finding that uncertainty-averse individuals exhibit increasingly differentiated and separated semantic representations. This effect is mirrored at the neural level, where uncertainty aversion predicts greater distances between activity patterns in the left inferior frontal gyrus when reading words, and enhanced sensitivity to the semantic ambiguity of these words in the ventromedial prefrontal cortex. Two direct tests of the behavioural consequences of semantic expansion further reveal that uncertainty-averse individuals exhibit reduced semantic interference and poorer generalization. Together, these findings show that the internal structure of our semantic representations acts as an organizing principle to make the world more identifiable.

Shared neural representations and temporal segmentation of political content predict ideological similarity.

Despite receiving the same sensory input, opposing partisans often interpret political content in disparate ways. Jointly analyzing controlled and naturalistic functional magnetic resonance imaging data, we uncover the neurobiological mechanisms explaining how these divergent political viewpoints arise. Individuals who share an ideology have more similar neural representations of political words, experience greater neural synchrony during naturalistic political content, and temporally segment real-world information into the same meaningful units. In the striatum and amygdala, increasing intersubject similarity in neural representations of political concepts during a word reading task predicts enhanced synchronization of blood oxygen level-dependent time courses when viewing real-time, inflammatory political videos, revealing that polarization can arise from differences in the brain's affective valuations of political concepts. Together, this research shows that political ideology is shaped by semantic representations of political concepts processed in an environment free of any polarizing agenda and that these representations bias how real-world political information is construed into a polarized perspective.

Latent motives guide structure learning during adaptive social choice.

Predicting the behaviour of others is an essential part of social cognition. Despite its ubiquity, social prediction poses a poorly understood generalization problem: we cannot assume that others will repeat past behaviour in new settings or that their future actions are entirely unrelated to the past. We demonstrate that humans solve this challenge using a structure learning mechanism that uncovers other people's latent, unobservable motives, such as greed and risk aversion. In four studies, participants (N = 501) predicted other players' decisions across four economic games, each with different social tensions (for example, Prisoner's Dilemma and Stag Hunt). Participants achieved accurate social prediction by learning the stable motivational structure underlying a player's changing actions across games. This motive-based abstraction enabled participants to attend to information diagnostic of the player's next move and disregard irrelevant contextual cues. Participants who successfully learned another's motives were more strategic in a subsequent competitive interaction with that player in entirely new contexts, reflecting that social structure learning supports adaptive social behaviour.

The polarized mind in context: Interdisciplinary approaches to the psychology of political polarization.

Existing research into the psychological roots of political polarization centers around two main approaches: one studying cognitive traits that predict susceptibility to holding polarized beliefs and one studying contextual influences that spread and reinforce polarized attitudes. Although both accounts have made valuable progress, political polarization is neither a purely cognitive trait nor a contextual issue. We argue that a new approach aiming to uncover interactions between cognition and context will be fruitful for understanding how polarization arises. Furthermore, recent developments in neuroimaging methods can overcome long-standing issues of measurement and ecological validity to critically help identify in which psychological processing steps-e.g., attention, semantic understanding, emotion-polarization takes hold. This interdisciplinary research agenda can thereby provide new avenues for interventions against the political polarization that plagues democracies around the world. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Moral strategies and psychopathic traits.

Psychopathy is a personality construct encompassing impaired interpersonal-affective functioning, combined with the inclination to lead an erratic lifestyle and to engage in antisocial acts. Individuals with elevated psychopathic traits often make decisions that have a negative impact on others. Some findings suggest that a lack of empathy and guilt is a key explanatory factor, while other results point toward a decreased sense of fairness in individuals with elevated psychopathic traits. The goal of the present study was to directly compare these hypotheses. Eighty-six healthy individuals completed the Self-Report Psychopathy scale and performed the Hidden Multiplier Trust Game, a socioeconomic decision-making task designed to untangle the roles of guilt and fairness during decision-making. Computational modeling of choice data identified five types of moral decision strategies: inequity aversion, guilt aversion, moral opportunism, greed, and generosity. The model-free results demonstrated that psychopathic traits were associated with lower levels of reciprocity. The model-based results suggested that a reduced sense of fairness, associated with affective traits, was driving this behavior. Our findings stress the importance of treating guilt and fairness as independent concepts, and highlight the importance of improving conceptual precision in untangling the individual impact of fairness and guilt, as this could help explain the mixed results in moral decision-making literature. Elucidating the psychological motivations underlying the relationship between psychopathic traits and poor social decision-making opens new avenues for research on the underlying cognitive mechanisms. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Intolerance of uncertainty modulates brain-to-brain synchrony during politically polarized perception.

Political partisans see the world through an ideologically biased lens. What drives political polarization? Although it has been posited that polarization arises because of an inability to tolerate uncertainty and a need to hold predictable beliefs about the world, evidence for this hypothesis remains elusive. We examined the relationship between uncertainty tolerance and political polarization using a combination of brain-to-brain synchrony and intersubject representational similarity analysis, which measured committed liberals' and conservatives' (n = 44) subjective interpretation of naturalistic political video material. Shared ideology between participants increased neural synchrony throughout the brain during a polarizing political debate filled with provocative language but not during a neutrally worded news clip on polarized topics or a nonpolitical documentary. During the political debate, neural synchrony in mentalizing and valuation networks was modulated by one's aversion to uncertainty: Uncertainty-intolerant individuals experienced greater brain-to-brain synchrony with politically like-minded peers and lower synchrony with political opponents-an effect observed for liberals and conservatives alike. Moreover, the greater the neural synchrony between committed partisans, the more likely that two individuals formed similar, polarized attitudes about the debate. These results suggest that uncertainty attitudes gate the shared neural processing of political narratives, thereby fueling polarized attitude formation about hot-button issues.

Stable distribution of reciprocity motives in a population.

Evolutionary models show that human cooperation can arise through direct reciprocity relationships. However, it remains unclear which psychological mechanisms proximally motivate individuals to reciprocate. Recent evidence suggests that the psychological motives for choosing to reciprocate trust differ between individuals, which raises the question whether these differences have a stable distribution in a population or are rather an artifact of the experimental task. Here, we combine data from three independent trust game studies to find that the relative prevalence of different reciprocity motives is highly stable across participant samples. Furthermore, the distribution of motives is relatively unaffected by changes to the salient features of the experimental paradigm. Finally, the motive classification assigned by our computational modeling analysis corresponds to the participants' own subjective experience of their psychological decision process, and no existing models of social preference can account for the observed individual differences in reciprocity motives. These findings support the view that reciprocal decision-making is not just regulated by individual differences in 'pro-social' versus 'pro-self' tendencies, but also by trait-like differences across several alternative pro-social motives, whose distribution in a population is stable.

The computational and neural substrates of moral strategies in social decision-making.

Individuals employ different moral principles to guide their social decision-making, thus expressing a specific 'moral strategy'. Which computations characterize different moral strategies, and how might they be instantiated in the brain? Here, we tackle these questions in the context of decisions about reciprocity using a modified Trust Game. We show that different participants spontaneously and consistently employ different moral strategies. By mapping an integrative computational model of reciprocity decisions onto brain activity using inter-subject representational similarity analysis of fMRI data, we find markedly different neural substrates for the strategies of 'guilt aversion' and 'inequity aversion', even under conditions where the two strategies produce the same choices. We also identify a new strategy, 'moral opportunism', in which participants adaptively switch between guilt and inequity aversion, with a corresponding switch observed in their neural activation patterns. These findings provide a valuable view into understanding how different individuals may utilize different moral principles.