How peer influence shapes value computation in moral decision-making

Moral trade-offs reveal foundational representations that predict unique variance in political attitudes

Moral Foundations Theory (MFT) explains variation in moral judgements on the basis of multiple innate, intuitive foundations and has been subject to criticism over recent years. Prior research has tended to rely on explicit self-report in the Moral Foundations Questionnaire (MFQ). In contrast, we seek to capture intuitive choices between foundations in a novel task - the Moral Foundations Conflict Task (MFCT). Across four studies, responses on this task reflect foundations measured by the MFQ (study 1), are not altered under cognitive load or reduced cognitive control (studies 2a and 2b); and explain unique variance in political orientation and related constructs (study 3). Furthermore, using responses and response times generated on the MFCT, we present a computationally explicit model of foundation-related intuitive judgements and show that these patterns are consistent with the theoretical claims of MFT. These findings show that the MFCT outperforms the MFQ and can contribute to the understanding of moral value conflicts, furthering debate on the nature of moral values.

Modulating social learning-induced evaluation updating during human sleep

People often change their evaluations upon learning about their peers' evaluations, i.e., social learning. Given sleep's vital role in consolidating daytime experiences, sleep may facilitate social learning, thereby further changing people's evaluations. Combining a social learning task and the sleep-based targeted memory reactivation technique, we asked whether social learning-induced evaluation updating can be modulated during sleep. After participants had indicated their initial evaluation of snacks, they learned about their peers' evaluations while hearing the snacks' spoken names. During the post-learning non-rapid-eye-movement sleep, we re-played half of the snack names (i.e., cued snack) to reactivate the associated peers' evaluations. Upon waking up, we found that the social learning-induced evaluation updating further enlarged for both cued and uncued snacks. Examining sleep electroencephalogram (EEG) activity revealed that cue-elicited delta-theta EEG power and the overnight N2 sleep spindle density predicted post-sleep evaluation updating for cued but not for uncued snacks. These findings underscore the role of sleep-mediated memory reactivation and the associated neural activity in supporting social learning-induced evaluation updating.

Empathy incites a stable prosocial decision bias

Empathy toward suffering individuals serves as potent driver for prosocial behavior. However, it remains unclear whether prosociality induced by empathy for another person's pain persists once that person's suffering diminishes. To test this, participants underwent functional magnetic resonance imaging while performing a binary social decision task that involved allocation of points to themselves and another person. In block one, participants completed the task after witnessing frequent painful stimulation of the other person, and in block two, after observing low frequency of painful stimulation. Drift-diffusion modeling revealed an increased initial bias toward making prosocial decisions in the first block compared with baseline that persisted in the second block. These results were replicated in an independent behavioral study. An additional control study showed that this effect may be specific to empathy as stability was not evident when prosocial decisions were driven by a social norm such as reciprocity. Increased neural activation in dorsomedial prefrontal cortex was linked to empathic concern after witnessing frequent pain and to a general prosocial decision bias after witnessing rare pain. Altogether, our findings show that empathy for pain elicits a stable inclination toward making prosocial decisions even as their suffering diminishes.

Transmission of social bias through observational learning

People often rely on social learning-learning by observing others' actions and outcomes-to form preferences in advance of their own direct experiences. Although typically adaptive, we investigated whether social learning may also contribute to the formation and spread of prejudice. In six experiments (n = 1550), we demonstrate that by merely observing interactions between a prejudiced actor and social group members, observers acquired the prejudices of the actor. Moreover, observers were unaware of the actors' bias, misattributing their acquired group preferences to the behavior of group members, despite identical behavior between groups. Computational modeling revealed that this effect was due to value shaping, whereby one's preferences are shaped by another's actions toward a target, in addition to the target's reward feedback. These findings identify social learning as a potent mechanism of prejudice formation that operates implicitly and supports the transmission of intergroup bias.

The politics of vaccination: a closer look at the beliefs, social norms, and prevention behaviors related to COVID-19 vaccine uptake within two US political parties

COVID-19 vaccine hesitancy and suboptimal vaccine uptake rates are pressing public health challenges. Vaccine hesitancy has been observed for different vaccines. For COVID-19 vaccines, multiple factors influence vaccine uptake in the U.S. including political ideology. A more nuanced understanding of the factors influencing COVID-19 vaccine uptake within political parties is needed. This study assesses the relationship between known vaccine hesitancy factors and vaccine uptake within two major political parties. Data from 804 U.S. participants in an online survey from June 2021 was used to assess the association between COVID-19 vaccine uptake (no dose vs. any dose) and categories of factors thought to influence vaccine uptake (sociodemographic variables, COVID-19 disease and vaccine belief variables, belief in COVID-19 prevention behavior variables, and social network features variables) for Republicans and Democrats using bivariate and multivariate regression. 65.4% of the sample reported having received at least one dose of the COVID-19 vaccine (22.6% Republican and 52.1% Democrat). In the total sample bivariate model, Democrat participants had significantly greater odds of having received a dose of the vaccine as compared to Republican participants (OR = 2.51, 95%CI = 1.73-3.64). In adjusted models, the speed of vaccine development was negatively associated with vaccine uptake for both Republicans (aOR = 0.18, 95%CI = 0.06-0.57) and Democrats (aOR = 0.40, 95%CI = 0.19-0.86), as was concern about side effects from the vaccine (Republicans: aOR = 0.15; 95%CI = 0.05-0.47; Democrats: aOR = 0.14, 95%CI = 0.06-0.31). COVID-19 vaccine uptake among Republicans, but not Democrats, was associated with belief that the vaccine prevents COVID-19 (aOR = 3.29, 95%CI = 1.29-8.37) and belief about friends' vaccine intentions (aOR = 6.19, 95%CI = 2.39-16.05). There were no significant factors unique to Democrats. Concerns about aspects of COVID-19 vaccine safety for both political groups suggest that vaccine advocacy interventions should universally address these factors. However, Republican beliefs in vaccine efficacy and in friends' vaccine intentions suggest a need for Republican-specific messaging.

Gratitude Is Morally Sensitive

Helping acts, however well intended and beneficial, sometimes involve immoral means or immoral helpers. Here, we explore whether help recipients consider moral evaluations in their appraisals of gratitude, a possibility that has been neglected by existing accounts of gratitude. Participants felt less grateful and more uneasy when offered immoral help (Study 1, N = 150), and when offered morally neutral help by an immoral helper (Study 2, N = 172). In response to immoral help or helpers, participants were less likely to accept the help and less willing to strengthen their relationship with the helper even when they accepted it. Study 3 (N = 276) showed that recipients who felt grateful when offered immoral help were perceived as less likable, less moral, and less suitable as close relationship partners than those who felt uneasy by observers. Our results demonstrate that gratitude is morally sensitive and suggest this might be socially adaptive.

Computational Social Psychology

Social psychologists attempt to explain how we interact by appealing to basic principles of how we think. To make good on this ambition, they are increasingly relying on an interconnected set of formal tools that model inference, attribution, value-guided decision making, and multi-agent interactions. By reviewing progress in each of these areas and highlighting the connections between them, we can better appreciate the structure of social thought and behavior, while also coming to understand when, why, and how formal tools can be useful for social psychologists.

Can monetary incentives overturn fairness-based decisions?

Fairness norms and resulting behaviours are an important prerequisite for cooperation in human societies. At the same time, financial incentives are commonly used to motivate social behaviours, yet it remains unclear how financial incentives affect fairness-based behaviours. Combining a decision paradigm from behavioural economics with hierarchical drift-diffusion modelling, we investigated the effect of different financial incentives on two types of fairness-based decisions in four experimental groups. In two groups, participants divided points between themselves and a disadvantaged person, inciting fairness-based compensation behaviour, in two other groups they divided points between themselves and a fairness violator, inciting fairness-based punishment behaviour. In addition, each group received financial incentives that were either aligned or in conflict with the respective fairness-based behaviour. This design allowed us to directly investigate how different incentives shape the cognitive mechanism of fairness-based decisions and whether these effects are comparable across different fairness domains (fairness-based punishment versus fairness-based compensation). Results showed that offering conflicting incentives diminished fairness-congruent decision behaviour and rendered the fairness-congruent decision process less efficient. These findings demonstrate that financial incentives can undermine fairness-based behaviour, and thus are relevant for the development of incentive schemes aimed at fostering cooperative behaviour.

Moral barrier to compassion: How perceived badness of sufferers dampens observers' compassionate responses

Compassion has been theorized as a desirable prosocial emotion due to its potential to transcend arbitrary boundaries (e.g., race, physical distance) and motivate us to alleviate the suffering of all human beings. Our paper nevertheless examines a potential moral barrier to compassion--whether and how moral evaluations of the suffering and the sufferer hinder our compassion and prosocial motivation. In four pre-registered studies (total N = 421, within-participant design), we demonstrated that adult U.S. participants withheld their compassion and willingness to help when they perceived moral badness of the sufferer, even when the perceived moral badness did not directly cause the suffering. The effects were found in terms of diverse types of moral judgments, including the sufferers' immoral intention (e.g., harming another; Study 1), bad moral character (e.g., being a dishonest person; Study 2), and even mere associations with groups perceived as deserving of suffering based on moral status (Studies 3-4). Deservedness judgment--how much the sufferer was viewed as deserving the suffering--mediated the effect between moral judgment and compassionate responses. Importantly, participants judged withholding compassion based on moral deservedness as what should be done and what morally good people would do, suggesting that people hold a normative view of the tendency that might make it difficult to overcome. Our findings thus reveal moral judgment as a barrier that prevents us from alleviating the suffering of all human beings.

Mindfulness training reduces slippery slope effects in moral decision-making and moral judgment

Extant research has demonstrated the positive intrapersonal effects of mindfulness training. However, the cognitive mechanisms underlying the effects of mindfulness training on interpersonal processes are less clear. Here, we combined a randomized control mindfulness training design with computational approach to moral decision-making and moral judgments. Participants were randomly assigned to a Training group (N = 32) who received an 8-week mindfulness training or a Control group (N = 26) who waited for the same period of time. Before and after the 8-week period, participants completed a moral decision-making task, where they made tradeoff between money for themselves and unpleasant electric shocks to another person, and a moral judgment task, where they evaluated the blameworthiness of someone else's choices in the same moral decision-making task. Trait mindfulness, as measured by the Five-Facet Mindfulness Questionnaire, significantly increased from the pre- to post-training session for the Training group, but not the Control group, demonstrating the effectiveness of the mindfulness manipulation. For the Control group, participants' moral preference in both the decision-making task and the judgment task declined over time, exhibiting a "slippery slope" effect. In contrast, for the Training group, mindfulness training prevented moral preferences from declining. Computational modeling revealed that mindfulness training specifically reduced the increase in the weights of money over time in both the decision-making and judgment tasks, thereby curbing the "slippery slope" effects. These findings provide a cognitive account of the prosocial effects of mindfulness training on moral decision-making and moral judgments.

Aneurysmal Subarachnoid Hemorrhage and Clinical Decision-Making: A Qualitative Pilot Study Exploring Perspectives of Those Directly Affected, Their Next of Kin, and Treating Clinicians

BACKGROUND

Exploring the experience and impact of aneurysmal subarachnoid hemorrhage (aSAH) from three perspectives, that of those directly affected (AFs), their next of kin (NoK), and treating clinicians, is a way to support and empower others to make informed medical decisions.

METHODS

In a Swiss neurosurgical intensive care unit (ICU), eleven semi-structured interviews were conducted as part of a Database of Individual Patient Experiences (DIPEx) pilot project and thematically analyzed. Interviews were held with two clinicians, five people experiencing aSAH, and four NoK 14-21 months after the bleeding event.

RESULTS

Qualitative analysis revealed five main themes from the perspective of clinicians: emergency care, diagnosis and treatment, outcomes, everyday life in the ICU, and decision-making; seven main themes were identified for AFs and NoK: the experience of the aSAH, diagnosis and treatment, outcomes, impact on loved ones, identity, faith, religion and spirituality, and decision-making. Perspectives on decision-making were compared, and, whereas clinicians tended to focus their attention on determining treatment, AFs and NoK valued participation in shared decision-making processes.

CONCLUSIONS

Overall, aSAH was perceived as a life-threatening event with various challenges depending on severity. The results suggest the need for tools that aid decision-making and better prepare AFs and NoK using accessible means and at an early stage.

Superior bias in trust-related decisions

Trust is conditional. Many studies have revealed its relative conditions in different situations, but when social status is characteristic of the person who receives trust (the “trustee”), our knowledge of how social status affects trust still remains limited. In this study, we used the trust game in order to: (1) characterize the effect of trustees’ social hierarchy on trust-related decisions in different trustworthiness situations and (2) explore the underlying computational process regarding the impact that social status has on trust-related decisions by using the computational modeling approach to integrate social status into trust-related situations. In Experiment 1, using a one-shot trust game with no feedback of information about reciprocity, we found that compared with inferiors, superiors gained more trust-related behaviors (investments) in spite of the fact that they were not rated as having higher trustworthiness. Then, in Experiment 2, when we controlled the trustworthiness of different social status partners by providing the same neutral reciprocity rate (50%) in a repeated trust game, the high-status partner gained more trust than the low-status partner. This superior bias extended to Experiment 3a and 3b, in which we set different levels of trustworthiness to match the different social statuses of partners. With respect to modeling results, we found that higher status holds an additional social value independent of trust profit, resulting in superior bias. Ultimately, this study has shed light on the superior bias that commonly leads people to grant high-status individuals goodwill in social interactions.

Temporal dynamics of decision making: A synthesis of computational and neurophysiological approaches

As interest in the temporal dynamics of decision-making has grown, researchers have increasingly turned to computational approaches such as the drift diffusion model (DDM) to identify how cognitive processes unfold during choice. At the same time, technological advances in noninvasive neurophysiological methods such as electroencephalography and magnetoencephalography now allow researchers to map the neural time course of decision making with millisecond precision. Combining these approaches can potentially yield important new insights into how choices emerge over time. Here we review recent research on the computational and neurophysiological correlates of perceptual and value-based decision making, from DDM parameters to scalp potentials and oscillatory neural activity. Starting with motor response preparation, the most well-understood aspect of the decision process, we discuss evidence that urgency signals and shifts in baseline activation, rather than shifts in the physiological value of the choice-triggering response threshold, are responsible for adjusting response times under speeded choice scenarios. Research on the neural correlates of starting point bias suggests that prestimulus activity can predict biases in motor choice behavior. Finally, studies examining the time dynamics of evidence construction and evidence accumulation have identified signals at frontocentral and centroparietal electrodes associated respectively with these processes, emerging 300-500 ms after stimulus onset. These findings can inform psychological theories of decision-making, providing empirical support for attribute weighting in value-based choice while suggesting theoretical alternatives to dual-process accounts. Further research combining computational and neurophysiological approaches holds promise for providing greater insight into the moment-by-moment evolution of the decision process. This article is categorized under: Psychology > Reasoning and Decision Making Neuroscience > Cognition Economics > Individual Decision-Making.

Distinct neurocomputational mechanisms support informational and socially normative conformity

A change of mind in response to social influence could be driven by informational conformity to increase accuracy, or by normative conformity to comply with social norms such as reciprocity. Disentangling the behavioural, cognitive, and neurobiological underpinnings of informational and normative conformity have proven elusive. Here, participants underwent fMRI while performing a perceptual task that involved both advice-taking and advice-giving to human and computer partners. The concurrent inclusion of 2 different social roles and 2 different social partners revealed distinct behavioural and neural markers for informational and normative conformity. Dorsal anterior cingulate cortex (dACC) BOLD response tracked informational conformity towards both human and computer but tracked normative conformity only when interacting with humans. A network of brain areas (dorsomedial prefrontal cortex (dmPFC) and temporoparietal junction (TPJ)) that tracked normative conformity increased their functional coupling with the dACC when interacting with humans. These findings enable differentiating the neural mechanisms by which different types of conformity shape social changes of mind.

Characterization of the Core Determinants of Social Influence From a Computational and Cognitive Perspective

Most human decisions are made among social others, and in what social context the choices are made is known to influence individuals' decisions. Social influence has been noted as an important factor that may nudge individuals to take more risks (e.g., initiation of substance use), but ironically also help individuals to take safer actions (e.g., successful abstinence). Such bi-directional impacts of social influence hint at the complexity of social information processing. Here, we first review the recent computational approaches that shed light on neural and behavioral mechanisms underlying social influence following basic computations involved in decision-making: valuation, action selection, and learning. We next review the studies on social influence from various fields including neuroeconomics, developmental psychology, social psychology, and cognitive neuroscience, and highlight three dimensions of determinants-who are the recipients, how the social contexts are presented, and to what domains and processes of decisions the influence is applied-that modulate the extent to which individuals are influenced by others. Throughout the review, we also introduce the brain regions that were suggested as neural instantiations of social influence from a large body of functional neuroimaging studies. Finally, we outline the remaining questions to be addressed in the translational application of computational and cognitive theories of social influence to psychopathology and health.

How conformity can lead to polarised social behaviour

Learning social behaviour of others strongly influences one’s own social attitudes. We compare several distinct explanations of this phenomenon, testing their predictions using computational modelling across four experimental conditions. In the experiment, participants chose repeatedly whether to pay for increasing (prosocial) or decreasing (antisocial) the earnings of an unknown other. Halfway through the task, participants predicted the choices of an extremely prosocial or antisocial agent (either a computer, a single participant, or a group of participants). Our analyses indicate that participants polarise their social attitude mainly due to normative expectations. Specifically, most participants conform to presumed demands by the authority (vertical influence), or because they learn that the observed human agents follow the norm very closely (horizontal influence).

What drives people to extreme acts of generosity? What causes behaviour that is unduly spiteful? This study explored how our social decisions polarise. Participants chose whether to spend money to increase or decrease the earnings of an unknown person. Halfway through this task, they observed another agent playing. The agent took participants’ choices to the extremes: if for instance the participant was moderately generous, it spent considerable sums to help the other. Participants conformed regardless of whether the agent was a computer algorithm, a person, or a group of people. We tested several competing explanations of why this happened with the help of cognitive modelling. Our analyses identify two factors behind polarisation: willingness to comply with the experimenter expectations (social desirability), and concern about appropriate behaviour (norm conformity). Our approach provided insight into how social choices are influenced by others, and could be applied in the study of conformity in other types of decisions.

Prosocial modeling: person role models and the media

Much of human learning comes from learning from others. In this article, I review empirical work on the extent to which prosocial behavior is inspired by exposure to prosocial models. In fact, witnessing a prosocial model in person leads to an increase in the future prosocial behavior of the observer. Other research has shown that exposure to media (TV, music, video games) with depictions of prosocial behavior can also lead to an increase in prosocial behavior. Theoretical explanations and underlying mechanisms of the prosocial modeling effect are discussed. As prosocial behavior seems to be contagious, exposure to prosocial models is an effective way to encourage positive social encounters.