A Behavioral Science Framework for Understanding College Campus Sexual Assault

We propose a behavioral-science approach to sexual assault on college campuses. In this framework, people commit assault when aspects of the immediate situation trigger certain psychological states. No set of mental processes or situational configurations is a precise predictor of assault. Instead, the interaction between mental processes and situational configurations predicts when sexual assault is more or less likely to occur. We begin with an illustrative story to show how a behavioral-science approach is relevant to sexual assault. Next, we map out a framework that suggests how behavioral theories of situations and mental processes have been or could be used to describe, predict, and develop ideas for the reduction of sexual assault. Relevant situational configurations include geographical configurations, local situational and informational cues, and situation-based power. Theories of mental processes include person perception, social norms, moral reasoning, and goals. Our framework can be used to demonstrate how “good” people can commit assault and how individuals can and will refrain from assault within institutions with a “bad” record. Compared with previous theories of sexual assault, a behavioral-science framework offers unique understanding and generative methods for addressing sexual assault on college campuses.

White Parents’ Socialization of Racial Attitudes: A Commentary on Scott et al. (2020)

In the September 2020 issue of Perspectives, Scott et al. argued that there is insufficient empirical work on White parents’ racial-socialization strategies to support generalizations about the topic and, therefore, that journalists’ recommendation that White parents discuss race and racism with their children represents a case of speculation without evidence. Although we strongly support Scott et al.’s call for additional, rigorous research on racial socialization in White families, we argue that their critique of popular-press pieces was unwarranted. Specifically, we argue that, although definitive tests of the effects of specific White parental racial-socialization strategies are lacking, the recommendation for parents to discuss race and racism with their children is both appropriate and empirically grounded. We describe research on racial socialization, intergroup contact, and cognitive development that is consistent with recommendations from developmental scientists reported in the popular press. Furthermore, we argue that parents may be the ideal socializers of racial attitudes. We conclude with a discussion of the broad context concerning media reports of findings from psychological science.

Good Theories in Need of Better Data: Combining Clinical and Social Psychological Approaches to Study the Mechanisms Linking Relationships and Health

The study of intimate relationships and health is a fast-growing discipline with numerous well-developed theories, many of which outline specific interpersonal behaviors and psychological pathways that may give rise to good or poor health. In this article, we argue that the study of relationships and health can move toward interrogating these mechanisms with greater precision and detail, but doing so will require a shift in the nature of commonly used research methods in this area. Accordingly, we draw heavily on the science of behavior change and discuss six key methodologies that may galvanize the mechanistic study of relationships and health: dismantling studies, factorial studies, experimental therapeutics, experimental mediation research, multiple assessments, and recursive modeling. We provide empirical examples for each strategy and outline new ways in which a given approach may be used to study the mechanisms linking intimate relationships and health. We conclude by discussing the key challenges and limitations for using these research strategies as well as novel ideas about how to integrate this work into existing paradigms within the field.

The Conceptual, Cunning, and Conclusive Experiment in Psychology

The ideal experiment in physics must be conceptual, cunning, and conclusive. Adoption of these same standards in psychology has led to experiments that are uninformative and frivolous. We explain why we believe that psychology is fundamentally incompatible with hypothesis-driven theoretical science and conclude that this erodes the logic behind recent proposals to improve psychological research, such as stricter statistical standards, preregistration, and replication. The failure of psychology is not that it is somehow insufficiently scientific but rather that it makes inordinate use of methods that are a mismatch for the aspirations of researchers in the field, at the expense of valuable empirical research.

A Description–Experience Framework of the Psychology of Risk

The modern world holds countless risks for humanity, both large-scale and intimately personal—from cyberwarfare, pandemics, and climate change to sexually transmitted diseases and drug use and abuse. Many risks have prompted institutional, regulatory, and technological countermeasures, the success of which depends to some extent on how individuals learn about the risks in question. We distinguish between two powerful but imperfect teachers of risk. First, people may learn by consulting symbolic and descriptive material, such as warnings, statistics, and images. More often than not, however, a risk’s fluidity defies precise description. Second, people may learn about risks through personal experience. Responses to risk can differ systematically depending on whether people learn through one mode, both, or neither. One reason for these differences—and by no means the only reason—is the discrepancy in the cognitive impact that rare events (typically the risk event) and common events (typically the nonoccurrence of the risk event) have on the decision maker. We propose a description–experience framework that highlights not only the impact of each mode of learning but also the effects of their interplay on individuals’ and collectives’ responses to risk. We outline numerous research questions and themes suggested by this framework.

Applying the Evidence We Have: Support for Having Race Conversations in White U.S. Families

Popular press articles have advocated for parent–child conversations about race and racism to prevent children from developing racial biases, yet empirical investigations of the impact of racial socialization in White U.S. families are scarce. In an article published in Perspectives on Psychological Science in 2020, Scott et al. warned that, given the lack of empirical evidence, parents might actually do more harm than good by talking to their children about race. In this comment, we draw upon the literature on (a) racial socialization, (b) parenting and parent–child discourse, and (c) the role of nonverbal communication in parental socialization to inform our understanding of parents’ ability to engage in race-related conversations in the absence of empirical guidance. We also highlight emerging evidence of the potential benefits of these conversations (even if parents are uncomfortable). In sum, the wealth of existing literature suggests that parents can successfully navigate challenging conversations with their children—which tends to result in better outcomes for children than avoiding those conversations. Thus, although we support Scott et al.’s call for researchers to develop more empirical research, we part with the authors’ assertion that researchers need to wait for more sufficient evidence before providing recommendations to White parents—we believe that the time for White families to begin talking about race and racism is now.

Values in Psychometrics

When it originated in the late 19th century, psychometrics was a field with both a scientific and a social mission: Psychometrics provided new methods for research into individual differences and at the same time considered these methods a means of creating a new social order. In contrast, contemporary psychometrics—because of its highly technical nature and its limited involvement in substantive psychological research—has created the impression of being a value-free discipline. In this article, we develop a contrasting characterization of contemporary psychometrics as a value-laden discipline. We expose four such values: that individual differences are quantitative (rather than qualitative), that measurement should be objective in a specific sense, that test items should be fair, and that the utility of a model is more important than its truth. Our goal is not to criticize psychometrics for supporting these values but rather to bring them into the open and to show that they are not inevitable and are in need of systematic evaluation.

Dismissing “Don’t Know” Responses to Perceived Risk Survey Items Threatens the Validity of Theoretical and Empirical Behavior-Change Research

Since the middle of the 20th century, perceptions of risk have been critical to understanding engagement in volitional behavior change. However, theoretical and empirical risk perception research seldom considers the possibility that risk perceptions do not simply exist: They must be formed. Thus, some people may not have formulated a perception of risk for a hazard at the time a researcher asks them, or they may not be confident in the extent to which their perception matches reality. We describe a decade-long research program that investigates the possibility that some people may genuinely not know their risk of even well-publicized hazards. We demonstrate that indications of not knowing (i.e., “don’t know” responses) are prevalent in the U.S. population, are systematically more likely to occur among marginalized sociodemographic groups, and are associated with less engagement in protective health behaviors. “Don’t know” responses are likely indications of genuinely limited knowledge and therefore may indicate populations in need of targeted intervention. This body of research suggests that not allowing participants to indicate their uncertainty may threaten the validity and generalizability of behavior-change research. We provide concrete recommendations for scientists to allow participants to express uncertainty and to analyze the resulting data.

Unstandard Deviation: The Untapped Value of Positive Deviance for Reducing Inequalities

Behavioral science is increasingly used in public policy to understand and address various manifestations of inequalities. Yet evidence from effective population-level interventions is limited. One framework, known as positive deviance, emphasizes individuals from disadvantaged circumstances who have significantly better outcomes than are typical for their group. Studying their behaviors and outcomes helps to understand what might explain their overall success. These insights could also be used to help others from these circumstances experience positive outcomes. Because positive deviance has been markedly understudied, we present a framework for doing so specifically within behavioral science for public policies aimed at reducing inequalities. Using examples from real-world and experimental insights on choices and outcomes of positive deviants, we encourage further study of their choices and trajectories over time to produce valuable insights. We propose that leveraging those findings would inform public policy by introducing interventions that are more ecologically sound and population-relevant and thus have a better chance at benefiting those who start off under adverse circumstances.

Person Perception, Meet People Perception: Exploring the Social Vision of Groups

Groups, teams, and collectives —people—are incredibly important to human behavior. People live in families, work in teams, and celebrate and mourn together in groups. Despite the huge variety of human group activity and its fundamental importance to human life, social-psychological research on person perception has overwhelmingly focused on its namesake, the person, rather than expanding to consider people perception. By looking to two unexpected partners, the vision sciences and organization behavior, we find emerging work that presents a path forward, building a foundation for understanding how people perceive other people. And yet this nascent field is missing critical insights that scholars of social vision might offer: specifically, for example, the chance to connect perception to behavior through the mediators of cognition and motivational processes. Here, we review emerging work across the vision and social sciences to extract core principles of people perception: efficiency, capacity, and complexity. We then consider complexity in more detail, focusing on how people perception modifies person-perception processes and enables the perception of group emergent properties as well as group dynamics. Finally, we use these principles to discuss findings and outline areas fruitful for future work. We hope that fellow scholars take up this people-perception call.