Different methods elicit different belief distributions.

When eliciting people's forecasts or beliefs, you can ask for a point estimate-for example, what is the most likely state of the world?-or you can ask for an entire distribution of beliefs-for example, how likely is every possible state of the world? Eliciting belief distributions potentially yields more information, and researchers have increasingly tried to do so. In this article, we show that different elicitation methods elicit different belief distributions. We compare two popular methods used to elicit belief distributions: Distribution Builder and Sliders.

Defining key concepts for mental state attribution.

The terminology used in discussions on mental state attribution is extensive and lacks consistency. In the current paper, experts from various disciplines collaborate to introduce a shared set of concepts and make recommendations regarding future use.

A multinational analysis of how emotions relate to economic decisions regarding time or risk.

Emotions have been theorized to be important drivers of economic choices, such as intertemporal or risky decisions. Our systematic review and meta-analysis of the previous literature (378 results and 50,972 participants) indicates that the empirical basis for these claims is mixed and the cross-cultural generalizability of these claims has yet to be systematically tested. We analysed a dataset with representative samples from 74 countries (n = 77,242), providing a multinational test of theoretical claims that individuals' ongoing emotional states predict their economic preferences regarding time or risk.

Unconstrained Descriptions of Facebook Profile Pictures Support High-Dimensional Models of Impression Formation.

Dominant models of impression formation focus on two fundamental dimensions: a horizontal dimension of warmth/communion/trustworthiness and a vertical dimension of competence/agency/dominance. However, these models have typically been studied using theory-driven methods and stimuli of restricted complexity. We used a data-driven approach and naturalistic stimuli to explore the latent dimensions underlying >300,000 unconstrained linguistic descriptions of 1,000 Facebook profile pictures from 2,188 participants.

A few theoretical results for Laplace and arctan penalized ordinary least squares linear regression estimators.

Two new nonconvex penalty functions - Laplace and arctan - were recently introduced in the literature to obtain sparse models for high-dimensional statistical problems. In this paper, we study the theoretical properties of Laplace and arctan penalized ordinary least squares linear regression models. We first illustrate the near-unbiasedness of the nonzero regression weights obtained by the new penalty functions, in the orthonormal design case.

Artificial intelligence in Medicare: utilization, spending, and access to AI-enabled clinical software.

Objectives: In 2018, CMS established reimbursement for the first Medicare-covered artificial intelligence (AI)-enabled clinical software: CT fractional flow reserve (FFRCT) to assist in the diagnosis of coronary artery disease. This study quantified Medicare utilization of and spending on FFRCT from 2018 through 2022 and characterized adopting hospitals, clinicians, and patients.

Study Design: Analysis, using 100% Medicare fee-for-service claims data, of the hospitals, clinicians, and patients who performed or received coronary CT angiography with or without FFRCT.

Once and Again: Repeated Viewing Affects Judgments of Spontaneity and Preparation.

Reality is fleeting, and any moment can only be experienced once. Rewatching a video, however, allows people to repeatedly observe the exact same moment. We propose that people may fail to fully distinguish between merely observing behavior again (through replay) from that behavior being performed again in the exact same way.

People quasi-randomly assigned to farm rice are more collectivistic than people assigned to farm wheat.

The rice theory of culture argues that the high labor demands and interdependent irrigation networks of paddy rice farming makes cultures more collectivistic than wheat-farming cultures. Despite prior evidence, proving causality is difficult because people are not randomly assigned to farm rice. In this study, we take advantage of a unique time when the Chinese government quasi-randomly assigned people to farm rice or wheat in two state farms that are otherwise nearly identical.

Ethical judgments of poverty depictions in the context of charity advertising.

Aid organizations, activists, and the media often use graphic depictions of human suffering to elicit sympathy and aid. While effective, critics have condemned these practices as exploitative, objectifying, and deceptive, ultimately labeling them 'poverty porn.' This paper examines people's ethical judgments of portrayals of poverty and the criticisms surrounding them, focusing on the context of charity advertising.

Lying is sometimes ethical, but honesty is the best policy: The desire to avoid harmful lies leads to moral preferences for unconditional honesty.

People believe that some lies are ethical, while also claiming that "honesty is the best policy." In this article, we introduce a theory to explain this apparent inconsistency. Even though people view prosocial lies as ethical, they believe it is more important-and more moral-to avoid harmful lies than to allow prosocial lies.

The puzzle of wrongless injustice: Reflections on Kürthy and Sousa.

The Database of Exemplars (DOE) account of moral cognition emerged in part to explain how wrongless harms could arise (Royzman & Borislow, 2022; henceforth, RB) in spite of being denied by most traditional models (Schein & Gray, 2018; Turiel, 1983; Shweder, 1997; Haidt, 2012). Herein, we defend this account against a set of results that have been claimed to disprove it (Kurthy & Sousa, this issue; henceforth, KS). We argue that DOE is in line with all the findings KS perceive as uniquely supportive of their own account (appraising an act as unjust engenders a judgment of wrong) while RB's findings (Royzman & Borislow, 2022, Studies 2 and 3) do challenge KS under varied conceptions of what it would take for an agent to be or appear unjust in his or her treatment of others, affirming that wrongless injustice is an empirical fact that one must strive to explain and that DOE helps us explain.

Reminders undermine impressions of genuine gratitude.

While reminders can help by encouraging prosocial behaviors, we propose that they can also hurt. Across 10 studies, most of which focus on reminders to express gratitude, we find that reminders interfere with impressions of genuine prosociality. Whether people are reminded subtly (Studies 1a and 6-8) or blatantly (Studies 2-5) to express gratitude, the reminder is perceived to put social pressure on the potential thanker, making reminded thankers seem less genuine and less likable than spontaneous thankers.

Reason Defaults: Presenting Defaults With Reasons for Choosing Each Option Helps Decision-Makers With Minority Interests.

Defaults are powerful tools for nudging individuals toward potentially beneficial options. However, defaults typically guide all decision-makers toward the same option and, consequently, may misguide individuals with minority interests. We test whether presenting defaults with information about heterogeneity can help individuals with minority interests select alternative options, and we dub this intervention a "reason default.

Disciplining the disciplined: Making sense of the gender gap that lies at the core of puritanical morals.

Because suppression of sex has been and is at the core of puritanical morals, a proper account thereof would need to explain why suppression of sex has been largely directed towards the human female. Not only do the authors not account for this pattern, but their general model would seem to predict the reverse - that is, greater suppression/control of the male libido.

Motivating vaccination with financial incentives.

Governments and organizations often offer cash payments for vaccination. How effective are such payments? A literature review shows that incentives usually increase vaccination, especially for nonhesitant populations and when using guaranteed payments. Concerns about negative unintended consequences are unsupported.

Effects of matching personal and organizational mindsets on belonging and organizational interest.

Growth mindsets are beliefs that abilities, like intelligence, are mutable. Although most prior work has focused on people's personal mindset beliefs, a burgeoning literature has identified that organizations also vary in the extent to which they communicate and endorse growth mindsets. Organizational growth mindsets have powerful effects on belonging and interest in joining organizations, suggesting that they may be a productive way to intervene to improve individual and societal outcomes.

Primary Care Continuity, Frequency, and Regularity Associated With Medicare Savings.

Importance: Reducing Medicare expenditures is a key objective of Medicare's transition to value-based reimbursement models. Improving access to primary care is an important way to reduce expenditures, yet less is known about how visits should be organized to maximize savings.

Objective: To examine the association between Medicare savings and primary care visit patterns.

Novel Application of a Dynamic, In-room Survey Platform to Measure Surgical Team Satisfaction.

Objective: To elucidate the potential usage of continuous feedback regarding team satisfaction and correlations with operative performance and patient outcomes.

Background: Continuous, actionable assessment of teamwork quality in the operating room (OR) is challenging. This work introduces a novel, data-driven approach to prospectively and dynamically assess health care provider satisfaction with teamwork in the OR.

Trustworthiness judgments without the halo effect: A data-driven computational modeling approach.

Trustworthy-looking faces are also perceived as more attractive, but are there other meaningful cues that contribute to perceived trustworthiness? Using data-driven models, we identify these cues after removing attractiveness cues. In Experiment 1, we show that both judgments of trustworthiness and attractiveness of faces manipulated by a model of perceived trustworthiness change in the same direction. To control for the effect of attractiveness, we build two new models of perceived trustworthiness: a subtraction model, which forces the perceived attractiveness and trustworthiness to be negatively correlated (Experiment 2), and an orthogonal model, which reduces their correlation (Experiment 3).

How well do laboratory-derived estimates of time preference predict real-world behaviors? Comparisons to four benchmarks.

A large literature implicates time preference (i.e., how much an outcome retains value as it is delayed) as a predictor of a wide range of behaviors, because most behaviors involve sooner and delayed consequences.

When Interdependence Backfires: The Coronavirus Infected Three Times More People in Rice-Farming Areas During Chinese New Year.

Interdependent cultures around the world have generally controlled COVID-19 better. We tested this pattern in China based on the rice theory, which argues that historically rice-farming regions of China are more interdependent than wheat-farming areas. Unlike earlier findings, rice-farming areas suffered more COVID-19 cases in the early days of the outbreak.

What can machine learning teach us about habit formation? Evidence from exercise and hygiene.

We apply a machine learning technique to characterize habit formation in two large panel data sets with objective measures of 1) gym attendance (over 12 million observations) and 2) hospital handwashing (over 40 million observations). Our Predicting Context Sensitivity (PCS) approach identifies context variables that best predict behavior for each individual. This approach also creates a time series of overall predictability for each individual.

Iterated learning reveals stereotypes of facial trustworthiness that propagate in the absence of evidence.

When we look at someone's face, we rapidly and automatically form robust impressions of how trustworthy they appear. Yet while people's impressions of trustworthiness show a high degree of reliability and agreement with one another, evidence for the accuracy of these impressions is weak. How do such appearance-based biases survive in the face of weak evidence? We explored this question using an iterated learning paradigm, in which memories relating (perceived) facial and behavioral trustworthiness were passed through many generations of participants.