Seven preregistered studies (total N = 2,443) demonstrate that feedback receptivity of people in power, or their openness to feedback, reduces bias concerns among members of marginalized groups (marginalized group meta-analytic dz = 0.53; nonmarginalized group meta-analytic dz = 0.10). Study 1 finds that the extent to which engineering students and staff perceive their faculty advisors as receptive to feedback predicts women's lower concerns about facing gender bias and that this effect is weaker for men. Studies 2-4 show that reading about a person in power who is high in feedback receptivity (vs. no information about feedback receptivity) reduces women's gender bias concerns in male-dominated environments; lesbian, gay, and bisexual people's sexual orientation bias concerns at work; and disabled students' ability bias concerns in the classroom. Studies 3-6 find that perceptions of relational leadership, or perceptions that the person in power is caring, trustworthy, and uses power for good, explain why feedback receptivity reduces bias concerns. Study 7 introduces an important caveat: When people in power ask for but then explicitly ignore feedback, bias concerns are higher than when they do not solicit feedback. Feedback receptivity may not appear tied to social identity but may be a helpful tool for making academic and professional cultures more equitable. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Self-esteem and depressive symptoms are important predictors of a range of societally relevant outcomes and are theorized to influence each other reciprocally over time. However, existing research offers only a limited understanding of how their dynamics unfold across different timescales. Using three data sets with different temporal resolutions, we aimed to advance our understanding of the temporal unfolding of the reciprocal dynamics between self-esteem and depressive symptoms. Across these data sets, participants (Ntotal = 6,210) rated their self-esteem and depressive symptoms between 6 and 14 times across days, months, and years, respectively. Using continuous time dynamic models, we found limited evidence for significant within-person cross-lagged effects between self-esteem and depressive symptoms. Only in the yearly data set, a cross-lagged effect from depressive symptoms to self-esteem emerged quite consistently. However, in all data sets, cross-lagged effects were small in size (-0.04 ≤ β ≤ -0.01). These findings suggest that the reciprocal dynamics between self-esteem and depressive symptoms may be less robust than commonly thought. Furthermore, exploratory analyses indicated that these effects depended on people's overall levels of depressive symptoms, suggesting that theoretical frameworks that highlight transactions between self-esteem and depression may not generalize across all levels of depressive symptoms. Finally, self-esteem and depressive symptoms were strongly correlated within measurements, similarly stable over time, and changed similarly in response to negative life events, provoking questions as to their conceptual distinctiveness and measurement approaches. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Affective, behavioral, and cognitive (i.e., personality) states fluctuate across situations and context, yet the biological mechanisms regulating them remain unclear. Here, we report two large, longitudinal studies that investigate patterns of change in personality states and affect as a function of the menstrual cycle, ovarian hormones, and hormonal contraceptive use. Study 1 (N = 757) is an online diary study with a worldwide sample, whereas Study 2 (N = 257) is a laboratory study including repeated hormone assays. Both studies came to somewhat diverging conclusions. In Study 1, we found that dynamics of daily affect and personality were very similar among naturally cycling women and hormonal contraceptive users, with two exceptions: Hormonal contraceptive users showed greater variability in negative affect than naturally cycling women, and, naturally cycling women showed a descriptive, but nonsignificant decrease in positive affect in the premenstrual phase. Results of Study 2 indicated robust premenstrual increases in neuroticism and negative affect but decreases in extraversion and positive affect. High extraversion and low neuroticism were positively related to conception risk and the estradiol-to-progesterone ratio, suggesting potentially adaptive effects consistent with a fertility-induced shift in motivational priorities. We discuss how differences in methods likely account for differences in results between both studies and suggest methodological and theoretical guidelines for future research. Taken together, our results suggest that hormonal variation across the menstrual cycle-and discrete menstrual cycle events, such as premenstruation-represent potential biological sources of personality state variation. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Perceptions of socioeconomic status (SES) can perpetuate inequality by influencing interpersonal interactions in ways that disadvantage people with low SES. Indeed, lab studies have provided evidence that people can detect others' SES and that they may use this information to apply stereotypes that influence interpersonal decisions. Here, we examine how SES and SES-based stereotypes affect real-world social interactions between people from a socioeconomically diverse population. We used the computer-mediated online round-robin method to facilitate interactions among 297 participants from across the U.S. Participants completed a series of dyadic interactions with other participants in virtual rooms in which they discussed a recent negative consumer experience. After each interaction, they judged the interaction partner's SES, personality traits, and credibility of their consumer experience. Results showed that people perceived SES with moderate accuracy in the interactions, which elicited negative interpersonal stereotypes of low-SES individuals for all 12 of the personality traits measured. People also preferred to affiliate with others with high SES, had more sympathy for them, and found their experiences more credible. SES-based interpersonal stereotypes about personality traits mediated these associations. The perception of SES in real-time interactions thus appears to activate stereotypes that guide social judgments, supporting the hypothesis that interpersonal effects contribute to economic inequality. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Human likes and dislikes can be established or changed in numerous ways. Three of the most well-studied procedures involve exposing people to regularities in the environment (evaluative conditioning, approach-avoidance, mere exposure), to verbal information about upcoming regularities (evaluative conditioning, approach-avoidance, or mere exposure information), or to verbal information about the evaluative properties of an attitude object (persuasive messages). In the present study, we investigated the relation between, on the one hand, different types of experiment-related beliefs (regularity, influence, and hypothesis awareness) and demand reactions (demand compliance and reactance) and, on the other hand, evaluative learning about novel food brands (Experiments 1 and 2) and well-known food brands (Experiment 2) via persuasive messages, experienced regularities, and verbal information about regularities. Participants were first exposed to an evaluative learning phase and then completed self-reported evaluation ratings, an Implicit Association Test, and a behavioral intention measure. Results indicate that regularity awareness was a necessary condition for most evaluative learning effects. Influence awareness was also a strong moderator of evaluative effects but more so for effects on self-reported ratings. Hypothesis awareness and reactance only weakly moderated evaluative learning, and demand compliance only played an important role for well-known brands. The theoretical and practical implications of our findings are discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Many lifestyle and psychosocial factors are associated with a longer lifespan; central among these is social connectedness, or the feeling of belongingness, identification, and bond as part of meaningful human relationships. Decades of research have established that social connectedness is related not only to better mental health (e.g., less loneliness and depression) but also to improved physical health (e.g., decreased inflammatory markers, reduced cortisol activity). Recent methodological advances allow for the investigation of a novel marker of biological health by deriving a predicted "age of the brain" from a structural neuroimaging scan. Discrepancies between a person's algorithm-predicted brain-age and chronological age (i.e., the brain-age gap) have been found to predict mortality and psychopathology risk with accuracy rivaling other known measures of aging. This preregistered investigation uses the Midlife in the United States (MIDUS) study to examine connections between the quality of social connections, the brain-age gap, and markers of mortality risk to understand the longevity-promoting associations of social connectedness from a novel biological vantage point. While social connectedness was associated with markers of mortality risk (number of chronic conditions and ability to perform activities of daily living), our models did not find significant links between social connectedness and the brain-age gap, or the brain-age gap and mortality risk. Supplemental and sensitivity analyses suggest alternate approaches to investigating these associations and overcoming limitations. While plentiful evidence underscores that being socially connected is good for the mind, future research should continue to consider whether it impacts neural markers of aging and longevity. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Decades of research have identified average patterns of normative personality development across the lifespan. However, it is unclear how well these correspond to trajectories of individual development. Past work beyond general personality development might suggest these average patterns are oversimplifications, necessitating novel examinations of how personality develops and consideration of new individual difference metrics. This study uses five longitudinal data sets from Germany, Australia, the Netherlands, and the United States (N = 128,345; Mage = 45.42; 53% female) to examine personality development using mixed-effects location scale models. These models quantify individual differences in within-person residual variability, or sigma, around trajectories-thereby testing if models that assume sigma is homogeneous, unsystematic noise are appropriate. We investigate if there are individual differences in longitudinal within-person variability for Big Five trajectories, if there are variables associated with this heterogeneity, and if person-level sigma values can uniquely predict an outcome. Results indicated that, across all models, there was meaningful heterogeneity in sigma-the magnitude of which was comparable to and often even greater than that of intercepts and slopes. Individual differences in sigma were further associated with covariates central to personality development and had robust predictive utility for health status, an outcome with long-established personality associations. Collectively, these findings underscore the presence, degree, validity, and potential utility of heterogeneity in longitudinal within-person variability and indicate the typical linear model does not adequately depict individual development. We suggest it should become the default to consider this individual difference metric in personality development research. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Frontal alpha asymmetry has been proposed as a ubiquitous marker of state and trait approach motivation, but recent meta-analyses found weak or nonexistent links with personality traits. It has been suggested that frontal asymmetry may show stronger individual differences in situations that elicit approach motivation (state-trait interaction). To investigate this with sufficient statistical power, we utilized data from the CoScience project (N = 740). Frontal asymmetry was measured during a resting period, a picture viewing task, and a guessing task, which were expected to trigger different levels of approach motivation. Results showed that frontal asymmetry was not reliably affected by task manipulations and did not relate to self-reported traits. Furthermore, Bayesian statistics and a cooperative forking path analysis were used to supplement the preregistered analyses. To conclude, this comprehensive analysis could not support the validity of frontal asymmetry as a marker of approach motivation, neither as a reliable state nor as a trait marker. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Face stereotypes are prevalent, consequential, yet oftentimes inaccurate. How do false first impressions arise and persist despite counter-evidence? Building on the overgeneralization hypothesis, we propose a domain-general cognitive mechanism: insufficient statistical learning, or Insta-learn. This mechanism posits that humans are quick statistical learners but insufficient samplers. Humans extract statistical regularities from very few exemplars in their immediate context and prematurely decide to stop sampling, creating and perpetuating locally accurate-but globally inaccurate-impressions. Six experiments (N = 1,565) tested this hypothesis using novel pairs of computer-generated faces and social behaviors by fixing the population-level statistics of face-behavior associations to zero (i.e., no relationship). The initial sample contained either 11, five, or three examples with either a positive, zero, or negative linear relationship between facial features and social behaviors. The sampling procedure contained a free-sampling condition in which participants were free to decide when to stop viewing more examples and a fixed-sampling condition in which participants were forced to view all stimuli before making decisions. Consistent with the Insta-learn mechanism, participants learned novel face stereotypes quickly, with as few as three examples, and did not sample enough when they were given the freedom to do so. This domain-general cognitive mechanism provides one plausible origin of false face stereotypes, demonstrating negative consequences when people learn too much from too little. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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