Journal of personality and social psychology最新文献

Rather than directly confronting their partners, people often use indirect strategies (e.g., making sarcastic comments, muttering under their breath, being passively aggressive). Yet, whereas directly confronting a partner can bring about desired change, indirect opposition tends to undermine relationship quality without bringing about subsequent change. So, why do people engage in indirect opposition? We suggest one reason is to obtain diagnostic information about their partner's commitment. We tested this idea using seven studies that were diverse in design (i.e., cross-sectional, experimental, longitudinal), method of assessment (i.e., observational, self-reports, reaction times), and type of sample (i.e., online crowdsourced, undergraduates, community couples). Across studies, people were more likely to use indirect (vs. direct) oppositional behaviors to the extent that they were uncertain, and motivated to obtain information, about a partner's commitment. Moreover, suggesting that people believe indirect opposition offers more diagnostic information about a partner's commitment, Studies 4 and 5 demonstrated that partners' responses to indirect opposition were perceived to be more authentic and thus reflective of their commitment than responses to direct opposition. Together, these studies suggest that people use indirect opposition to test a partner's level of commitment. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Individual differences in psychological reactivities (i.e., the degree to which individuals react differently to social interactions) are central to psychological research. Previous theory-based research has identified substantial individual differences in reactivities but few robust predictors of these differences. This work aimed to address two questions: First, can individual differences in reactivities to social interactions be accurately predicted at all? Second, what are the most important person-level variables for this prediction? A data-driven machine learning approach was applied to three large-scale experience sampling data sets (overall N = 5,047) to predict the extent to which individuals reacted with positive and negative affect to momentary social interaction characteristics (e.g., interaction depth). Individual differences in reactivities were extracted via multilevel modeling (i.e., random slopes) and then predicted with machine learning methods using a variety of person-level variables (i.e., sociodemographics, personality traits, and political and societal attitudes). The robustness of predictions was examined by built-in cross-validation and across independent samples. Feature importance and interactions were analyzed with SHapley Additive exPlanations values. Our results suggest that, whereas complex prediction models outperformed a baseline model in predicting individual differences in reactivities in most analyses, the overall predictive performance was limited. This finding underlines the importance of replicating machine learning results across outcomes and independent samples. We revealed several predictive patterns that can stimulate future research, elaborate on limitations of current machine learning approaches for intensive within-person data, and discuss the results against the background of dynamic conceptualizations of personality. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

In psychology, mobile sensing is increasingly used to record behavior in real-life situations. However, little is known about the selectivity of samples participating in these new data collection approaches and thus about potential risks to the validity of research findings. We therefore investigated two potential sources of selection bias in smartphone-based data collections. Specifically, we examined whether smartphone system ownership (Android vs. iOS, i.e., platform-related differences) and willingness to participate (nonparticipation vs. intention to participate vs. actual participation, i.e., nonresponse error) are associated with sociodemographic, socioeconomic, and personality characteristics. Using two large-scale panel studies, we found replicable patterns for platform-related differences (N = 1,218 and N = 5,123) and nonresponse error (N = 1,673 and N = 2,337): The ownership of Android devices (in comparison to iOS devices) was associated with lower levels of education, income, and extraversion. The willingness to participate in mobile sensing studies was found to be higher among younger age groups, males, those with higher levels of openness to experience, and those with lower levels of neuroticism. Furthermore, different person characteristics played different roles at different stages of the recruitment process. Taken together, the results show that some selection bias in mobile sensing studies exists and that the effects were small to moderate in magnitude as well as comparable to selection bias for other, more common data collection approaches, such as online surveys. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

A substantial part of people's social lives unfolds within groups. However, there is a notable research gap concerning if and how the personality characteristics that people bring to group interactions combine to predict person and group outcomes. In this study, we used the group actor-partner interdependence model (Kenny & Garcia, 2012) as a framework to integrate prior approaches and understand how the composition of two socially relevant personality traits-agency and communion-affects people and groups. We analyzed data from 432 participants (M_age = 26.61, 51% female) who formed 108 four-person groups and engaged in four different group tasks. Our findings yield three key insights: (a) At the person level, people's own trait levels were the main drivers of their behaviors, experiences, and performance. (b) At the group level, personality composition affected different outcomes than at the person level, with agency playing an overall more important role for group behaviors and experiences. (c) Notable composition effects at both levels emerged for conflict behavior: People who were similar to their group in terms of agency were more engaged in conflicts, and groups whose members had similar agency levels were more likely to experience conflicts as a whole. We contextualize our findings within a theoretical framework to better understand when and how personality composition in social interactions is important, and we review methodologies to capture its multifaceted components. (PsycInfo Database Record (c) 2026 APA, all rights reserved).