scholarly journals Explaining Individual Differences in Advantageous Inequity Aversion by Social-Affective Trait Dimensions and Family Environment

2021 ◽  
pp. 194855062110277
Author(s):  
Hongbo Yu ◽  
Chunlei Lu ◽  
Xiaoxue Gao ◽  
Bo Shen ◽  
Kui Liu ◽  
...  
Keyword(s):  
Individual Differences ◽  
Family Environment ◽  
Large Scale ◽  
Dictator Game ◽  
Inequity Aversion ◽  
Social Emotions ◽  
Student Sample ◽  
Affective Traits ◽  
Callous Unemotional ◽  
Supportive Family

Humans are averse to both having less (i.e., disadvantageous inequity aversion [IA]) and having more than others (i.e., advantageous IA). However, the social-affective traits that drive individual differences in IA are not well understood. Here, by combining a modified dictator game and a computational model, we found in a sample of incarcerated adolescents ( N = 67) that callous-unemotional traits were specifically associated with low advantageous but not disadvantageous IA. We replicated and extended the finding in a large-scale university student sample ( N = 2,250) by adopting a dimensional approach to social-affective trait measures. We showed that advantageous IA was strongly and negatively associated with a trait dimension characterized by callousness and lack of social emotions (e.g., guilt and compassion). A supportive family environment negatively correlated with this trait dimension and positively with advantageous IA. These results identify a core set of social-affective dimensions specifically associated with advantageous IA.

scholarly journals Explaining individual differences in advantageous inequity aversion by social-affective trait dimensions and family environment

2021 ◽  
Author(s):  
Hongbo Yu ◽  
Xiaoxue Gao ◽  
Shen Bo ◽  
Molly Crockett
Keyword(s):  
Individual Differences ◽  
Family Environment ◽  
Large Scale ◽  
Dictator Game ◽  
Inequity Aversion ◽  
Social Emotions ◽  
Student Sample ◽  
Affective Traits ◽  
Callous Unemotional ◽  
Supportive Family

Humans are averse to both having less (i.e., disadvantageous inequity aversion) and having more than others (i.e., advantageous inequity aversion). However, the social-affective traits that drive individual differences in inequity aversion (IA) are not well understood. Here, by combining a modified Dictator Game and a computational model, we found in a sample of incarcerated adolescents (N = 67) that callous-unemotional traits were specifically associated with low advantageous but not disadvantageous IA. We replicated and extended the finding in a large- scale university student sample (N = 2,250) by adopting a dimensional approach to social- affective trait measures. We showed that advantageous IA was strongly and negatively associated with a trait dimension characterized by callousness and lack of social emotions (e.g., guilt and compassion). A supportive family environment negatively correlated with this trait dimension and positively with advantageous IA. These results identify a core set of social- affective dimensions specifically associated with advantageous IA.

Large-Scale Demonstration Experiment of Mental Imagery Ability

1993 ◽  
Vol 76 (3_suppl) ◽  
pp. 1089-1090 ◽  
Author(s):  
F. Richard Ferraro
Keyword(s):  
Gender Differences ◽  
Individual Differences ◽  
Present Article ◽  
Mental Imagery ◽  
Large Scale ◽  
Introductory Psychology Class ◽  
Imagery Ability ◽  
Psychology Class ◽  
Demonstration Experiment ◽  
And Gender

The present article describes a demonstration experiment used in a large introductory psychology class pertaining to mental imagery ability. The experiment is effective in providing a concrete instance of mental imagery as well as an effective discussion regarding individual differences and gender differences in imagery ability.

The Affiliative Role of Empathy in Everyday Interpersonal Interactions

2019 ◽  
Author(s):  
Whitney R. Ringwald ◽  
Aidan G.C. Wright
Keyword(s):  
Individual Differences ◽  
Structural Equation ◽  
Community Sample ◽  
Empirical Support ◽  
Interpersonal Behavior ◽  
Equation Modeling ◽  
Experimental Conditions ◽  
Student Sample ◽  
Ecological Momentary

Empathy theoretically serves an affiliative interpersonal function by satisfying motives for intimacy and union with others. Accordingly, empathy is expected to vary depending on the situation. Inconsistent empirical support for empathy’s affiliative role may be due to methodology focused on individual differences in empathy or differences between controlled experimental conditions, which fail to capture its dynamic and interpersonal nature. To address these shortcomings, we used ecological momentary assessment to establish typical patterns of empathy across everyday interactions. Associations among empathy, affect, and interpersonal behavior of self and interaction partner were examined in a student sample (N=330), then replicated in a pre-registered community sample (N=279). Multi-level structural equation modeling was used to distinguish individual differences in empathy from interaction-level effects. Results show people are more empathetic during positively-valanced interactions with others perceived as warm and when expressing warmth. By confirming the typically affiliative role of empathy, existing research to the contrary can be best understood as exceptions to the norm.

scholarly journals When Fair Is Not Equal

2017 ◽  
Vol 8 (8) ◽  
pp. 847-857 ◽  
Author(s):  
Kun Zhao ◽  
Eamonn Ferguson ◽  
Luke D. Smillie
Keyword(s):  
Individual Differences ◽  
Social Norms ◽  
Personality Traits ◽  
Big Five ◽  
Real World ◽  
Dictator Game ◽  
Prosocial Behaviors ◽  
Contextual Cues ◽  
Economic Games ◽  
The Real

Growing evidence has highlighted the importance of social norms in promoting prosocial behaviors in economic games. Specifically, individual differences in norm adherence—captured by the politeness aspect of Big Five agreeableness—have been found to predict fair allocations of wealth to one’s partner in the dictator game. Yet, most studies have used neutrally framed paradigms, where players may default to norms of equality in the absence of contextual cues. In this study ( N = 707), we examined prosocial personality traits and dictator allocations under salient real-world norms of equity and need. Extending on the previous research, we found that—in addition to politeness—the compassion aspect of agreeableness predicted greater allocations of wealth when they were embedded in real-world norms. These results represent an important step in understanding the real-world implications of laboratory-based research, demonstrating the importance of both normative context and prosocial traits.

scholarly journals Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

2020 ◽  
Vol 117 (32) ◽  
pp. 19061-19071 ◽  
Author(s):  
Samantha Joel ◽  
Paul W. Eastwick ◽  
Colleen J. Allison ◽  
Ximena B. Arriaga ◽  
Zachary G. Baker ◽  
...  
Keyword(s):  
Machine Learning ◽  
Individual Differences ◽  
Relationship Quality ◽  
Individual Difference ◽  
Large Scale ◽  
Well Being ◽  
Attachment Anxiety ◽  
Self Report ◽  
Individual Difference Variables ◽  
Partner Satisfaction

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships.

scholarly journals Learning to be selfish? A large-scale longitudinal analysis of Dictator games played on Amazon Mechanical Turk

2019 ◽  
Author(s):  
Antonio Alonso Arechar ◽  
David Gertler Rand
Keyword(s):  
Longitudinal Analysis ◽  
Large Scale ◽  
Dictator Game ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Social Setting ◽  
Negative Effects ◽  
Dictator Games

We investigate whether experience playing the Dictator Game (DG) affects prosociality by aggregating data from 37 experiments run on Amazon Mechanical Turk over a six-year period. While prior evidence has shown a correlation between experience on Amazon Mechanical Turk and selfishness, it is unclear to what extent this is the result of selection versus learning. Examining a total of 27,266 decisions made by 17,791 unique individuals, our data shows evidence of significant negative effects of both selection and learning. First, people who participated in a greater total number of our experiments were more selfish, even in their first game – indicating that people who are more likely to select into our experiments are more selfish. Second, a given individual tends to transfer less money over successive experiments – indicating that experience with the DG leads to greater selfishness. These results provide clear evidence of learning even in this non-strategic social setting.

scholarly journals Sex differences in virtual navigation influenced by visual factors and individual differences

2019 ◽  
Author(s):  
Lace Padilla
Keyword(s):  
Sex Differences ◽  
Individual Differences ◽  
Mental Rotation ◽  
Morris Water Maze ◽  
Water Maze ◽  
Large Scale ◽  
Small Scale ◽  
Standard Design ◽  
Males And Females ◽  
Virtual Morris Water Maze

The Morris water maze is a task adapted from the animal spatial cognition literature and has been studied in the context of sex differences in humans, particularly because of the standard design, which manipulates proximal (close) and distal (far) cues. However, there are mixed findings with respect to the interaction of cues and sex differences in virtual Morris water maze tasks, which may be attributed to variations in the scale of the space and previously unmeasured individual differences. We explore the question of scale and context by presenting participants with an outdoor virtual Morris water maze that is four times the size of the mazes previously tested. We also measured lifetime mobility and mental rotation skills. Results of this study suggest that for the small-scale environment, males and females performed similarly when asked to navigate with only proximal cues. However, males outperformed females when only distal cues were visible. In the large-scale environment, males outperformed females in both cue conditions. Additionally, greater mental rotation skills predicted better navigation performance with proximal cues only. Finally, we found that highly mobile females and males perform equally well when navigating with proximal cues.

scholarly journals Natural Leaders: Some interlocutors elicit greater convergence across conversations and across characteristics

2020 ◽  
Author(s):  
Uriel Cohen Priva ◽  
Chelsea Sanker
Keyword(s):  
Individual Differences ◽  
Large Scale ◽  
Social Aspects ◽  
Large Collection ◽  
Human Communication ◽  
Large Scale Study ◽  
Different Characteristics

Are there natural followers in human communication, speakers who consistently converge more than others? Similarly, are there natural leaders, speakers with whom others converge more? Are such tendencies consistent across different linguistic characteristics? We use the Switchboard Corpus, a large collection of telephone conversations, to perform a large-scale study of convergence of speakers in multiple conversations with different interlocutors, across six linguistic characteristics. Having data from each speaker in several conversations makes it possible to investigate whether there are individual differences in likelihood to converge, among speakers (more or less likely to converge), and among interlocutors (more or less likely to elicit convergence). We only find evidence for individual differences by interlocutor, not by speaker; this shows that there are natural leaders, who elicit greater degrees of convergence than others, across different characteristics and different conversations. The absence of a similar finding for natural followers, speakers who converge more than others, suggests that the role of social aspects in mediating convergence is stronger than that of putative individual differences in propensity to converge, or that such propensities are characteristic-specific.

Individual differences in response to a large-scale language and pre-literacy intervention for preschoolers in Denmark

2018 ◽  
Vol 68 ◽  
pp. 51-60
Author(s):  
Philip S. Dale ◽  
Jessica Logan ◽  
Dorthe Bleses ◽  
Anders Højen ◽  
Laura Justice
Keyword(s):  
Individual Differences ◽  
Large Scale ◽  
Literacy Intervention
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