“What’ve I done to deserve this?” The role of deservingness in reactions to being an upward comparison target

2016 ◽  
Vol 34 (1) ◽  
pp. 3-25
Author(s):  
Erika J. Koch ◽  
Shawnee F.M. Totton
Keyword(s):  
Positive Affect ◽  
Individual Difference ◽  
Self Report ◽  
Individual Difference Variables ◽  
Upward Comparison ◽  
Report Measure ◽  
Comparison Target

Outperforming others may be an ambivalent experience, simultaneously evoking pride and discomfort. Two experiments examined the role of deservingness in reactions to being an upward comparison target. Study 1 took place online and experimentally manipulated deservingness by modifying a self-report measure of Sensitivity about Being the Target of a Threatening Upward Comparison (STTUC). Participants predicted more distress and less positive affect under conditions of undeserved (vs. deserved) success; several individual difference variables moderated these effects. Study 2 systematically varied a confederate’s effort to manipulate the perceived deservingness of an outperformed person. Participants were especially likely to downplay their score in the presence of a confederate who appeared to work hard on a task but nevertheless performed poorly. Collectively, findings suggest that people respond most strongly to STTUC when a mismatch exists between deservingness and outcomes.

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 A Neurocomputational Theory of Nightmares: The role of formal properties of nightmare images

2021 ◽  
Author(s):  
Patrick McNamara ◽  
Wesley J Wildman ◽  
George Hodulik ◽  
David Rohr
Keyword(s):  
Individual Difference ◽  
Parameter Space ◽  
Computational Models ◽  
Computational Simulation ◽  
Time Varying ◽  
Individual Difference Variables ◽  
Image Characteristics ◽  
Nightmare Disorder ◽  
Formal Properties

Abstract Study Objectives To test and extend Levin & Nielsen’s (2007) Affective Network Dysfunction (AND) model with nightmare disorder (ND) image characteristics, and then to implement the extension as a computational simulation, the Disturbed Dreaming Model (DDM). Methods We used AnyLogic V7.2 to computationally implement an extended AND model incorporating quantitative effects of image characteristics including valence, dominance, and arousal. We explored the DDM parameter space by varying parameters, running approximately one million runs, each for one month of model time, varying pathway bifurcation thresholds, image characteristics, and individual-difference variables to quantitively evaluate their combinatory effects on nightmare symptomology. Results The DDM shows that the AND model extended with pathway bifurcations and image properties is computationally coherent. Varying levels of image properties we found that when nightmare images exhibit lower dominance and arousal levels, the ND agent will choose to sleep but then has a traumatic nightmare, whereas, when images exhibit greater than average dominance and arousal levels, the nightmares trigger sleep-avoidant behavior, but lower overall nightmare distress at the price of exacerbating nightmare effects during waking hours. Conclusions Computational simulation of nightmare symptomology within the AND framework suggests that nightmare image properties significantly influence nightmare symptomology. Computational models for sleep and dream studies are powerful tools for testing quantitative effects of variables affecting nightmare symptomology and confirms the value of extending the Levin & Nielsen AND model of disturbed dreaming/ND.

scholarly journals Role of Hope and Perceived Social Support in Predicting Posttraumatic Growth among Half- Widows in Kashmir

2017 ◽  
Vol 4 (3) ◽  
Author(s):  
Sadaf Anjum ◽  
Shahina Maqbool
Keyword(s):  
Social Support ◽  
Posttraumatic Growth ◽  
Perceived Social Support ◽  
Subjective Assessment ◽  
Self Report ◽  
Internal Reliability ◽  
Total Growth ◽  
Strongly Agree ◽  
Report Measure

Purpose: The study investigates the role of hope and perceived social support in predicting posttraumatic growth among half-widows in Kashmir. Method: A correlational design was applied. The sample consists of 150 half widows with age ranging between (35-65) yrs, taken from Srinagar, Kupwara and Kulgam districts in Kashmir. Purposive sampling was the technique used for collection of data. Tools used: The Posttraumatic growth inventory developed by Tedeschi and Calhoun in 1996 is a 21-item, 6-point scale self-report measure. The summation of all 21 items yielded a total growth score which can range from 0 to 105. Higher scores were indicative of greater growth. In the present study, internal consistency (Cronbach’s α) of the total score was .96 and item-total correlations ranged from .59 to .82. The Trait Hope Scale (Snyder et al., 1991), comprising the 4-item Agency subscale and the 4-item Pathways subscale. Items are scored on an 8-point Likert scale, anchors ranging from ‘1 = Definitely False’ to ‘8 = Definitely True’. Both subscales have adequate internal reliability, with Cronbach’s alphas ranging from .70 to .84 for the Agency subscale, and from .63 to .86 for the Pathways subscale (Snyder et al., 1991). Perceived Social Support was measured using the Multidimensional Scale of Perceived Social Support (MSPSS). The MSPSS was developed by Zimet et al. (1988). The scale is a 12-item self-report measure for subjective assessment of experienced social support from three sources: Family, Friends, and Significant Other. Each item is rated on a 7-point Likert-type scale ranging from “strongly disagree” to “strongly agree”. The total score ranges from 12 to 84 for the entire 12-item questionnaire and from 4 to 28 for each of the three subscales. For these three subscales higher scores indicate greater perceived social support. In the current study reliability coefficient of the scale is 0.89.

Why Won’t You Listen to Me? Measuring Receptiveness to Opposing Views

2020 ◽  
Vol 66 (7) ◽  
pp. 3069-3094 ◽  
Author(s):  
Julia A. Minson ◽  
Frances S. Chen ◽  
Catherine H. Tinsley
Keyword(s):  
Decision Making ◽  
Discriminant Validity ◽  
Mind Wandering ◽  
Judgment And Decision Making ◽  
Self Report ◽  
Donald Trump ◽  
Convergent And Discriminant Validity ◽  
Opposing Party ◽  
Report Measure

We develop an 18-item self-report measure of receptiveness to opposing views. Studies 1a and 1b present the four-factor scale and report measures of internal, convergent, and discriminant validity. In study 2, more receptive individuals chose to consume proportionally more information from U.S. senators representing the opposing party than from their own party. In study 3, more receptive individuals reported less mind wandering when viewing a speech with which they disagreed, relative to one with which they agreed. In study 4, more receptive individuals evaluated supporting and opposing policy arguments more impartially. In study 5, we find that voters who opposed Donald Trump but reported being more receptive at the time of the election were more likely to watch the inauguration, evaluate the content of the inauguration speech in a more even-handed manner, and select a more balanced portfolio of news outlets for later consumption than their less receptive counterparts. We discuss the scale as a tool to investigate the role of receptiveness for conflict, decision making, and collaboration. This paper was accepted by Elke Weber, judgment and decision making.

Emotional intelligence and authentic leadership: a meta-analysis

2018 ◽  
Vol 39 (5) ◽  
pp. 679-690 ◽  
Author(s):  
Chao Miao ◽  
Ronald H. Humphrey ◽  
Shanshan Qian
Keyword(s):  
Emotional Intelligence ◽  
Individual Difference ◽  
Design Methodology ◽  
Authentic Leadership ◽  
Meta Analysis ◽  
Self Report ◽  
Effect Sizes ◽  
Content Type ◽  
Individual Difference Variables ◽  
Male Dominated

Purpose Authentic leadership is a popular leadership construct that stimulates considerable scholarly interest and has received substantial attention from practitioners. Among different individual difference variables, there has been a growing interest in studying the connection between emotional intelligence (EI) and authentic leadership; nevertheless, most of the existing literature on this relation was atheoretical and the results for this relation were mixed. Thus, the purpose of this paper is to clarify the relation between EI and authentic leadership. Design/methodology/approach A meta-analysis was conducted to examine the relation between EI and authentic leadership and the moderators that affect this relation. Findings The results of the present study indicated that: EI is significantly and positively related to authentic leadership (overall EI: ρ ¯ ˆ = 0.49 ; ability EI: ρ ¯ ˆ = 0.08 ; self-report EI: ρ ¯ ˆ = 0.52 ; mixed EI: ρ ¯ ˆ = 0.49 ); self-report EI and mixed EI have larger associations with authentic leadership than ability EI has; and the relation between EI and authentic leadership does not differ between male-dominated and female-dominated studies. Originality/value The present study couches the relation between EI and authentic leadership in theories and identifies important moderators for this relation which explain the heterogeneity in effect sizes for this relation across studies.

Who is playing that wonderful music? Exploring predictors of playing a musical instrument

2018 ◽  
Vol 48 (5) ◽  
pp. 642-656
Author(s):  
Stanislav Treger
Keyword(s):  
Individual Difference ◽  
Need For Cognition ◽  
Musical Instrument ◽  
Musical Instruments ◽  
Openness To Experience ◽  
Cross Sectional ◽  
Individual Difference Variables ◽  
Number Of Factors ◽  
Almost All

Music is a phenomenon enjoyed by almost all people. Although music fans may believe that music is an important part of their lives, not every music appreciator decides to venture further by making music themselves. The purpose of this research was to investigate potential variables that may be associated with whether one plays a musical instrument. Specifically, I investigated the role of four individual difference variables that have previously been correlated with a number of factors related to music: openness to experience, self–music overlap (SMO), curiosity, and need for cognition (NFC). Results from two cross-sectional investigations ( ns = 369 and 295) revealed that all four variables were positively related to whether one plays a musical instrument. SMO mediated the relation between openness and whether one plays a musical instrument in all studies. Unlike hypothesized, curiosity and NFC did not serve as mediators to the openness–music link. Collectively, this research sheds light on the underexplored question of who plays musical instruments.

scholarly journals Measuring Epistemic Weather Curiosity: Initial Development and Validation of an Individual Difference Questionnaire

2021 ◽  
Author(s):  
Matthew J. Bolton ◽  
Lara K. Ault ◽  
Keith Burton ◽  
Dylan R. Allen ◽  
H. Michael Mogil
Keyword(s):  
Psychometric Properties ◽  
Individual Difference ◽  
Self Report ◽  
General Interest ◽  
Initial Development ◽  
Academic Researchers ◽  
Development And Validation ◽  
Report Measure

This paper addresses work at the intersection of meteorology and the psychology of curiosity andlearning (Bolton et al. 2020; Stewart et al. 2015, 2018). Specifically, we report on thedevelopment and validation of the first self-report measure of epistemic (i.e., information-based)weather curiosity. Two studies derived 11 items measuring general interest in learning aboutweather and curiosity for the science behind weather. Psychometric properties and implicationsof the scale for use by meteorologists, educators, and academic researchers are discussed.

scholarly journals Educational and cultural background as a learner individual difference and the role of motivation in learning

2019 ◽  
Vol 2 (4) ◽  
pp. 14-15
Author(s):  
Yuldosheva Charos Olloyor qizi ◽  
Alimjanova Shohsanam Azamat qizi ◽  
Anvarova Sarvinoz Jumanazar qizi
Keyword(s):  
Individual Difference ◽  
Foreign Languages ◽  
Learning And Teaching ◽  
Individual Difference Variables ◽  
Learning Attitudes ◽  
The Subject ◽  
Learner Differences ◽  
The Individual ◽  
Acquisition Processes

In the literature of learner characteristics in applied linguistics, learning attitudes, strategies and motivation have received most attention. These learner individual difference variables have usually been seen as background learner variables that modify and personalize the overall trajectory of the language acquisition processes (Dörnyei, 2009).It means the individual differences of learner affect the learning and teaching process. And also, without any motivation or positive attitude, there can hardly be a successful process of learning. The question why people learn foreign languages can be put forward.A variety of factors can create a desire to learn. Perhaps the learners love the subject they have chosen, or maybe they are simply interested in seeing what it is like. Perhaps, as with young children, they just happen to be curious about everything, including learning. So, there are given some results of research on individual learner differences and the role of motivation in learning

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