Relevant Degree Programs
Graduate Student Supervision
Doctoral Student Supervision (Jan 2008 - April 2022)
Some people have an exaggerated self-image: They imagine their abilities to be greater than they are. This discrepancy between self-perception and reality has been studied for at least a century under the names of overstatement, overestimation, overconﬁdence, and overclaiming, yet considering this research altogether reveals some contradictions. By introducing a uniﬁed approach (the Residualized Exaggeration Index, or RExI), the present research rectiﬁes past oversights and shows that exaggeration reliably predicts narcissism, entitlement, and impatience, as well as lower academic performance regardless of cognitive ability. As a more precise operationalization of what is connoted by “overconﬁdence”, the RExI approach can also easily be incorporated into common educational practice to provide more accurate and wholistic learner assessment, and perhaps provide a foundation for improving self-awareness and critical thinking skills.
Much research on the accuracy of interpersonal perception has focused on either the good judge– the individual who accurately perceives others’ personality (e.g., Letzring, 2008), or the good target– the individual whose personality is accurately perceived by others (e.g., Human & Biesanz, 2013). Despite there being reliable variance attributable to the dyad (Biesanz, 2010) previous work has largely overlooked the importance of the dyad and little is known as to why some dyads result in more accurate and more positive impressions than do others. To more fully understand the process of impression formation, it is imperative to investigate the characteristics of the good dyad. As such, this dissertation examines the mechanisms associated with changes in dyadic accuracy in first impressions of personality. In order to understand the behaviors and characteristics associated with dyadic accuracy, 77 participants were videotaped engaging in a total of 437 unstructured 3-minute interactions with another previously unacquainted participant. Raters then coded participants’ behavior and personality, as well as general aspects of the interaction. This dissertation investigates dyadic characteristics and processes associated with dyadic accuracy, how behavior changes across interactions, and the role of changes in behavior in understanding dyadic accuracy. Using the social accuracy model (SAM; Biesanz, 2010), the good dyad is considered in terms of two components of accuracy: distinctive accuracy, understanding an individual’s own unique patterning of traits, and normative accuracy, viewing an individually positively and as similar to the average person. For distinctive accuracy, stable characteristics of the individuals in the dyad impacted the degree to which targets were viewed in line with their own unique traits. Further, between-person differences in behavior generally moderated the impact of within-person changes in behavior on distinctive accuracy. For normative accuracy, the quality of the interaction, interpersonal attraction, and engagement impacted the positivity impressions. Additionally, changes in behavior mediated the impact of changes in dyadic characteristics (e.g., engagement) on normative accuracy. In sum, examining dyadic characteristics and processes, as well as behavior allows greater insight into the process of impression formation by looking beyond stable individual differences and considering variability across dyadic interactions.
Well-adjusted, happy people appear to be judgeable: their personalities tend to be seen more accurately than the personalities of less adjusted individuals (Colvin, 1993a, 1993b). The mechanisms behind this effect, however, are not well understood. One possibility is that well-adjusted individuals are not more judgeable at all; instead, they may have greater self-knowledge that makes them appear to be more easily understood. Studies 1 and 2 address this question by utilizing trait observability to disentangle self-knowledge from judgeability. Across these two round-robin studies of new acquaintances, well-adjusted individuals were seen with greater distinctive self-other agreement, but more so on low rather than highly observable traits. Thus, well-adjusted individuals provide new acquaintances with greater information regarding their less observable traits, enhancing others’ knowledge and thus distinctive self-other agreement. In sum, these studies indicate that well-adjusted individuals are indeed more judgeable. But how does adjustment facilitate judgeability? Across two video perceptions studies (Studies 3 and 4), I examined several potential mechanisms through which adjustment could promote judgeability at three stages of the Realistic Accuracy Model (RAM; Funder, 1995): 1) cue relevance, 2) cue availability, and 3) cue detection. In both studies, well-adjusted individuals were more judgeable because they provided others with more relevant cues: specifically, well-adjusted individuals behaved more in line with their distinctive personalities, which in turn led them to be seen more accurately. In contrast, neither cue availability nor detection could sufficiently account for the link between adjustment and judgeability. In sum, well-adjusted individuals are more judgeable because to their own selves, they are true.
Master's Student Supervision (2010 - 2021)
Researchers in psychology are often interested in questions of whether the magnitude of the similarity or difference between two measures or variables is related to an outcome of interest. These types of questions usually address theoretical issues in psychology that are linked with optimization. Such questions, for example, are whether a certain extent of similarity or difference between two constructs predicts the optimal levels of dyadic satisfaction, attraction, relationships, intrapersonal consistency; or what are the ideal levels of similarity or difference of person-environment fit on health outcomes, just to name a few. Methods such as difference scores and distance measures have been proposed and are commonly used to examine such research questions. However, these measures, when used in isolation, are restrictive and make strong modeling assumptions. More recently, response surface analysis (RSA) methods have been adapted to provide more modeling flexibility and less restrictive models to examine questions of whether (dis)similarity are related to outcomes of interest. The RSA model uses two predictors instead of one which preserves data dimensionality and allows each predictor to have both linear, curvilinear, and interactive relationship with the outcome. Given the functionality and utility of RSA, we advocate its use in similarity research while proposing to conceptualize the modeling of (dis)similarity measures in a simpler way for researchers who currently use or plan to use RSA to address such questions. We propose that researchers use an average (A) and a half of a difference (D) instead of the two original predictors. This new model specification has several advantages. First, it helps researchers to define (dis)similarity coefficients, the parameters that researchers of this topic are truly interested in, more precisely. Second, this new model specification utilizes two orthogonal variables, unlike the original model that uses two predictors that are mostly correlated with each other, thus avoiding multicollinearity issues altogether. Third, this usage allows researchers to interpret (dis)similarity coefficients on a response surface graph more easily. We demonstrated the incremental benefits of the proposed reparameterization approach through mathematical proofs and an empirical example.
Accurately perceiving the personality of the average person corresponds broadly with stereotype accuracy – the generalizability of one’s impressions to other individuals. Previous research has demonstrated that the normative personality profile is highly socially desirable (Borkenau & Zaltauskas, 2009; Wood, Gosling & Potter, 2007). Due to the highly evaluative nature of the normative personality profile, individual differences in perceiving others either more or less positively – the halo effect – is often considered an evaluative artifact that is either statistically removed or minimized through item selection. However, what if individual differences in normative judgments reflect not just evaluative tendencies but also individual differences in generalized knowledge? In Study 1, 1027 participants watched video clips and rated the personality of targets using the Big Five Inventory (BFI; John & Srivastava, 1999) and also completed personality self reports. Using the average self-reports and the social desirability of the personality items (Paulhus, 2009) to predict impressions, we find that despite a high correlation between the normative profile and social desirability, the two independently predict ratings of others. Further, in Study 2 using a modified Q-sort, perceivers (Sample 1 N = 77, Sample 2 N = 88, Sample 3 N = 62) sorted an abbreviated 24-item version of the BFI (John & Srivastava, 1999) describing the average person’s personality. On average, perceivers had accurate knowledge of the average individual’s personality. Additionally, perceivers with greater accuracy in describing the average person rated the personality of ten videotaped targets or the personality of other participants in the round-robin more normatively. This strongly suggests that individual differences in normative judgments are not simply evaluative, but also include a component of knowledge regarding the average personality. Further, consistent with these effects representing separate constructs, well-adjusted individuals achieve greater levels of normative accuracy by having greater normative knowledge, while perceivers who explicitly evaluate others more positively achieve greater normative accuracy by rating others in a more socially desirable manner.