The aim of this proposal is to examine what people do and do not know about themselves. Self-views are central to people's daily lives, influencing their subjective experience and playing an important role in shaping their behavior, their environments, and others' reactions to them. This project is designed to explain and predict how self-knowledge differs from other-knowledge. By identifying ways in which self- and other-knowledge may differ, the project will yield a better understanding of the unique strengths and weaknesses of self-knowledge. The Self-Other Knowledge Asymmetry (SOKA) model contends that self-knowledge should be high for characteristics that are relatively neutral (i.e., not desirable or undesirable; e.g., talkative, assertive), but low for characteristics that are highly evaluative (e.g., funny, selfish). Furthermore, other people (e.g., coworkers, friends) should be in a better position than the self to judge these evaluative characteristics. The proposed study will test this idea by focusing on real-world behavior and examine whether people are aware of their own desirable, neutral, and undesirable behaviors. There are several unique strengths of the proposed study. First, it will make use of the latest technological advances to measure participants' real-world behavior. Measures of everyday behavior can be obtained accurately and efficiently using the Electronically Activated Recorder (EAR; Mehl, et al. 2001). The EAR consists of a small, pocket-sized digital audio recorder worn by participants that periodically records snippets of their speech and ambient sounds. These recordings are then carefully coded for behaviors relevant to the study. Second, both self-perceptions of behavior from participants and perceptions of participants' behavior from four people who know them well (i.e., informants) will be assessed. This research will inform social psychological work on the self, illuminating the processes that contribute to accuracy and bias in self-perception.
Identifying the potential blind spots in self-perception can reveal how self-knowledge can be improved, a central goal of psychological inquiry and practice. This research will have important practical implications for anyone relying on self-reports to measure behavior (e.g., employers). This grant would also help promote the involvement of underrepresented groups in scientific research by supporting a research team from a wide variety of backgrounds, including a graduate student who is a first-generation college graduate. In addition, this research is likely to be of significant interest to a wider public including laypersons and clinicians.
This project examined what people do and do not know about themselves. Self-views are central to people’s daily lives, influencing their subjective experience and playing an important role in shaping their behavior, their environments, and others’ reactions to them. In this project I sought to explain and predict how self-knowledge differs from other-knowledge. By identifying the asymmetries between self- and other-knowledge, we have gained a better understanding of the unique strengths and weaknesses of self-knowledge. In a series of previously published papers, I demonstrated that people know themselves about as well as, but no better than, other people know them (Vazire, 2010; Vazire & Carlson, in press; Vazire & Mehl, 2008). In the Self-Other Knowledge Asymmetry (SOKA) model I proposed (Vazire, 2010), I argued that self-knowledge should be high for characteristics that are relatively neutral (i.e., not desirable or undesirable; e.g., talkative, assertive), but people should lack self-knowledge for characteristics that are highly evaluative (e.g., funny, selfish). Furthermore, other people (e.g., coworkers, friends) should be in a better position than the self to judge evaluative characteristics. I presented some preliminary evidence for this hypothesis in a laboratory-based study. In studies I conducted with this award, I extended this research to real-world behavior and examined whether people are aware of their own desirable, neutral, and undesirable behaviors. There are several unique strengths of the studies I conducted with this award. First, I made use of the latest technological advances to unobtrusively measure participants’ real-world behavior. Naturalistic, non-reactive measures of everyday behavior can be obtained using the Electronically Activated Recorder (EAR; Mehl, et al. 2001). The EAR consists of a small, pocket-sized digital audio recorder worn by participants that periodically records snippets of ambient sounds. These recordings are then coded for the behaviors relevant to the study. This results in an objective, ecologically-valid measure of everyday behavior (Mehl et al.). Second, I also collected laboratory-based measures of behavior in a more controlled context that allowed for the coding of behavior from video files. While the EAR allows for the collection of objective behavior in participants’ naturalistic environment, it cannot pick up behaviors that are not acoustically-detectable. Thus, supplementing EAR assessments with video-based codings of laboratory behavior allows for a more comprehensive behavior assessment. Third, I obtain both self-perceptions of behavior from the participants, and perceptions of participants’ behavior from four people who know them well (i.e., informants). Specifically, I asked participants and their informants to provide ratings describing the participant’s typical behavior including evaluative (e.g., bragging) and neutral behaviors (e.g., talking). By comparing self- and informant-perceptions to actual behavior captured by the EAR, I am able to test my hypothesis that people have insight into their neutral behaviors, but others know more than the self about evaluative behaviors. We have finished data collection on two studies and are now in the process of coding behavior from the audio and video files. We will then conduct analyses to determine whether self-reports or reports from close others are more accurate for predicting how a person behaves. I predict that the self-reports will be more accurate for neutral behaviors, but close others will be more accurate at predicting evaluative behaviors. Preliminary analyses suggest that self-reports of evaluative behaviors (e.g., moral behaviors) may be inaccurate, and close others’ ratings are likely to provide insight not available from people’s self-reports. This research will inform social psychological work on the self, illuminating the processes that contribute to accuracy and bias in self-perception. Furthermore, identifying the blind spots in self-perception can help us discover how self-knowledge can be improved, a central goal of psychological inquiry and practice. Finally, this research will have important implications for anyone relying on self-reports to measure behavior. I anticipate that this line of research will lead to an empirically-validated model to guide researchers’ and practitioners’ decisions about when to use self- or informant-reports. In addition, this grant has helped promote the involvement of underrepresented groups in scientific research by supporting a research team from a wide variety of backgrounds, including women scientists, researchers from minority ethnic groups, and first-generation college students.
