The Bivariate Model of Self-Monitoring
Self-Monitoring and Getting Ahead Criteria
Status has major implications for success in social and organizational hierarchies. Accordingly, researchers have shown great interest in the dispositional antecedents of getting ahead criteria. Among antecedents, few constructs have stimulated as much interest and debate as self-monitoring (Snyder, 1987). Self-monitoring concerns individual differences in the expressive control of public self-presentations, and is among the most studied self-presentational constructs in the psychological and management literatures.
For 45 years, the dominant model has been that self-monitoring is univariate, typological (i.e., high vs. low self-monitors), and distinct from other psychological constructs (i.e., the Big Five personality traits). Further, self-monitoring theory posits that the motivational foundation of self-monitoring is a concern for and ability to get ahead in social hierarchies.
My research contests this prevailing univariate model. I show that the theoretical structure of self-monitoring is not typological, but is better described in terms of two self-monitoring dimensions: acquisitive self-monitoring involves using self-presentation to gain social approval, whereas protective self-monitoring concerns social disapproval avoidance (Wilmot, 2015). Because these dimensions are uncorrelated, we advocate their separate assessment in a bivariate model, which we use to test other fundamental claims about self-monitoring. In contrast to the claim about psychological distinctness, we show that the bivariate model is integral to the Big Five model, at the metatrait level. Acquisitive self-monitoring relates positively to metatrait Plasticity (i.e., covariance of Extraversion and Openness/Intellect), and protective self-monitoring relates negatively to metatrait Stability (i.e., covariance of Emotional Stability, Agreeableness, and Conscientiousness; Wilmot, DeYoung, Stillwell, & Kosinski, 2016). Regarding the theoretical links to getting ahead criteria, we use meta-analysis to compare univariate and bivariate self-monitoring models to getting ahead criterion variables (i.e., motivations for status, enterprising vocational interests, social status, leadership emergence, promotions/ advancement, salary attainment, and leadership role occupancy). Findings indicate that the bivariate model has greater incremental and relative importance than the univariate model. What is more, acquisitive self-monitoring is the sole source of getting ahead criteiron prediction, establishing it as one of the strongest predictors in the literature. By comparison, protective self-monitoring shows nil/negative relations (Wilmot, Ones, & Barbuto, under review). Results suggest a paradigm shift is needed to the bivariate model of self-monitoring. Accordingly, we developed acquisitive and protective self-monitoring scales from items comprising the original Self-Monitoring Scale (Wilmot, Kostal, Stillwell, & Kosinski, 2017). By using the SMS as the item pool, 45 years of archival data can be reanalyzed anew via our bivariate model.
Acquisitive and Protective Self-Monitoring Scales
The interested reader can take advantage of our IRT-based scoring approach by applying item parameters to their raw SMS data. IRT parameters are available for data that use either true-false or 5-point Likert-type response formats.
We are in the process of developing a user-friendly scoring program that will enable researchers to score their data online. While this function is currently under construction, please feel free to download the relevant parameter estimates and contact me for assistance in scoring raw data.
Status has major implications for success in social and organizational hierarchies. Accordingly, researchers have shown great interest in the dispositional antecedents of getting ahead criteria. Among antecedents, few constructs have stimulated as much interest and debate as self-monitoring (Snyder, 1987). Self-monitoring concerns individual differences in the expressive control of public self-presentations, and is among the most studied self-presentational constructs in the psychological and management literatures.
For 45 years, the dominant model has been that self-monitoring is univariate, typological (i.e., high vs. low self-monitors), and distinct from other psychological constructs (i.e., the Big Five personality traits). Further, self-monitoring theory posits that the motivational foundation of self-monitoring is a concern for and ability to get ahead in social hierarchies.
My research contests this prevailing univariate model. I show that the theoretical structure of self-monitoring is not typological, but is better described in terms of two self-monitoring dimensions: acquisitive self-monitoring involves using self-presentation to gain social approval, whereas protective self-monitoring concerns social disapproval avoidance (Wilmot, 2015). Because these dimensions are uncorrelated, we advocate their separate assessment in a bivariate model, which we use to test other fundamental claims about self-monitoring. In contrast to the claim about psychological distinctness, we show that the bivariate model is integral to the Big Five model, at the metatrait level. Acquisitive self-monitoring relates positively to metatrait Plasticity (i.e., covariance of Extraversion and Openness/Intellect), and protective self-monitoring relates negatively to metatrait Stability (i.e., covariance of Emotional Stability, Agreeableness, and Conscientiousness; Wilmot, DeYoung, Stillwell, & Kosinski, 2016). Regarding the theoretical links to getting ahead criteria, we use meta-analysis to compare univariate and bivariate self-monitoring models to getting ahead criterion variables (i.e., motivations for status, enterprising vocational interests, social status, leadership emergence, promotions/ advancement, salary attainment, and leadership role occupancy). Findings indicate that the bivariate model has greater incremental and relative importance than the univariate model. What is more, acquisitive self-monitoring is the sole source of getting ahead criteiron prediction, establishing it as one of the strongest predictors in the literature. By comparison, protective self-monitoring shows nil/negative relations (Wilmot, Ones, & Barbuto, under review). Results suggest a paradigm shift is needed to the bivariate model of self-monitoring. Accordingly, we developed acquisitive and protective self-monitoring scales from items comprising the original Self-Monitoring Scale (Wilmot, Kostal, Stillwell, & Kosinski, 2017). By using the SMS as the item pool, 45 years of archival data can be reanalyzed anew via our bivariate model.
Acquisitive and Protective Self-Monitoring Scales
The interested reader can take advantage of our IRT-based scoring approach by applying item parameters to their raw SMS data. IRT parameters are available for data that use either true-false or 5-point Likert-type response formats.
We are in the process of developing a user-friendly scoring program that will enable researchers to score their data online. While this function is currently under construction, please feel free to download the relevant parameter estimates and contact me for assistance in scoring raw data.
| sm_parameter_estimates.xlsx |