Individual difference construct that captures an individual’s ability to observe and control one’s own behavior, based on situational cues and social appropriateness.
Self-monitoring is a personality trait or individual difference that reflects the fact that people meaningfully differ in whether (or how) they regulate their behavior in different social situations (Snyder 1974). “Behavior” in this sense reflects both the language one uses in a social setting, as well the nonverbal communication (e.g., facial expressions, body language) employed, based on an individual’s appraisal of which actions are appropriate for a given context. Self-monitoring is viewed as existing on a continuum, such that individuals range from “low” to “high” in their tendency to alter their behavior based on social cues from one context to the next. On one end, high self-monitors (HSMs) are exceptionally attuned to social situations and can be chameleon-like in their actions and behaviors from one context to another. Conversely, low self-monitors (LSMs) “are not controlled by deliberate attempts to appear situationally appropriate; instead, their expressive behavior fundamentally reflects their own inner attitudes, emotions, and dispositions” (Gangestad and Snyder 2000: 531). According to Day and Schleicher (2006) and predicated on socioanalytic theory (Hogan 1983, 1991; Hogan et al. 1985), HSMs are focused on two of three broad motive patterns: getting along (e.g., acceptance and approval) and getting ahead (e.g., status, power, and the control of resources) – predictability and order, the third motive pattern within socioanalytic theory, is not a consideration within the purview of self-monitoring.
Self-monitoring, as a personality construct, has been predominantly measured with self-report scales. Measurement of self-monitoring has been the subject of considerable debate since the first item battery was proposed by Snyder (1974). Based on an initial set of validity concerns proposed by several authors (e.g., Briggs and Cheek 1986, 1988; Briggs et al. 1980; Lennox and Wolfe 1984), the original 25-item scale was amended by Snyder and Gangestad (1986) to an 18-item scale which was purported to have greater psychometric properties. Indeed, the Snyder and Gangestad (1986) scale is currently the standard measure of self-monitoring, although a contingent of scholars remain skeptical of its validity (e.g., Parks-Leduc et al. 2014; Warech et al. 1998). Whether self-monitoring should be considered as a single higher-order factor (e.g., Gangestad and Snyder 1986) or a multidimensional construct (Warech et al. 1998) that combines elements of motivation and skill (Parks-Leduc et al. 2014) remains an open question in the literature.
Nevertheless, a significant volume of research has been compiled over the past 30 years regarding how self-monitoring influences individuals in the workplace. In terms of direct effects, the most recent comprehensive meta-analysis on the subject (Day et al. 2002) found that self-monitoring has moderate positive relationships with leadership (r = 0.21) (all correlations provided in this section are from the Day et al. (2002) meta-analysis and were corrected for measurement error) and job involvement (r = 0.22), as well as a weak positive relationship with overall job performance (r = 0.10). These findings lend support to the general notion that HSMs are highly focused on “getting along and getting ahead” (Day and Schleicher 2006). Self-monitoring also has modest relationships with some demographic variables, including age (r = −0.08) and gender (r = 0.13, indicating that males are more likely to be higher in self-monitoring; Day et al. 2002).
However, self-monitoring also has a “dark side,” in that HSMs have been linked to several negative work outcomes. Self-monitoring has a moderately positive relationship with job ambiguity (r = 0.24) and weaker relationships with organizational commitment (r = −0.13) and role conflict (r = 0.17; Day et al. 2002). These findings suggest that HSMs may be more likely to lack clarity in their job roles relative to LSMs and that the “getting ahead” motive among HSMs can lead to decreased support and affiliation with employers. Indeed, Caligiuri and Day (2000) found that self-monitoring was negatively related to contextual performance (operationalized via non-self-report items that measure employee motivation, commitment, and strength of working relationships) among expatriates (i.e., employees working in a different country than their place of origin), perhaps because the contextual ambiguity that is inherent in an expatriate assignment creates difficulty for HSMs to effectively adapt their behavior (Bedeian and Day 2004). Along these same lines, Allen et al. (2005) found that self-monitoring is positively related to turnover. Interestingly, the authors also found that high levels of self-monitoring attenuate the relationship between turnover intentions and actual turnover.
Another “dark side” aspect of self-monitoring relates to trustworthiness. Ogunfowora et al. (2013) found that self-monitoring is negatively related to trait honesty-humility (Ashton and Lee 2005), which suggests that HSMs are more likely to be dishonest and driven by a motive for personal gain. In their study, the authors also found that HSMs were more likely than their LSM counterparts to engage in moral disengagement and unethical decision making. In fact, additional studies have found that HSMs are less likely to achieve consistency in 360-feedback (i.e., multi-rater/source feedback) ratings (Miller and Cardy 2000), and that while HSMs may enjoy larger social networks than LSMs, they also experience significantly higher levels of close friendship tie dissolutions over time (Bhardwaj et al. in press). In total, these findings suggest that HSMs can be perceived as disingenuous by others, particularly as the time in a relationship increases.
Self-monitoring has also been examined as a potential moderator variable across a number of different studies. In regard to social network development, Kleinbaum et al. (2015) found that self-monitoring interacts with trait empathy, such that HSMs that are also perceived as highly empathic have stronger social networks than low empathy/HSM individuals. Additionally, Barrick et al. (2005) compared the relationship between performance ratings and Big Five personality traits between HSMs and LSMs and found that the positive effects of multiple Big Five traits on performance were attenuated by high self-monitoring. Specifically, the benefits of the Big Five traits of extraversion and emotional stability were less pronounced for HSMs. From a counterproductive work (CWB) perspective, Oh et al. (2014) also found moderation effects for self-monitoring related to the Big Five: high levels of self-monitoring suppressed the effects of low agreeableness on the enactment of individually-focused CWB, while the combination of high self-monitoring and low conscientiousness resulted in higher levels of organizationally focused CWB.
Finally, Turnley and Bolino (2001) investigated the interaction between self-monitoring and impression management tactics, including ingratiation (the use of flattery or favors to seem likeable), self-promotion (the “playing up” of abilities to seem competent), and exemplification (exceeding expectations to appear dedicated). Using a sample of student work groups, the authors found that HSMs achieve more favorable image outcomes than LSMs when using these impression management tactics, thus demonstrating the ability of HSMs to effectively manipulate others to achieve personal goals. In turn, Parks-Leduc et al. (2014) extended the aforementioned multidimensional view of self-monitoring by Warech et al. (1998) with their findings that self-monitoring skill is positively related to extraversion, while self-monitoring motivation is positively related to “power” values (e.g., authority, wealth, social recognition, prestige). In total, these (and other) studies suggest that self-monitoring as a theoretical construct encompasses multiple perspectives.
To conclude, there are multiple avenues of exploration that remain available to researchers to study self-monitoring. First, debate over the theory and measurement of self-monitoring continues to rage. In their second rebuttal to critics, Gangestad and Snyder (2000) agreed that their revised scale presents a multifactorial structure, interpreted by others as three factors: acting, extraversion, and other-directedness. Yet, the authors also argue that the preponderance of research supports the validity of an overarching latent variable (e.g., self-monitoring) above the three factors. Nevertheless, whether self-monitoring should be viewed and measured as a single entity or a multidimensional construct remains unresolved. Second, it is also worth noting that, although considerable research on self-monitoring has been compiled since the Day et al. (2002) meta-analysis, no comprehensive meta-analytic update has since been compiled, thus providing another prospect for interested researchers. In summary, it is clear that there are still considerable opportunities for continued research into self-monitoring in the future.
- Bhardwaj, A., Qureshi, I., Konrad, A. M., & Lee, S. H. M. (in press). A two-wave study of self-monitoring personality, social network churn, and in-degree centrality in close friendship and general socializing networks. Group & Organization Management. doi:10.1177/1059601115608027.Google Scholar
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