Encyclopedia of Personality and Individual Differences

Living Edition
| Editors: Virgil Zeigler-Hill, Todd K. Shackelford

Self-Monitoring Scale

  • Michael P. WilmotEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-28099-8_82-1




Self-monitoring is a personality variable defined as the extent to which individuals are willing and able to engage in the expressive control of their public self-presentations, which is measured using the Self-Monitoring Scale (SMS; Snyder 1974; Snyder and Gangestad 1986). Recent work indicates that self-monitoring is better described as comprising two distinct forms of self-presentation, acquisitive and protective. Accordingly, researchers have repurposed the SMS to assess these two self-monitoring dimensions (Wilmot et al. 2015).


Self-monitoring (Snyder 1974) is a major construct of interest in the personality and social psychological literature. Traditionally, self-monitoring has been assessed using total SMS scores, which are interpreted as tapping a single, unitary variable that is categorically distributed (i.e., high vs. low self-monitors; Snyder and Gangestad 1986). At the turn of the century, quantitative reviews appeared to provide evidence for the construct validity of this univariate model of self-monitoring (Day et al. 2002; Gangestad and Snyder 2000), which served to stimulate interest in, and broader use of, the SMS.

Empirical success notwithstanding, emerging evidence challenges key assumptions and measurement practices of the conventional model. First, factor analyses of the SMS indicate that the scale is multidimensional in both its original 25-item (Briggs et al. 1980) and revised 18-item versions (SMS-R; Briggs and Cheek 1988; Snyder and Gangestad 1986). Further, evidence from taxometric analysis shows that the SMS does not, in fact, assess one typological variable but rather captures variance from two independent dimensional variables: acquisitive and protective self-monitoring (Wilmot 2015). Finally, finding that acquisitive and protective self-monitoring have divergent networks of relations to external variables (Briggs and Cheek 1988; Wilmot et al. 2016) has prompted the call to conceptualize and assess these dimensions separately in a bivariate model (Wilmot et al. 2015). However, little was known about the comparative validity of these two self-monitoring models until recently.

Psychometric Properties

Wilmot et al. (under review) used meta-analysis to appraise the respective evidence for the univariate and bivariate models of self-monitoring. As part of this investigation, authors examined the internal consistency reliability of the SMS, the SMS-R, and SMS-based factorial subscale measures of acquisitive and protective self-monitoring (Briggs and Cheek 1988, p. 664); results are reproduced in Table 1. As Table 1 shows, the reliability of the 25-item SMS is quite modest (α = .70), and the reliability of the 18-item revision is slightly higher (α = .72). Relatively low reliability coefficients reflect the multidimensionality of the SMS, that is, total SMS scores are blends of scores from the two distinct dimensions of acquisitive (α = .72) and protective self-monitoring (α = .67). Thus, psychometric evidence favors the bivariate model.
Table 1

Frequency-weighted artifact distributions of reliability coefficients





\( \overline{r} \) xx

SD r

Univariate model


 Self-Monitoring Scale

Snyder (1974)





 Self-Monitoring Scale-Revised

Snyder and Gangestad (1986)





Bivariate model a


Acquisitive self-monitoring subscale

Briggs and Cheek (1988)





Protective self-monitoring subscale





Note. k total number of independent samples, \( \overline{r} \) xx mean internal consistency coefficient, SD r standard deviation of internal consistency coefficients (Table reproduced with permission from Wilmot et al. (under review))

Relations to External Variables

Prior reviews concluded that self-monitoring is a unique, distinct psychological construct that predicts theoretically relevant behavior (e.g., expressive control; Gangestad and Snyder 2000) and work-related variables (e.g., leadership; Day et al. 2002). Wilmot et al. (under review) retested these claims by conducting an updated and expanded meta-analysis of univariate and bivariate models and their respective relations to other psychological constructs (e.g., Big Five personality traits) and to work-related variables – especially those linked to motivations for, and ability to attain, status (e.g., leadership role occupancy; Gangestad and Snyder 2000, p. 548).

Concerning relations to other psychological constructs, results disconfirmed prior review claims. Meta-analytic findings indicated that self-monitoring only appears to be an independent construct because the practice of using total SMS scores obscures the divergent relations of its two underlying factors. However, upon their separation, results indicated that acquisitive self-monitoring related positively to agentic variables (i.e., Extraversion and Openness/Intellect), whereas protective self-monitoring related negatively to communal variables (e.g., Emotional Stability, Agreeableness, Conscientiousness; Wilmot et al., under review). Evidence of divergent networks across factors provided meta-analytic confirmation of a related finding that acquisitive and protective self-monitoring are largely integral to the consensual taxonomy of personality traits, but are located above the Big Five, at the metatrait level (Wilmot et al. 2016). Indeed, studies provided convergent evidence that acquisitive self-monitoring and metatrait Plasticity, the higher-order personality trait composed of the shared variance of Extraversion and Openness/Intellect, are virtually equivalent constructs (p. 342).

Concerning work-related criteria, meta-analytic results again contrasted with prior review claims (Wilmot et al., under review). Although the SMS related positively to criteria reflecting concerns for, and ability to obtain, social status (e.g., interpersonal task performance, leadership emergence, job offers/promotions), upon separation into its bivariate model measures, the source of this underlying prediction was revealed. Across all variables examined, ostensible SMS effects were found to fully attributable to acquisitive self-monitoring; by comparison, protective self-monitoring had nil, even negative, relations to the variables examined. What is more, with the theoretically irrelevant variance of the protective dimension removed, criterion relations of acquisitive self-monitoring scores were appreciably stronger than scores of the SMS.

Taken together, cumulative meta-analytic findings provided consistent, convergent evidence against the univariate model of self-monitoring and support for the bivariate model. Authors concluded that 45 years of self-monitoring research has led to a somewhat ironic and unexpected conclusion. That is, the self-monitoring literature is not about self-monitoring after all. Rather, the construct at its heart is acquisitive self-monitoring, a construct that is synonymous with metatrait Plasticity (Wilmot et al., under review).

Recommendations for Assessment

Based on the meta-analytic evidence, data-analytic procedures and assessment practices associated with the conventional self-monitoring model merit serious reconsideration. First, although the familiar typology of high versus low self-monitors may have some heuristic value, any continued treatment of these classes as an ontological reality is empirically indefensible (Wilmot 2015). Second, sampling methods (i.e., range enhancement using extreme SMS scores) and data manipulation (i.e., artificially dichotomization) that reflect categorical assumptions should be replaced by dimensional approaches and corresponding statistical procedures. Finally, seeing as total SMS scores conflate variance from the two independent dimensions of acquisitive and protective self-monitoring, each of which have demonstrably divergent empirical relations to external variables, there appears to be no logical reason to continue using total SMS scores.

Instead, researchers are urged to use bivariate model measures. In particular, Wilmot et al. (2015) used item response theory (IRT) to develop measures of acquisitive and protective self-monitoring from the original SMS. A representative acquisitive self-monitoring item is, “I would probably make a good actor,” while an item representative of protective self-monitoring is, “I’m not always the person I appear to be.” Results indicate that the new acquisitive (six-item) and protective (seven-item) self-monitoring scales are reliable, unbiased in terms of gender and age, and show theoretically consistent relations to measures of personality traits and cognitive ability. Additionally, authors report IRT parameter estimates for both dichotomous (i.e., true-false) and polytomous (i.e., 5-point Likert-type) response formats (Wilmot et al. 2015).

Although the acquisitive and protective self-monitoring scales hold promise for future research, they have particular value for reanalyzing archival data. By virtue of using the SMS as the original item pool for the new measures, previously collected responses can be reanalyzed according to the bivariate model; for recommendations for reanalysis and online data scoring, see Wilmot et al. (2015). Finally, it bears reiterating that acquisitive self-monitoring and Plasticity are the same construct (Wilmot et al. 2016). As such, the new acquisitive self-monitoring scale is presently the first and only validated direct-measure of Plasticity in the published literature.


The construct of self-monitoring and its associated measure, the Self-Monitoring Scale, have a rich, if controversial, history of research. Although recent meta-analytic evidence now indicates that the conventional model of self-monitoring (i.e., self-monitoring as a univariate, typological variable that is best assessed by total SMS scores) should be abandoned, this by no means marks the end of self-monitoring research. Much to the contrary: The bivariate model, a model that repurposes the SMS to assess the two independent dimensions of acquisitive and protective self-monitoring, represents the next generation of self-monitoring scholarship. This bivariate model, and its IRT-based scales built from the original SMS, will help to propel new and deeper investigations into the antecedents and consequences of individual differences in self-presentational behavior.



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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of PsychologyUniversity of MinnesotaMinneapolisUSA

Section editors and affiliations

  • Brendan Clark
    • 1
  1. 1.Wichita State UniversityWichitaUSA