Testing the Structured Free Recall Intervention for Reducing the ...

J Bus Psychol (2012) 27:205–222 DOI 10.1007/s10869-011-9240-7

Testing the Structured Free Recall Intervention for Reducing the Impact of Bodyweight-Based Stereotypes on Performance Ratings in Immediate and Delayed Contexts Cort W. Rudolph • Boris B. Baltes • Ludmila S. Zhdanova • Malissa A. Clark Anne C. Bal

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Published online: 9 July 2011 Ó Springer Science+Business Media, LLC 2011

Abstract Purpose This article investigates the efficacy of the Structured Free Recall Intervention (SFRI; J Bus Psychol 15:229–246, 2000a; Organ Behav Hum Decis Process 82:237–267, 2000b) for reducing the impact of bodyweight-based stereotype endorsement on performance ratings, both immediately and when a time delay occurs between the observation and rating of performance. Design/Methodology/Approach 512 undergraduates participated in a 2 9 2 9 2 between-subjects factorial experiment. A measure of bodyweight-based stereotype endorsement was pre-screened, and participants were randomly assigned to (a) either a no-delay or two-day time delay condition, (b) view either an average bodyweight or overweight ratee, and (c) undergo the SFRI or not. Findings Results suggest that (a) bodyweight-based stereotype endorsement predicts performance ratings for overweight ratees, (b) the SFRI is effective at reducing the impact of such stereotypes on performance ratings when conducted immediately after the observation of performance, and (c) the SFRI

C. W. Rudolph (&) Department of Psychology, Florida International University, DM 256, 11200 S.W. 8th street, Miami, FL 33199, USA e-mail: [email protected]; [email protected] B. B. Baltes
A. C. Bal Department of Psychology, Wayne State University, Detroit, MI, USA L. S. Zhdanova Department of Psychology, Carleton University, Ottawa, ON, Canada M. A. Clark Department of Psychology, Auburn University, Auburn, AL, USA

maintains this efficacy after a two-day delay between the observation and rating of performance. Implications These findings suggest that the best realworld application of the SFRI paradigm may be to situations with minimal delays between the observation and rating of performance, such as selection assessment centers or pre-employment interviews. Originality/Value Drawing on theories from the cognitive information processing literature, this paper extends previous research regarding the efficacy of the SFRI by demonstrating that short time delays between performance observation and rating—a common organizational phenomena—have minimal observed effects on the efficacy of the SFRI as a performance rating intervention. Keywords Performance rating
Stereotype endorsement
Bodyweight-based bias
Structured free recall intervention (SFRI) Although demographic characteristics such as age, race, and sex can influence judgments of ratee performance (Murphy and Cleveland 1995), such characteristics typically have small and inconsistent effects on actual performance ratings (e.g., Ford et al. 1986; Huffcut and Roth 1998; Kraiger and Ford 1985). As a means of explaining this variability, researchers have examined the relationship between explicitly endorsed stereotypes and performance ratings. Such research suggests that raters who endorse stereotypes that negatively characterize a specific group consistently and systematically provide lower performance ratings to members of that group (e.g., Baltes et al. 2007; Bauer and Baltes 2002; Dobbins et al. 1988; Rudolph and Baltes 2008). With respect to this phenomenon, this study was conducted to address two related goals. The first was to explore the impact that explicitly endorsed bodyweight-based

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stereotypes have on performance ratings. While the impact of bodyweight on evaluative workplace outcomes has been studied for over 30 years (e.g., Judge and Cable 2011; King et al. 2006; Larkin and Pines 1979; Nieminen et al. in press; Roehling et al. 2007; 2008), we know little about how the endorsement of workplace-specific bodyweightbased stereotypes impact performance ratings. As we will explore, this gap in the literature is unfortunate given the strength of the theory supporting the prediction that bodyweight-based stereotypes affect performance ratings. The second goal of this study was aimed at applying an intervention to mitigate this effect. Specifically, this study sought to demonstrate the efficacy of the Structured Free Recall Intervention (SFRI; Baltes and Parker 2000a, b) for reducing the impact of bodyweight-based stereotypes on performance ratings, both immediately, and after a delay between the observation and rating of performance. While past research has suggested various means for reducing bodyweight-based bias in general (e.g., manipulating beliefs about the controllability of bodyweight—Crandall and Moriarty 1995; Rodin et al. 1989; Tiggemann and Anesbury 2006; manipulating social consensus regarding bodyweight attitudes—Puhl et al. 2005), there have been few studies that have attempted to mitigate the influence of this bias in practical ways that organizations could implement. Furthermore, and perhaps just as importantly, no study has addressed how the influence of time delays between performance observation and rating impacts the efficacy of the SFRI intervention. With these goals in mind, this study employed a 2 (time delay: no-delay or two-day delay) 9 2 (ratee bodyweight: average bodyweight or overweight) 9 2 (intervention: SFRI or no SFRI) between-subjects experimental design to test the efficacy of the SFRI for reducing the impact of bodyweightbased stereotype endorsement on performance ratings in both immediate and delayed rating contexts. While the specifics of this design will be discussed at length later, we will now turn our attention to the theory, processes, and phenomena relevant to the current investigation.

Bodyweight-Based Bias in the Workplace A recent trend indicating a rise in obesity rates in the United States has led some researchers to conclude that bodyweight may represent ‘‘the new race’’ when it comes to workplace discrimination (Randle and Bell 2009). Indeed, an emerging literature suggests that bodyweightbased discrimination is a rampant and detrimental workplace phenomenon (for a summary and qualitative review, see Crandall et al. 2009; for a review of workplace and legal implications, see Roehling 1999; for a quantitative review of workplace literature, see Rudolph et al. 2009).

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Research on bodyweight-based bias suggests that overweight individuals are negatively affected across many aspects of work life, such as hiring decisions (e.g., Finkelstein et al. 2007; Larkin and Pines 1979; Pingitore et al. 1991; Roehling 1999), promotions (e.g., Rothblum et al. 1990), and training expectations and appraisals (Shapiro et al. 2007). In addition, this effect generalizes across various levels of employment, evidenced by the fact that overweight individuals are judged negatively in the roles of the subordinate, coworker, and supervisor (Roehling 1999; Rudolph et al. 2009).

Theory Explaining Bodyweight-Based Bias in the Workplace Theories explaining why the endorsement of bodyweightbased stereotypes impact performance ratings can be borrowed from a number of psychological domains. To this end, Stigma Theory (e.g., Goffman 1963) provides a useful framework for understanding how bodyweight may affect performance ratings. According to Stigma Theory, a stigmatized person is perceived to possess a set of attributes that mark them as different, which leads them to be devalued by others through the use of stereotypes and subsequently negative evaluations (Crocker et al. 1998; Major and O’Brien 2005). In terms of bodyweight, Goffman (1963) suggests that overweight individuals are dually stigmatized by both abominations of the body (i.e., stigmas regarding physical deformities) and blemishes of individual character (i.e., stigmas that are the responsibility of the stigmatized). Extending this notion, Crocker et al. (1998) argues that the visibility (i.e., concealability) and controllability (i.e., origin) of stigma are the most salient dimensions when considering the impact of stigma of various evaluations. Because visible stigma cannot be easily hidden from others, they provide a readily available schema with which to view and judge the stigmatized (Crocker et al. 1998). Furthermore, perceptions of the controllability of stigma also impact how the stigmatized are perceived and treated. This is due to the fact that people often make internal attributions for stigmatized characteristics that are perceived as controllable. Indeed, across a variety of evaluative scenarios, those with a controllable stigma often experience harsher judgments than those with an uncontrollable stigma (e.g., Seacat et al. 2007). Because excess bodyweight is visible and perceived as a controllable condition (e.g., Weiner et al. 1988), raters may be excessively harsh towards overweight individuals in evaluative contexts, particularly if one is making judgments on factors directly attributable to the entity, such as ratings of individual job performance.

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One modern interpretation of Stigma Theory provides some insight into how and why stereotypes regarding bodyweight may influence the evaluation of overweight ratees, particularly, in workplace contexts. Specifically, the Stereotype Content Model (SCM; Fiske et al. 2002) suggests that stereotypes vary along two basic dimensions: warmth and competence. According to the SCM, the point at which a particular stereotype is located along these two dimensions predicts reactions toward a stigmatized target. Because excess bodyweight is perceived as a controllable factor (e.g., Weiner et al. 1988), and is often associated with perceptions of laziness (e.g., Hebl and Kleck 2002), stereotypes regarding overweight individuals are likely to be low on both warmth and competence. This ‘‘low–low’’ combination is said to be indicative of the worst possible amount of stigmatization (Fiske et al. 2002). Likewise, affective reactions towards overweight individuals are often marked by disgust and contempt (Crandall et al. 2009). Like schema (Hastie 1981), stigmas are also highly context-dependent (e.g., Crocker et al. 1998). Within a workplace performance judgment scenario, if one is perceived as lazy (i.e., unmotivated), cold1 (Sorge 2008), and incompetent, as a result of their bodyweight, such perceptions can carry over to influence performance judgments. In terms of these theories, it is interesting to note that motivation, warmth, and competence represent important dimensions of both contextual and task performance (e.g., Borman and Motowidlo 1997; Motowidlo and Van Scotter 1994). Thus, stereotypes that characterize overweight individuals as low on these dimensions may be particularly damning in situations where job performance is being evaluated. Interestingly, workplace-specific bodyweight stereotypes closely map onto this general model. Specifically, commonly endorsed stereotypes of overweight individuals in workplace contexts suggest among other things that overweight individuals lack self-discipline and self-control (e.g., Bellizzi and Norvell 1991); are lazy and unmotivated (e.g., Klassen et al. 1993); are less conscientious, competent, and skilled, are of a lower ability, possess poor work habits, and are more likely to be absent from work (Klesges et al. 1990); and are less likely to get along with and be 1

Interestingly, there is some evidence to suggest that people’s implicit theories about the controllability of bodyweight may influence perceptions of warmth in terms of SCM. Sorge (2008) suggests that incremental theorists (i.e., those who see bodyweight as a controllable factor) tend to categorize overweight people as both low competence and low warmth. However, entity theorists (i.e., those who see bodyweight as a stable, uncontrollable factor) tend to perceive overweight people as low competence, but high warmth. These differences in the perception of warmth and competence may help to explain the mixed content (i.e., positive and negative characterizations) of stereotypes that describe overweight individuals.

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accepted by their coworkers and subordinates (e.g., Boridieri et al. 1997). With regard to measuring bodyweight-based stereotypes, research has shown that the endorsement of negative bodyweight-based stereotypes is more widely accepted than the endorsement of negative racial or gender stereotypes (Cossrow et al. 2001; Cramer and Steinwert 1998; Finkelstein et al. 2007; Pingitore et al. 1991; Puhl et al. 2005). Moreover, bodyweight-based stereotypes are one of the few forms of negative stereotypes still viewed as socially acceptable to explicitly endorse (Finkelstein et al. 2007). Indeed, measures of bodyweight-based stereotypes are less susceptible to socially desirable response patterns than other forms of stereotypes, such as race (Crandall 1994). Furthermore, stereotype endorsement is an important consideration in the study of performance ratings, because research that has examined individual differences in explicit stereotype endorsement has garnered strong empirical and theoretical support for the predictive ability of explicitly endorsed stereotypes to account for explicit behavior and judgments (e.g., Baltes et al. 2007; Bauer and Baltes 2002; McConahay 1983; Stewart and Perlow 2001). Measuring the explicit endorsement of stereotypes is also important, because research has demonstrated that stereotype endorsement can vary widely between individuals (Devine 1989). In support of this notion, research has found that individuals who endorse negative stereotypes provide lower ratings to targets who possess a stigma that matches the stereotype under investigation, while individuals who do not endorse the stereotype likewise do not provide biased ratings to these same targets. Thus, to accurately examine how stereotypes affect performance ratings one must move beyond considering main effect differences between ratees, and instead measure individual differences in stereotype endorsement. Applying this method allows one to directly test whether a rater’s level of stereotype endorsement affects performance ratings.

The Nature of Performance Ratings Performance ratings differ from formal performance evaluations in that the former tends to occur in short-timeframe and limited-contact situations, such as ratings of preemployment interviews or assessment center performance,2 2

Although this situation may be most commonly encountered in a pre-employment context, this scenario may also occur at various other stages of the employment process. A classic example comes to us from academia, where tenure review boards are often comprised of people who may be assessing individuals on the basis of limited amounts of information (e.g., vitae, letters of recommendation) and/or limited amounts direct interpersonal contact.

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whereas the latter tends to encompass a longer time frame with an increased level of contact between the rater and ratee. This distinction is important to note because a different set of dependencies and contextual factors accompany performance evaluation situations (i.e., motivated rating, various dyadic processes, etc.). Given that evidence from social psychological research suggests that intergroup contact serves to lessen bias (e.g., Allport 1954; Pettigrew and Tropp 2006) and that increasing individuating information regarding stigmatized ratees can have a similar effect (e.g., Fiske and Neuberg 1990), it is not surprising that performance ratings—which do not provide much chance for these processes to occur—are particularly susceptible to the impact of stereotypes. It is interesting to note that this phenomenon is relatively understudied, despite the fact that the results of performance ratings can represent high-stake evaluative outcomes for organizations. Based on this notion and the theory reviewed that suggests how excess bodyweight can be detrimental in performance rating scenarios, we expect that a relationship exists between individuals’ endorsement of bodyweightbased stereotypes and performance ratings for overweight ratees. Hypothesis 1 There is a negative relationship between the strength of negative bodyweight-based stereotype endorsement and level of performance ratings.

Reducing the Effects of Stereotype Endorsement on Performance Ratings Given that prior research provides support for the argument that stereotype endorsement can affect performance ratings, reducing the impact of stereotypes is an important issue for organizations to address from an ethical, legal, and fairness perspective. To this point, it would be helpful to identify an intervention that could reduce the relationship between stereotype endorsement and performance ratings, such that biased raters no longer exhibit biased ratings, without affecting the ratings of unbiased raters. Although several bias-reducing interventions exist (for reviews, see Fiske and Neuberg 1990; Fiske 1998), such interventions are either largely impractical for use by organizations (e.g., providing raters with stereotypeinconsistent information) or provide mixed and inconsistent results (e.g., motivating rater accuracy). However, a recently developed cognitively based intervention, the SFRI, has demonstrated compelling utility for reducing the impact of raters’ stereotype endorsement on performance ratings (e.g., Bauer and Baltes 2002; Baltes et al. 2007). The SFRI is an active intervention in which raters are instructed to explicitly recall and record both positive and

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negative behaviors that they have observed ratees performing before rating performance. The SFRI works by explicitly structuring the process of recalling positive and negative behaviors performed by the ratee. To understand how the SFRI works at a cognitive level, it is useful to consult the Threshold Cognitive Model used by Baltes et al. (2007). This model, which contrasts structured with unstructured free recall, suggests that stereotypes affect the strength of memory representations for specific behaviors observed by raters. Thus, stereotype-consistent memory representations are stronger than stereotype-inconsistent memory representations, and raters are more likely recall stronger memory representations than weaker representations. This suggests that when free recall is unstructured, stronger memory representations lead to biased recall and subsequently to biased performance ratings. This threshold model can also be used to explain the effectiveness of the SFRI for reducing the impact of stereotypes on performance ratings. Specifically, the SFRI works by modifying the retrieval threshold of observed behaviors. Because the SFRI asks raters to recall both positive behaviors (i.e., which are typically inconsistent with negative stereotypes) and negative behaviors (i.e., which are typically consistent with negative stereotypes) that they have observed ratees performing, both weak and strong memory representations are recalled and subsequently used in the rating process. Indeed, Baltes et al. (2007) found that raters who underwent the SFRI recalled both stereotype-consistent and stereotype-inconsistent memory representations, which led to unbiased free recall, and subsequently unbiased performance ratings (i.e., with respect to the stereotype in question). In essence, the SFRI severs the relationship between stereotype endorsement and the valence of behaviors recalled, thereby eliminating the effect of stereotypes on performance ratings. At least two published studies (i.e., Baltes et al. 2007; Bauer and Baltes 2002) and several unpublished studies (e.g., Palmer et al. 2009; Zhdanova et al. 2007) have demonstrated that a SFRI enacted immediately before rating performance can dramatically reduce the effect that the endorsement of a variety of stereotypes have on performance ratings. What is less understood is how this intervention will generalize to different ratees and rating scenarios. Thus, the decision to study the efficacy of the SFRI with bodyweight was 2-fold. First, as discussed previously, there is a great deal of evidence to suggest that bodyweight can bias evaluative workplace outcomes (e.g., Rudolph et al. 2009), and an intervention to lessen this effect would thus greatly benefit personnel practices and decisions. Second, while the efficacy of the SFRI has been demonstrated for race (e.g., Baltes et al. 2007) and gender (e.g., Bauer and Baltes 2002)-based biases, it is important to generalize across stimuli (i.e., bodyweight) to support

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the external validity of an intervention (Fontenelle et al. 1985). Thus, based upon the accumulated evidence concerning the efficacy of the SFRI for reducing raters’ reliance on stereotypes,3 the following hypothesis was tested in the condition with no time delay: Hypothesis 2 There is a three-way interaction between ratee bodyweight, SFRI, and bodyweight-based stereotype endorsement. Specifically, there is only a relationship between bodyweight-based stereotype endorsement and performance ratings when raters (a) rate an overweight ratee and (b) do not undergo the SFRI intervention.

Temporal Effects on the SFRI Intervention Although several studies have investigated the effect of temporal delays on performance ratings (e.g., Feldman 1981; DeNisi 1989; Judge and Ferris 1993), the effectiveness of the SFRI has not been examined when there is a time delay between the observation and rating of performance. Understanding the efficacy of the SFRI with the addition of a time delay is an important contribution of this study, because it is rare that the observation of performance immediately precedes the rating of performance in applied settings. What is more likely is for some period of delay to occur between performance observation and rating (Feldman 1981). Research investigating time delays in the performance rating process has suggested that contrary to the ‘‘noisy’’ environment of actual organizations, performance evaluation in research laboratories is likely to occur differently. One of the ways in which actual organizations are ‘‘noisier’’ is the possibility of time delays between receiving, processing, and encoding performance-relevant information and recalling it for the purposes of ratings (e.g., Feldman 1981; DeNisi 1989; Judge and Ferris 1993). For example, ratings may not be committed in a typical two-day assessment center until the conclusion of the second day (e.g., Byham 1971). To mimic such processes, this study utilized both immediate and delayed rating contexts to study the efficacy of the SFRI. A two-day delay was specifically chosen here, because this represents a reasonable proxy for the maximum amount of time

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It should be pointed out that an assumption is made here that stereotypes operate unconsciously (i.e., individuals do not realize how the stereotypes they endorse affect decisions they make such, as performance ratings). This assumption seems reasonable since social psychologists now argue that most prejudice is of an unconscious nature (e.g., Devine 1989; Devine and Elliot 1995). However, if individuals are consciously motivated to discriminate, then the SRFI will probably not have any effect, and the consciously discriminating person will still exhibit bias in their ratings.

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between performance observation and rating in a welldesigned and managed two-day assessment center. Despite the accumulated evidence for the benefits of the SFRI, the effectiveness of the intervention with a time delay between performance observation and performance rating has gone untested. Part of the concern regarding the efficacy of the SFRI under time delays can be explained by memory decay theory, which suggests that forgetting occurs if information is not activated for a period of time (Barrouillet and Camos 2001; Nelson and Goodman 2003). For example, Harris et al. (1989) demonstrate that people’s memory for specific details suffers after 2 days, as compared to shorter durations of time. Furthermore, research suggests that weaker memory representations are more quickly affected by memory decay. Thus, with the passage of time, stereotype-inconsistent (i.e., weaker) behaviors may be forgotten, making them irretrievable during the intervention, thus leading to biased free recall and subsequently biased performance ratings. This suggests that introducing a time delay into the performance rating process may lead to a decrease in the efficacy of the SFRI, such that even in the presence of the SFRI, the relationship between bodyweight-based stereotype endorsement and performance ratings may be observed in the presence of a time delay. Hypothesis 3 The efficacy of the SFRI for reducing the impact of bodyweight-based stereotype endorsement on performance ratings will be diminished when a two-day delay is introduced between the observation and rating of performance. Specifically, there is a three-way interaction between stereotype endorsement, SFRI, and time delay on performance ratings for overweight ratees, which suggests that after a time delay, the SFRI no longer aids in severing the relationship between stereotype endorsement and performance ratings. Beyond testing for the reduced efficacy of the SFRI in a delayed rating context, it is also interesting to consider the process by which the SFRI may lose this efficacy. As mentioned earlier, the SFRI achieves unbiased performance ratings by severing the relationship between stereotype endorsement and the overall valence of behaviors recalled during the SFRI. Thus, if the SFRI loses efficacy after a time delay, this should be evident in the relationship between stereotype endorsement and the valence of behaviors recalled. The cognitive theory of congruency bias can help to explain why this process may occur. Congruency bias posits that individuals are more likely to recall information that is consistent with an activated schema or stereotype (e.g., Brewer and Treyens 1981; Johnson et al. 1974). In a no-delay context, the SFRI helps to overcome this effect. However, in a time delay context, the process of memory decay may reintroduce the

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Method

overweight individuals in managerial positions within organizations (Randolph et al. 2007; Zhdanova et al. 2007). Thus, the OAMS was developed to contain items that tap both general stereotypes of obese individuals in the workplace (e.g., Obese people have poor work habits—see item 1 in the Appendix; Obese people possess lower competence—see item 4 in the Appendix) and specific stereotypes of obese people in managerial roles (e.g., Obese managers have more emotional problems—see item 2 in the Appendix; Obese people are less suitable for managerial professions—see item 6 in the Appendix; Obese managers lack motivation, are lazy, and do not try as hard as others—see item 8 in the Appendix). The OAMS contains statements rated on a 7-point Likert-type scale. The scale is anchored by strongly agree (7), neither disagree nor agree (4), and strongly disagree (1); items are averaged to form a composite score, ranging from 1 to 7. A higher overall score on the OAMS indicates stronger endorsement of negative stereotypes regarding overweight individuals as managers. Coefficient alpha for the OAMS across all conditions in this study was 0.83. As evidence for the unidimensionality of this index, an exploratory factor analysis was conducted (principal axis extraction, with a varimax rotation). The results indicated that a one-factor solution that accounted for 51% of the variance; factor loadings ranged from 0.52 to 0.85.

Participants

Performance Videos

Participants (N = 512) were drawn from the subject pool of a large, urban, Midwestern university, and were recruited to participate in exchange for extra credit in their university courses. Before involvement, participants were assigned to either a no-delay rating condition (N = 250) or a two-day delay condition (N = 262). Sample demographics were as follows: 62% of the sample was employed and worked an average of 19 h per week, the average age was 21, and 73% of the sample was female. The racialethnic composition was as follows: 10% Arabic/Middle Eastern, 11% Asian, 29% Black, 5% Hispanic, 7% Multiracial, and 38% White.

To manipulate the bodyweight of the ratee, two separate videos of approximately 2 min in duration (i.e., comprised of eight vignettes of approximately 15 s each) were developed using scripts borrowed from earlier research by Sulsky and Day (1992, 1994). These scripts were originally developed from a series of critical incidents of managerial performance identified by Roberson and Banks (1986), which were derived from earlier work (i.e., Borman 1977) that studied the interaction of managers and problem subordinates. These critical incidents are related to four separate performance dimensions: (a) motivating employees, (b) developing employees, (c) establishing and maintaining rapport, and (d) resolving conflicts. Using these scripts, each video presented identically scripted behaviors enacted by a white female actor who was either of average bodyweight or overweight (i.e., defined as 40% above normal body mass index). Actors were selected specifically to match age and gender, and to make differences in bodyweight as salient as possible. Specifically, the average weight actor was chosen based upon the criteria that they meet the Department of Health, Education and Welfare (DHEW) standard for normal weight (BMI = 20–25). The overweight actor was selected to meet the criteria of being approximately 140% of their ideal body weight. Under the

possibility of such a congruency effect—that is, it is plausible that through the memory decay process, the behaviors that participants recall after a time delay are biased with respect to their level of stereotype endorsement. In turn, raters experiencing memory decay may be more likely rely on stereotypes when committing performance ratings. Thus, it is reasonable to posit that after a time delay between performance observation and rating, participant’s endorsement of negative stereotypes should become related to the valence of the behaviors recalled during the SFRI. Hypothesis 4 When considering overweight ratees, structured free recall valence is related to stereotype endorsement in the two-day delay condition but not in the no-delay condition. Specifically, for overweight ratees there is a two-way interaction between OAMS scores and time delay on free recall valence scores (FRVSs). This relationship suggests that a statistically significant bivariate relationship exists between OAMS scores and FRVS in the two-day delay condition but not in the no-delay condition, such that biased raters are more likely to recall negatively valenced behaviors after a time delay.

Materials Measure of Bodyweight-Based Stereotype Endorsement This study directly assessed whether or not participants endorsed negative stereotypes toward overweight individuals in the specific role of ‘‘manager’’ using the eight-item Obese as Managers Scale (OAMS, See Appendix). The OAMS was designed to assess raters’ endorsement of both general negative stereotypes toward overweight individuals in the workplace, and more specific stereotypes about

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DHEW criteria for obesity, 140% constitutes obesity (BMI [ 30) (Abraham et al. 1979). The tapes depicted the actor ostensibly portraying a manager interacting with a problem subordinate. The performance to be rated was associated with the quality of the manager’s interactions with the subordinate in this context. This interaction was filmed in a conference-style meeting room. The manager was seated on one side of a conference table, facing the camera, with the subordinate facing them. The same setting was used for both videos. In both the average bodyweight and overweight condition, the subordinate was portrayed by the same white male of approximately the same age as the ostensible manager. Thus, the manager and subordinate were not matched in terms of gender, but were matched in terms of race and age. From an ecological validity standpoint, this type of exercise (i.e., assessing the performance of a manager by observing their interaction with a subordinate) is a common exercise in management development assessment centers. Because two different actors (i.e., one of average bodyweight, one overweight) portrayed the manager in each of the videos, several measures were taken to ensure that the performance depicted was as equal as possible. Foremost of which was that the two videos presented identically scripted behaviors. Furthermore, the actors used were matched on age and wore similar clothing. Likewise, the same camera angle and setting were used for both videos, and the ‘‘problem subordinate’’ was the same individual in both conditions. It should be noted that although measures were taken to ensure that the performance depicted was as equal as possible across the two videos, subtle differences associated with vocal intonation and physical attractiveness could not be equated. However, the exact equality of performance across tapes (i.e., average bodyweight vs. overweight) was not of primary concern because we were interested in the impact of stereotype endorsement on performance ratings—not mean-level differences in performance ratings. Because of the scripts that were used, the ratee in each video was depicted in eight separate vignettes or ‘‘discrete incidents’’ of performance. The performance depicted pertained to one of four dimensions of effective managerial performance (i.e., motivating employees, developing employees, establishing and maintaining rapport, and resolving conflict) that were originally identified by Roberson and Banks (1986). In both videos, each ratee exhibited two behaviors per dimension. Each performance dimension is portrayed in the behaviors exhibited by the manager in their interaction with the ostensible subordinate. Consistent with Sulsky and Day (1992, 1994), the performance relevant to the resolving conflict dimension

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was treated as a distracter,4 and as such was not rated by participants (see description of performance ratings below). Furthermore, the scripts were constructed in such a way that the ratee depicted in the videotape displayed varying performance across the three dimensions (i.e., both positive and negative behaviors), but had overall average performance. As an example of a positive behavior corresponding to the ‘‘developing employees’’ dimension, one vignette depicted the manager explaining training opportunities to the subordinate. Specifically, the manager stated to the subordinate, ‘‘There are a few things that we would like for you to work on. Fortunately, the personnel department has some courses that you can take to help you improve those skills which you’re lacking in.’’ As an example of a negative behavior corresponding to the ‘‘developing employees’’ dimension, one vignette depicted the manager explaining their stance on changing managerial styles. Specifically, the manager stated to the subordinate, ‘‘There’s nothing I can do to help you, if you are going to change your supervisory style, you’re going to have to do it on your own.’’ Each participant in this study was randomly assigned to view one of these videotapes (i.e., average bodyweight or overweight). SFRI As specified by the design, approximately half of the participants underwent the SFRI. The SFRI is an active intervention that directs people to recall and record both positive and negative behaviors relevant to the performance dimensions on which the ratee will be rated. After viewing performance, raters were instructed to take 5 min to record as many positive behaviors they could recall that relate to the dimensions of performance to be assessed. After this time expired, participants were again instructed to take 5 min to record as many negative behaviors they can recall that relate to the same dimensions of performance. To eliminate order effects, the SFRI order (i.e., negative/positive recall) was counterbalanced across raters. Overall, a total of 10 min of structured free recall was allotted for each rater. Both the positive and negative SFRI recall forms listed the dimensions and definitions of performance to be rated, and participants were given access to this information while completing their performance ratings.

4 Sulsky and Day (1994) recommend obtaining the resolving conflicts dimension as noise to increase the generalizability of the task, because raters often have to reconcile information that is not pertinent to the central dimensions of performance.

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FRVSs Baltes et al. (2007) method for calculating FRVS was applied to the content of each participant’s SFRI in both the immediate and two-day delay conditions. Specifically, a free recall valance score was calculated for each participant in the structured free recall condition by subtracting the total number of negative behaviors recalled from the total number of positive behaviors recalled. Thus, FRVSs above zero indicate a positive free recall valence, and scores below zero indicate a negative free recall valence. Two research assistants were trained to code the SFRI data by the third author. The third author and research assistants determined initial agreement based on a randomly selected subset of participants who underwent the SFRI. During this process, any coding disagreements were resolved through discussion. After this initial calibration, both research assistants rated all subsequent behaviors, and the third author resolved any disagreements. Because the performance that was rated was based upon scripts that contained a pre-determined set of positively and negatively valenced behaviors for each performance dimension, the ‘‘true’’ classification of behaviors as either positive or negative was built into the script. Furthermore, because the SFRI tasks raters with recalling and recording positive and negative behaviors separately, an initial classification of these behaviors as positive or negative was done by the raters. Thus, the coders were left to decide if the behaviors depicted in the scripts as negative (positive) were correctly recorded (i.e., as established by previously literature, see Sulsky and Day 1994) during the SFRI as negative (positive). For example, one rater recalled a positive behavior for the establishing and maintaining rapport dimension (i.e., ‘‘Manager is willing to talk to subordinate, and values communication.’’). This behavior was classified by coders as corresponding to the performance depicted in the positive-establishing and maintaining rapport vignette (i.e., ‘‘I’d like to make sure you know that I am here to talk to you anytime you want me to, and in conclusion, I’d just like to say how you feel about that is important to me.’’). Thus, this rater correctly identified a positive behavior that corresponded to this dimension of performance. Likewise, another rater recalled a negative behavior for the employee development dimension (i.e., ‘‘Manager doesn’t support for subordinate’s desire to change supervision style.’’). This behavior was classified as corresponding to the performance depicted in the negative-employee development vignette (i.e., ‘‘There’s nothing I can do to help you. If you are going to change your supervisory style, you’re going to have to do it on your own.’’). Thus, the coder’s task was to note how many negative (positive) behaviors contained in the scripts were correctly

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identified as negative (positive) in rater’s recall data. For each rater, coders noted (a) the total number of correct negative behaviors recalled during the negative SFRI and (b) the total number of correct positive behaviors recalled during the negative SFRI. As suggested above, the difference (i.e., total number of negative behaviors recalled subtracted from the total number of positive behaviors recalled) represented the FRVS. Manipulation Check In all conditions, a manipulation check was administered once participants’ ratings were completed. Participants were asked about the sex and bodyweight of the ratee; this served to ensure that participants remembered salient details of the ratee when committing their ratings. Participant’s who failed to correctly recall the sex and bodyweight of the ratee were excluded from analysis. Approximately 6% (n = 15) failed the manipulation check in the no-delay condition and approximately 9% (n = 24) failed in the two-day delay condition; thus, the final sample was N = 473 (nno delay = 235; ntwo-day delay = 238). Dependent Measures Performance Ratings The rating scales that were used to rate the performance depicted in the videotapes were based on the same research as the scripts used to construct the videos (Sulsky and Day 1992, 1994). Managerial performance was rated on the three non-distracter dimensions of managerial behaviors depicted in the videos (i.e., employee motivation, employee development, and the establishment and maintenance of rapport; Sulsky and Day 1992, 1994). Each dimension was assessed on a 7-point rating scale where higher scores indicated higher performance. Behavioral anchors that were indicative of performance at various levels defined each point on this scale. Performance ratings were obtained from each rater for each of the three performance dimensions described above. For each rater, these three ratings were then averaged to form an overall rating representing a composite of the three-dimensional ratings. Thus, each rater had one overall performance rating score, which could range from 1 to 7 where higher numbers indicate higher performance. Coefficient alpha for the performance ratings across all conditions in this study was 0.73. As evidence for the unidimensionality of this index, an exploratory factor analysis was conducted (principal axis extraction, with a varimax rotation). The results indicated that a one-factor solution that accounted for 50% of the variance; factor loadings ranged from 0.52 to 0.85.

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Procedure The study was conducted in several phases. First, all participants completed the OAMS during a mass screening of all potential participants at the university. This mass screening included various individual difference and demographic measures along with the OAMS, and was completed between 1 and 12 weeks before participation. This procedure was ideal, as temporally removing the OAMS measure from the rest of the study procedures ensured that the purpose of the study was not apparent to participants who completed subsequent phases. Because participants’ OAMS scores were critical to the design of this study, participants were invited to participate in the laboratory portion of the study contingent upon their completion of the OAMS during the mass screening. As suggested previously, this study utilized a 2 (time delay: no-delay or two-day delay) 9 2 (ratee bodyweight: average bodyweight or overweight) 9 2 (intervention: SFRI or no SFRI) between-subjects factorial design, with the time delay variable assigned to participants before participation. Thus, when participants arrived at the lab, they were randomly assigned to one of four possible conditions; the ‘‘no SFRI’’ condition served as a control to demonstrate the effect of stereotype endorsement on performance ratings—independent of the SFRI (i.e., Hypothesis 1). In all conditions, participants viewed one video depicting either an average bodyweight or overweight female ratee interacting with a problem subordinate. Consistent with past research that has investigated the SFRI (e.g., Baltes et al. 2007) and with other performance rating research in laboratory settings (e.g., Dobbins et al. 1988), participants in all conditions were given the following instructions from the experimenter before viewing the performance video: This study is designed to help MBA students become better managers. We are going to show you a video recording of an MBA student interacting with a fictional employee. This video will show you eight short examples of their interactions. After watching the video you will be asked to rate the MBA student on various dimensions of effective managerial performance. Your performance ratings of this MBA students will be used for both training and grading purposes, so please make sure you pay close attention to the video. Participants were told that they were viewing the performance of an MBA student participating in an assessment center, as opposed to an actor, because previous performance rating research (e.g., Dobbins et al. 1988) has shown that the effects found in experimental manipulations in which participants are told that they are rating the

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performance of actors are not as strong as when they are ostensibly rating an actual person. No-Delay Condition In the ‘‘no-delay’’ condition, participants undergoing the SFRI first viewed the performance, then underwent the SFRI, and finally provided performance ratings. Participants in the ‘‘no SFRI’’ condition underwent the same sequence, except that instead of the SFRI, they completed several distracter tasks (i.e., unrelated personality scales) to account for the time between viewing the videotape and rating performance. The completion of the scales took approximately 10 min. Two-Day Delay Condition The procedure in the ‘‘two-day delay’’ condition was identical to the procedure in the immediate rating condition, with the only difference being the addition of the time delay. Specifically, participants returned to the laboratory 2 days after initially viewing the performance to complete the SFRI and the performance ratings. Participants in the ‘‘no SFRI’’ condition also returned 2 days later, and underwent the same sequence but without the SFRI. In both the SFRI and no SFRI groups, participants were told during their first laboratory session that they would be rating the person they had observed when they returned to the lab for their second laboratory session.

Results Table 1 contains descriptive statistics and reliability estimates for all relevant study variables by condition. To ensure that there were no systematic differences in OAMS scores by condition, a 2 (Intervention—SFRI vs. No SFRI) 9 2 (Ratee Bodyweight—Average vs. Overweight) 9 2 (Time Delay—no-delay vs. two-day delay) ANOVA was run on the OAMS scores. As expected by random assignment, there were no statistically significant effects of OAMS scores on Intervention, F(1,465) = 0.03, n.s., Ratee Bodyweight, F(1,465) = 2.035, n.s., or Time Delay F(1,465) = , n.s., nor were there any statistically significant interactions. To ensure that the videos depicted equal levels of performance across ratees, the ratings provided by unbiased raters (i.e., raters who do not strongly endorse negative bodyweight-based stereotypes) were examined between average bodyweight and overweight ratees in the no SFRI (i.e., control) conditions. To do so, data were collapsed by condition (i.e., no-delay and two-day delay were combined) and a between-subjects t test was conducted to test

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214 Table 1 Descriptive statistics for measured variables across study conditions

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Variable

Mean

SD

Avg (n = 50)

4.54

1.10

Ovr (n = 51)

3.27

1.14

Perf. rating (a = 0.73)

No-delay

No-delay No SFRI

Avg (n = 50)

2.53

1.18

Ovr (n = 51)

2.63

1.28

SFRI

Avg (n = 66)

2.46

1.09

Avg (n = 66)

4.38

1.21

Ovr (n = 68)

2.70

1.17

Ovr (n = 68)

3.99

1.15

Two-day delay

Two-day delay

No SFRI

No SFRI

Avg (n = 57)

2.40

1.12

Avg (n = 57)

4.37

1.10

Ovr (n = 65)

2.71

1.23

Ovr (n = 65)

3.70

1.15

2.78 2.50

1.28 1.21

4.24 3.98

1.21 1.15

SFRI Avg (n = 63) Ovr (n = 53)

SFRI

for mean-level difference in performance ratings between average bodyweight and overweight ratee for participants with low-levels of stereotype endorsement (i.e., a score of 2.0 or lower on the OAMS). Across both the no-delay and two-day delay conditions, there was no statistically significant difference between average bodyweight (M = 4.40, SD = 1.20, N = 42) and overweight ratees (M = 4.14, SD = 1.17, N = 38) t(75) = 0.96, n.s. This provides evidence that the performance of the average bodyweight and overweight ratees was perceived to be equal by people who do not strongly endorse negative bodyweight-based stereotypes, and thus supports the notion that the videos used here depict equal levels of performance. To ensure that other rater characteristics were not influencing our results, several rater demographic variables (i.e., sex—male, female; ethnicity—white, nonwhite; work status—employed, unemployed) were included as preliminary control variables for all analyses.5 The inclusion of these variables had no appreciable (i.e., statistically significant) effect on the pattern or direction of our results, and thus did not change the substantive conclusions presented here. For the sake of parsimony, the results are presented without these control variables. Hypothesis 1 was tested by observing the bivariate correlation between OAMS scores and performance ratings for the overweight ratee in the no SFRI (i.e., control) conditions of our design. These correlations appear in Table 2. In both the no-delay condition (r = -0.47, P \ 0.01) and the two-day delay condition (r = -0.36, P \ .01), there were statistically significant bivariate We thank our anonymous reviewers for this suggestion.

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SD

(a = 0.83)

SFRI

5

Mean

OAMS

No SFRI

OAMS obese as managers scale; Perf. rating performance ratings; a Coefficient Alpha; SD standard deviation; Avr average bodyweight ratee; Ovr overweight ratee

Variable

Avg (n = 63) Ovr (n = 53)

Table 2 Correlations between overall performance ratings and the OAMS by intervention type and ratee bodyweight across conditions Intervention type

No-delay

Two-day delay

Avg

-0.05

-0.02

Ovr

-0.47**

-0.36**

Avg

-0.11

-0.08

Ovr

-0.10

-0.20

No SFRI

SFRI

* P \ 0.05, ** P \ 0.01, two-tailed. Columns indicate correlations between overall performance rating and OAMS score Avr average bodyweight ratee; Ovr overweight ratee

correlations, which suggest that people with stronger endorsement of negative stereotypes (i.e., higher OAMS scores) provided lower performance ratings for overweight ratees. As seen in Table 2, this relationship was not statistically significant for ratings of average bodyweight ratees in either condition. Of note is the amount of variance explained in the performance ratings by the OAMS for overweight ratees in these no SFRI conditions (i.e., 22.09% in the no-delay condition; 12.96% in the two-day delay condition). These values are relatively large, and speak to the strength of the effect that the bodyweight-based stereotype endorsement can have on performance ratings. Hypothesis 2 predicted a three-way interaction of ratee bodyweight (i.e., average bodyweight vs. overweight) by intervention (i.e., SFRI vs. no SFRI) 9 stereotype endorsement (i.e., OAMS score) on performance ratings, and thus was tested with a hierarchical OLS regression model. Because demonstrating this phenomenon is

J Bus Psychol (2012) 27:205–222 Table 3 Regression analyses using the OAMS scale to predict overall performance rating scores in no time delay condition

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Variable

R2

First step

0.135

SE B

b

OAMS score (OAMS)

-0.196

0.065

-0.186**

Ratee weight (TW)

-0.775

0.153

-0.315**

0.257

0.154

0.103

Intervention type (I) Second step

0.146

OAMS score (OAMS)

-0.153

0.288

-0.145

Ratee weight (RW)

-2.424

0.602

-0.985**

Intervention type (I)

-0.745

0.567

-0.299

(OAMS) 9 (RW)

-0.128

0.130

-0.246

0.104

0.129

0.192

0.841

0.305

0.762**

(OAMS) 9 (I) (RW) 9 (I) Third step

N = 235; OAMS obese as managers scale; Intervention type = SFRI vs. no SFRI (* P \ 0.05, ** P \ 0.01, twotailed)

B

0.181

OAMS score (OAMS)

-0.950

0.670

-0.901

Ratee weight (RW)

-4.271

1.177

-1.735**

Intervention type (I) (OAMS) 9 (RW)

-2.581 -0.847

1.155 0.415

-1.037* -1.624*

(OAMS) 9 (I)

0.619

0.417

1.144

(RW) 9 (I)

2.051

0.730

1.857**

(OAMS) 9 (RW) 9 (I)

0.570

0.258

1.680*

necessary to understand the nature of the bias under investigation and the means for reducing its effects with the introduction of a time delay, the following analyses were conducted only in the no-delay condition. Before running this analysis, the continuous independent variable (i.e., OAMS) was centered before the calculation of interaction terms to reduce problems associated with multicollinearity (Aiken and West 1991; Tabachnick and Fidell 2001). In addition, to obtain the correct standardized regression coefficients for interaction terms, regressions were run with standardized variables and their respective interaction terms (Cohen et al. 2003). As suggested, this hierarchical regression analysis was performed on the performance rating score; a three-way interaction was expected, because at the bivariate level, OAMS scores should only correlate with performance ratings in the no SFRI condition and only for the overweight ratee (i.e., see Hypothesis 1). Thus, performance ratings were regressed on bodyweight of the ratee (i.e., average bodyweight vs. overweight), intervention (i.e., SFRI vs. no SFRI), OAMS score, and all possible interactions. The results of this hierarchical regression analysis, shown in Table 3, revealed a statistically significant the three-way interaction (Model R2 = 0.18, b = 1.68, P \ 0.05). To understand this interaction more clearly, the data were graphed following the suggestions of Dawson and Richter (2006). Specifically, simple slopes representing the relationship between OAMS scores and performance ratings were plotted as separate regression lines for each of

the cells of the design. These slopes are depicted in Fig. 1. Slope difference tests were then calculated for each pairwise comparison of these simple slopes to further explore this interaction. The results of these difference tests are shown in Table 4. As predicted in Hypothesis 2, the relationship between OAMS scores and performance ratings for the overweight ratee in the SFRI condition is less negative than that observed for the overweight ratee in the no SFRI condition (see Table 4—1 and 2; t = 2.37, P \ 0.05). Furthermore, the relationship between OAMS scores and performance ratings for the overweight ratee in the SFRI condition is not statistically significantly different than the average bodyweight ratee in either the SFRI condition (see Table 4—1 and 3; t = 0.05, n.s.), or the no SFRI condition (see Table 4—1 and 4; t = -0.18, n.s.) This, coupled with evidence for Hypothesis 1 (see above), and the observed bivariate correlation between OAMS scores and performance ratings for the overweight ratee in the SFRI condition (see Table 2, r = -0.10, n.s.), provides evidence that the SFRI severs the relationship between stereotype endorsement (i.e., OAMS scores) and performance ratings (i.e., raters with more negative bodyweight-based stereotype endorsement did not evaluate the overweight ratee less favorably after participating in the SFRI). These results support Hypothesis 2 and provide further support for the efficacy of the SFRI (e.g., Baltes et al. 2007; Bauer and Baltes 2002). Hypothesis 3, which posited that the efficacy of the SFRI would diminish when a two-day delay is introduced

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Fig. 1 Three-way interaction between OAMS, bodyweight, and SFRI on performance ratings in the no-delay condition. Lines represent simple slopes defined by the relationship between OAMS and performance ratings for each of each of four groups of the current design

Table 4 Simple slope difference tests for three-way interaction between OAMS, bodyweight, and SFRI on performance ratings in the no-delay condition Sig (P \ 0.05)

Slope pair

t-value

(1) and (2)

2.37

(1) and (3)

0.05

(1) and (4)

-1.80

(2) and (3)

-2.02

*

(2) and (4)

-4.09

*

(3) and (4)

-0.77

*

Slope pair pairwise comparison of simple slopes depicted in Fig. 1. t-value represents test of difference between slopes. (1) overweight— SFRI; (2) overweight—no SFRI; (3) average bodyweight—SFRI; (4) average bodyweight—no SFRI; * P \ 0.05

between the observation and rating of performance, was tested via a hierarchical OLS regression model in which a three-way interaction was specified between OAMS scores, SFRI, and time delay on performance ratings. Because the interest here was testing the hypothesis that the efficacy of the SFRI for reducing the impact of bodyweight-based stereotype endorsement on performance ratings would diminish with the addition of a time delay, this analysis was run only for overweight ratees. The results of this hierarchical regression analysis for overweight ratees, shown in Table 5, revealed a non-statistically significant three-way interaction (Model R2 = 0.131, b = -0.73, n.s.). Because of the strength of the theory underlying this hypothesis, we proceeded by following up this analysis

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with the same procedure described above. Thus, simple slopes representing the relationship between OAMS scores and performance ratings were again plotted as separate regression lines for each possible combination of delay (i.e., delay, no-delay) and SFRI (i.e., SFRI, no SFRI). These slopes are depicted in Fig. 2. Slope difference tests were again calculated for each pairwise comparison of these simple slopes (see Table 6). Contrary to Hypothesis 3, there is no statistically significant difference between the slopes for the no-delay and delay SFRI conditions (See Table 6—1 and 3, t = -0.08, n.s). This is not entirely surprising given that the correlation between OAMS and performance ratings for overweight ratees in the SFRIdelay condition is likewise non-significant (r = -0.20, n.s., See Table 2). Thus, considering this evidence collectively, there is no evidence here to suggest that the efficacy of the SFRI diminishes with the addition of a time delay. In addition to directly testing the efficacy of the SFRI after a two-day delay, it is reasonable to inquire about the processes that may influence diminished efficacy for this intervention. Thus, as suggested by Hypothesis 4, the efficacy of the SFRI was tested as a function of the types of behaviors recalled during the free recall process, as reflected in raters FRVSs. Table 7 contains the means and standard deviations for the FRVS. Across SFRI conditions (i.e., no-delay average and overweight, two-day delay average and overweight), there was no statistically significant difference in the valence of behaviors recalled, F(3, 249) = 0.96, n.s. (see Table 7). This suggests that across conditions, the average ratio of positive to negative behaviors recalled was similar. Furthermore, it is interesting to note that in line with past research concerning the SFRI (i.e., Baltes et al. 2007) the information recalled during the SFRI was free from intrusions. That is, the content of the SFRI was accurate with respect to the behaviors observed in the performance videos. Hypothesis 4 predicts a two-way interaction of OAMS scores and time delay on FRVSs for overweight ratees, and thus was tested with a hierarchical OLS regression model. The first step of this model included OAMS scores and time delay as main effects; the second step of this model included their interaction. Overall, this model was not statistically significant, R2 = 0.02, F(3,117) = 1.11, n.s., nor was the two-way interaction term (b = -0.07, t = -1.01, n.s.). Thus, Hypothesis 4 was not supported. While a two-way interaction was not found, a follow up analysis was undertaken to explore this effect. Thus, the bivariate correlations between OAMS and the free recall valence scores were examined to determine if participants stereotype endorsement became more related to the valence of their recall after a time delay (see Table 8). Not surprisingly, all correlations in Table 8 are non-statistically significant, suggesting that there is no evidence that

J Bus Psychol (2012) 27:205–222 Table 5 Regression analyses using the OAMS scale to predict overall performance rating scores for overweight ratees in both the no-delay and two-day delay conditions

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Variable

R2

First step

0.109

OAMS score (OAMS)

b

-0.337**

-0.265

0.064

0.719

0.200

0.292**

Intervention type (I)

0.502

0.156

0.204**

0.130

OAMS score (OAMS)

-0.564

0.282

-0.716*

Time delay (T)

1.150

0.790

-0.513*

Intervention type (I)

0.720

0.515

0.292

(OAMS) 9 (T)

-0.046

0.127

-0.151

(OAMS) 9 (I)

0.252

0.128

0.648*

-0.844

0.400

-0.706*

-0.852

0.631

-1.075

0.526

0.523

0.559

-0.013 0.141

1.556 0.395

-0.005 0.462

(T) 9 (I) Third step

0.131

OAMS score (OAMS) Time delay (T)

* P \ 0.05, ** P \ 0.01, twotailed

SE B

Time delay (T) Second step

N = 229; OAMS obese as managers scale; Intervention type = SFRI vs. no SFRI

B

Intervention type (I) (OAMS) 9 (T)

0.443

0.402

1.139

(T) 9 (I)

(OAMS) 9 (I)

-0.213

1.135

-0.276

(OAMS) 9 (T) 9 (I)

-0.127

0.254

-0.727

participants OAMS scores were related to the valence of their behavioral recall in the no-delay or two-day delay condition. Thus, there was no evidence for congruency bias present here. One possible explanation for this null result is that memory decay may not have affected the recall process as much as expected. That is, participants may have recalled a similar number of behaviors in both the no-delay and twoday delay conditions. Memory decay theory suggests that forgetting may occur in the presence of a time delay because observed behaviors are not activated for some period of time. Thus, after a time delay, it is also expected that the number of behaviors recalled should be less, particularly when contrasted with the number of behaviors recalled in the no-delay condition. As a follow up to Hypothesis 4, a between-subjects ANOVA was conducted on the absolute number of behaviors recalled across all SFRI conditions (i.e., no-delay—average bodyweight and overweight; two-day delay—average bodyweight and overweight, see Table 7). Contrary to what memory decay would suggest, there were no statistically significant differences in the absolute number of behaviors recalled across conditions, F(3,249) = 2.39, n.s., suggesting that, in the aggregate, memory decay with respect to the number of behaviors recalled during the SFRI is not evident with this amount of time delay. This may help to explain the lack of support for a congruency effect, as suggested by the evidence presented for Hypothesis 4.

Fig. 2 Three-way interaction between OAMS, SFRI, and time delay, on performance ratings for overweight ratees. Lines represent simple slopes defined by the relationship between OAMS and performance ratings for each possible combination of delay (i.e., delay, no-delay) and SFRI (i.e., SFRI, no SFRI)

Discussion The purpose of this study was to demonstrate the effect that bodyweight-based stereotypes have on performance ratings (Hypothesis 1), to demonstrate the efficacy of the SFRI intervention for reducing such effects (Hypothesis 2), and determine if introducing a time delay between the

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Table 6 Simple slope difference tests for three-way interaction between OAMS, SFRI, and time delay on performance ratings for overweight ratees

Condition

Correlation

No-delay (N = 68)

-0.14

Two-day delay (N = 53)

-0.22

Sig (P \ 0.05)

Slope pair

t-value

(1) and (2)

0.64

(1) and (3)

-0.08

(1) and (4)

-2.10

*

(2) and (3)

-2.04

*

(2) and (4)

0.40

(3) and (4)

2.37

*

Slope pair pairwise comparison of simple slopes depicted in Fig. 1. t-value represents test of difference between slopes. (1) delay—SFRI; (2) delay—no SFRI; (3) no-delay—SFRI; (4) no-delay—no SFRI; * P \ 0.05

observation and rating of performance affects the efficacy of the SFRI for mitigating such effects (Hypotheses 3 and 4). To this end, Hypothesis 1 was supported; namely, there is an observed relationship between participants’ endorsement of bodyweight-based stereotypes (i.e., OAMS scores) and their performance ratings of overweight ratees in the no SFRI condition of both the no-delay and two-day delay conditions. Hypothesis 2 was also supported; for participants in the SFRI condition, there is no demonstrable relationship between participants OAMS scores and performance ratings for overweight ratees. Hypothesis 3 was not supported. That is, there was no evidence to suggest that a time delay between performance observation and ratings reduces the efficacy of the SFRI intervention. Thus, despite the prediction of an effect of memory decay, it appears that the efficacy of the SFRI holds after 2 days of delay between the observation and rating of performance. Furthermore, Hypothesis 4 suggested that the efficacy of the SFRI may decline as a function of congruency bias, a phenomenon that could be demonstrated by observing the relationship between FRVSs and OAMS scores across time. If congruency bias occurs, one would expect that the relationship between free recall valence and OAMS scores to increase as a function of time; the increase of this relationship would also indicate evidence for memory decay in that congruency bias is suggested to exist as a function of decay. Table 7 Means and standard deviations for FRVS and absolute behaviors recalled by condition

Table 8 Correlations between OAMS and FRVSs across conditions for overweight ratees in the SFRI condition

Condition

All correlations are not statistically significant (i.e., P [ 0.05)

However, there is no evidence for either congruency bias or memory decay affecting the content of the SFRI in the two-day delay condition. Specifically, there was no statistically significant interaction between OAMS scores and time delay on FRVSs, suggesting that the content of a person’s recall was not biased with respect to stereotype endorsement after 2 days of delay. Furthermore, there was no statistically significant difference in the number of behaviors recalled during the SFRI between the no-delay and two-day delay conditions, suggesting no evidence for memory decay affecting recall. Practical Implications Overall, the results of this and other studies indicate that the efficacy of the SFRI holds in an immediate rating context. Furthermore, the current study failed to find evidence that memory decay impacts the efficacy of the SFRI after a time delay. Thus, the efficacy of the SFRI endures even when a two-day delay is introduced. Taken collectively, these findings suggest that the best implementation of the SFRI paradigm may be to situations with short time delays between the observation and rating of performance. Such situations occur often in organizations, such as in a well-managed selection or development assessment centers, or with pre-hire employment interviews in which there is limited contact and limited performance-relevant information available to raters, where decisions follow highstake assumptions. Furthermore, the demonstrated efficacy of the SFRI across time is promising for organizations that may consider implementing the SFRI as part of multi-day assessment centers. The SFRI may be particularly effective at reducing the impact of stereotype endorsement in such FRVSa M

Behaviors recalledb SD

M

SD

No-delay a

F(3, 249) = 0.96, n.s.

b

F(3, 249) = 2.39, n.s.

FRVS free recall valence score; Behaviors recalled absolute number of behaviors recalled during SFRI

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SFRI average (n = 66) SFRI overweight (n = 68) Two-day delay SFRI average (n = 63) SFRI overweight (n = 53)

0.10

0.58

9.10

3.21

-0.02

0.67

8.84

3.05

0.08

0.61

7.84

3.80

-0.07

0.70

7.70

4.27

J Bus Psychol (2012) 27:205–222

situations, because performance ratings may not be committed immediately following observation of performance. Indeed, it is in these types of situations where the impact of stereotype endorsement may be strongest, and not later stages of the pre-employment evaluation process. In terms of the practical implications of this study for overweight employees, the results presented here give hope to a class of individuals who face a detrimental form of bias that has social, economic, and psychological implications. Indeed, we hope that the current research serves as a call for more in-depth investigations of the processes and outcomes associated with bodyweight-based bias in the workplace, and beyond. Furthermore, researchers should further endeavor to refine intervention strategies to mitigate such effects. On a more theoretical level, this study presents compelling evidence for the utility of explicit attitudes (i.e., stereotype endorsement) for predicting evaluative workplace outcomes. The evidence presented here, coupled with other research that has shown similar relationships (e.g., Baltes et al. 2007; Bauer and Baltes 2002; McConahay 1983; Stewart and Perlow 2001) provides compelling evidence to support the notion that explicit attitudes can meaningfully aide in explaining overt behaviors. Limitations and Future Research This study makes an important contribution to the existing body of literature that has examined the cognitive processes underlying the effects of negative stereotypes on performance ratings, and on interventions designed to reduce these effects. However, as with all studies, there are potential limitations as well as opportunities for future research. For example, in this study, which was lab-based, the relationship between the endorsement of the bodyweight-based stereotypes and performance ratings were quite large; however, future research should test whether these relationships generalize to applied settings. Furthermore, the typically cited limitations that accompany laboratory-based research using student samples could apply to the current investigation. While several reviews have debated the use of student samples in organizational research (e.g., Diboye and Flanagan 1979; Campbell 1986), such criticisms are probably not as universally warranted as once suggested. Also, given that a majority of people in the current sample were employed and worked approximately half-time, such issues may be less problematic for the current investigation. A possible additional limitation with regard to this sample is an unknown level of managerial experience, a lack of which may have limited the knowledge of effective managerial behaviors among our participants.

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In addition, caution should be taken when generalizing the efficacy of SFRI to an actual work environment. It is important for future research to test the effectiveness of this intervention in actual organizational settings. In addition, this study relied upon the investigators’ assistance in administering the SFRI by instructing raters, while in a real work setting, raters would most likely have to manage the intervention independently. Thus, future studies need to test the efficacy of the SFRI in the situations where it must be self-managed by the rater. Future research should also investigate whether a combination of the SFRI with rater training or other interventions aimed at increasing raters’ accuracy-focused motivation might further reduce the effects of stereotypes on performance ratings. For example, pairing the SFRI, a recall driven intervention, with an encoding driven intervention such as frame-of-reference training (Bernardin and Buckley 1981) may serve to further bolster the efficacy of performance ratings. Furthermore, future research should endeavor to further test the temporal limits of the SFRI for reducing the impact of stereotype endorsement on performance rating contexts. While the efficacy of this intervention has now been demonstrated for delays of up to 2 days, longer delays (e.g., one-week) may be worthwhile to investigate. As we have suggested above, the results of this study have distinct implications for personnel decisions and evaluative workplace outcomes made on the basis of limited information and limited contact (e.g., initial applicant screening), or evaluations of performance potential early in the talent acquisition cycle (e.g., recruitment). This notion begs another interesting and untested venue for future research. Indeed, such limited information and limited contact decision processes are indicative of the initial stages of many selection systems, where ensuring a representative applicant pool is a primary concern. In such situations, stigmatized attributes of the ratee would be particularly salient to raters, a fact that is directly reflected in the currently employed experimental design. Thus, curtailing the impact of stereotypes at such an early stage is fundamentally important in helping to promote organizational diversity. For example, assuming that certain applicants are removed from the talent pool early in the application process, it is possible that many forms of bias do not affect evaluative workplace outcomes that occur in the later stages of selection systems because of the elimination of stigmatized individuals via biased initial screening processes. This article serves to extend our knowledge of the SFRI by providing evidence that this intervention is effective at reducing the impact of explicitly endorsed stereotypes on performance ratings when such ratings are conducted up to 2 days after the observation of performance. With this in mind, we offer this intervention with the hope of reducing

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the injustice associated with stigmatization in the workplace. Our hope here is that through well-designed psychological interventions, the impact of bias in workplace contexts can be curtailed.

Appendix The Obese as Managers Scale (OAMS) 1. 2.

3. 4. 5. 6.

7.

8.

Obese people can be relied upon in difficult business situations. (R) In a stressful situation, an obese manager would be more likely to act in a hostile manner than would an average weight person. The possibility of rude behavior makes obese people less desirable employees than average weight people. All things considered, obese people and average weight people are intellectually equivalent. (R) Challenging work is as important to obese people as it is to average weight people. (R) In general, average weight people are more suitable than obese people for professional (e.g., lawyer, doctor, etc.) and management positions. Obese people should be given at least as much preference in being hired or promoted as average weight people. (R) Obese people possess the drive to be successful leaders. (R)

(R) indicates that this is a reverse coded item.

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