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Page 1 of 13 Original Research
Orientation: The use of personality tests for selection and screening has been consistently
criticised resulting from the risk of socially desirable responding amongst job applicants.
Research purpose: This study examined the magnitude of culture and language group mean-
score differences amongst job applicants and the moderating effect of race on the relationship
between social desirability and cognitive ability.
Motivation for the study: The influence of cognitive ability and potential race and ethnic
group differences in social desirability scale scores, which can lead to disproportional selection
ratios, has not been extensively researched in South Africa.
Research design, approach and method: A quantitative, cross-sectional research design,
based on secondary datasets obtained from the test publisher, was employed. The dataset
consisted of 1640 job applicants across industry sectors.
Main findings: Moderated multiple regression analyses revealed that the relationship between
social desirability and general reasoning was moderated by culture and language, with group
differences in social desirability being more pronounced at the low general reasoning level.
This suggests that social desirability scales may be an ambiguous indicator of faking as the
scales may indicate tendency to fake, but not the ability to fake, that is likely to be connected
to the level of cognitive ability of the respondent.
Practical/managerial implications: Individual differences in social desirability are not fully
explained by cognitive ability as cultural differences also played a role. Responding in a
certain manner, reflects a level of psychological sophistication that is informed by the level
of education and socio-economic status. In relation to selection practice, this study provided
evidence of the potentially adverse consequences of using social desirability scales to detect
response distortion.
Contribution/value-add: The exploration of cross-cultural differences in the application of
social desirability scales and the influence of cognitive ability is seen as a major contribution,
supported by possible explanations for the differences observed and recommendations
regarding the practice of universal corrections and adjustments.
Author:
Alea Odendaal1
Aliaon:
1Department of Industrial
Psychology and People
Management, University of
Johannesburg, South Africa
Correspondence to:
Alea Odendaal
Email:
aodendaal@uj.ac.za
Postal address:
PO Box 781615, Sandton
2146, South Africa
Dates:
Received: 15 Dec. 2015
Accepted: 08 May 2015
Published: 17 July 2015
How to cite this arcle:
Odendaal, A. (2015). Cross-
cultural dierences in social
desirability scales: Inuence
of cognive ability. SA Journal
of Industrial Psychology/SA
Tydskrif vir Bedryfsielkunde,
41(1), Art. #1259, 13 pages.
hp://dx.doi.org/10.4102/
sajip.v41i1.1259
Copyright:
© 2015. The Authors.
Licensee: AOSIS
OpenJournals. This work is
licensed under the Creave
Commons Aribuon
License.
Cross-cultural dierences in social desirability scales:
Inuence of cognive ability
Introducon
The inferences made from social desirability scales included in personality instruments in
cross-cultural settings remain questionable. This is so despite the fact that the use of personality
instruments in personnel selection has increased in the last decade because these instruments
have been shown to predict job performance and other related behaviours across employment
settings (Hough & Oswald, 2008; Ones, Dilchert, Viswesvaran & Judge, 2007; Sackett, 2011;
Viswesvaran, Deller & Ones, 2007). Furthermore, well-constructed personality instruments have
sound psychometric properties, are relatively inexpensive to administer and score, and are likely
to cause less adverse impact on minority groups than cognitive ability tests (Ones, Viswesvaran
& Reiss, 1996; Schmidt & Hunter, 2004). Adverse impact in personnel selection typically occurs
when a specific selection strategy gives members of a specific group a lower likelihood of being
selected than members of another group (Theron, 2007).
Notwithstanding the advantages, the use of personality tests for selection and screening has
been consistently criticised consequent to the risk of socially desirable responding amongst
job applicants (Birkeland, Manson, Kisamore, Brannick & Smith, 2006; Griffith, Chmielowski
& Yoshita, 2007; Hogan, Barrett & Hogan, 2007; Morgeson et al., 2007). Evidence suggested
that the self-report format of personality instruments is highly susceptible to response
distortion by applicants, as individuals can intentionally distort their responses to create a
favourable impression of themselves (Holden & Passey, 2010; O’Connell, Kung & Tristan, 2011;
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Page 2 of 13 Original Research
Visweswaran & Ones, 1999). Empirical studies have further
demonstrated that applicants actually engage in response
distortion behaviour (Barrick & Mount, 1996; Schmit &
Ryan, 1993). The possibility that applicants can, and indeed
do distort their responses, has serious implications for
employers as one might hire an individual based on their
ability to assumedly distort their responses on an instrument
rather than as a result of the characteristic being measured.
Despite the criticism, personality instruments are widely
used in South Africa for selection and development
purposes. Although the effect of socially desirable
responses on the validity and utility of personality testing
in employment settings has been extensively debated and
researched in the international literature, the issue remains
unresolved (e.g. Birkeland et al., 2006; Dilchert, Ones,
Viswesvaran & Deller, 2006; Ellingson, Sackett & Connelly,
2007; Li & Bagger, 2006; O’Connell et al. 2011; Ones et al.,
1996). In addition to this, there is a growing recognition
that the cross-cultural transferability of constructs has
not been systematically examined in the multi-cultural
and multi-lingual South African context (De Beer, 2004;
Meiring, Van de Vijver, Rothmann & Barrick, 2005;
Schaap & Vermeulen, 2008). Specifically, the influence
of potential race and ethnic group differences in social
desirability scale scores, and the relationship between social
desirability and cognitive ability amongst job applicants
in a cross-cultural context, have also not been extensively
researched (Dilchert & Ones, 2005).
Considering the relationship between social desirability
and cognitive ability a meta-analytic review by Ones
et al. (1996) suggested a weak negative relationship. The
estimates were, however, not solely based on applicant
samples and in a subsequent study, using a job applicant
sample, Dilchert and Ones (2005) found that race and
ethnic group differences in social desirability scale mean-
scores is partially explained by group differences in
cognitive ability. Limited research has been conducted in
South Africa examining the relationship between social
desirability and cognitive ability. A study by Meiring et al.
(2005) investigating method bias in a selection battery
for entry-level police officials in the South African Police
Services, found that the extent of cross-cultural differences
between the language groups was not influenced by
socially desirable responding or cognition. Greene (2000)
and also Dilchert and Ones (2005) reviewed the influence of
group differences in cognitive ability on social desirability
scale mean-scores, and suggested that socially desirable
responding appear to be associated with a certain form of
social naïveté, likely to be connected to cognitive ability.
The magnitude of the social desirability and cognitive ability
relationship amongst job applicants in a cross-cultural context
remains an open question that requires further exploration.
It is against this background that this article aims to report
on the findings of a study that examined the influence of
cognitive ability on group differences in social desirability
amongst job applicants in South Africa, addressing the
following research questions:
• What is the relationship between socially desirable
responding and cognitive ability?
• Are any race differences in social desirability scores
related to differences in cognitive ability?
More specifically the objectives of the study are to:
1. Examine the magnitude of culture and language group
mean-score differences on social desirability scores and
cognitive ability amongst job applicants.
2. Examine whether or not race moderates the relationship
of social desirability with cognitive ability.
The main contribution of this research is not only the
exploration of cross-cultural differences in the application
of social desirability scales and the influence of cognitive
ability, but also the provision of possible explanations
for the differences observed. The author also provides
recommendations regarding the practice of universal
corrections and adjustments.
In the next section the construct social desirability will be
described, followed by a review of evidence regarding cross-
cultural differences in socially desirable responding, and
the influence of cognitive ability, in order to advance our
understanding regarding the pattern of relationships that
requires further exploration.
Literature review
Socially desirable responding is viewed as an important
component of self-report inventories that has inspired much
debate, and has generated mixed and at times contradictory
research results, depending on the operational definition of
social desirability and research design employed. Reviewing
the large body of research on social desirability revealed that
various terms have been used to describe the construct. These
terms include impression management (Hogan et al., 2007;
Paulhus, 1984), faking (Barrick & Mount, 1996; Ones et al.,
1996; Rossė, Stecher, Miller & Levin, 1998), self-deception
(Paulhus, 1984, 2002) and self-enhancement (Heine, 2005;
Heine & Lehman, 1997). These terminologies are regularly
used interchangeably and are conceptualised as a unitary
construct, notwithstanding clear differences in meaning and
application (Griffith & Robie, 2013; Li & Bagger, 2006; Ones
et al., 1996). Although many of the terms are conceptually
distinct they all relate to the elevation of scores on a self-
report inventory. It should, however, be noted that socially
desirable responding is not only restricted to personality
inventories but is also a concern in any assessment conducted
for the purpose of decision-making (selection, promotion or
development opportunities) regardless of the assessment
instrument or medium (Dilchert et al., 2006).
The terms ‘distortion’ and ‘faking’ are furthermore perceived
to be misleading concepts because they imply that there is a
‘true’ response that can be determined independently of the
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Page 3 of 13 Original Research
behaviour of the test-taker (Mueller-Hanson, Heggestad &
Thornton, 2006). The term faking implies that test-takers
are aware of the ‘amount of a psychological construct they
actually possess, and they respond to items in a way that
is knowingly inconsistent with this (known) possessed
amount of the psychological construct’ (Davies, Norris,
Turner & Wadlington, 2005, p. 4). Faking, therefore, has a
negative connotation and is applied only to personality test
responses and not to cognitive ability (where changes in
cognitive test scores are commonly referred to as practice
effects) or any other type of responses that may vary in a
similar manner (Davies et al., 2005; Hogan et al., 2007).
In this study social desirability was operationalised as
response patterns that can result from both self-deception
and impression management. Faking was defined as the
purposeful misrepresentation and conscious distortion
of responses in order to score favourably and was, thus,
viewed as a form of impression management. In applied
settings psychologists work towards eliminating sources of
bias or systematic error, such as self-enhancement, which
are not relevant to the measured attributes through the use
of different measures of socially desirable responding.
Measures of socially desirable responding
In an attempt to address the effects of socially desirable
responding, different strategies are employed. These
strategies largely depend on the purpose and level of
application, broadly classified as (1) identification versus
prevention strategies and (2) item and scale versus person
level strategies (Aurthur & Glaze, 2011; Dilchert & Ones,
2011). Identification strategies typically aim to detect response
distortion amongst test-takers, whereas prevention strategies
attempt to discourage test-takers from engaging in response
distortion by making socially desirable responding more
difficult (Burns & Christiansen, 2011; Rothstein & Goffin,
2006). Social desirability scales are, therefore, employed as
a strategy to identify response distortion on scale or test
level. Common approaches to identify socially desirable
responding in personality instruments include the use of one
or more social desirability, impression management or faking
scale(s), referred to as validity scales (Burns & Christiansen,
2011; Ellingson, Heggestad & Makarius, 2012) and should be
distinguished from other response style indicators such as
acquiescence and extreme response sets. Validity scale items
are typically dispersed amongst the personality items in the
personality instrument. These validity scales examine the
pattern of responses and infer the credibility of the personality
profile obtained (Holden & Passey, 2010; O’Connell et al.,
2011). A survey conducted by Goffin and Christiansen (2003)
reported that 80% of commercial self-report inventories
include social desirability scales, such as the Balanced
Inventory of Desirable Responding (BIDR, Paulhus, 1984),
the Marlowe-Crowne Scale (Crowne & Marlowe, 1960),
or the Edwards Social Desirability Scale (Edwards, 1957).
It was further evident from the survey that the majority of
psychologists using personality questionnaires reported
that they interpret validity scales despite the lack of clear
directives on how these scales should be interpreted.
Several independent social desirability scales are also
available that can be administered separately from the
other assessments in a battery. In this regard different short
forms of the Marlowe-Crowne Scale have subsequently been
developed with reported internal consistencies around .60
(Barger, 2002). A meta-analyses conducted by Ones et al.
(1996) reported a mean estimate of the social desirability
scales’ reliability of .74 across 119 reliabilities with an
associated standard deviation of .14. It is evident that none
of these reported reliabilities suggest that scores on these
scales should be used to make decisions about individuals
(cf. Nunnally & Bernstein, 1994). Irrespective of reported
reliabilities, current personality instruments widely used
in South Africa include one or more validity scale, and the
practice remains that Industrial and Organisational (IO)
Psychologists treat scores on these scales as signs of response
bias and evidence of faking.
Given the pervasive influence of socially desirable
responding on all types of behaviours, in everyday life, Tett,
Freund, Christiansen, Fox & Coaster (2011) argue that it is
important to examine process models of how responses are
generated and develop an understanding of the antecedents
of response bias behaviour. This argument is in accordance
with more recent definitions of socially desirable responding
that view faking as representing a response set aimed at
providing a description of the self in an attempt to achieve
personal goals. According to this theory faking occurs ‘when
this response set is activated by situational demands and
person characteristics to produce systematic differences in
test scores that are not due to the attribute of interest’ (Ziegler,
MacCann & Roberts, 2011, p. 8). Despite this definition little
is known about the actual process of socially desirable
responding in a cross-cultural context.
In an attempt to obtain answers to questions regarding
how responses are generated, and to questions concerning
what people think when completing a self-report inventory,
various cognitive (Krosnick, 1999; Tett & Simonet, 2011;
Ziegler, 2012) and psychological process models have been
conceptualised (cf. McFarland & Ryan, 2000, 2006; Mueller-
Hanson et al., 2006; Snell, Sydell & Lueke, 1999). Cognitively,
people go through a four-step process of responding which,
according to Krosnick (1999), consists of comprehension,
retrieval, judgement and mapping. When people are
motivated to respond in a sincere manner an optimising
strategy is followed. In contrast, a satisficing strategy is
used when factors such as motivation, cognitive ability and
fatigue influence optimal responding. The cognitive process
model, thus, supports the assumption that a person’s ability
and motivation for faking influences their strategy of either
optimising or satisficing (Ziegler & Bühner, 2009).
In order to explain the psychological processes that underlie
faking behaviour Snell et al. (1999) proposed an interactional
framework for understanding both individual differences
(ability and willingness or motivation to fake) and also
situational differences in successful faking. In an attempt
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to address the conceptual limitations of the interactional
model, McFarland and Ryan (2006) proposed a second model
based on the theory of planned behaviour (Ajzen, 1991). A
central factor in the theory of planned behaviour concerns
the individual’s intention to engage in the behaviour. Within
this model faking is viewed as a result of three conceptually
independent determinants, namely:
• attitude towards faking (beliefs about rightness or
wrongness of faking)
• subjective norms (beliefs about how others view faking
and the perceived social pressure to perform or not
perform the behaviour)
• perceived behavioural control (beliefs about the ease or
difficulty of faking).
Some support was found in research for this model but it
was limited as it did not address the impact of dispositional
factors on faking intentions (Mcfarland & Ryan, 2006).
To address limitations from the earlier models, Mueller-
Hanson et al. (2006) integrated the models of faking
proposed by McFarland and Ryan (2000) and Snell et al.
(1999), to develop an integrative model of faking behaviour
that explains the predictors of individual differences in the
motivation and ability to distort responses. This integrative
model of faking (Mueller-Hanson et al., 2006) includes both
dispositional and attitudinal antecedents. In accordance
with the theory of planned behaviour (Ajzen, 1991) these
antecedents precede intentions, which precede behaviour.
Antecedents include:
• a person’s perception of the situation (based on belief in
the importance of faking, perceived behavioural control
and subjective norms)
• ability to fake (operationalised as knowledge)
• willingness to fake
• the two core personality characteristics of
conscientiousness and emotional stability.
Whilst a full review of all process models of faking is
outside the scope of this article, the preceding discussion
clearly indicates that explaining human behaviour and
specifically socially desirable responding is a complex and
cognitively demanding task. The fact that an individual
can fake responses to an item when instructed to do so,
and can present themselves as the ideal employee for a
position, entails a complex set of cognitive processes and it is
expected that respondents, higher in general ability, will be
better at enhancing performance on a self-report inventory
(O’Connell et al., 2011; Tett & Simonet, 2011). Process models
of socially desirable responding, therefore, provide useful
conceptual frameworks for understanding how responses
are generated, and for working towards the implementation
of interventions that may be effective in changing them.
The evidence provided further suggests that people differ
in relation to how much they will fake on a personality
instrument, with some people faking substantially and others
faking little or not at all. The extent to which individuals fake
is partially determined by their perception of the situation,
their willingness and ability to fake and also their personality
characteristics (Mueller-Hanson et al., 2006). The evidence also
suggests that people tend to implement a total test strategy
of self-presentation and take into account how specific
responses may relate to other items in the instrument, in an
effort to optimise the impact of their overall performance
(Hogan et al., 2007; Tett & Simonet, 2011). These findings
bring into question the use of social desirability scales to
determine the validity of a personality profile. In addition,
the literature leaves unaddressed a central theoretical and
practical consideration, regarding potential race and ethnic
group differences, in relation to the use of social desirability
scales in selection decisions.
Group dierences in socially desirable responding
The importance of group differences in a cross-cultural
context cannot be underestimated as it can lead to
disproportional selection ratios and possible adverse impact.
For example, if scores on the social desirability scale are used
to make a judgement regarding the validity of the profile,
and subsequent corrections are made, then individuals from
different groups will receive systematically different scores
on these scales. In addition, political and social changes
in South Africa over the last 20 years present additional
challenges to the use of personality instruments in selection
decisions, as the differences between race groups and
people from diverse backgrounds are constantly changing
(Foxcroft & Roodt, 2009).
The issue of race and language group differences in social
desirability has been researched internationally and has
yielded mixed results. Hough and Ones (2001) found small to
moderate group mean-score differences between some racial
and ethnic groups on social desirability scales. They reported
d-values of -.05, .56, .03, .40 for the black-white, Hispanic-
white, American Indian-white and Asian-white group
comparisons, respectively. The effect sizes for the Hispanic-
white and Asian-white comparisons were large. Dilchert
and Ones (2005) criticised this study because it did not focus
specifically on job applicants and did not explore potential
explanations for the race and ethnic group differences (e.g.,
cognitive ability). In addition, relatively small sample sizes
for the American Indian and Asian groups limited the
strength of the estimates.
There is currently strong evidence that job applicants’ score
distributions are significantly different from those of the
general population and, therefore, the use of job applicant
samples is imperative when studying group differences in
social desirability (Rossė et al., 1998; Tett & Simonet, 2011;
Viswesvaran, Ones, Cullen, Drees & Langkamp, 2003). Two
independent studies conducted by Dilchert and Ones (2005),
which made use of a sample of over 50 000 job applicants,
from two occupational groups, showed that black, Hispanic
and Asian groups displayed moderately higher mean-
scores on social desirability scales than white applicants
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(differences ranging from .14 to .16 standard deviations). This
study concluded that race and ethnic group differences in
socially desirable responding scale mean-scores can partially
be explained by group differences in cognitive ability.
However, the magnitude of the relationship between social
desirability and cognitive ability amongst job applicants in a
South African context remains an open question that requires
further exploration.
Inuence of cognive ability on
socially desirable responding
Ability and aptitude tests have commonly been used as
predictors in personnel selection. A typical assessment
battery for selection purposes in South Africa (and many
other countries) tends to include both personality and ability
instruments. The relationship between cognitive ability and
work performance has been extensively researched with a
substantial body of evidence indicating that general cognitive
ability (or general mental ability, ‘g’) is the strongest predictor
of learning and acquisition of job knowledge and also
overall job performance for virtually every job (Arneson,
Sackett & Beatty, 2011; Kuncel & Hezlett, 2010; Schmidt
& Hunter, 2004). In reviewing research evidence, Ones,
Dilchert and Viswesvaran (2012) asserted that general mental
ability is also relevant for understanding and predicting
other important behaviours and outcomes in occupational
settings (e.g. leadership effectiveness, innovation, counter
productivity, and work attitudes). It is, further, well
documented that g-tests show mean sub-group differences in
cognitive ability test performance by race and ethnicity, sex,
and age both within the United States and internationally
(see Ones et al., 2012 for a quantitative review of group
differences; Roth, Bevier, Bobko, Switzer & Tyler, 2001).
The cross-cultural comparison of cognitive test scores is
also not new in South Africa, with results reflecting those
commonly reported in the international literature (for a
review see Odendaal, 2013). It should, however, be noted that
these studies were conducted prior to the 1990s, and labour
force participation and occupational distribution of women
and ethnicity in the workplace are totally different to 20–30
years ago. In addition, changes in the nature and demands of
jobs (e.g. greater complexity and technological demands) may
manifest differently in cognitive ability relations. Important
outcomes of early research is the recognition that home
environment, schooling, language proficiency, nutrition
and other factors may impact cognitive ability measures
in a multi-cultural society such as South Africa (Claassen,
1997; Meiring et al., 2005). Reviewing research it is further
evident that mean-scores on cognitive ability measures have
been documented to be steadily increasing, referred to as the
Flynn effect, after the researcher who first documented the
narrowing of mean group differences on cognitive ability
tests over time (cf. Ang, Rodgers & Wänström, 2010; Rushton
& Jensen, 2010).
Typical standardised tests of cognitive ability used in South
Africa assess verbal ability, numerical ability, and deductive
reasoning. Following Cattell’s theory, these areas can be
viewed as indicators of crystallised intelligence and often
concern specialised skills or knowledge required by a given
culture (Taylor, 1994). South African studies have found that
race, level of education, socio-economic status, language and
understanding of English are the main factors impacting the
construct and item comparability of cognitive and personality
tests (Abrahams & Mauer, 1999; Meiring et al., 2005; Stephen,
Welman & Jordaan, 2004; Van Zyl & Visser, 1998). A study
by Watkins and Elliot (1997) also raised serious questions
regarding the functionality of g in the prediction of work
performance in South Africa. These authors rejected the
notion of a g-factor and argued instead in support of the
notion of seven distinct intelligences (logical-mathematical,
musical, intra-personal, interpersonal, bodily-kinesthetic
and spatial intelligence) based on the work of Gardner
(Watkins & Elliot, 1997).
Given the educational differences in South Africa, research
has focused on the educability and trainability of South
Africans. In this regard Taylor (1994) suggested the
identification of learning potential as an alternative to
conventional cognitive ability assessment. This suggestion
is based on the belief that cognitive ability is not fixed but
can change and, following Vygotsky’s view, supports the
approach that performance on its own is not a true reflection
of cognitive ability (Bedell, Van Eeden & Van Staden, 1999).
Based on this argument several non-verbal tests have been
developed to measure fluid intelligence, which is a relatively
culture-reduced form of mental efficiency and is related to
a person’s inherent capacity to learn and solve problems
(Schaap & Vermeulen, 2008). There is, furthermore,
recognition that different cultures have different views
regarding intelligence, for example, the speed at which a
herdsman recognises his own cattle amongst a big herd may
be perceived as intelligence in some African tribes., whereas
other forms of pattern recognition might be acknowledged
as intelligence within Western cultures (De Klerk, 2008).
The comparability of test scores may, therefore, be
influenced by ability patterns that are influenced by socio-
cultural patterns. In contrast, the main cognitive processes
and functions (fluid intelligence) are universally shared
properties of intellectual life and may result in highly varied
crystallised performances across cultures (Berry, Poortinga,
Segall & Dasen, 2002). It is also evident that the greater the
amount of information that needs to be manipulated the
more important g becomes (Arneson et al., 2011; Kunzel &
Hezlett, 2010; Schmidt & Hunter, 2004). In practical terms
this means that as the information-processing demands of a
position increase, a person with lower general mental ability
is less likely to be successful than a person with a higher
g. Although this research study did not aim to investigate
the taxonomy of cognitive ability it remains important
to emphasise the impact of cross-cultural differences on
cognitive performance.
In this regard a study by Helms-Lorentz, Van de Vijver,
and Poortinga (2003) examined the cultural loadings of
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test material. The term cultural loading refers to a specific
cultural context that is reflected in the instrument or in the
administration thereof. The cultural context is usually that of
the test developer and it can create intergroup differences that
are not related to the construct measured by the instrument.
The results of the study by Helms-Lorentz et al. (2003)
suggested that cultural complexity (c) was as important as
g in the explanation of performance differences between
cultural groups on cognitive tests.
According to the discussion of process models of faking, the
ability to fake successfully implies that a respondent must be
able and motivated to distort responses (cf. Tett et al., 2011).
According to English et al. (2005) individuals who are able to
fake must have analytical ability to apply problem-solving
to understand the construct being measured and also to
understand the advantages of faking such behaviour. In this
regard they reported that individuals high in g recognise and
solve problems more successfully than individuals low in g.
In addition, individuals high in g can understand the items in
the instrument, can detect desirable answers and can respond
accordingly. However, the study found that intelligence
did not predict response distortion but that job knowledge
moderated (strengthened) the ability to fake. The findings
were consistent with previous research, which indicated that
general mental ability has a major effect on the acquisition
of job knowledge (Arneson et al., 2011; Kunzel & Hezlett,
2010). People higher in general mental ability acquire more
job knowledge and at a faster rate than people with lower
general mental ability. In addition, research conducted by
Wrensen and Biderman (2005) indicated that cognitive ability
was positively related to the ability to fake extroversion,
conscientiousness and stability (individual differences). t
is, therefore, important to investigate whether or not race
moderates the relationship between social desirability and
cognitive ability.
Research design
Research approach
To meet the main objective of this study a quantitative,
cross-sectional research design based on secondary data
were employed. The secondary datasets were obtained from
Psytech South Africa, the test publisher for the measuring
instruments utilised in the study. The use of secondary data
is appropriate as the datasets were collected anonymously.
The researcher, therefore, need not be concerned with ethical
issues concerning the protection of participant identity
(Spector, cited in Anderson, Ones, Sinangil & Viswesvaran,
2001). The main limitations of using secondary data involve
the researcher’s inability to control for data collection
errors, the lack of control over the selection of samples and
comparison groups and also the quality of the sampling
frame which can influence the generalisability of the results
(Mouton, 2001). In order to counter the effects of sample
selection, both language and race were utilised as independent
variables as they are of particular concern in South Africa
when evaluating an instrument for the presence of bias (Van
de Vijver & Rothman, 2004). Language in South Africa also
varies in relation to culture. South Africa recognises eleven
official languages and the custom is, therefore, to assess in
the language used in the workplace. The dominant language
of business and industry in South Africa is English and all
of the measuring instruments utilised in this study were
administered in English.
Research method
Measuring instruments
In this study the influence of cognitive ability on socially
desirable responding was examined utilising a social
desirability measure and a cognitive ability measure. The
Social Conformity scale of the Occupational Personality
profile (OPP) was used to operationalise social desirability.
The Marlow-Crowne Scale (Crowne & Marlow, 1960) forms
the basis of the Social Conformity scale in the OPP and
consists of 8 items with a 5–point response format ranging
from (1) ‘strongly agree’ to (5) ‘strongly disagree’. Budd
(1991) reported that the reliability of the Social Conformity
scale, as estimated by the Cronbach alpha coefficient, is .59.
The reliability of the Social Conformity scale is below the
acceptable standard of .70, but was considered acceptable
for research purposes as the personality inventory with the
social conformity scale is currently in use in South Africa (cf.
Aguinis, Henle & Ostroff, 2001). The General Reasoning Test
Battery (GRT2), which measures general verbal, numerical
and abstract reasoning, was employed to measure cognitive
ability. The three sub-tests within this battery have been
shown to demonstrate a good standard of reliability, as
reported by the following reliability coefficients:
• verbal reasoning (35 items, α = .83)
• numerical reasoning (25 items, α = .84)
• abstract reasoning (25 items, α = .83) (Budd, 1993).
Research parcipants and procedure
Participants were 1640 adult job applicants1 (595 female
and 1045 male) who completed both the Social Conformity
Scale of the OPP and the GRT2. Job applicant data sets
were utilised as there is currently strong evidence that the
job applicants’ score distributions are significantly different
from those of the general population and, therefore, the
use of job applicant samples is imperative when studying
group differences in social desirability (Rossė et al., 1998;
Viswesvaran et al., 2003). The average age of the participants
was 26 years. Closer inspection revealed that comparing the
collective black Nguni languages representing Zulu, Xhosa,
Ndebele and Swazi (n = 638), and black Sotho language
groupings representing Tswana, Pedi and South Sotho
(n = 517), with that of white Afrikaans (n = 272) and white
English speakers (n = 212) would provide a large enough
sample for comparison. As there were insufficient numbers
of participants from the coloured2 and Asian ethnic groups,
1.Limitaons for the use of secondary datasets are the inability to control for level of
educaon and gender representaon.
2.The term ‘coloured’ is used to refer to people of mixed racial descent and is used
by the South African government as part of its ocial racial categorisaon scheme.
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Page 7 of 13 Original Research
these were excluded from the study. The data were collected
from various South African companies who used the OPP
and GRT2 for selection purposes. During test administration
all participants provided consent to the Test Publisher that
information can be utilised for research purposes. In addition,
all psychometric data were dealt with confidentially and
strict ethical publishing practices were followed (Ethical
Rules of Conduct, HPCSA, 2006).
Stascal analysis
To achieve the main research objectives of the study the
abstract, numerical and verbal reasoning sub-tests of the
GRT2 were subjected to a principal axis factor analysis
with iterated communalities, followed by a multi-group
confirmatory factor analysis. The objective of these analyses
was to establish whether or not an invariant total General
Reasoning factor could be extracted from the three sub-tests.
Next, mean differences, standard deviations and effect sizes
were calculated using the white English-speaking group as
the reference group. To examine the relationships between
social desirability, cognitive ability and culture and language,
a moderated multiple regression (MMR) was conducted,
where the English group served as the reference group.
Next, the results are presented followed by a discussion of the
results to provide possible explanations for the differences
observed.
Results
The main objective of the study was to determine whether or
not any potential race group differences in social desirability
scores are the result of potential group differences in cognitive
ability. As a first step it was important to establish whether
or not an invariant total General Reasoning factor could be
extracted from the three sub-tests of the General Reasoning
Test battery (GRT) employed to measure cognitive ability.
The Abstract, Numerical and Verbal Reasoning sub-tests
were subjected to a principal axis factor analysis with iterated
communalities, followed by a multi-group confirmatory
factor analysis. The principal axis factor analysis was chosen
as the extraction method because the objective of the analysis
was to detect structure and to estimate the proportion of
variance that each item has in common with other items. A
one-factor solution produced a very good fit with the data,
with all the correlation residuals very close to zero (the
largest residual was 0.01) showing that no more than one
meaningful factor could be extracted. The three eigenvalues
of the unreduced correlation matrix were 2.39, 0.32, and 0.29,
which also points to the retention of a single factor. The factor
loadings of the three sub-tests on this factor were as follows:
• Abstract Reasoning = 0.85
• Numerical Reasoning = 0.82
• Verbal Reasoning = 0.82.
In addition, the multi-group confirmatory factor analysis
showed a satisfactory fit for a one-factor model requiring
equal unstandardised factor loadings across the four ethnic
groups [χ2(6) = 53.808, p < .001; CFI = 0.973; RMSEA = 0.070].
On the basis of these results it was deemed appropriate to
calculate a single General Reasoning score for each person
by aggregating scores with unit weighting over the three
sub-tests. The General Reasoning score was conceptualised
as being representative of general mental ability or g. The
results of this study are consistent with the test developers’
intention of constructing a test that measures general
reasoning ability (Budd, 1993). The mean General Reasoning
score was subtracted from each respondent’s observed score,
which resulted in a centred General Reasoning variable with
a mean of zero. These centred General Reasoning scores
were used in the subsequent moderated multiple regression
analyses (cf. Aguinis, 2004).
Next, the means, standard deviations and effect sizes of
the culture and language groups for the Social Conformity
Scale and General Reasoning were examined. The uncentred
means and standard deviations of the four culture and
language groups, for OPP Social Conformity Scale and
General Reasoning, are provided in Table 1, which also
contains the group mean differences.
Using the white English-speaking group as the reference
group, the effect sizes of the differences in means for General
Reasoning were as follows: black Sotho-speaking, d = -1.29;
black Nguni-speaking, d = -1.30; and white Afrikaans-
speaking, d = -0.18. On average, the two black groups scored
substantially lower than the two white groups on General
Reasoning. However, the differences between the two black
groups and between the two white groups were small.
Table 1 also shows that the two black groups scored higher
than the two white groups on the OPP Social Conformity
Scale. However, within the black group the Sotho and Nguni
groups obtained very similar mean-scores. Similarly, within
the white group the Afrikaans and English groups obtained
very similar scores. Using the white English-speaking-group
as the reference group, the effect sizes of the mean differences
for OPP Social Conformity were as follows: black Sotho-
speaking, d = 0.38; black Nguni-speaking, d = 0.38; and white
Afrikaans-speaking, d = -0.04.
To examine the relations of the General Reasoning and cultural
and language group with OPP Social Conformity Scale a
TABLE 1: Descripve stascs for general reasoning and social conformity scale.
Variable M SD Eect size (d)
General Reasoning
English 45.44 14.89 *
Afrikaans 42.71 14.48 -0.18
Nguni 26.10 11.41 -1.30
Sotho 26.30 11.37 -1.29
Social Conformity Scale
English 22.86 4.05 *
Afrikaans 22.67 4.14 -0.04
Nguni 24.52 4.48 0.38
Sotho 24.66 4.42 0.38
M, mean; SD, standard deviaon
*, Note. The white English-speaking group served as the reference group.
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Page 8 of 13 Original Research
moderated multiple regression (MMR) was undertaken. For
the purpose of the MMR the language group variable was
dummy coded. The English group served as the reference
group and three coded vectors were created to represent the
Afrikaans, Nguni, and Sotho groups. The MMR proceeded
in three steps as indicated in Table 2. General Reasoning
(centred) was entered in the first step, the dummy coded
language group vectors were added in the second step, and
the products of General Reasoning (centred) and the dummy
coded language group vectors were added in the third step.
General Reasoning, language group, and their interaction
jointly accounted for approximately 5.2% of the variance
in OPP Social Conformity Scale, R2 = 0.052, F (7, 1632) =
12.747, p < .001. Inspection of the ΔR2 for the third step shows
that the interaction of General Reasoning and language
group made a statistically significant contribution to the
prediction of OPP Social Conformity above and beyond the
contributions made by the General Reasoning and language
group, ΔR2 = 0.006, F (3, 1632) = 3.247, p = .021. The data,
therefore, support the proposition that culture and language
moderates the relationship between General Reasoning
and the OPP Social Conformity Scale. The effect size for the
interaction of General Reasoning and language group was
f2 = 0.006. Aguinis and Henle (2003) reported a mean effect
size of 0.009 with 95% confidence intervals of 0.006 and 0.012
in their review of studies, using MMR in top tier industrial
and organisational psychology and management journals.
The effect size for the interaction obtained in this study is
consistent with those reported in the industrial psychology
literature in general.
Inspection of the ΔR2 for the second step shows that the
cultural group made a small but statistically significant
contribution to the prediction of the OPP Social Conformity
Scale above and beyond the contribution of General
Reasoning [ΔR2 = 0.010, F(3, 1635) = 5.454, p = .001]. Hence,
the data also support the proposition that there are cultural
differences in social desirability when cognitive ability is
held constant. Finally, the first step of the MMR showed that
General Reasoning was a statistically significant predictor
of OPP Social Conformity [R2 = 0.037, F (3, 1638) = 62.292,
p < .0001].
Against the background of the significant interaction
between General Reasoning and culture, indicating that the
slope of the regression lines differs across groups, separate
regression equations were calculated for the four language
groups. Predicted scores for each of the four language groups
were calculated at one standard deviation below the mean
and one standard deviation above the mean of General
Reasoning. These predicted scores are plotted in Figure 1,
which shows that the relations between cognitive ability and
social desirability differ across groups.
Figure 1 shows that at low General Reasoning levels, the
biggest difference in predicted Social Conformity scores
was observed for the Sotho and English groups (with the
Sotho group having higher predicted Social Desirability
scores). In contrast, at high General Reasoning levels the
biggest absolute difference was observed for the Afrikaans
and Nguni groups (with the Nguni group having higher
predicted Social Conformity scores). Finally, Figure 1 shows
that the group differences in Social Conformity are much
more pronounced at the lower end of General Reasoning.
Although the group differences at the upper end of General
Reasoning are much smaller they remain clearly visible. For
the English group there is virtually no relationship, whereas
for the remaining three groups there is a clear trend towards
individuals with high cognitive ability tending to give less
socially desirable responses.
To conclude, the exploratory factor analysis showed that a
one-factor solution produced a very good fit and the total
score of the Verbal, Numerical and Abstract reasoning tests
was, therefore, used to operationalise General Reasoning
ability. Examining the magnitude of culture and language
group mean-score differences on social desirability scores
and cognitive ability amongst job applicants, the results
showed that the two black groups scored higher than the
two white groups on the Social Conformity Scale. However,
TABLE 2: Hierarchical moderated mulple regression of the relaons between OPP Social Conformity Scale, cognive ability, and language/culture.
Model R R2Adjusted R2SE of the esmate
Change stascs
ΔR2ΔF df1df2p
1 0.191 0.037 0.036 4.344 0.037 62.292 1 1638 < .001
2 0.215 0.046 0.044 4.326 0.010 5.454 3 1635 .001
3 0.228 0.052 0.048 4.318 0.006 3.247 3 1632 .021
SE, standard error; df, degrees of freedom.
The English group served as the reference group.
FIGURE 1: Relaonship of general reasoning with social desirability.
22.25
22.50
22.75
23.00
23.25
23.50
23.75
24.00
24.25
24.50
24.75
25.00
25.25
25.50
General Reasoning (Centered)
Social Desirability
Low GR
1 SDBelow
High GR
1 SDAbove
Afrikaans
English
Nguni
Sotho
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Page 9 of 13 Original Research
within the black group the Sotho and Nguni groups obtained
very similar mean-scores. Similarly, within the white group
the Afrikaans and English groups obtained very similar
scores. In terms of the relationship of social desirability with
cognitive ability, the results showed group mean differences
in General Reasoning with the Nguni and Sotho groups
scoring lower on General Reasoning and higher on Social
Desirability than the Afrikaans and English groups. The
relationship of Social Desirability and General Reasoning is,
therefore, moderated by culture and language with group
differences in Social Desirability more pronounced at the low
General Reasoning level.
Discussion
Early on in the conceptualisation of social desirability
Crowne and Marlowe (1960) suggested that people respond
in a manner that is culturally acceptable in order to obtain
social approval. Culture was therefore recognised as an
important factor when determining whether opinions and
behaviours of people are desirable or not (Johnson & Van de
Vijver, 2003). However, questions have never been seriously
examined in South Africa regarding the relationship between
socially desirable responding and cognitive ability amongst
job applicants, and whether or not race differences in social
desirability scores are related to differences cognitive ability.
The results of this study show that on average, Nguni-
speaking and Sotho-speaking participants scored lower on
the GRT2 and slightly higher on the Social Conformity scale
than their Afrikaans and English-speaking counterparts. Of
greater significance is the finding that general reasoning
is negatively related to social desirability and that this
relationship is moderated by ethnicity. Possible explanations
for group differences in the South African context can be
attributed to:
1. the level of education, socio-economic status, language
and understanding of English (Abrahams & Mauer, 1999;
Meiring et al., 2005; Stephen et al., 2004; Van Zyl & Visser,
1998).
2. cultural loadings of test material that include implicit
and explicit references to a specific cultural context,
usually that of the test author, in the instrument or its
administration (Helms-Lorent et al., 2003). In this regard
cultural complexity (c) was as important as g in the
explanation of performance differences between cultural
groups on cognitive tests.
In totality, the results support the proposition that culture
moderates the relationship between General Reasoning
and the OPP Social Conformity Scale. It also supports
suggestions that this moderation may be attributed to social
naïveté or conformity, and is likely to be connected to the
level of cognitive ability of the respondent (Dilchert & Ones,
2005; Greene, 2000; Tett et al., 2011). In addition, Mueller-
Hanson et al. (2006) provided evidence that in order to distort
responses successfully the respondent must be able and
motivated to distort responses. The ability to distort responses
is connected to the analytical ability to apply problem-solving
to understand the construct being measured, and also to
understand the advantages of faking behaviour (English
et al., 2005; Kunzel & Hezlett, 2010; Tett et al., 2011). Thus,
individuals high in g recognise and solve problems more
successfully than those low in g. In addition, individuals
high in g understand the items in the instrument, can detect
desirable answers and respond accordingly. Research
evidence has also shown that intelligence does not predict
response distortion but that job knowledge moderates the
ability to fake (Tett & Simonet, 2011). In support of the ability
and also the motivation to fake, Wrensen and Biderman
(2005) reported that social desirability was negatively related
to faking ability, as those high in social desirability obtained
the lowest faking ability scores. The results of this study are
consistent with the findings of previous research, which
suggest that social desirability scales may be an ambiguous
indicator of faking as the scales may indicate propensity for
faking (tendency to fake) but not the ability to fake.
If one assumes that cognitive ability is a primary selection
tool, then it appears that there is a substantial threat
of adverse impact (with proportionally more white
participants being selected than black participants). If
on top of this high scores on social desirability are used
to eliminate candidates suspected of faking, the adverse
may be exacerbated (with proportionally even more white
participants being selected).
Against the background that (1) there are group mean
differences in social desirability scores, (2) there are
large group mean differences in cognitive ability scores
and (3) cognitive ability is differentially related to social
desirability across the groups, it also appears unreasonable
to apply uniform corrections for social desirability for all
groups. Such corrections are likely to penalise individuals
with lower cognitive ability scores who tend to give more
socially desirable responses. Individual differences in social
desirability are also not fully explained by General Reasoning;
cultural differences also played a role. This is consistent with
findings by Greene (2000) that suggested a link between
cognitive ability and social desirability, as responding in a
certain manner reflects a level of psychological sophistication
informed by the level of education and socio-economic status,
thus supporting the literature of acculturation (Johnson &
Van de Vijver, 2003; Shuttleworth-Jordan, 1996).
Based on the discussion of the results, the practical
implications of the study follow.
Praccal implicaons
As alluded to in the introduction, one of the biggest concerns
raised by practitioners in the use of personality inventories
is the potential impact of socially desirable responding on
selection decisions. The most popular strategy to address
response distortion is the inclusion of social desirability scales
in personality inventories. In applied settings Industrial
Psychologists use these scales to eliminate sources of bias or
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systematic error that are not relevant to the measured attribute,
to identify applicants who are deliberately presenting
themselves in a positive manner, to adjust personality scale
scores to compensate for socially desirable responding and to
flag potentially invalid personality profiles.
An important implication of this study is the confirmation
that the relationship between social desirability and general
reasoning is moderated by culture and language, with group
differences in social desirability being more pronounced at
the low general reasoning level. This suggests that social
desirability scales may be an ambiguous indicator of faking
as the scales may indicate propensity for faking (tendency to
fake) but not the ability to fake.
The results of this study also suggest that it is ethically
questionable to deny someone a job opportunity based on
the proposed validity of the personality profile, as a result
of a score on a social desirability scale. This type of ethical
implication is rarely discussed on a practical level. For
example, the use of social desirability scales in personality
instruments means that the typical instructions on a
personality inventory (there are no right or wrong answers on
this test) are, therefore, not true (or even ethical) as different
strategies are used to identify potential fakers and corrections
are then made based on the results (Dilchert & Ones, 2011).
Finally, in terms of selection practice, this study provided
evidence of potential adverse consequences of using social
desirability scales to detect response distortion and to disqualify
applicants from the selection process. This study reported large
group mean differences in cognitive ability and also social
desirability scores, with the differences more pronounced at
the lower cognitive ability level. The practical implication is
that the use of a social desirability scale could adversely impact
black applicants in ways that are not job related. If multiple
predictors, such as cognitive ability, are utilised for selection
the adverse impact may be exacerbated (with proportionally
even more white applicants being selected).
Limitaons and recommendaons
Although the study made significant contributions to the
body of knowledge concerning social desirability in a multi-
cultural context, several limitations should be noted and
addressed in future research. Firstly, the study used a cross-
sectional design and, therefore, the relationships between
variables cannot be interpreted causally. It is recommended
that future research make use of longitudinal analytical
methods to explore how the impact of socially desirable
responding unfolds over time.
Secondly, the study used secondary data and the researcher
was, therefore, unable to control for data collection errors. The
researcher’s lack of control over the selection of samples and
comparison groups and also the quality of the sampling frame
(e.g. gender representation and level of education) should be
noted. This could potentially influence the generalisability of
the results across groups. In an attempt to counter the effects
of sample selection, a decision was taken to compare groups
across race and language. However, although respondents
may share a common language they may be separated
by a large cultural distance that requires further research,
especially as there are assumed to be large cultural distances
between indigenous and western cultures in South Africa.
The results of this study provided evidence that suggests
that culture, socio-economic status, level of education and
language are possible sources of item or test bias.
The literature review furthermore provided evidence that
job-relevant predictor composites often contain cognitive
ability measures that produce fairly substantial group mean-
score differences, contributing to potential adverse impact.
These findings were replicated in the current study. The
challenge of achieving accurate predictions (criterion-related
validity) whilst also achieving similar selection ratios for sub-
groups (reduced adverse impact), requires further research.
Using linear programming methods, De Corte, Lievens and
Sackett (2007) proposed a procedure for forming a weighted
composite that reduces adverse impact as much as possible,
given a specified level of validity. It is recommended that
future research be undertaken in the South African context to
examine this procedure in order to understand the sensitivity
of predictor weights on adverse impact and validity outcomes.
The use of multiple assessments is further seen as a best
practice standard in applied settings and is recommended
when using personality measures (Hough & Ones, 2001;
Mueller-Hanson et al., 2006). The identification of potential
adverse impact resulting from the use of social desirability
scales and also cognitive ability measures, highlights the
importance of accumulating evidence regarding the impact
of multiple predictors on selection decisions. To this end it is
recommended that employers using personality inventories
in high-stakes selection settings need to accurately assess the
requirements of the work context (job analysis) to identify
appropriate predictors that may or may not have adverse
impact on some groups (see Hough & Oswald, 2008). The legal
context in South Africa must also be taken into consideration,
as the pressure to ensure job relevance, reliability, validity and
lack of bias of instruments, administered as part of a selection
battery, remains a priority. In order to make cross-cultural
comparisons continuous research must be undertaken
to establish the cross-cultural equivalence of assessment
outcomes and to address possible causes of cultural bias.
Conclusion
Given the prevalent use of social desirability scales in
personality assessment in South Africa, the study provided
evidence that there are culture and language group mean
differences in social desirability scores. Within the black
group the Sotho and Nguni groups, and within the white
group the Afrikaans and English groups obtained very
similar scores. The data support the hypothesis that culture
and language moderates the relationship between General
Reasoning (cognitive ability) and OPP Social Conformity
(social desirability).
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Results further show that the relations between cognitive
ability and social desirability differ across groups. For the
English group there is virtually no relation, whereas for the
remaining groups there is a trend where individuals with
high cognitive ability tend to give less socially desirable
responses. The results also show that the differences in
group means for social desirability are not fully explained by
differences in cognitive ability. Cultural differences appear
to play a role above and beyond the role of differences in
cognitive ability.
Cognitive ability is, therefore, differentially related to
social desirability across culture and language groups and
it appears unreasonable to apply uniform corrections for
social desirability across culture and language groups. The
differences in cognitive ability and social desirability mean-
scores across the different culture and language groups can
lead to differential selection ratios between groups and, thus,
potentially to adverse impact. It is further evident from this
study that the validity and fairness of social desirability
scales to detect applicant faking in the operational setting
should be seriously questioned.
In the South African context the following should be taken
into account:
[It does not seem] unreasonable to attribute at least some part
of the systematic group-related differences, especially on the
measure of cognitive ability, to a socio-political system that
systematically denied the members of specific groups the
opportunity to develop and acquire those crystallised abilities
required to succeed on the criterion. (Theron, 2007, p. 114)
The solution lies in affirmative development interventions
aimed at developing those attainments and dispositions
needed to succeed. This will present numerous exiting
and stimulating challenges to the IO psychologist in
South Africa.
Acknowledgements
This study forms part of a doctoral study that consists of
four empirical studies. The author acknowledges with
great appreciation the contribution of Professor Gideon
P. de Bruin and Professor Gert Roodt from the University
of Johannesburg, and Nanette Tredoux (Psytech SA) for
supporting this research by providing access to data sets.
Compeng interests
The author declares that she has no financial or personal
relationship(s) that may have inappropriately influenced her
in writing this article.
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