Review of Faking in Personnel Selection

1
Review of Faking in Personnel Selection
Chris D. Fluckinger University of
Akron cdf12_at_uakron.edu
Deborah L. Whetzel Human Resources Research
Organization dwhetzel_at_humrro.org

• Michael A. McDaniel
• Virginia Commonwealth University
• mamcdani_at_vcu.edu

Prepared for International Workshop on Emerging
Frameworks and Issues for ST Recruitments Societ
y for Reliability Engineering, Quality and
Operations Management (SREQOM) Delhi, India
September, 2008
2

• We note that Chris D. Fluckinger is the senior
  author of our book chapter associated with this
  conference. Although not present at the
  conference, his contributions to this
  presentation were substantial.

3
Goal of this Presentation

• Provide practitioners and researchers with a
  solid understanding of the practical issues
  related to faking in test delivery and
  assessment.

4
Overview

• Typical vs. maximal performance
• The usefulness of different strategies to
  identify faking
• How faking creates challenges to test delivery
  and measurement
• Review and critique of common strategies to
  combat faking

5
Faking

• Faking is a conscious effort to improve ones
  score on a selection instrument.
• Faking has been described using various terms
  including
• Response distortion
• Social desirability
• Impression management
• Intentional distortion, and
• Self enhancement
• Hough, Eaton, Dunnette, Kamp, McCloy (1990)
  Lautenschlager, (1994) Ones, Viswesvaran
  Korbin (1995).

6
Maximal vs. Typical Performance

• Faking can be understood by comparing the
  distinction between maximal and typical
  performance.
• Cronbach, (1984)
• This distinction is useful in understanding
  faking.

7
Maximal Performance

• Maximal performance tests assess how respondents
  perform when doing their best.
• A mathematics test of subtraction is an
  assessment of maximal performance in that one is
  motivated to subtract numbers as accurately as
  one is able.
• Cognitive ability and job knowledge tests are
  also maximal performance measures.

8
Maximal Performance

• In high stakes testing, such as employment
  testing, people are motivated to do their best,
  that is, to provide their maximal performance.
• In high stakes testing, both those answering
  honestly and those seeking to fake have the same
  motivation Give the correct answer.
• One can guess on a maximal performance test but
  one cannot fake.

9
Maximal Performance

• Maximal performance tests do not have faking
  problems because the rules of the test (make
  yourself look good by giving the correct answer)
  and the rules of the testing situation (make
  yourself look good by giving the correct answer)
  are the same.

10
Typical Performance

• In typical performance tests, the rules of the
  test are to report how one typically behaves.
• In personality tests, the instructions are
  usually like this
• Please use the rating scale below to describe how
  accurately each statement describes you. Describe
  yourself as you generally are now, not as you
  wish to be in the future. Describe yourself as
  you honestly see yourself.
• Adapted from http//ipip.ori.org/newIPIPinstructio
  ns.htm

11
Typical Performance

• Thus, in a typical performance test, if one is
  lazy and undependable, one is asked to report on
  the test that one is lazy and undependable.
• The rules of the test (describe how you typically
  behave) contradict the rules of the testing
  situation (make yourself look good by giving the
  correct answer).
• This contradiction makes faking likely.

12
Typical Performance

• If one who is lazy and undependable, answers
  honestly, one will do poorly on the test.
• If one who is lazy and undependable fakes, the
  respondent reports that they industrious and
  dependable. The respondent who fakes will do
  well on the test.
• Example McDaniels messy desk

13
Typical Performance

• Thus, one can improve ones score on a
  personality test by ignoring the rules of the
  test (describe how you typically behave) and by
  following the rules of the testing situation
  (make yourself look good by giving the correct
  answer).

14
Typical Performance

• On typical performance tests, it is easy to know
  the correct responses
• Dependable
• Agreeable
• Emotionally stable
• Thus, it is easy to fake on typical performance
  measures, such as personality tests, and one can
  dramatically improve ones score through faking.

15
How much faking is there?

• Over two-thirds (68) members of the Society for
  Human Resource Management (SHRM) thought that
  integrity tests were not useful because they were
  susceptible to faking.
• Rynes, Brown Colbert (2002)
• Similarly, 70 of professional assessors believe
  that faking is a serious obstacle to measurement.
• Robie, Tuzinski Bly (2006)
• These results suggest that there is frequent
  faking in testing situations.

16
How much faking is there?

• There is some emerging evidence that patterns
  exist regarding the proportion of fakers in a
  given sample.
• Specifically, converging evidencethough
  tentativeindicates that approximately 50 of a
  sample typically will not fake, with most of the
  rest being slight fakers, and a select few being
  extreme fakers.

17
How much faking is there?

• One study found that 30-50 of applicants
  elevated their scores compared to later honest
  ratings.
• Griffeth et al. (2005)
• There is also self-reported survey evidence that
  65 of people say they would not fake an
  assessment, with 17 unsure and 17 indicating
  they would fake.
• Rees Metcalfe (2003)
• None of this is encouraging for practitioners,
  because the presence of moderate numbers of
  fakers, particularly small numbers of extreme
  fakers, presents significant problems when
  attempting to select the best applicants.
• Komar (2008)

18
Personality tests are big business

• Over a third of US corporations use personality
  testing, and the industry takes in nearly 500
  million in annual revenue.
• Rothstein Goffin (2006)

19
Stop using personality tests?

• The fact that applicants may be highly motivated
  to fake in order to gain employment has raised
  many questions as to the usefulness of
  non-cognitive measures.
• Some have even gone far enough to suggest that
  personality measurement should not be used for
  employee selection.
• Murphy Dzieweczynski (2005)

20
But personality predicts

• Personality tests predict important work
  outcomes, such as job performance and training
  performance.
• Barrick, Mount Judge, 2001 Bobko, Roth
  Potosky, 1999 Hough Furnham, 2003 Schmidt
  Hunter, 1998.

21
Predict even with faking

• Personality measures predict work outcomes, even
  under conditions where faking is likely.
• Rothstein and Goffin state that there are
  abundant grounds for optimism that the
  usefulness of personality testing in personnel
  selection is not neutralized by faking (p. 166).

22
Faking still causes problems

• Even though personality measures often produce
  moderate predictive validities, there are a
  number of other ways that faking can cause
  problems, including
• the construct validity of measures
• changes in the rank-order of who is selected.

23
Evidence of faking
24
Evidence of faking

• The concept of faking is relatively
  straightforward
• People engage in impression management and
  actively try to make themselves appear to have
  more desirable traits than they actually possess.
  
• However, identifying actual faking behaviors in a
  statistical sense has proven to be exceedingly
  difficult.
• Hough Oswald (2005)

25
Faking shows itself in various ways

• Attempts to fake can show up in a number of
  statistical indicators
• test means
• social desirability scales
• criterion-related validity
• actual or simulated hiring decisions
• construct validity.
• There is ample evidence that faking likely
  influences most of these crucial test properties

26
Social desirability as faking

• The construct of social desirability states that
  the tendency to manage the impression one
  maintains with others is a stable individual
  difference that can be measured using a
  traditional, Likert-style, self-report survey.
• Paulhus John (1998)
• Social desirability items are unlikely virtues,
  that is, behaviors that we recognize as good but
  that no one usually does
• I have never been angry
• I pick up trash off the street when I see it.
• I am always nice to everyone

27
Social desirability as faking

• Applicants for a job had higher social
  desirability scores than incumbents, which was
  interpreted as evidence that the applicants were
  faking.
• Rosse, Stecher, Miller, Levine (1998)
• The initial view regarding social desirability
  from an applied perspective was that it could be
  measured in a selection context and used to
  correct, or adjust, the non-cognitive scores
  included in the test.

28
Social desirability as faking

• Social desirability does not function as
  frequently theorized.
• A meta-analysis showed that social desirability
  does not account for variance in the
  personality-performance relationship.
• Ones, Viswesvaran and Reiss (1996)
• This means that knowledge of a persons level of
  social desirability will not improve the
  measurement of that persons standing on a
  non-cognitive trait.

29
Social desirability as faking

• Stated another way, this means that one cannot
  correct a persons personality test score for
  social desirability to improve prediction.
• Applicants often fake in ways that are not likely
  to be detected by social desirability scores.
• Alliger, Lilienfeld Mitchell (1996) Zickar
  Robie, (1999)
• Summary Social desirability is a poor indicator
  of applicant faking behavior.

30
Mean difference as faking

• Faking is apparent when one compares responses of
  groups of people who take a test under different
  instructions
• Test scores under fake-good instructions lead to
  higher test means than scores under honest
  instructions (d .6 across Big 5 personality
  dimensions).
• Viswesvaran Ones (1999)

31
Mean difference as faking

• This pattern is similar when comparing actual
  applicants and incumbents
• The largest effects are found for the
  traditionally most predictive personality
  dimensions in personnel selection,
  conscientiousness (d .45) and emotional
  stability (d .44).
• Birkeland, Manson, Kisamore, Brannick Smith
  (2006)
• Integrity test means shows the same pattern of
  increased means in faking conditions (d .36 to
  1.02).
• Alliger Dwight (2000)

32
Mean difference as faking

• Thus, people have the highest means in
  experimental, fake-good designs and somewhat
  lower means in applicant settings, and these
  means are nearly always higher than
  honest/incumbent conditions.
• These are the most consistent findings in faking
  research, and they are often taken as the most
  persuasive evidence that faking occurs.

33
Mean difference as faking

• Although the mean differences between faking and
  honest groups permits one to conclude that faking
  occurs, it is of little help in identifying which
  applicants are faking.

34
Criterion-related validity and faking

• Criterion-related validity is the correlation
  between a test and an important work outcome,
  such as job performance.
• It is logical to assume that as applicants fake
  more, the test will be less able to predict
  important work outcomes.

35
Criterion-related validity and faking

• Students conscientiousness ratings (measured
  with personality and biodata instruments) were
  much less predictive of supervisor ratings when
  they completed the measures under fake-good
  instructions.
• Douglas, McDaniel and Snell (1996)
• The general pattern in applied samples is
  similar, as predictive validity is highest in
  incumbent (supposedly honest) samples, slightly
  lower for applicants, and drastically lower for
  fake-good directions.
• Hough, 1998
• These findings are commonly interpreted as
  supporting the hypothesis that faking may lower
  criterion-related validity, but it often does not
  do so drastically.

36
Criterion-related validity and faking

• There are a number of caveats to this general
  pattern regarding predictive validity.
• One is situation strength when tests are
  administered in ways that restrict natural
  variation, criterion-related validity will drop.
• Beatty, Cleveland Murphy (2001)
• For example, if an organization clearly
  advertises that it only hires the most
  conscientious people, then applicants are more
  likely to fake to appear more conscientious.

37
Criterion-related validity and faking

• Another caveat is the number of people who fake.
• A Monte Carlo simulation found that the best-case
  scenario for faking is an all-or-nothing
  proposition validity is retained with no fakers
  or many fakers, but if there is a small minority
  of fakers present, they are likely to be
  rewarded, thus dragging overall test validity
  down.
• Komar, Brown, Komar Robie (2008)

38
Criterion-related validity and faking

• A final caveat is that the criterion-related
  validity of the test as a whole may not be
  sensitive to changes in the rank-ordering of
  applicants.
• Komar et al., (2008)
• This assumption was tested by rank-ordering
  participants from two conditions (honest and
  fake-good), and then dividing the distribution
  into thirds.
• Mueller-Hanson, Heggestad and Thornton (2003)
• The results indicated that the top third, which
  included a high percentage of participants who
  were given faking instructions, had low validity
  (r .07), while the bottom third produced high
  validity (r .45).

39
Criterion-related validity and faking

• Thus, a criterion-related validity study may show
  that the test predicts job performance. However,
  the test may not predict well for the top scoring
  individuals because these are the individuals who
  fake.

40
Selection decisions and faking

• The last slide suggested that those who fake may
  cluster at the top of the score list.
• This introduces the topic of selection decisions
  and faking.

41
Selection decisions and faking

• It is a common finding that people who fake
  identified by higher social desirability scores
  or by higher proportions of those from a faking
  condition will rise to the top of the selection
  distribution and increase their probability of
  being hired.
• Mueller-Hanson et al. (2003) Rosse et al.,
  (1998)
• This situation worsens as the selection ratio is
  lowered (fewer people are selected), because more
  of them are likely to be fakers.

42
Selection decisions and faking

• One study obtained applicant personality scores
  and then honest scores one month later.
• Out of 60 participants, one individual who was
  ranked 4 for the applicant test dropped to 52
  for the honest test, indicating a large amount of
  faking.
• Griffeth, Chmielowski and Yoshita (2005)

43
Selection decisions and faking

• Numerous additional studies have provided similar
  findings, suggesting that the rank order of
  applicants will change considerably under
  different motivational and instructional
  conditions.
• This pattern is usually attributed to faking
  behavior, but it can also be partly explained by
  random or chance variation.

44
Selection decisions and faking

• People might score higher or lower on a second
  test administration due to random factors (e.g.,
  feeling ill).
• Regardless, these consistent findings demand that
  users of non-cognitive tests cannot simply rely
  on a tests predictive validity to justify its
  utility as a selection device.

45
Construct validity and faking

• The construct validity of a test concerns the
  internal structure and reliable relationships
  with other variables.
• Construct validity helps one to understand what
  the test measures and what it does not.

46
Construct validity and faking

• Construct validity is often overlooked in favor
  of criterion-related validity.
• However, construct validity is crucially
  important regarding the quality of what is
  measured.
• Construct validity can also help us understand
  faking.

47
Construct validity and faking

• Factor analysis is a statistical method to help
  determine constructs measured by a test.
• Research indicates that construct validity does
  indeed drop when faking is likely present.
• The factor structure of non-cognitive tests,
  especially personality, tends to degrade when
  applicants are compared with incumbents, as an
  extra factor often emerges with each item loading
  on that factor in addition to loading on the
  hypothesized factors.
• Zickar Robie (1999) Cellar, Miller, Doverspike
  Klawsky (1996)

48
Construct validity and faking

• This means that the non-cognitive constructs
  actually change under faking conditions, shedding
  some doubt as to how similar they remain to the
  intended, less-biased constructs.

49
Summary of Faking Studies

• Applicants can fake and some do fake.
• Evidence for faking can be seen in various types
  of studies.
• But there is no good technology for
  differentiating the fakers from the honest
  respondents.

50
Practical issues in test delivery
51
Properties of the selection system

• Two key aspects of selection systems are
  particularly relevant to the issue of faking
• Multiple-hurdle vs. compensatory systems
• Use and appropriate setting of cut scores

52
Properties of the selection system
Multiple-hurdle vs. compensatory systems

• A multiple-hurdle system involves a series of
  stages that an applicant must pass through to
  ultimately be hired for the job.
• This usually involves setting cut scoresa line
  below which applicants are removed from the
  poolat each step (or for each test in a
  selection battery).

53
Properties of the selection system
Multiple-hurdle vs. compensatory systems

• A compensatory system, on the other hand,
  typically involves an overall score that is
  computed for each applicant, meaning that a high
  score for one test can compensate for a low score
  on another.
• Bott, OConnell, Ramakrishnan Doverspike, (2007)

54
Properties of the selection system
Multiple-hurdle vs. compensatory systems

• A common validation procedure involves setting
  cut scores based on incumbent data and then
  applying that standard to applicants.
• The higher means in applicant groups could result
  in systematic bias in the cut scores.
• Basically, since there is faking in applicant
  samples, using the cut score determined from
  incumbent data will result in too many applicants
  passing the cut score.
• Bott et al. (2007)

55
Properties of the selection system
Multiple-hurdle vs. compensatory systems

• Personality tests may best be used from a
  select-out versus the traditional select-in
  perspective.
• Mueller-Hanson et al. (2003)
• This means that the non-cognitive measures
  primary purpose would be to weed out the very
  undesirable candidates rather than to identify
  the applicants with the highest level of the
  trait.
• Dont hire the people who state that they are
  lazy and undependable
• But know that many of the people who score well
  on the personality test are also lazy and
  undependable
• Thus, the goal of the personality test is to
  reject those who are lazy and undependable and
  willing to admit it.

56
Properties of the selection system
Multiple-hurdle vs. compensatory systems

• Using a personality test or other non-cognitive
  measures as a screen-out allows many more
  applicants to pass the hurdle, thereby increasing
  the potential cost of the system.
• One still needs to screen the remaining
  applicants.
• Select-out may be a reasonable option under
  conditions of
• A high selection ratio (with many positions to
  fill per applicant)
• Or low cost per test administered (such as
  unproctored internet testing).
• Practitioners have to carefully consider and
  justify how the setting of cut scores matches
  with the goals and constraints of different
  selection systems.

57
Situational judgment tests with knowledge
instructions

• As noted in a previous presentation at this
  conference, situational judgment tests can be
  administered with knowledge instructions.
• Knowledge instructions ask the applicants to
  identify the best response or to rate all
  responses for effectiveness

58
Situational judgment tests with knowledge
instructions

• Knowledge instructions for situational judgment
  tests should make them resistant to faking.
• McDaniel, Hartman, Whetzel, Grubb (2007)
  McDaniel Nguyen (2001) Nguyen, Biderman,
  McDaniel (2005)

59
Situational judgment tests with knowledge
instructions

• Although resistant to faking, these tests still
  measure non-cognitive traits, specifically
• Conscientiousness
• Agreeableness
• Emotional stability
• McDaniel, Hartman, Whetzel, Grubb (2007)

60
Situational judgment tests with knowledge
instructions

• Thus, situational judgment tests hold great
  promise for measuring non-cognitive traits while
  reducing, and perhaps eliminating, faking.
• There are some limitations.

61
Situational judgment tests with knowledge
instructions

• Limitations
• It is hard to target a situational judgment test
  to a particular construct
• It is hard to build homogenous scales
• With personality tests, one can easily build a
  scale to measure conscientiousness and another to
  measure agreeableness
• Situational judgment tests seldom have clear
  subtest scales

62
Faking and cognitive ability

• The ability to fake may be related to cognitive
  ability such that those who are more intelligent
  can fake better.
• The little literature on this is contradictory.
• If faking is dependent on cognitive ability, then
  faking should increase the correlation between
  personality and cognitive ability.

63
Faking and cognitive ability

• One advantage of non-cognitive tests is that they
  show smaller mean differences across ethnic
  groups.
• If the ethnic group differences are due to mean
  differences in cognitive ability, and if faking
  increases the correlation between personality and
  cognitive ability, faking should make the ethnic
  group differences in personality larger.

64
Faking and cultural differences

• Almost all faking research is done with U.S.
  samples.
• The prevalence of faking might be substantially
  larger in other cultures.
• For example, in cultures where bribery is a
  common business practice, one might expect more
  faking.

65
Potential solutions to faking
66
Social desirability scales

• The literature is very clear that social
  desirability scales do not help in identifying
  fakers.
• Statistical corrections based on social
  desirability scales do not improve validity.
• Ellingson, Sackett and Hough (1999)
• Ones, Viswesvaran and Reiss (1996)
• Schmitt Oswald (2006)

67
Frame of reference

• The rationale behind frame of reference testing
  is to design tests that encourage test takers to
  focus on their behavior in a particular setting
  (e.g., work).

68
Frame of reference

• An example of frame of reference is the addition
  of the phrase at work at the end of each items.
• Typical item I am dependable
• Frame of reference item I am dependable at work.

69
Frame of reference

• There is some evidence that frame of reference
  testing may increase validity.
• Bing, Whanger, Davison VanHook (2004)
  Hunthausen, Truxillo, Bauer Hammer (2003)
• However, there is no evidence that frame of
  reference testing reduces faking behavior.

70
Test instructions Coaching

• If we want people to respond to our tests in a
  certain way, we can simply tell them via test
  instructions.
• Coaching is one kind of instruction, usually in
  the form of a vignette or example describing how
  to approach an item in a socially desirable way.
• Coaching predictably leads to faking behavior (as
  evidenced by higher test means) and is certainly
  a problem as advice to beat non-cognitive tests
  circulates around the internet.

71
Test instructions Warning

• Another popular strategy is to warn test takers
  that they will be identified and removed from the
  selection pool if they fake (known as a warning
  of identification and consequences).

72
Test instructions Warning

• A meta-analysis indicated that warnings generally
  lower test means over standard instructions (d
  .23), although there was considerable variability
  in the direction and magnitude of effects in the
  studies included.
• Dwight and Donovan (2003)

73
Test instructions Warning

• Problems
• Warnings may increase the correlation between the
  personality scales and cognitive ability.
• Vasilopoulos et al. (2005)
• Since one can not actually identify the fakers,
  it is dishonest to warn test-takers that fakers
  can indeed be identified.
• Zickar Robie (1999)

74
Test instructions Warning

• If most applicants heed the warning and do not
  fake, those who do fake may more easily obtain
  higher test scores.
• Thus, warnings are admittedly an imperfect method
  for combating faking, and more research is needed
  to determine the extent of their utility.

75
Get data other than self-report

• Personality and other non-cognitive constructs
  are often evaluated for selection purposes
  through ratings of others, including interviews
  and assessment centers.
• Approximately 35 of interviews explicitly
  measure non-cognitive constructs, such as
  personality and social skills, according to
  meta-analytic evidence.
• Huffcutt, Conway, Roth Stone (2001)

76
Get data other than self-report

• Similarly, many common assessment center
  dimensions involve non-cognitive aspects,
  including communication and influencing others.
• Arthur, Day, McNelly Edens (2003)

77
Get data other than self-report

• Little faking and impression management research
  has examined faking in interviews and assessment
  centers.
• However, it is logical that those who would fake
  in a personality inventory would also fake in an
  interview or an assessment center.

78
Forced-choice measures

• Item 1Choose one item that is Most like you, and
  one item that is Least like you

79
Forced-choice measures

• Forced-choice measures differ from Likert-type
  scales because they take equally desirable items
  (desirability usually determined by independent
  raters) and force the respondent to choose.
• Forced-choice has costs
• Abandoning the interval-level scale of
  measurement
• Abandoning the clearer construct scaling that
  Likert measures offer.

80
Forced-choice measures

• Whether the benefits of forced-choice formats,
  such as potentially reducing faking, justify
  these costs is questionable.
• The effect of forced-choice on test means is
  unclear, as some studies show higher means of
  forced-choice compared with Likert measures and
  others indicate lower means.
• Heggestad, Morrison, Reeve McCloy, (2006)
  Vasilopoulos, Cucina, Dyomina, Morewitz Reilly
  (2006)

81
Forced-choice measures

• Research on the effect of forced-choice on
  selection decisions used items in both a
  forced-choice and Likert format under
  pseudo-applicant instructions (pretend you are
  applying for a job).
• Heggestad et al. (2006)

82
Forced-choice measures

• They compared the rank-order produced by both
  tests to an honest condition using a different
  personality measure.
• Results showed few differences in the rank-orders
  between the measures, offering preliminary
  evidence that forced-choice does not improve
  selection decisions.
• In summary, forced-choice tests do not
  necessarily reduce faking, and the statistical
  and conceptual limitations associated with their
  use probably does not justify replacing
  traditional non-cognitive test formats.

83
Recommendations for Practice
84
Avoid corrections

• Little evidence exists that social desirability
  scales or lie scales can identify faking.
• Many tests include lie scales with instructions
  about how to correct scores based on lie scales,
  with the justification that corrections will
  improve test validity.
• Rothstein Goffin (2006)
• There is no evidence to support this assertion,
  rendering corrections a largely indefensible
  strategy.

85
Specify how non-cognitive measures fit the goals
of the selection system

• Given the consistent effect of faking on test
  means, faking will affect cut scores and who is
  selected in both compensatory and multiple hurdle
  systems.
• Bott et al. (2007)
• Cut scores may have to be adjusted upward if they
  are set based on incumbent scores.

86
Specify how non-cognitive measures fit the goals
of the selection system

• The select-out strategy is an option.
• Reject applicants who are willing to admit that
  they are lazy and undependable
• Screen the remaining applicants with a maximal
  performance measure that is faking-free or
  faking-resistant.
• Select-out is a good strategy when the selection
  ratio is high (i.e., you will hire most of those
  who apply).

87
Recognize that criterion-related validity may say
little about faking

• It is common to have a useful level of validity
  for the test, when known faking is present.
• However, the fakers are represented in greater
  proportions at the high end of the test scores.
• The validity may be much worse among these
  applicants.

88
Manipulate the motivation of the applicants

• If applicants are given information about the job
  to which they are applying, they can fake their
  scores toward that stereotype.
• Mahar, Cologon Duck (1995)
• On the other hand, if applicants are informed
  about the potential consequences of poor fit,
  which faking could realistically lead to during
  the placement phase, they may be motivated to
  respond more honestly, and initial research
  indicates that this may be true.
• Nordlund Snell (2006)

89
Conclusion

• Non-cognitive tests can be faked.
• Non-cognitive tests are faked.
• There is no method to eliminate faking.
• Consider using non-cognitive tests as select-out
  screens

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Conclusion

• Use maximal performance tests (cognitive ability
  and job knowledge) to screen those who remain.
• Consider measuring non-cognitive traits with
  faking-resistant situational judgment tests with
  knowledge instructions.

91
References

• References are in the book chapter.

92

• Thank you.
• Questions??