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Running Head: PROFILE ANALYSES OF PERSONALITY

Profile Analyses of Personality-Leadership Performance Relations

Jeff Foster and Joyce Hogan

Hogan Assessment Systems

Paper presented in M. Ingerick & L. M. Hough (symposium chairs) What Makes a Great

Leader? Refining the Personality-Leadership Relationship. 21st Annual Conference of Society

for Industrial and Organizational Psychology, May 2006, Dallas, Texas.

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Abstract

We examine the effects of both bright side and dark side personality characteristics on

leadership performance. Specifically, three profiles are evaluated using meta-analyses from

datasets (K = 6; N = 881) containing bright side personality variables, dark side personality

variables, and leadership performance ratings. Using three leadership models, we created

profiles using: (a) bright side marker HPI scales only; (b) dark side marker HDS scales only; and

(c) a combination of HPI and HDS scales. All profiles produced positive results, with

individuals who fit the profiles receiving significantly higher leadership ratings than those who

did not. Standardized group mean difference scores were .33 for the bright side profile, .36 for

the dark side profile, and .44 for the combination leadership profile. These results demonstrate

the value of selecting for positive personal characteristics while selecting out characteristics

detrimental to effective leadership performance. Implications and directions for future research

are discussed.

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Profile Analyses of Personality-Leadership Performance Relations

Leadership requires taking personality seriously because leadership, personality, and

personality assessment are necessarily related. How leaders view themselves is difficult to

measure with any scientific certainty; how observers view them is easy, reliable, and valid. Prior

to the appearance of Judge, Bono, Ilies, and Gerhardts (2002) meta-analysis of five-factor model

personality measures and leadership effectiveness, the literature suggested that personality

factors had only modest influence on leadership effectiveness. Because of the difficulties

involved in measuring leadership effectiveness, we approached the topic from the opposite

viewincompetence. This tactic has several advantages since there is no shortage of failed

managers/leaders, they can be identified by observers, and their characteristics can be mapped

empirically using well-validated personality assessments.

The assertion that there are flawed leaders has gone from the unthinkable to the obvious.

Issues of contemporary business journals describe the practices of failed executives; entire

volumes appear on personality factors associated with leader derailment (cf. Dotlich & Cairo,

2003). Some of these writings are a rediscovery of Bentzs (1985) research on management

incompetence among failed Sears executives. Bentz identified seven themes in flawed managers

who were otherwise bright, socially skilled, and identified as high-potential: (1) unable to

delegate or prioritize; (2) being reactive rather than proactive; (3) unable to sustain relationships;

(4) unable to build a team; (5) having poor judgment; (6) being a slow learner; and (7) having an

overriding personality defect.

Center for Creative Leadership researchers replicated and refined Bentzs original

findings. McCall, Lombardo, and Morrison (1988) and Leslie and Van Velsor (1996) summarize

their findings about managerial failure with four themes: (1) problems with interpersonal

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relations; (2) failure to meet business objectives; (3) inability to build a team; and (4) inability to

adapt to transitions.

Since Judge et al.s (2002) definitive identification of positive personality factors

associated with leadership effectiveness and an emerging literature on negative personality

characteristics associated with ineffectiveness, it is possible to assimilate these perspectives into

a comprehensive character model of leadership competence. The current research investigated

and compared three approaches for predicting leadership outcomes: (a) predicting leadership

with bright side personality measures; (b) predicting leadership with dark side personality

measures; and (c) predicting leadership with a combination of both. We anticipated that each

type of measure would predict performance but, because both have implications for distinct

components of leadership behavior, the greatest degree of overall leadership effectiveness

prediction would be achieved when both bright side and dark side measures were used

simultaneously. Specifically, we proposed and tested the following hypotheses:

Hypothesis 1: A profile constructed from bright side personality measures will be

significantly related to leadership performance.

Hypothesis 2: A profile constructed from dark side personality measures will be

significantly related to leadership performance.

Hypothesis 3: A profile constructed from both bright side and dark side personality

measures will be significantly related to leadership performance.

Hypothesis 4: A profile constructed from both bright side and personality measures will

be more highly predictive of leadership performance than profiles that use only one type

of personality measure.

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Method

Measures

Bright Side Personality. Most important bright side personality characteristics can be

described in terms of the Five-Factor Model (FFM; cf. De Raad & Perugini, 2002; Digman,

1990; Goldberg, 1992; John, 1990, p. 72; McCrae & Costa, 1987; Wiggins, 1996). The FFM is

comprised of five dimensions that represent how we think about and describe people (Goldberg,

1990):

I. Surgency/Extraversion - the degree to which a person seems outgoing and talkative.

II. Agreeableness - the degree to which a person seems pleasant and rewarding to deal with.

III. Conscientiousness the degree to which a person complies with rules, norms, and standards.

IV. Emotional Stability - the degree to which a person appears calm and self-accepting.

V. Intellect/Openness to Experience - the degree to which a person seems creative and open-

minded.

The Hogan Personality Inventory (HPI; R. Hogan & Hogan, 1995) was used for this

study to assess bright side characteristics of personality. The HPI was developed specifically to

predict real-world outcomes such as job performance and assesses the FFM in occupational life

within a normal population. The HPI contains seven primary scales that are aligned with the

FFM as follows:

I. Adjustment the degree to which a person is steady in the face of pressure, or conversely,

moody and self-critical (FFM: Emotional Stability).

II. Ambition the degree to which a person seeks status and values achievement (FFM:

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Extraversion).

III. Sociability the degree to which a person needs and/or enjoys social interaction (FFM:

Extraversion).

IV. Interpersonal Sensitivity the degree to which a person is socially sensitive, tactful, and

perceptive (FFM: Agreeableness).

V. Prudence the degree to which a person is concerned with self-control and

conscientiousness (FFM: Conscientiousness).

VI. Inquisitive the degree to which a person seems imaginative, adventurous, and analytical

(FFM: Intellect/Openness).

VII. Learning Approach the degree to which a person enjoys academic activities and values

education as an end in itself (FFM: Intellect/Openness).

The seven dimensions of the HPI are assessed using 206 true-false items. The internal

consistency and test-retest reliability of the scales are as follows: Adjustment (.89/.86),

Ambition (.86/.83), Sociability (.83/.79), Interpersonal Sensitivity (.71/.80), Prudence (.78/.74),

Inquisitive (.78/.83), and Learning Approach (.75/.86).

Dark Side Personality. The Hogan Development Survey (HDS; R. Hogan & Hogan,

1997) was used for this study to assess dark side characteristics of normal personality. The dark

side personality characteristics measured by the HDS represent flawed interpersonal strategies

that (a) reflect peoples distorted beliefs about others, and (b) negatively influence careers and

life satisfaction (Bentz, 1985; R. Hogan & Hogan, 1997; Leslie & Van Velsor, 1996).

Behavioral manifestations of dark side personality measures emerge during times of stress or

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when people let their guard down. These dispositions reflect maladaptive behaviors that coexist

with bright side personality characteristics.

In the context of personnel selection, the HDS identifies applicants whose behavior, over

time, will erode relationships with others because of flawed interpersonal strategies. The HDS is

designed to assess 11 dysfunctional dispositions that can impede job performance and lead to

career difficulties:

I. Excitable concerns being initially enthusiastic about people or projects, and then becoming

disappointed with them. Result: seems to lack persistence.

II. Skeptical concerns being socially insightful, but cynical, mistrustful, and overly sensitive

to criticism. Result: seems to lack trust.

III. Cautious concerns being overly worried about making mistakes and being criticized.

Result: seems resistant to change and reluctant to take chances.

IV. Reserved concerns seeming tough, remote, detached, and hard to reach. Result: seems to

be a poor communicator.

V. Leisurely concerns being independent, ignoring others requests, and becoming irritable if

they persist. Result: seems stubborn, procrastinating, and uncooperative.

VI. Bold concerns seeming entitled and having inflated views of ones competence and worth.

Result: seems unable to admit mistakes or share credit.

VII. Mischievous concerns being charming, but manipulative and ingratiating. Result: seems to

have trouble maintaining relationships and learning from experience.

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VIII. Colorful concerns being dramatic, engaging, and attention-seeking. Result: seems

preoccupied with being noticed and may lack sustained focus.

IX. Imaginative concerns thinking and acting in interesting, unusual, and even eccentric ways.

Result: seems creative but often lacking good judgment.

X. Diligent concerns being conscientious, perfectionistic, and hard to please. Result: tends to

disempower staff and subordinates.

XI. Dutiful concerns being eager to please and reluctant to act independently. Result: tends to

be pleasant and agreeable, but reluctant to support subordinates and co-workers.

The eleven dimensions of the HDS are assessed using 168 agree-disagree items that have

no psychiatric or mental health content. Principal components analysis of the HDS yields three

clearly defined factors that support interpreting the inventory in terms of Horneys (1950)

taxonomy of flawed interpersonal characteristics (R. Hogan & Hogan, 2001). The average alpha

for the scales is .67 and test-retest reliabilities range from .58 to .87. The test manual documents

the instruments development and psychometric properties.

Leadership Performance. The criteria used for this study was leadership performance.

Although performance ratings varied by sample, each contained at least one item for assessing

global leadership performance (e.g., leads by example) or multiple items used to construct an

overall leadership scale. All ratings were provided by supervisors who were knowledgeable of

the targets job performance.

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Profile Construction

We constructed and subsequently evaluated three personality-based predictor profiles.

The first profile, which was consistent with Judge et al.s (2003) approach of focusing on

leadership bright side characteristics, used bright side personality scales that have been found to

be predictive of leadership performance. The second profile corresponded to Bentzs (1985) and

McCall et al.s (1998) approach of focusing on derailing behaviors, particularly those

characterizing problems with interpersonal relations (i.e., volatile, aloof, cold, overly ambitious,

and arrogant). The final profile used both bright side and dark side personality scales to predict

leadership performance.

Bright Side Profile. In reviewing the Hogan Archive, which contains results from over

200 criterion studies conducted over the past three decades, Foster and Hogan (2005) identified

35 studies using the HPI to predict performance for leadership jobs. Results from applying

Hunter and Schmidts (1990) meta-analysis methods to validation studies (K = 35; N =3751)

indicated that four HPI scales had correlations with overall performance for managers and

executives at = .10 or higher: Adjustment ( = .22), Ambition ( = .31), Interpersonal

Sensitivity ( = .15) and Prudence ( = .13). These results provided the architecture for

constructing a leadership profile based upon bright side personality characteristics.

The HPI technical manual (R. Hogan & Hogan, 1995) stipulates that, in evaluating scores

on the HPI, one rule of thumb is to interpret scores above the 65th percentile high and scores

below the 35th percentile low (p. 49). Because the four scales used to construct the Bright Side

Profile are positively related to job performance, we labeled individuals falling above the 35th

percentile on each scale as having high leadership potential whereas those falling below the 35th

percentile on any of the four scales were labeled as having low leadership potential.

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Dark Side Profile. Foster (2006) applied Hunter and Schmidts (1990) meta-analysis

methods to studies from the Hogan Archive (K = 12; N = 1,058) to determine relationships

between HDS scales and managerial job performance. Six HDS scales were related to

performance at = .10 or higher: Excitable ( = -.18), Skeptical ( = -.19), Cautious ( = -.17),

Bold ( = -.10), Mischievous ( = -.15), and Imaginative ( = -.20). These results provided the

architecture for constructing a leadership profile based upon dark side personality characteristics.

According to the HDS technical manual (R. Hogan & Hogan, 1997), scores at or above

the 90th percentile are considered high on the HDS. The implications of high scores on the HDS,

in general, are undesirable. Because each of the six scales used to construct the Dark Side

Profile are negatively related to job performance, we labeled individuals falling below the 90th

percentile on each scale as having high leadership potential whereas those falling above the 90th

percentile on any of the six scales were labeled as having low leadership potential.

Total Leadership Profile. To determine the effectiveness of both bright side and dark

side personality measures in predicting leadership performance, a comprehensive leadership

profile was constructed using scales from both the HPI and HDS. Previous research indicates

incremental validity of the HDS measures over the HPI in predicting leadership performance,

with multiple Rs ranging from .31 to .56 (Davies, Hogan, Foster, & Elizondo, 2005).

Davies et al. (2005) explored the predictive power of both bright side and dark side

personality measures for use with the Leadership Domain Model (R. Hogan & Warrenfeltz,

2003; Warrenfeltz, 1995). This model synthesizes existing competency models into the domains

of Intrapersonal Skills, Interpersonal Skills, Technical Skills, and Leadership Skills. These four

domains form a hierarchy of trainability, with earlier skills being harder to train than later skills,

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and serve as the a basis for personnel selection, training, and performance evaluation (J. Hogan,

Davies, & Hogan, in press; R. Hogan & Warrenfeltz).

The structure of this performance model is presented in Table 1. Previous research

outlining relationships between personality predictors and job performance (Davies et al., 2005;

Foster & Hogan, 2005; J. Hogan, Davis, & Hogan, in press) was used to align both HPI and HDS

scales with performance competencies specific to each of the four domains and these appear in

Table 2.

As seen in Table 2, each of the HPI and HDS scales used to construct the first two

profiles relate to specific areas of leadership performance. The Total Leadership Profile was

constructed using cutoff scores at the 35th percentile for four HPI scales (Adjustment, Ambition,

Interpersonal Sensitivity, and Prudence) and the 90th percentile for six HDS scales (Imaginative,

Excitable, Skeptical, Reserved, Bold, and Cautious). Individuals falling above the 35th percentile

on each of the HPI scales and below the 90th percentile on each of the HDS scales were coded as

having high leadership potential whereas those failing to meet any of these cuts were coded as

having low leadership potential.

Analytical Approach

A series of meta-analyses (Hunter and Schmidts, 1990) were conducted to determine the

leadership predictiveness of each profile. Studies included in the Hogan Archive met six criteria:

(a) data were gathered from job incumbents for the purpose of criterion validation; (b) job

incumbents held leadership positions; (c) HPI data were collected; (d) HDS data were collected;

(e) job performance data were collected; and (f) job performance rating data included a rating of

leadership ability.

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Six studies were identified meeting these criteria (N = 810). For each dataset, individuals

were coded as high leadership potential versus low leadership potential based on: (a) the Bright

Tide Profile; (b) the Dark Tide Profile; and (c) the Total Leadership Profile. Group mean

differences, expressed in standard deviations [i.e., Cohens (1962) d], were calculated based on

each profile. Then, these effect sizes were meta-analyzed to determine the predictability of each

profile.

Results

Table 3 shows the group mean differences for each profile examined in each of the six

datasets used for this study. As seen, the results for all three profiles were in a positive direction

across nearly all six studies, indicating that each profile effectively predicted leadership ratings.

The one exception to this finding came from using the Bright Side Profile for a single small

sample study; it is likely that a lack of power contributed to the discrepancy associated with this

result. The results presented in Table 4 indicate that the Bright Side Profile, the Dark Side

Profile, and the Total Leadership Profile all effectively predicted leadership performance, with

effect sizes frequently nearing or falling within the moderate range, described by Cohen (1962)

as .50 to .80.

Meta-analytical results for difference scores are presented in Table 4, which indicates

positive effects were found with both the Bright Side and Dark Side Profiles, with estimated

population parameters of = .33 and = .36 respectively. To test Hypotheses 1 and 2, 95%

confidence intervals were reviewed. Lower limit confidence intervals for both profiles were

greater than .00 (.24 and .26, respectively), thereby supporting Hypotheses 1 and 2.

Results for the Total Leadership Profile were higher, with a population parameter of =

.44. To test Hypothesis 3, 95% confidence intervals were again reviewed. As seen in Table 4,

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the lower limit confidence interval for the total leadership profile was greater than .00 (.35),

thereby supporting Hypothesis 3. Population parameters were examined for Hypothesis 4. As

shown in Table 4, the population parameter estimating the group mean leadership rating scores

was higher for the Total Leadership Profile than for either the Bright Side or Dark Side Profiles,

thereby supporting for Hypothesis 4.

Together, these results clearly support the usefulness of both bright side and dark side

personality measures in predicting leadership performance. Furthermore, the greatest

predictability was obtained using the Total Leadership Profile representing both bright side and

dark side personality characteristics.

Discussion

These results demonstrate that both bright side and dark side personality measures can be

used to construct leadership profiles identifying high performers at both practically and

statistically significant levels. Furthermore, a profile consisting of scales from both inventory

types produced the greatest predictability, indicating that both bright and dark side personality

measures should be used to develop comprehensive leadership profiles. These results are

particular impressive given that a standard, generic set of cutoff scores was used to assess each

profile across each of the six datasets examined for this study.

In most applied settings, the validity of a specific set of cut-scores will vary based upon

job characteristics. Best practices in validity research require a full job analysis and the

development of a specific selection profile based upon a number of contextual factors relating to

the KSAs required for successful job performance and the context in which the job is performed

(J. Hogan, Davies, & Hogan, in press). The variability of difference scores presented in Table 3,

along with the percentage of variance accounted for from each profile presented in Table 4,

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suggest that the profiles used for this study were more effective at predicting leadership

performance for some jobs than others. From a meta-analytical perspective, these results

indicate the presence of moderators that influence the relationship between the profiles examined

and job performance across samples. From a practical perspective, these results indicate that

more effective profiles could be constructed for some, if not all, of the jobs examined in this

study.

The purpose of the current study was not, however, to demonstrate methods for obtaining

the largest possible effect size through the use of personality profiles. Instead, we sought to

compare standardized, generic profiles constructed using bright side, dark side, and a

combination of the two types of personality measures. As expected, both bright side and dark

side personality measures were effective at predicting leadership performance. Moreover, a

combination of both types of personality measures resulting in the greatest predictability,

suggesting that traits associated with both effective leadership behaviors and those associated

with ineffective or maladaptive behaviors are useful in predicting leadership performance in

organizational settings.

This study provides a number of directions for future research. First, as noted above, it

would be worthwhile to examine other profiles that may be more effective in predicting

leadership performance. Although it is almost certain that profiles customized to fit the needs

and context related to a specific job would produce greater effect sizes in the forms of group

mean performance differences, it is also possible that alternative generic profiles would also be

more effective across jobs. For example, the current profiles employed equal cut-scores to each

scale found to be predictive of performance from both the HPI (greater than or equal to the 35th

percentile on each scale) and the HDS (less than the 90th percentile on each scale). It may be

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beneficial to explore other possibilities, such as giving greater weight (i.e., more stringent cuts)

to scales that have higher correlations with job performance.

Finally, because strengths of the current research were the use of multiple samples and

meta-analytical methods, it also may be beneficial to reexamine these analyses on more samples

as they become available. The increasing use of both the HPI and HDS for the prediction of

leadership performance, as well as other personality assessments, should provide a rich source of

data for the further examination of the issues presented in this research and the generalizibility of

these findings in the future.

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References

Bentz, V. J. (1985, August). A view from the top: A thirty year perspective of research devoted to

the discovery, description, and prediction of executive behavior. Paper presented at the

93rd Annual Convention of the American Psychological Association, Los Angeles, CA.

Cohen, J. (1962). The statistical power of abnormal-social psychological research: A review.

Journal of Abnormal and Social Psychology, 65, 145-153.

Davies, S., Hogan, J., Foster, J. L., & Elizondo, F. (2005). Recombinant personality measures for

predicting leadership performance. Paper presented at the 20th Annual Conference of the

Society of Industrial and Organizational Psychology, Los Angeles, CA.

De Raad, B., & Perugini, M. (Eds.). (2002). Big Five assessment. Seattle, WA: Hogrefe &

Huber.

Digman, J. M. (1990). Personality structure: Emergence of the five-factor model. Annual

Review of Psychology, 41, 417-440.

Dotlich, D. L., & Cairo, P. C. (2003). Why CEOs fail. San Francisco, CA: Jossey-Bass.

Goldberg, L. R. (1990). An alternative description of personality: The Big-Five factor

structure. Journal of Personality and Social Psychology, 59, 1216-1229.

Goldberg, L. R. (1992). The development of markers for the Big-Five factor structure.

Psychological Assessment, 4, 26-42.

Foster, J. L. (2006). Validity of the Hogan Development Survey: Meta-analytical results from the

Hogan Archive. Technical Report. Tulsa, OK: Hogan Assessment Systems.

Foster, J. L., & Hogan, J. (2005). Validity of the Hogan Personality Inventory for job family

profiles. Technical Report. Tulsa, OK: Hogan Assessment Systems.

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Hogan, J., Davies, S., & Hogan, R. (in press). Generalizing personality-based validity evidence.

In S. M. McPhail (Ed.), Alternative validation strategies. San Francisco: Jossey-Bass.

Hogan, R., & Hogan, J. (1995). Hogan Personality Inventory manual. Tulsa, OK: Hogan

Assessment Systems.

Hogan, R. & Hogan, J. (1997). Hogan Development Survey manual. Tulsa, OK: Hogan

Assessment Systems.

Hogan, R., & Warrenfeltz, W. (2003). Educating the modern manager. Academy of Management

Learning and Education, 2, 74-84.

Horney, K. (1950). Neurosis and human growth. New York: Norton.

Hunter, J. E. & Schmidt, F. L. (1990). Methods of meta-analysis: Correcting error and bias in

research findings. New York: Sage.

John, O. P. (1990). The Big-Five factor taxonomy: Dimensions of personality in the natural

language and in questionnaires. In L. A. Pervin (Ed.), Handbook of personality theory

and research (pp. 66-100). New York: Guilford.

Judge, T. A., Bono, J. E., Ilies, R., & Gerhardt, M. W. (2002). Personality and leadership: A

qualitative and quantitative review. Journal of Applied Psychology, 87, 765-780.

Leslie, J. B., & Van Velsor, E. (1996). A look at derailment today: North American and Europe.

Greensboro, NC: Center for Creative Leadership.

McCall, M. W., Jr., Lombardo, M. M., & Morrison, A. M. (1988). Lessons of experience.

Lexington, MA: Lexington Press.

McCrae, R. R., & Costa, P. T., Jr. (1987). Validity of the five-factor model of personality across

instruments and observers. Journal of Personality and Social Psychology, 52, 81-90.

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Warrenfeltz, R. B. (1995, May). An executive-level validation of the Borman and Brush

taxonomy. Paper presented at the 10th Annual Conference of the Society for Industrial

and Organizational Psychology, Orlando, FL.

Wiggins, J. S. (1996). The Five-Factor Model of personality. New York: Guilford.

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Table 1

Leadership Domain Model of Job Performance, Example Competencies, and Personality Measures

Metaconcept Domain Example Competency FFM Measurement

Leadership

Achievement Building Teams Business Acumen Decision Making Delegation Employee Development Initiative Leadership Managing Performance Resource Management

Surgency/Extraversion Emotional Stability Agreeableness Conscientiousness

Getting Ahead

Technical

Analysis Creating Knowledge Decision Making Political Awareness Presentation Skills Problem Solving Safety Technical Skill Training Performance Written Communication

Openness to Experience Conscientiousness

Interpersonal

Building Relationships Communication Consultative Skills Cooperating Influence Interpersonal Skill Organizational Citizenship Service Orientation Teamwork Trustworthiness

Agreeableness Surgency/Extraversion Emotional Stability

Getting Along

Intrapersonal

Dependability Detail Orientation Flexibility Following Procedures Integrity Planning Respect Risk Taking Stress Tolerance Work Attitude

Conscientiousness Emotional Stability Surgency/Extraversion

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Table 2

Predictor Alignment with the Leadership Domain Model

Domain Predictor Scale Example Behaviors p

Leadership Skills HPI Adjustment Leading and Building Teams 0.31

HPI Ambition Employee Development 0.29

HPI Interpersonal Sensitivity Leading and Building Teams 0.24

HPI Prudence Leading and Building Teams 0.23

HDS Imaginative Leadership -0.23

HDS Mischievous Leading and Building Teams -0.13

HDS Bold Leading and Building Teams -0.09

HDS Excitable Leadership -0.19

HDS Skeptical Leading and Building Teams -0.15

HDS Cautious Delegation -0.23

Technical Skills HPI Learning Approach Training Performance 0.25

HPI Prudence Safety 0.21

HPI Inquisitive Decision Making 0.20

HDS Imaginative Safety -0.22

HDS Skeptical Technical Skill -0.34 Continued on the next page.

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Table 2 (Cont.)

Predictor alignment to the Leadership Domain Model

Domain Predictor Scale Example Behaviors p

Interpersonal Skills HPI Interpersonal Sensitivity Influence 0.25

HPI Adjustment Building Relationships 0.17

HPI Sociability Influence 0.21

HDS Bold Trustworthiness -0.22

HDS Cautious Communication -0.17

HDS Imaginative Influence -0.21

HDS Reserved Customer Service -0.30

HDS Mischievous Teamwork -0.20

Intrapersonal Skills HPI Adjustment Work Attitude 0.36

HPI Ambition Flexibility 0.21

HPI Prudence Respects Others 0.23

HDS Leisurely Planning -0.19

HDS Skeptical Work Attitude -0.20

HDS Excitable Stress Tolerance -0.23

HDS Imaginative Work Attitude -0.26

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Table 3

Group Mean Differences for the Bright Side, Dark Side, and Total Leadership Profiles

Archive Study # N Bright Side Profile Difference Dark Side

Profile Difference Total Leadership Profile Difference

182 107 .39 .15 .43

267 23 -.10 .57 .01

291 63 .11 .40 .47

324 295 .29 .35 .38

330 69 .26 .62 .34

375 253 .16 .02 .16

Note. All difference scores were calculated by subtracting the group mean score of those not fitting the profile

from those fitting the profile expressed in standard deviations.

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Table 4

Meta-Analytic Results for the Bright Side, Dark Side, and Total Leadership Profiles

Profile k N dobs SDd v %VE 90% CV 95% CI Bright Side HPI Profile

6 810 .24 .11 .33 53 .16 .24

Dark Side HDS Profile

6 810 .24 .22 .36 11 -.11 .26

Total Leadership Profile

6 810 .31 .13 .44 33 .19 .35

Note. k = number of studies; N = number of participants across k studies; dobs = observed group mean difference; v = operational difference (corrected for criterion reliability only); %VE = percentage of variance explained; 90% CV

= lower limit credibility value; 95% CI = lower limit confidence interval

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Participant information: Presenter: Jeff Foster, Hogan Assessment Systems 2622 E. 21st St. Tulsa, OK 74114 Tel: 918-749-0632 Email: jfoster@hoganassessments.com SIOP Member Coauthor: Joyce Hogan, Hogan Assessment Systems 2622 E. 21st St. Tulsa, OK 74114 Tel: 918-749-0632 Email: jhogan@hoganassessments.com SIOP Fellow