BI Norwegian Business School Master Thesis · GRA 19003 Master Thesis 01.09.2016 ii Abstract The...

Hedda Lærum Jacobsen: 0978668

Ulrika Vengelin: 0971100

BI Norwegian Business School

Master Thesis

Divergent thinking in military leader selection

process:

What is the relationship between divergent thinking,

interview ratings and admission into non-

commissioned officer training?

Hand-in date:

01.09.2016

Campus:

BI Oslo

Examination code and name:

GRA 19003 Master Thesis

Supervisor:

Øyvind Lund Martinsen

Programme:

Master of Science in Leadership and Organisational Psychology

This thesis is a part of the MSc programme at BI Norwegian Business School. The school takes no

responsibility for the methods used, results found and conclusions drawn.

GRA 19003 Master Thesis 01.09.2016

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Acknowledgements

This master thesis was only possible with the help and kind support of many

people, to whom we would like to extend our sincere thanks.

Foremost, we would like to thank the Norwegian Defence College, with

Thomas Fosse, Ole-Christian Lang-Ree and Rino Bandlitz Johansen in particular, for

the opportunity of being part of this research project and to collect data during the

Norwegian Armed Force’s recruitment and selection process in January 2016. We are

also tremendously thankful to Kine Kristiansen for her help and advice, and for

allowing us to occupy her office during all of the days we transcribed our data.

Thereafter, we would like to express our gratitude to our supervisor at BI

Norwegian Business School, Øyvind Lund Martinsen for the access to data collected

as part of the Norwegian Armed Force’s recruitment and selection process in the

summer of 2007. Without this data, and his valuable guidance and support, we would

not have been able to carry out such an extensive study.

We are also highly indebted to Ellisiv Lærum Jacobsen for all of her help and

good advises, and to Sigve Garsjø for the immense amount of work he put into

transcribing the data in 2007.

Our families and loved ones, also deserve much appreciations for the support

during the last year of work on this thesis. For understanding our frustration, and

sharing our joys. Without this support and understanding our journey would at times

have been unbearable.

Finally, we would also like to thank all of our friends for accepting our absence

due to the hard work we have put into this thesis. We are happy that they are still

around for the future to come, in which we look forward to seeing them all a lot more.

With the sincerest gratitude,

Ulrika Vengelin & Hedda Lærum Jacobsen

“Leadership in war is an art, a free creative activity” (Germany’s 1933 Field Service Regulations, in Nelsen (1987:23)

Oslo

28th of August, 2016


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Abstract

The aim of this thesis was to investigate the relationship between divergent

thinking, interview ratings and admission into non-commissioned officer training.

Directive control leadership has been the prevailing leadership philosophy in the

Norwegian Armed Forced since 1995, and the joint operational doctrines emphasise

several abilities and characteristics essential to their military leaders. Amongst these

is creativity, in which we argue that divergent thinking is a central ability. The

personality trait Openness to experience is the construct that has been found most

frequently to be significantly related to measures of divergent thinking, and was thus

included in our analyses. Because non-commissioned officer training is the first step

into further military training, identifying divergent thinking in candidates should be

evident in the selection process.

The thesis consists of three cross-sectional studies. Study one builds on data

collected in 2007, whereas study two was designed and conducted as a replication

study in 2016. The third study combines the samples of study one and two. All

studies use samples of candidates enrolled into the non-commissioned officer

selection process. Divergent thinking was measured by Wallach and Kogan’s (1965)

divergent thinking test, Openness to experience was measured by NEO PI-R, and

interview ratings and admission status was provided by the joint recruitment and

selection process. Multiple regressions, mediation and moderation analyses were

performed in order to test associations related to divergent thinking, interview ratings

and admission in study one and two. Finally, the third study combined the two

samples for comparison and an overall analysis of admissions in the two selections.

The results of the three studies indicated that there is no direct, or indirect

relationship between divergent thinking, interview rating and admission. A significant

relationship between interview ratings and admission was found in study one

OR=.64, 95% CI .50-.83, p<.001, and study two OR=1.21, 95% CI 1.03-1.41, p=.020.

Openness to experience was found to be significantly related to interview ratings in

study one (OR=1.02, 95% CI 1.01-1.02, p<.001), but was not found to be related to

admission (p=.254). In study two results indicated that Openness to experience was

not related to interview ratings (p=.109), and results in both study two and three

indicated that Openness to experience was not related to admission (study two:

p=.267; study three: p=.856). The results and limitations of the studies are discussed,

and implications for future selection processes and future research are suggested.

Keywords: divergent thinking, Openness to experience, military selection, creativity,

directive control, military leadership, selection interview.


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Abbreviations and explanations

NAF Norwegian Armed Forces – Forsvaret

NCO Non-Commissioned Officer – Befal

FFOD The NAF’s joint operational doctrine – Forsvarets Felles Operative Doktrine

FDLO The NAF’s doctrine for land operations – Forsvarets Doktrine for

Landoperasjoner

FDLO The NAF’s doctrine for air operations – Forsvarets Doktrine for Luftoperasjoner

FDMO The NAF’s doctrine for naval operations – Forsvarets Doktrine for Maritime

Operasjoner

FO Norwegian National Defence High Command – Forsvarets Overkommando

Branch of application – refers to the three main branches in the Norwegian Armed Forces (Army,

Air force, Navy) – Forsvarsgren (Hæren, Luftsforsvaret, Sjøforsvaret)

Defence Staff Norway – Forsvarsstaben

Norwegian Defence Staff College – Forsvarets Stabskole


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Content

ACKNOWLEDGEMENTS............................................................................................................. I

ABSTRACT .................................................................................................................................... II

ABBREVIATIONS AND EXPLANATIONS ............................................................................. III

CONTENT ..................................................................................................................................... IV

1.0 INTRODUCTION ..................................................................................................................... 1

2.0 RESEARCH QUESTION AND SCOPE OF THESIS ........................................................... 3

3.0 LITERATURE REVIEW AND HYPOTHESES ................................................................... 5

3.1 THE NORWEGIAN ARMED FORCES .......................................................................................... 5

3.2 DIRECTIVE CONTROL LEADERSHIP .......................................................................................... 7

3.3 CREATIVITY AND DIVERGENT THINKING IN MILITARY LEADERSHIP ......................................... 8

3.4 SELECTION INTERVIEWS ........................................................................................................ 10

3.6 DIVERGENT THINKING ........................................................................................................... 11

3.7 INTELLIGENCE AND DIVERGENT THINKING ............................................................................ 12

3.8 MEASURING DIVERGENT THINKING ....................................................................................... 13

3.9 PERSONALITY AND DIVERGENT THINKING ............................................................................. 14

4.0 STUDY 1 .................................................................................................................................. 17

4.1 METHOD ............................................................................................................................... 17

4.1.1 Design ........................................................................................................................... 17

4.1.2 Setting ........................................................................................................................... 17

4.1.3 Sample and procedures ................................................................................................ 18

4.1.4 Literature ...................................................................................................................... 19

4.1.5 Ethics ............................................................................................................................ 20

4.2 MEASUREMENTS ................................................................................................................... 20

4.2.1 Divergent thinking tests ................................................................................................ 20

4.2.2 The personality test....................................................................................................... 21

4.2.3 The selection interview ................................................................................................. 21

4.2.4 Admission ..................................................................................................................... 22

4.3. RELIABILITY ........................................................................................................................ 22

4.3.1 Interrater reliability...................................................................................................... 23

4.4 VALIDITY .............................................................................................................................. 24

4.5 DATA ANALYSES ................................................................................................................... 25

4.6 RESULTS ............................................................................................................................... 26

4.6.1 Sample characteristics .................................................................................................. 26

4.6.2 Correlations.................................................................................................................. 27

4.6.3 Relationships: divergent thinking, Openness and interview ratings............................. 28

4.6.4 Relationships: divergent thinking, Openness, interview ratings and admission .......... 29

4.6.5 Moderation and mediation analyses ............................................................................. 31


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4.7 DISCUSSION OF RESULTS ....................................................................................................... 32

5.0 STUDY 2 .................................................................................................................................. 33

5.1 METHOD ............................................................................................................................... 34

5.1.1 Design ........................................................................................................................... 34

5.1.2 Setting ........................................................................................................................... 34

5.1.3 Sample and procedures ................................................................................................ 34

5.1.4 Literature ...................................................................................................................... 35

5.1.5 Ethics ............................................................................................................................ 35

5.2 MEASUREMENTS ................................................................................................................... 35

5.2.1 The selection interview ................................................................................................. 35

5.3 RELIABILITY ......................................................................................................................... 35

5.3.1 Interrater reliability...................................................................................................... 36

5.4 VALIDITY .............................................................................................................................. 36

5.5 DATA ANALYSES ................................................................................................................... 36

5.6 RESULTS ............................................................................................................................... 37

5.6.1 Sample characteristics .................................................................................................. 37

5.6.2 Correlations.................................................................................................................. 38

5.6.3 Relationships: divergent thinking, Openness, and interview ratings............................ 38

5.6.4 Relationships: divergent thinking, Openness, interview ratings and admission .......... 40

5.6.5 Moderation and mediation analyses ............................................................................. 41


6.0 STUDY 3 .................................................................................................................................. 43

6.1 METHOD ............................................................................................................................... 43

6.1.1 Setting ........................................................................................................................... 43

6.1.2 Sample and procedure .................................................................................................. 43

6.2 MEASUREMENTS ................................................................................................................... 44

6.3 RELIABILITY AND VALIDITY .................................................................................................. 44

6.4 DATA ANALYSES ................................................................................................................... 44

6.5 RESULTS ............................................................................................................................... 44

6.5.1 Descriptive statistics ..................................................................................................... 44

6.5.2 Relationships: divergent thinking, Openness and admission ....................................... 45


7.0 GENERAL DISCUSSION ..................................................................................................... 47

7.0.1 Replication.................................................................................................................... 47

7.0.2 Reliability ..................................................................................................................... 48

7.0.3 Correlations.................................................................................................................. 48

7.0.4 Scoring divergent thinking............................................................................................ 49

7.0.6 Divergent thinking tests ................................................................................................ 51

7.0.7 Relationship between Openness, interview rating and admission ................................ 52


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7.0.8 Relationship between background variables, interview rating and admission ............. 54

8.0 LIMITATIONS ....................................................................................................................... 55

8.1 RESEARCH DESIGN AND MATERIAL ....................................................................................... 55

8.1.1 A cross-sectional design ............................................................................................... 55

8.1.2 NEO PI-R ..................................................................................................................... 55

8.1.3 Divergent thinking test and scoring .............................................................................. 56

8.1.4 Sample .......................................................................................................................... 57

8.1.5 Selection of participants ............................................................................................... 57

8.1.6 Generalisation .............................................................................................................. 58

8.2 SETTING ................................................................................................................................ 58

8.3 STATISTICAL ANALYSES ........................................................................................................ 59

8.3.1 Interview ratings ........................................................................................................... 59

8.3.2 Assumptions .................................................................................................................. 59

8.3.3 PCA requirements ........................................................................................................ 59

8.3.4 Excluded variables ....................................................................................................... 60

9.0 PRACTICAL AND THEORETICAL IMPLICATIONS .................................................... 60

10.0 FUTURE RESEARCH ......................................................................................................... 61

11.0 CONCLUSION ..................................................................................................................... 62

12.0 REFERENCES ...................................................................................................................... 63

13.0 APPENDICES ....................................................................................................................... 74

Appendix 1 – Inclusion and exclusion: Figure 2 and 3 .............................................................

Appendix 2 – Divergent thinking test ........................................................................................

Appendix 3 – Literature search .................................................................................................

Appendix 4 – Scoring manual ....................................................................................................

Appendix 5 – Correlation matrices (study one and two) ...........................................................

Appendix 6 – Mediation analyses (study one and two) .............................................................

Appendix 7 – Information to candidates for study two ..............................................................

Appendix 8 – NSD approval for study two ................................................................................


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1.0 Introduction

Leadership has been defined as a type of problem-solving that occurs in

dynamic, complex and ill-defined settings, in which leaders must identify, select and

implement solutions and courses of action that will result in goal attainment

(Mumford & Connelly, 1992). Ill-defined problems by definition mean that there is

no right or wrong answer, and the dynamic and changing conditions require leaders to

develop and guide adaptive responses (Mumford et al, 2000). Leaders solve problems

in ‘real-world’ settings in which demands are many and time is short. This often

necessitates the generation of solutions to various, rapidly unfolding problems, which

calls for flexibility in adjusting strategies opportunistically (Mumford et al, 2000).

Military leadership, in particular, is characterised by problem-solving under stressful

circumstances in dynamic, ambiguous and volatile environments, in which rapid

decisions are made based on incomplete information, and with possible life or death

consequences (De Church et al, 2011).

There is a great emphasis on the importance of leadership within most military

organisations, in fact, the military and leadership are almost inseparable (Wong et al,

2003). The highly ambiguous military operations present modern professional

military leaders with several challenges, such as unclear or multiple conflicting

missions, or missions that may change over time, in addition to unclear roles and

responsibilities (Bartone, 2006). In these situations, the outcomes of leadership may

lead to severe psychological or physical injury, and even death to the leader and

members of their unit (Campbell et al, 2010). It has, therefore, been suggested that

effective leadership requires an ability to generate multiple solutions and to think in

flexible ways when solving problems, all of which are aspects of creative thinking

(Reiter-Palmon, 2003; Mumford & Connelly, 1992).

Indeed, creativity is one of the most stable and strongest predictor of effective

leadership in ambiguous environments, in which fluency and flexibility of ideas and

originality, particularly contribute to performance on complex problem-solving skills

needed for leadership (Matthew, 2009; Connelly et al, 2000). The ability to generate

multiple solutions, that is, engaging in creative problem-solving, can be considered a

measure of cognitive flexibility and has often been referred to as divergent thinking

(Mumford et al, 2000). Divergent thinking has been found to predict leadership

effectiveness (Vincent et al, 2002), and performance (Zaccaro et al, 2000). Studies

have actually shown stronger validity coefficients between divergent thinking skills

and leadership effectiveness, than between general mental ability and performance

(Zaccaro et al, 2015; Scratchley & Hakstian, 2001). Although divergent thinking has


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been found to be positively related to general intelligence, the latter may be necessary

for creative thinking, but it is not sufficient (Guilford, 1966; von Stumm et al, 2011).

Kaufmann (2004) thus claims that creativity can be meaningfully and rightfully

distinguished from the concept of intelligence, because creativity has to be linked to

novelty. While the type of creativity may vary depending on the situation faced by the

leader, it would seem that some kind of creativity is essential for effective leadership

in dynamic environments (Sternberg, 2008). Divergent thinking then, has been

considered so fundamental to creativity that the two terms have often been used

synonymously in the literature (Williams, 2004). It has also been argued that a leader

lacking divergent thinking skills will be unable to handle ambiguous and novel

situations, such as unpredicted or new sources of hostility (Sternberg, 2008). So even

though military leaders may not often be described as creative human beings

(Mumford & Connelly, 1992), the non-routine and complex problems faced by

military leaders do in fact necessitate divergent thinking and creative problem-solving

skills (Mumford et al, 1998; Zaccaro, 2014), as these situations generally call for non-

typical and/or novel solutions (Marshall-Mies et al, 2000).

The challenges facing today’s military leaders require them to be capable of

independent decision-making in dynamic and uncertain environments (Boe, 2015a;

Bartone et al, 2007). Complex operational environments call for leaders to think in

new ways to be effective, and greater reliance is thus placed on divergent thinking

(Zaccaro, 2014). Because future military operational settings are expected to become

increasingly more complex and uncertain (Rumsey, 2014), and the fact that military

leaders in command are answerable to everything that their unit does, or fails to do

(Wong et al, 2003); identifying the individuals with the right leadership skills needed

to effectively respond to such contexts has become critical for military organisations

(Morath et al, 2011; Wolters et al, 2014).

Due to the use of closed personnel systems where leaders are promoted from

within, and generally no lateral entry into senior positions are made (Wong et al,

2003), the military is required to have systems in place that are able to identify, select

and develop leader potential at all levels (Zaccaro, 2014). As a result, military

services have been and still are, at the forefront of selection (Rumsey & Arabian,

2014). They invest substantial financial-, and human resources to establish optimal

selection-, and training systems for their future leaders, both prior to and after they

have been commissioned (i.e. military personnel who have completed military officer

training) (Rumsey, 2014; Zaccaro et al, 2015). The recognition that divergent

thinking is essential for military leaders, has encouraged military organisations to

strive towards identifying individuals who are likely to engage in divergent thinking.


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2.0 Research question and scope of thesis

With the increasing need for divergent thinking skills among military leaders in

operational contexts (Bartone et al, 2007), and an emphasis in the Norwegian Armed

Forces’ joint operational doctrine on the use of creativity within, and across all

leadership levels (Forsvarsstaben, 2014), suggest that these attributes should be

evident within the Norwegian Armed Forces (NAF), and particularly within military

training institutions. This in turn, highlights the importance of identifying divergent

thinking as part of the selection process into non-commissioned officer (NCO)

training. The question, however, is to what degree the officers and personnel

responsible for the selection are actually able to detect such abilities in their

candidates. As accurate measures of divergent thinking are not used as part of the

standard selection process today, it would require the interview ratings to reflect the

candidates that are likely to engage in divergent thinking and for these to be admitted

into NCO training. Therefore, we propose the following research question:

Divergent thinking in military leader selection process: What is the

relationship between divergent thinking, interview ratings and admission into non-

commissioned officer training?

Rationale After NATO shifted their strategic focus by the end of the Cold War,

Norway’s military operations became more characterised by the involvement in

multinational missions rather than as homeland defence and war (Johansen et al,

2014). This shift made the operational context increasingly complex and ambiguous,

and placed higher demands on Norwegian military leaders to respond to the

unexpected (Boe, 2015a). The acquisition of the leadership skills needed to respond

to these challenges is provided through leadership development by formal education

within the NAF, where leadership training and development has always been a central

element (Hosar, 2000). In order to be recruited into military training and careers

within the NAF, individuals wanting to join will first have to undergo the NCO

training (Rones & Fasting, 2011). This is the first step into military leadership

training within the NAF. To gain access into NCO training and subsequent military

leadership development, individuals take part in a jointly organised recruitment and

selection process (henceforward in the thesis referred to as NCO selection process),

which aims to identify leader potential among the participating candidates (Rones &

Fasting, 2011). The NCO selection process takes place twice a year and selects

candidates into different programmes for military leadership training within the NAF

(i.e. Army, Navy and Air force), based on medical selection, physical tests, abilities

and personality (Forsvaret, 2016a).


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Scope We focus on divergent thinking skills, rather than the creative person per

se, and how these abilities may be identified through selection interviews and

recognised by admission into NCO training. More specifically we investigate

divergent thinking as part of the NCO selection process conducted by the NAF, with

an aim to identify relationships between the main variables: divergent thinking,

interview ratings and admission. Our thesis includes three studies, in which the third

study is based on two cross-sectional studies, where study one consists of data

collected as part of a larger research project during the summer NCO selection

process in June 2007. Due to this data being roughly nine years we decided to attempt

a replication study, in which data was collected during the winter NCO selection

process, in January 2016. This was done as part of another larger research project led

by the Norwegian Defence College. The main argument for including a replication

study was initiated by our interest in investigating whether the relationships would be

the same for study one and two, or if possible differences in results could indicate that

changes had been made in the selection process between 2007 and 2016.

Limitations Because divergent thinking is only an aspect of creativity and only

give an indication of a person’s potential for engaging in creative thinking, we

decided to include it as an ability. The selection interview is one of the most

important aspects of the NCO selection process, and was thus a vital variable to

include. Since personality tests are already part of the regular selection processes, and

the personality trait Openness to experience has been found to be closely related to

divergent thinking, this variable was also included. In contrast, due to less consistent

findings with regards to the relationship between divergent thinking and intelligence,

the latter was not included. Selection variables from the NCO selection process

excluded in our thesis were those that had not been equally calculated for all

candidates. The terms ‘relationship’ and ‘association’ reported and discussed

throughout the thesis will be used interchangeably. The term ‘candidate’ refers to

NCO applicants who are enrolled into the selection process (the participants of our

studies), whereas ‘applicant’ refers to individuals applying for NCO training prior to

enrolment into phase one of the selection process.

Implications While there have been previous studies on e.g. military group

cohesion (Bartone et al, 2002a), military identity (Johansen et al, 2014), and theses

examining the selection process (Vik, 2013; Kjenstadbakk, 2012) in a Norwegian

context, it has to the best of our knowledge not been made any studies on divergent

thinking. Although research on creativity in military contexts is generally sparse,

there is much research to support the importance of divergent thinking among modern

military leaders (e.g. Connelly et al, 2000; Mumford et al, 1998; Zaccaro et al, 2015;


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Vincent et al, 2002; Hansen, 2013). The findings in our thesis will thus have potential

important practical implications for the NAF in terms of developing measures for

divergent thinking, or improving procedures for selection interviews in order to

identify such abilities among their candidates in the future selection processes.

First we conducted an extensive review of the military literature to provide a

solid background of the context of the Norwegian military, as well as a review of the

previous research in order to identify what has been done on divergent thinking in the

past. This review was conducted to gain a broader understanding and to support the

formulation of our hypotheses.

3.0 Literature review and hypotheses

“Continual change and the need to respond to it, compels the Commander to

carry the whole apparatus of his knowledge with him. He must always be ready to

bring forth the appropriate decision by total assimilation of his mind and life” (von

Clausewitz, 1984:147).

This statement highlights the constantly changing operational environments

military leaders are faced with, in which they are required to make rapid, yet

appropriate decisions in situations where life and death consequences are present.

Indeed, the ability to withstand extreme situations where both their own life and unit

members’ lives may be in danger, and having to make decisions under severe

pressure that involve risking and taking lives, is what distinguishes military leaders

from leaders in civilian contexts (Boe, 2015b). In the last 20 to 30 years, the NAF and

other military organisations have undergone radical changes in their use of military

power, including shifting skill requirements for military officers (Johansen et al,

2014; Zaccaro, 2014). The new complexity stems from the uncertainty regarding both

mission and opponent, where it is no longer obvious against whom the combat will

be, nor is it obvious when it will be required or what role the military power will have

to take on (Halpin, 2011).

3.1 The Norwegian Armed Forces

In the NAF’s doctrines (FFOD; FDLO; FDLO; FDMO), the terms ‘war’ and

‘armed conflict’ are used synonymously (Forsvarsstaben, 2014; 2004; Forsvarets

Stabskole 2002a; 2002b). By answering the question of ‘what is war?’ it is possible to

define the nature of war, its goals and the use of military means (Forsvarsstaben,

2014). The NAF’s doctrines are all based on von Clausewitz’s (1984) view on war

from 1893, as characterised by constant uncertainty, danger and physical exertions,

which is collectively referred to as ‘friction’. This concept captures the difference


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between the theory and reality of war, and explains what may obstruct or postpone

the planning and implementation of military operations. This friction is considered a

type of force that makes what may seem easy, become difficult (Forsvarsstaben,

2014). What constitutes this friction will vary between wars, as well as change

depending on how the specific war or conflict develops. The constantly changing

character of war highlights the very nature of it, namely, that no conflict or war is the

same (von Clausewitz, 1984). As a result, the elements will differ in both form and

content, as well as how and when they will occur (Forsvarsstaben, 2014). The way we

understand war will also determine how we see leadership in military operations, and

so the ability to handle this friction has become vital for military officers (Boe,

2015a).

To be effective in responding to novel and non-routine problems not previously

encountered, military officers are required to possess a broad range of skills.

Fortunately, most leadership definitions provided by military doctrines share the idea

that it is a process, in which effective leaders can be developed through proper

training (Fallesen et al, 2011), as part of formal education, self-development and

operational assignments (Wong et al, 2003). As a result of the changes in strategic

focus the NAF currently cover the whole conflict spectrum from crisis to war

(Forsvarsstaben, 2014). In order to maintain the required preparedness and a certain

level of force production, there is a need to continuously train and educate soldiers

and officers (Forsvarsstaben, 2014). The military leadership development provided by

the NAF thus intends to provide their military officers with the relevant skills needed

to prepare them in meeting this ‘friction’. This is achieved by making them able to

plan, implement and evaluate missions within contexts of war, crisis and conflict

(Boe, 2015b).

Military leadership in the NAF, however, was publicly debated after the

avalanche disaster in Vassdalen, Norway in 1986, as part of the NATO winter

exercise “Anchor Express”, where 16 soldiers from the Engineering 2nd unit lost their

lives (Lied, 1988). This tragedy is considered the worst accident within the NAF

during peacetime, and gave rise to a report to the Norwegian Parliament

(Forsvarsdepartementet, 1986-87) and a public investigation made by Norwegian

Official Report that addressed the organisation and leadership challenges faced by the

NAF (Lied, 1988; Forsvarsdepartementet, 1991). The officer for the unit had raised

doubts about sending his soldiers into Vassdalen, but chose to do so based on the

orders he had been given (Veum & Hotvedt, 2016). The debate after the accident thus

raised critique regarding military officers’ ability to achieve their missions based on

their own insight and competence, without having to disobey orders.


7

3.2 Directive control leadership

The NAF learned a great deal from the accident, and after 1995 they shifted

towards the use of a new operational concept (FO, 1995) based on manoeuvre theory

(Lind, 1985). This shift made directive control leadership become the organisational

leadership philosophy to guide the NAF. Directive control leadership (oppdrags-

basert ledelse) stands in great contrast to the previously held philosophy, as well as

the more traditional leadership philosophies within military organisations, namely

restrictive control leadership (ordrebasert ledelse) (Forsvarsstaben, 2014; Keithley &

Ferris, 1999). This meant a shift from a stricter hierarchical authority (where orders

are given by the commander and subordinated leaders follow them) into a more type

of shared leadership, where subordinated leaders are expected to take initiatives with

minimal guidance (Halpin, 2011).

Directive control leadership corresponds with the leadership philosophy of

manoeuvre theory and originates in mission-type orders. Mission-type orders, or

mission-oriented tactics, in turn comes from the concept of “Auftragstaktik”

originating from the German doctrine, where the command in modern operations is

based on situation and task (Auftrag) (Keithley & Ferris, 1999). This idea proposes a

general guidance rather than prescriptive omission. Nelsen (1987), however, claims

that Auftragstaktik means more than just mission-oriented tactics, as it is much more

comprehensive by including a broad range of aspects, such as flexibility, independent

decision-making, individual initiative and thinking leaders that are able to reach

strategic decisions in their own right (Keithley & Ferris, 1999). Using the concept of

directive control is thus more suitable both for explaining “Auftragtatktik”, as well as

to define the kind of leadership style the NAF is now adhering to (Forsvarsstaben,

2014).

The NAF’s joint operational doctrine (FFOD) uses the term directive control,

whereas the NAF’s doctrine for land operations (FDLO) applies the term intent-based

leadership (intensjonsbasert ledelse) (Forsvarsstaben, 2014; 2004). Directive control

leadership is based upon intent-based leadership, and what is central to both of these

concepts is the absence of detailed directions on how to implement an order, which

should only be communicated when it is absolutely necessary (Fitz-Gibbon, 1995).

Directive control is meant to entail leaders at all levels, and to promote initiatives

among subordinated leaders. This is claimed to increase tempo and surprise, by

encouraging quick and independent decision-making by those who are at the forefront

and actually facing the situations (Nelsen, 1987). This is accomplished by the

commander giving general directions (intent) of what is to be done, yet still allowing


8

subordinates the freedom to determine how to do it, to the extent that the intent is not

endangered (Keithley & Ferris, 1999).

Intent should be clarified in terms of purpose, method and end state, so it is

clear not only what should be accomplished, but also why (Nelsen, 1987; Bech,

2001). Understanding the commander’s intent and how it can be implemented, is vital

for the subordinated leaders to achieve the final aim of the mission (Fitz-Gibbon,

1995). The freedom needed in order to do this, however, includes: trust, initiative,

decentralisation, independence and flexibility (Nyhammar, 2009), all of which

emphasise a number of important skills demanded by military officers under directive

control leadership.

3.3 Creativity and divergent thinking in military leadership

The NAF’s participation in recent international operations, such as in Iraq and

Afghanistan, has placed increasingly higher demands on their military leader’s ability

to operate in dynamic and hostile environments (Forsvaret, 2016b). There has also

been an increasingly wide range of new operational methods in combination with

operations between units that have cooperated less frequently in the past (Forsvaret,

2016b). Being able to adapt to new operational environments and adjusting plans of

action according to rapidly changing situations, has increased the need for flexibility

among military leaders (Bech, 2001), because a proposed action may quickly become

obsolete when the situation changes and novel problems unfold.

Indeed, “Leadership in war is an art, a free creative activity” (Germany’s 1933

Field Service Regulations, in Nelsen (1987:23)), and is a statement that helps draw

attention to the importance of creative thought and divergent thinking skills among

leaders in order for them to solve their missions. Similarly, the NAF’s joint

operational doctrine emphasises that directive control includes “the use of creativity

within the entire organisation”, and also suggests that a well-accomplished mission

“will be the result of all subordinated leaders being able to take goal-oriented

initiatives based on the commander’s intent” (Forsvarsstaben, 2014:166).

The ability to take initiative is also one of the preferable leader characteristics

specified in the NAF’s officer evaluation format (Forsvarsstaben, 2014). In here, it is

held that initiative requires an understanding of the situation at hand and actively

striving to do something about it, including actions that will end status quo situations.

Initiative also relies upon the ability to generate solutions in situations where no clear

pre-defined operational procedure is available (Mumford & Connelly, 1992). These

are all aspects of creative thought, and the NAF’s joint operational doctrine describes

creativity as the ability to think divergent in order to take goal-oriented initiatives


9

(Forsvarsstaben, 2014). The ill-defined problems faced by officers in military

operations do not allow knowledge to be used in a traditional manner, but rather

requires the use of divergent thinking to generate solutions (Hansen, 2013). In the

NAF’s joint operational doctrine, directive control leadership encourages the use of

divergent thinking in order to successfully fulfil the mission according to the

commander’s intent (Forsvarsstaben, 2014). To develop effective leaders that are able

to deal with the situations faced in war and conflict, however, will require training

that is based on a proper understanding of the factors that are linked, and may

contribute to effective leadership (Bartone et al, 2002b).

Because divergent thinking skills have been found to be strong predictors of

leadership effectiveness, problem-solving efforts, and subsequent leader performance

even after the effects of both expertise and intelligence have been accounted for

(Mumford et al, 1998), it would be reasonable to assume that the NAF are interested,

and in fact able to identify individuals who are likely to engage in divergent thinking.

In addition, as NCO training is the first step into further military training, identifying

divergent thinking should be an important aspect of the NCO selection process.

Prior to this NCO selection process, applicants are selected based on previous

grades and specialisation subjects from high school, in which only those best suited

are chosen to attend (Forsvaret, 2016b). The NCO selection process is divided into

two main phases, where phase one includes selection tests and phase two consists of a

field exercise. In phase one several ability and personality tests are conducted in

addition to physical tests, officer interviews and medical selection (Forsvaret, 2016a).

Although phase one may share some similarities with selection processes in a civilian

context, the second phase is a military exercise where candidates are divided into

teams and given military equipment and requested to solve different tasks in the field

(Forsvaret, 2016a). The purpose of phase two is for officers to assess the candidates

who are best suited and most motivated for military leadership training.

The candidates are evaluated as potential military leaders on five main criteria:

i) initiative, ii) ability to handle uncertainty, iii) ability to create trust, iv) caretaking,

and v) independent and reasonable decision-making (Rones & Fasting, 2010). These

five leadership criteria are based on directive control-, and intent-based leadership,

where divergent thinking is an important aspect of initiative-taking, ability to handle

uncertainty, and independent and reasonable decision-making. At the end of phase

two, the best-suited candidates are offered admission into NCO training (Forsvaret,

2016a).

Since the five leadership criteria have been formulated as a result of NAF’s

adoption of directive control leadership, and are assessed during the NCO selection


10

process (Rones & Fasting, 2011), it would be reasonable to suggest that divergent

thinking should be related to admission into NCO training, and so, we propose the

following hypothesis:

H1: There is a positive relationship between divergent thinking scores and

admission into NCO training.

3.4 Selection interviews

Typical selection processes in civilian contexts include reference checks,

testing of abilities and personality traits, and selection interviews (Schmidt & Hunter,

1998). Even though general mental ability and personality measures are useful for

selection, job interview ratings generally, and largely, influence selection decisions,

and it is also one of the most commonly used selection methods today (Podsakoff et

al, 2011; Schmidt & Hunter, 2004). As a result, interviews play an essential part in

most selection processes, including those conducted during the NCO selection.

In their meta-analysis, Huffcutt et al (2001) found that social skills and

personality traits were among the most rated constructs in structured interviews, of

which focused on job knowledge/skills and interpersonal/social skills. Unstructured

interviews, on the other hand, mainly assessed general intelligence, education,

interests and experience. A structured interview is characterised by mostly predefined

questions designed prior to the interview and include clear scoring criteria (Huffcutt

et al, 2001). Low-structured, or unstructured interviews, however, are characterised

by a few predefined questions and topics intended to be covered during the interview

(Huffcutt et al, 2001). Gimsø (2014) suggests that the selection interviews conducted

as part of the NCO selection process are semi-structured. Additionally, Batey et al

(2009a) found that trained interviewers during structured interviews were in fact able

to identify how creative the ideation of candidates being selected for university would

be in their divergent thinking test scores.

The selection interviews are one of the most central parts of the NCO selection

process. In order to identify the right candidates, officers who perform the interviews

have received training and clear instructions of what characteristics and qualities to

look for in the candidates (Rones & Fasting, 2011). Taken together, there is support

to suggest that candidates who do well in interviews are also selected for NCO

training. Therefore, we propose the following hypothesis:

H2: There is a positive relationship between interview scores and admission

into NCO training.


11

Directive control leadership was introduced into the NAF in 1995 (FO, 1995),

which means that it was a fairly new leadership philosophy in 2007. In 2016, on the

other hand, it has been the central and guiding philosophy for 21 years. With the

increasingly dynamic and complex operational environment faced by leaders during

military operations, divergent thinking skills should be expected to have become

more acknowledged and evident within the NAF. Consequently, they should now be

able and more willing to identify divergent thinking among their potential NCOs

during the selection processes. Although the candidates will be different from those in

2007, the potential changes should be observable and reflected in the interview

ratings that are given, as well as in the final admission status of the candidates. The

second study enables us to compare the results with those collected in study one in a

third comparative study.

We argue that directive control leadership has become more integrated into the

system in 2016, than was the case in 2007. We believe that this will be evident in

higher interview ratings given to those candidates that score high on divergent

thinking. Therefore, we propose the following hypotheses:

H3: There is a positive relationship between interview ratings and divergent

thinking scores in the 2007 selection

H4: There is a significant and positive relationship between interview ratings

and divergent thinking scores in the 2016 selection.

In addition to the above hypotheses we are also interested in testing whether or

not there is an indirect effect of divergent thinking on admission into NCO training

through interview ratings.

3.6 Divergent thinking

The term ‘divergent thinking’ was first introduced by Guilford as ‘divergent

production’ consisting of abilities of fluency (i.e. generating multiple ideas),

flexibility (i.e. generating a variety of different categories of ideas), originality (i.e.

generating novel or unusual ideas), and elaboration (i.e. ability to add details to ideas)

(Lin et al, 2012; Kaufman et al, 2011). Within the scientific study of creativity,

divergent thinking has been one of the largest and oldest research areas (Silvia et al,

2008). Despite being used synonymously with creativity at times, divergent thinking

is in fact not creativity per se (Runco, 2008). Rather it is an important cognitive

process that is necessary for complex problem-solving by allowing for thinking to

move in many directions (Acar & Runco, 2015). Since military leaders are certain to

face ill-defined and novel problems as part of the operational contexts, and being


12

under the pressure of time when doing so; they will often not have the luxury of being

able to analytically formulate solutions (Mumford et al, 2000). Relying on using

knowledge in traditional ways will no longer be sufficient to solve complex problems,

but will instead require the use of more creative ways of generating solutions,

namely, to use divergent thinking (Hansen, 2013).

The use of divergent thinking will help leaders to identify interesting problems

and more creatively implement their solutions, whereas leaders lacking divergent

thinking skills are considered unequipped to handle complex problems (Williams,

2004). The ability to determine whether or not these ideas are viable, however, will

require intelligence (Sternberg, 2008), and convergent thinking (Chamorro-Premuzic

& Reichenbacher, 2008). Convergent thinking is the opposite of divergent thinking,

where thinking moves towards a single-point, i.e. the correct solution, based on

reasoning, structure and analysis (Acar & Runco, 2015). Even if both divergent and

convergent thinking are important for solving complex problems, it has been argued

that the two should be separated as convergent thinking may supress divergent

thinking by critically resisting its novelty (de Ven et al, 1999). Successful solutions

therefore require both modes of thinking with an ability to shift between the two

(Kaufman et al, 2011).

3.7 Intelligence and divergent thinking

General intelligence has often been related to leadership, and it would therefore

be logical to include it as an important aspect of the NCO selection process.

Nonetheless, the reason why divergent thinking has received such attention lately is

due to the increasingly consistent research findings indicating that divergent thinking

skills are strong predictors of leader effectiveness, even after accounting for both

intelligence and expertise (e.g. Mumford et al, 1998; Vincent et al, 2002). According

to Kaufmann (2004) divergent thinking, as a key aspect of creativity, can be

distinguished from intelligence because it requires novelty, which intelligence does

not. Guilford (1956) also argued that general intelligence was distinct from divergent

thinking, and more recent research do in fact support the notion that divergent

thinking skills represent capacities above and beyond general intelligence (Mumford

et al, 2000; Vincent et al, 2002; Kim, 2005; Kuhn & Holling, 2009).

Due to this distinction, Guilford (1966) also claimed that traditional intelligence

tests would not measure all aspects of divergent thinking (Kim, 2008). Consequently,

using intelligence tests as measures of divergent thinking, and a subsequent predictor

of future military leadership effectiveness would not be sufficient for the purpose of

our thesis. Intelligence may not be sufficient for divergent thinking, but it is,


13

however, necessary to a certain degree (Kaufmann, 2004). Fortunately, studies have

consistently given support to the findings that higher intelligence is more often found

among leaders than non-leaders (Zaccaro et al, 2004). Most military leaders also tend

to be fairly good at convergent thinking, which is likely to be a result of them being

continuously trained in completing complex analyses (Hansen, 2013).

Even though school grades may not be measures of intelligence, previous

performance has in fact been found to be one of the strongest predictors of future

performance (Grimsø, 2004), and there is research that suggests a strong relationship

between grades and intelligence (Behling, 1998). Studies from the US Army have

also shown that school grades are strongly related to accomplishing military

leadership training, and points to the importance of other factors for predicting future

performance other than intelligence (Farr & Tippins, 2010). For these reasons, there

is some support to the idea that a certain level of intelligence will be found among the

candidates participating in the NCO selection process, since decisions of admission

are based on grades from high school, as well as sufficient support for not including

intelligence in its own right, or as a measure of divergent thinking in our studies.

3.8 Measuring divergent thinking

For the reason that traditional intelligence tests are not directly able to assess

creative potential, divergent thinking (although just an aspect of creative ability) has

been the theoretical basis for most standardised creativity tests (Lin et al, 2012). Most

research also relies upon divergent thinking to cognitively conceptualise creativity

(von Stumm et al, 2011; Scratchley & Hakstian, 2001), and creative problem-solving

(Runco & Acar, 2012). Since divergent thinking has been viewed as a general process

of cognitive flexibility found to relate to many creative activities (Reiter-Palmon et al,

2009), divergent thinking tests have become the most commonly used method to

assess creative potential (von Stumm et al, 2011). The notion that creative ability

could be captured in paper-and-pencil tests of divergent thinking, initiated a number

of different divergent thinking tests and new scoring methods, which have been

developed in the past 30 years (Runco, 2004).

Even though some criticisms have been raised, it would seem that divergent

thinking tests do in fact have some psychometric qualities similar to intelligence tests

(Runco, 2004), and several studies have repeatedly offered evidence to support

divergent thinking tests as predictors of certain features related to individuals’

performance in creative problem-solving (Runco, 1991; Vincent et al, 2002). The

relationship between divergent thinking and creative potential may well be attributed

the greater possibility of finding creative ideas the more directions (divergence) is


14

involved in thinking (Acar & Runco, 2015). Similarly, individuals who have

cognitive styles that are more prone to divergent thinking and who also enjoy

divergent thinking, seems to be more creative (Williams, 2004). This, however, is not

to say that divergent thinking tests are a guarantee for creative behaviour, but rather

provides estimates of an individual’s potential for engaging in creative thinking

(Runco, 2004).

Unlike regular tests that have a correct answer, the divergent thinking tests

contain open-ended stimulus requiring individuals to generate as many responses as

possible (Runco & Mraz, 1992). Responses are then typically scored on fluency,

flexibility and originality, which are considered to be a general scoring system across

different domains and meant to provide an overall evaluation of creative potential

(Mumford et al, 1998). The validity of the scoring system has received much support

in research (Runco, 2008), and several studies have also found support for the validity

of divergent thinking tests (e.g. Guilford, 1956; Wallach & Kogan, 1965; Runco,

2008; Kim, 2008). Nonetheless, there are several divergent thinking tests available,

yet not all are equally useful (Mumford et al, 1998), or equally predictive (Furnham

& Nederstrom, 2010).

The two most widely used divergent thinking measures of creativity are

Torrance (1972) Tests of Creative Thinking (TTCT) and Wallach & Kogan’s (1965)

Divergent Thinking Tasks (Lau & Cheung, 2010). The latter provides different tasks

meant to measure divergent thinking, e.g. the line meaning tests involve pictures of

continuous lines, of which the individual is requested to suggest as many

interpretations as possible (Silvia, 2008). The Wallach & Kogan tests have also been

found to be less correlated with intelligence than the TTCT tests (Kim, 2008).

For these reasons, we believe there is sufficient support for the application of

Wallach & Kogan’s line and pattern meanings test, as the measure of divergent

thinking in our thesis. Since divergent thinking has been found to be a good predictor

of leader performance among military leaders (Zaccaro et al, 2000; Matthew, 2009),

identifying those individuals that are likely to engage in divergent thinking should be

important for the NAF. Consequently, this provides the main argument for us to

collect measures of divergent thinking as an assessment of the candidates’ potential

for engaging in creative thinking.

3.9 Personality and divergent thinking

The failure of intelligence tests to measure all aspects of divergent thinking

stimulated a tendency in research to explore the relationship between personality and

creativity (Chamorro-Premuzic & Reichenbacher, 2008). Indeed, evidence of


15

significant relationships between divergent thinking and personality has been found

(e.g. McCrae, 1987; Batey et al, 2009b; Batey & Furnham, 2006; Batey et al, 2010),

and the growing body of such research has started yielding increasingly consistent

results (Batey et al, 2010). Much has also indicated personality effects on divergent

thinking, but not on convergent thinking (Chamorro-Premuzic & Reichenbacher,

2008). Overall, these findings seem to indicate that divergent thinking is a function of

more general personality and cognitive states (An et al, 2016).

It is mainly research using the Five Factor Model (FFM) of personality, also

called the Big Five (in which five broad dimensions are used to explain personality,

i.e. Openness to experience, Extroversion, Conscientiousness, Agreeableness, and

Neuroticism), that has been most consistent in providing evidence of the positive

relationship between divergent thinking and the factor Openness to experience (e.g.

Walker & Jackson, 2014; Furnham & Nederstrom, 2010; King et al, 1996; McCrae,

1987; von Stumm et al, 2011; Chamorro-Premuzic & Reichenbacher, 2008; Batey &

Furnham, 2006). These results also received wide support in Feist’s (1998) broad

meta-analysis.

There has, however, been some disagreement in research regarding whether it

is either Openness to experience (henceforward in the thesis Openness to experience

and Openness will be used interchangeably) and/or Extraversion that is more related

to divergent thinking (McCrae, 1987; Furnham & Bachtiar, 2008). Extraversion is

believed to improve divergent thinking by increasing risk-taking and stimulation-

seeking, whereas Openness is believed to increase divergent thinking by improving

peoples’ openness to novel ideas and imagination (An et al, 2016). In contrast to the

construct of Extroversion, Openness is the only construct that has been found to

predict creative ability independent of the four other factors (McCrae, 1987; King et

al, 1996; Silvia et al, 2008; Walker & Jackson, 2014).

Since most research seems to suggest that Openness to experience is more

strongly related to divergent thinking than Extroversion, we expect to find similar

results in our data. Hence, we propose the following hypothesis:

H5: There is a higher positive correlation between divergent thinking

(including each sub-score) and Openness to experience, than between divergent

thinking and Extroversion.

When describing patterns in cognition among individuals high on Openness,

these often include: divergence, flexibility, fluency, imagination and curiosity

(McCrae, 1987), which all emphasise a close link to divergent thinking. Previous

research has also shown significant relationships between personality and leader


16

performance (Connelly et al, 2000). It would seem that both leaders and creators

share an openness to experience (Matthew, 2009). McCormack & Mellor (2002) also

found in their study of military officers in the Australian Army that personality was

an important contributing factor for leader effectiveness, and that the effective

commissioned officers were characterised by high Openness to experience.

The link between Openness and divergent thinking has been found to be both

theoretically and empirically supported (King et al, 1996). When using the NEO-PI

(i.e. Neuroticism-Extroversion-Openness Personality Inventory used to assess the Big

Five personality traits), all the relevant facets of the Openness construct have been

found to be positively and significantly related to measures of divergent thinking

(McCrae, 1987; King et al, 1996). The NEO-PI is a self-report measure of personality

indicating an individuals’ likelihood or preference for being divergent and flexible in

their thinking, i.e. ‘thinking outside the box’ (King et al, 1996). Divergent thinking

tests, in contrast, are more performance-based measures indicating individuals’

likelihood or preferences for such type of thinking (King et al, 1996). Due to its close

relationship to divergent thinking, various studies have even suggested that Openness

to experience can be understood as a proxy of creativity (Chamorro-Premuzic &

Reichenbacher, 2008; King et al, 1996).

The close relation between Openness and divergent thinking seems to support

the idea that candidates applying for NCO training would not be any different. By

using scores on divergent thinking and Openness from NEO PI-R (i.e. revised NEO-

PI) as part of our data collection, we propose the following hypothesis:

H6: Divergent thinking scores are positively and significantly correlated with

scores of Openness to experience.

Moreover, because the Big Five personality tests are frequently used in the

selection process within the NAF (Johansen et al, 2014), and there are no other

divergent thinking tests typically included, it would be reasonable to suggest that

Openness obtained through NEO PI-R is possible to use as a proxy for divergent

thinking. Hence, we propose the following hypothesis:

H7: There is a positive relationship between candidate’s scores of Openness to

experience and interview ratings.

Based on the literature review we believe that there is enough support to argue

that the NAF should be interested in identifying individuals who are likely to engage

in divergent thinking. Consequently, we propose a partly normative research model as

the basis of our thesis, in which study one and two test all of the relationships:


17

4.0 Study 1

4.1 Method

A quantitative approach was chosen to test the hypotheses 1, 2, 3, 5, 6 and 7. In

the following the study will be presented with regards to design, setting, samples and

procedures, literature search, ethics, measurements, data analyses, results and

discussion of results.

4.1.1 Design

A cross-sectional study was designed and conducted. The study consists of a

combination of self-report measures of personality (NEO PI-R), ability test (divergent

thinking test) and performance data (interview rating and admission). The data was

not collected by us but was provided by our supervisor as a data set in SPSS, along

with some verbal information regarding the method. The data collection took place as

part of the summer NCO selection in 2007.

4.1.2 Setting

The purpose of the NCO selection process is to select the candidates with the

best potential and highest motivation for military leadership (Gimsø, 2014). The full

selection process is explained in Figure 1. Prior to selection the potential applicants

are screened on minimum requirements including high school grades, certificates of

good conduct and accountability for military service (Gimsø, 2014). Only those

applicants fulfilling these requirements are invited to the NCO selection process. The

first phase lasts approximately five to seven days and includes medical selection,

physical tests, selection interviews, theoretical tests and ability tests. Other tests may

also be required depending on the branch of application (Army, Air force, or Navy).

The candidates who do not fulfil the requirements or score too low on the tests in the

first phase, may not be selected into the second phase.


18

Duration and content also vary to some degree in the second phase depending

on the specific branch of application. The second phase is a field exercise, in which

candidates are tested on practical military leadership potential. Here assigned officers

follow the teams throughout the second phase and rate the candidates on practical

military leadership potential (Forsvaret, 2016a). Those candidates who score high in

both phases are offered admission into NCO training.

4.1.3 Sample and procedures

The sample consists of 1375 candidates enrolled into phase one, and data

regarding sex, interview ratings and admission status were collected from this sample.

Of these 1375, 91.7% (N=1261) candidates took part in the divergent thinking test,

and 89.1% (N=1225) in the personality test. Inclusion and exclusion in the study is

explained in Figure 2 in appendix 1. In total, 89.1% (N=1225) of the candidates

participated and completed the tests. 10.9% (N=150) of the candidates did not

complete the tests and were considered non-responses. There are several reasons for

the reduced number of participation throughout the selection process. The main

reasons are voluntary withdrawal (i.e. lack of motivation, or physical injuries), and

lack of fulfilled requirements for continued involvement, as well as tight selection

schedules causing reduced time for testing.


19

The divergent thinking and personality tests were conducted as part of phase

one together with other research measures not related to our study. All of the tests and

research measures included was collected in a compendium, which was given to the

candidates in a specific room/test-area. The candidates came in smaller groups to the

room/test-area and their attendance was arranged so that the research testing took

place in between the original programme of the selection process.

In the divergent thinking tests (section 4.2.1) each task was to be completed

within four minutes. The total amount of time used on the test was eight minutes,

excluding introduction and instructions. The only instructions given to candidates

were the written instructions on the front page of the divergent thinking test, which

were read out loud (see appendix 2). The word ‘test’ was not used in the instructions,

due to the possibility of increased test anxiety (Cooper, 2010). In the personality test

(section 4.2.2.), no instructions were given except those written in the compendium,

which are the regular instructions for such personality tests, and candidates were

given free disposal of time. Both the divergent thinking and personality tests were

conducted by paper-and-pencil prior to interviews.

4.1.4 Literature

The literature search was based on American Psychological Association’s

guidelines for literature search (APA, 2013). The search terms were generated by

examining literature in the field of divergent thinking and military selection

processes, in relation to the research question. Search terms were then divided into

three categories; 1) main constructs (divergent thinking, creativity, openness to

experience, fluency, flexibility, originality), 2) main variables (interview rating,

interview score, selection interview) and 3) setting/context/sample (officer selection,

military selection, non-commissioned officer, officer candidate school, military

leadership, military leadership training). Four central databases in organisational

psychology research were then chosen: PsycInfo, PsychArticles, Business Source

Complete and Sage Premier.

First, each search term was applied individually in each of the four databases,

before various combinations of these were applied. In the different combinations

AND was used in order to narrow the search, whereas OR was used to broaden the

search (De Brun & Pearce-Smith, 2009). Two inclusion criteria were initially applied

and are used in the search matrices (appendix 3): 1) only studies written in English,

and 2) studies published between 1950 to 2016, were included. Older articles were

included because they constitute original knowledge within the area of divergent

thinking, which forms the basis for more recent research. After the initial search,


20

articles based on non-western samples (apart from Australia) were excluded, as the

possible different cultural context may not apply to our studies (Bryman & Bell,

2011).

The reference lists in these articles were then reviewed in order to identify

essential articles or sources to include. For the same reasons searches in Oria and

Google Scholar were also conducted with the similar combinations of key terms used

for the search in databases. The initial searches were carried out in January 2016, and

then again in March 2016. Searches were first performed individually before the

results were compared. The final search was quality assured by librarian, and

consisted of 93 articles, excluding secondary literature. Secondary literature search is

not included in appendix 3, but consists of doctrines and reports from the Norwegian

Armed Forces, and books on military theory. The articles and secondary literature

were then carefully evaluated with respect to their relevance for our studies.

4.1.5 Ethics

All candidates received written and verbal information about the study, and

were informed that neither participation or performance would have any influence on

admission. The written information given to the candidates were not available to us.

In 2007 the Norwegian Defence College had a general approval from the Norwegian

Centre for Research Data (NSD) to collect data on their candidates as part of internal

development. Hence, no specific application for the data collection this study built on

was forwarded. All the received data was completely anonymous so that no personal

information was known to us.

4.2 Measurements

The measurements used in the study were divergent thinking tests, NEO PI-R,

selection interviews and admission into NCO training. All measurements are

described in the following.

4.2.1 Divergent thinking tests were based on Wallach & Kogan’s (1965)

Divergent Thinking Tasks (appendix 2), which consist of two tasks (figures), in

addition to an example of how the tasks are to be performed. Both figures are visual

stimulus material, in which one is a pattern and the other a line. It asks the candidates

to generate interpretations or meanings that are relevant to the specific line and

pattern (Wallach & Kogan, 1965). Since divergent thinking tests are open-ended,

scores can range from zero to infinite. There are several ways to score divergent

thinking tests, but the method that are relied upon in this study is based on Guilford’s

(1966) method of assessing divergent thinking. Guilford’s (1966) method scores


21

divergent thinking on four criteria: fluency, flexibility, originality, and elaboration.

Because most of the responses consisted of single words elaboration was not included

in our studies. The study was scored on fluency, flexibility and originality according

to the total responses given on both tasks.

Fluency was scored by the number of generated responses. Flexibility was

calculated by the number of different categories that could be formed from the

responses. The categories for each task were outlined in a scoring manual developed

by us in accordance with Torrance’s (1990) Manual for scoring and interpreting

results. These categories were then based upon the existing responses and established

prior to carrying out the scoring. Both tasks gave rise to 28 categories each (see

appendix 4). Originality was calculated on the basis of the relative frequency of a

particular response using an unusualness index with a 5% cut-off level (Runco, 2008).

Although the Wallach and Kogan’s (1965) uniqueness method is the most

common method, i.e. awarding one point for each response occurring only once in the

dataset, the large amount of responses in our data set (22 385 responses) made it

inappropriate to do so. Therefore, we followed Runco’s (2008) advice and used the

unusualness index to identify unusual responses, namely, those responses that

appeared less than 5% of the total number of responses per task were rewarded one

point each. Other cut-off levels in line with previous research (Runco, 2008), such as

10%, was also attempted. Because the 5% cut-off on the unusualness index is closer

to the uniqueness method, this was applied.

4.2.2 The personality test was applied to measure personality based on the

Five Factor Model of personality. This was done by including the Norwegian version

of the NEO PI-R. The NEO PI-R contains 240 test items forming the five factors

(Martinsen et al, 2005). Each item is scored on a Likert scale from 0 (strongly

disagree/completely wrong) to 4 (strongly agree/completely correct). The purpose of

applying NEO PI-R was to specifically assess the factor Openness to experience,

which is measured by 48 items consisting of six facets (fantasy, aesthetics, feelings,

actions, ideas, and values) (Costa & McCrae, 1992). The scores can thus range

between 0-192. Extroversion was also assessed in order to test if our data corresponds

to previous research, in that divergent thinking has been found to correlate more

strongly with Openness, than with Extroversion (McCrae, 1987). The overall score of

the Openness construct was then calculated for each candidate and included in our

analyses.

4.2.3 The selection interview format and procedures are developed by the

psychological department at the Norwegian Defence University College in order to


22

assess each candidate’s leadership potential, and lasts for approximately 60 minutes

(Gimsø, 2014). The interviews were carried out by trained and experienced officers,

who prior to the selection received course training in interview techniques to ensure

appropriate interview skills (Gimsø, 2014). Two interview officers conducted each

interview together, and in cases of uncertainty officers consulted with a psychologist.

The interviews addressed several topics according to a predefined template that

included five main criteria of leadership potential, although each interview officer had

the freedom to probe each topic if necessary. The interviews were thus considered

semi-structured (Gimsø, 2014). Each of the five criteria was scored separately but

only the total interview scores were available in our data set. The interview ratings

scale ranged from 0.5-6, in which half points were given and 6 was the highest score

indicating strong leadership potential (Gimsø, 2014). Interview ratings thus indicate a

leadership prognosis.

4.2.4 Admission was based on candidates’ performance in both phase one and

two. The selection interview ratings from phase one in combination with officer

rating from phase two are both important aspects of the admission decision. The

admission decision is an overall evaluation of the candidates’ suitability for military

leadership training in combination with the specific requirements for each of the three

branches. Therefore, no fixed requirements were set for minimum performance on the

two phases of the selection. The final admission decisions, however, were made by

the admission council consisting of participating principals from each of the branches,

a physician, a psychologist and a sports officer (Gimsø, 2014).

4.3. Reliability

Reliability refers to the “consistency of a measure of a concept” (Bryman &

Bell, 2011:158). The reliability of the selection interview was not estimated, but

according to similar studies (Gimsø, 2014), the reliability estimates from previous

meta-analytical studies (McDaniel et al, 1994) can be relied upon. McDaniel et al

(1994) found that reliability estimates for structured selection interviews were .84,

and .68 for unstructured interviews. As the selection interviews were considered

semi-structured, they are likely to have reliability estimates closer to the structured

(Gimsø, 2014).

No reliability estimates for the divergent thinking test were available, and these

were therefore calculated. The estimated internal consistency using Cronbach’s alpha

for divergent thinking (α=.894) and all sub-scores in our study are presented in Table

1. Overall, these were found to be satisfactory (Field, 2013), ranging from α=.689 to

.828.


23

The internal consistency for the two tasks was estimated to be α=.850 for task

1, and α=.851 for task 2 (Table 2). Internal consistency was also measured for the six

facets forming the Openness construct and estimated to be α=.703. The internal

consistency for each Openness facet ranged from α=.677 to .759 (see Table A in

appendix 5). Internal consistency for all facets forming the Extroversion construct

were estimated to be α=.768 (Table B in appendix 5).

4.3.1 Interrater reliability

Interrater reliability was only calculated for flexibility scores, since fluency

and originality scores were mathematically calculated and jointly scored by both

raters. In order to assess the interrater reliability of flexibility scores we applied an

intraclass correlation coefficient (ICC) (Shrout & Fleiss, 1979), in addition to

Cronbach’s alpha.

Many forms of ICC exist and we were thus required to make some basic

decisions. A two-way mixed model was appropriate to us because each candidate had

been rated by us, which were also the only raters of interest (Shrout & Fleiss, 1979).

We then used an average measure based on consistency rather than agreement

because the variance between columns in this option is considered irrelevant

(McGraw & Wong, 1996). By using the average based on consistency, it does not

matter that rater one has given relatively low scores and rater two higher scores. The

intraclass correlation coefficient then provides the appropriate estimate for the

consistency among our flexibility ratings on each of the candidates. This was found to

Table 1. Means, standard deviation, correlations and reliability

for divergent thinking (N=1261)

Mean(±SD)

1

2

3

4

1. Fluency

r

8.88(±3.54)

(.828)

2. Flexibility

r

6.58(±1.83) .858** (.716)

3. Originality

r

2.106(±1.86) .831** .698** (.689)

4. Total DT

r

17.561(±6.79) .980** .907** .895** (.894)

** p<.01. Estimated Cronbach’s alpha in brackets on the diagonal.

Table 2. Means, standard deviation, correlations and reliability

for task 1 and 2 (N=1261)

Mean(±SD)

1

2

3

1. DT total task 1

r

17.25(±7.15)

(.850)

2. DT total task 2

r

17.87(±7.58) .702** (.851)

3. DT total task 1-2

r

35.12(±13.59) .918** .927** (.894)



24

be satisfactory (ICC =.884), presented in Table 3 along with estimated Cronbach’s

alpha, correlations, means and standard deviations.

4.4 Validity

Amongst the most important criterion of research is validity, which concerns

integrity of the conclusions that are generated from a research study (Bryman & Bell,

2011). The study relied upon several measurements with various degree of validity.

NEO PI-R is a well-tested measurement and has been found to have high construct

validity in several studies (Martinsen et al, 2005), whereas the validity of the

selection interview has not been possible to accurately estimate (Gimsø, 2014).

The validity was not estimated for our divergent thinking test but the Wallach

and Kogan’s test has been found valid (Runco, 2008; Wallach & Kogan, 1965). The

study had no intention of demonstrating causality, but rather associations. Because

the study is cross-sectional it is reasonable to evaluate the external validity with

regards to the generalisability of the results beyond the specific research context, and

this would include generating a representative sample (Bryman & Bell, 2011).

The sample, however, represents all candidates enrolled into the first part of the

selection. As mentioned in section 4.1.3, some candidates were not tested, but the

number of non-responses is relatively low (10.9 %, N=150). The impact of these non-

responses is likely to have low influence on the external validity of the study. Each

individual who aim to become a military leader within the NAF will have to

participate in the NCO selection process. This would suggest that a relatively large

degree of the population will be represented in the sample, which in turn increases

both the sample’s representativeness of the population, as well as the external

validity. It is, therefore, likely that our study has a relatively high external validity.

The study has ecological validity in that the findings are applicable to a natural social

setting (Bryman & Bell, 2011), which in this case is the NCO selection process.

Table 3. Intraclass correlations coefficient and reliability for

flexibility scores (N=1261)

Mean(±SD)

1

2

3

1. Flexibility rater 1

r

6.52(±1.82)

(.690)


r

6.64(±1.90) .940** (.695)

3. Flexibility Total

r

6.58(±1.83) .984** .985** (.884)

** p<.01.


25

4.5 Data analyses

All continuous variables are reported as the mean value ± standard deviation

(SD), while categorical variables are reported as frequency and percentage within

each category. Descriptive analyses were performed in order to get an overview of

sample characteristics. All variables have been checked regarding distribution and

linearity and appropriate assessments have been applied (i.e. parametric, non-

parametric tests) (Bishara & Hittner, 2012; Arndt et al, 1999; Hair, 2010). Differences

between dichotomous variables at baseline were assessed using independent t-tests

and Mann-Whitney U tests (for continuous variables), or chi-square tests (for

categorical variables).

In order to test hypothesis 5 and 6, correlation analyses were performed to

explore covariation between continuous variables. To test hypothesis 3 and 7,

univariate logistic regressions were first performed. Results of logistic regression are

reported in odds ratio (OR). Odds, is the probability of an event occurring divided by

the probability of that event not occurring (Field, 2013). The proportionate change in

odds is the odds ratio (the exponential of B, i.e. eB or exp (B)), and can be interpreted

in terms of the changes in odds, where a value >1.00 indicates that as the predictor

increases, the odds of the outcome increases (Field, 2013). Conversely, a value <1.00

indicates that as the predictor increases, the odds of the outcome occurring decreases

(Field, 2013). A logistic regression was chosen due to interview ratings having been

recoded into a dummy variable, because the original ordinal variable did not meet the

assumption of linearity on the logits in binary logistic regression (Field, 2013). It was

thus treated as a dichotomous variable in all analyses except for mediation analysis.

Linearity of the logits is an important and essential assumption in logistic

regression and is widely recognised in psychological method and statistics in general

(Pregibon, 1981; Hosmer et al, 1997; Hosmer & Lemeshow, 2000; Weiner et al,

2003; Field, 2013). In accordance with Field (2013), Hosmer & Lemeshow (1989),

Weiner et al (2003), and Box & Tidwell (1962), the Box-Tidwell method was used to

test the assumption of linearity of the logits. To overcome this problem, it is highly

recommended to transform the variable (Box & Tidwell, 1962; Weiner et al, 2013).

Attempts of creating a quadratic term of the variable did not solve the problem.

The interview ratings variable was therefore recoded into dummy variables for each

possible interview score (i.e. 12), including reference category. Linear regression

analyses with these variables showed that scores lower than 3.5 had negative betas,

and were insignificant, while interview scores from 4.0 and higher had positive betas,

and were significant. Interview ratings were therefore recoded into 0=low and

1=high, where low ranged from 0.5-3.5 and high ranged from 4.0-6.0. Attempts of


26

dividing the interview variable into three categories rather than two in order to

preserve more data did not improve the results and is therefore not reported. A

multiple logistic regression model was then fitted for interview ratings and controlled

for sex.

To test hypothesis 1 and 2, we first performed univariate binary logistic

regression models with the outcome variable admission (0=no admission,

1=admission) before a multiple model was fitted. The simultaneous method for

inclusion of variables in the multiple model was used (Field, 2013). All multiple

logistic regression models were carefully examined with respect to criteria for logistic

regression (i.e. linearity of the logits, multicollinearity, independency of errors,

normal distribution of the residuals) (Field, 2013).

In addition, measures of classification accuracy were calculated in order to

assess the utility of the logistic regression models (Bayaga, 2010). Classification

accuracy compares predicted group membership based on the logistic model to the

actual known group membership (Småstuen, 2015). Accordingly, a proportional by

chance accuracy rate (PCA) with a 25% margin was computed for each fitted model

and compared to the proportional by chance criteria (PCC) given by SPSS (White,

2013). Models not fulfilling PCA requirements were considered insufficient for

explaining the variance in the dependent variable.

Furthermore, the indirect effects of divergent thinking and Openness to

experience on admission through interview ratings were investigated, and mediation

and moderation analyses were then performed. A regression-based approach (Hayes,

2013) was chosen and the PROCESS custom dialog box was applied to perform these

analyses. All independent variables with p-values ≤0.15 in the univariate regression

models were included in multivariate models. P-values ≤0.05 were considered

statistically significant, and all tests were two tailed.

4.6 Results

4.6.1 Sample characteristics

The descriptive statistics is presented in Table 4. The total number of

participants in the study was 1375, which equals the total number of candidate

attendance on the first day of selection. In this sample 15.1 % (N=207) were women,

and 84.9% (N=1168) were men. Amongst the candidates, 48.1% (N=661) were

admitted into NCO training, of which 14.2% (N=94) were women and 85.8%

(N=567) were men. Age was not recorded as a background variable in this dataset,

but based on previous studies the majority of the applicants were assumed to be in the

range of 18-21 years (Gimsø, 2014). The scores on divergent thinking tests for the


27

candidates were on average 17.56(±6.79) points, and no significant differences were

found between candidates admitted and not admitted. The divergent thinking scores

ranged from 3.75 to 56.30. The Openness scores were on average 107.11(±16.29)

points, and there was no significant statistical difference between those who were

admitted and not admitted. The Openness scores ranged from 58.00-172.00.

Overall, 72.2% (N=1000) of the candidates achieved high interview ratings

(4.0-6.0), and 27.3% (N=375) achieved low interview ratings (0.5-3.5). The

candidates admitted had significantly higher interview ratings compared to those not

admitted (p<.001). Amongst the candidates that were admitted, 22.5% (N=149)

achieved low interview ratings, whereas 77.5% (N=512) achieved high interview

ratings. In the non-admitted group, 31.7% (N=226) of the candidates achieved low

interview ratings, and 68.3% (N=488) achieved high interview ratings.

4.6.2 Correlations

Divergent thinking scores were found to be positively, and significantly

correlated with Openness to experience (r=.214 p<.01) and interview ratings (rρ=.149

p<.01) (Table 5). Openness was found to be positively, and significantly correlated

with interview ratings (rρ=.133 p<.01) and with each sub-score of divergent thinking,

i.e. fluency (r=.196, p<.01), flexibility (r=.259, p<.01), originality (r=.155, p<.01).

The correlation between Extroversion and divergent thinking was positive, and

significant (r=.167 p<.01), but less so than with Openness to experience, including for

each sub-scores, i.e. fluency (r=.167, p<.01), flexibility (r=.185, p<.01), and

originality (r=.111, p<.01) (Table 6).

Table 4. Descriptive statistics over sample characteristics and selection variables

Sample

characteristics

Selection variables

Variables

Sex

Women N(%)

Men N(%)

Divergent thinking

Mean(±SD)§

Openness to

experience

Mean(±SD) ¤

Interview rating

low/high***

Low N(%)

High N(%)

Total

(N=1375)

207(15.1)

1168(84.9)

17.56(±6.79)

107.11(±16.29)

375(27.3)

1000(72.2)

Admission

(N=661)

94(14.2)

567(85.8)

17.73(±6.71)

107.81(±16.07)

149(22.5)

512(77.5)

No Admission

(N=714)

113(15.8)

601(84.2)

17.38(±6.87)

106.45(±16.48)

226(31.7)

488(68.3)

*** p<.001. §=admission (N= 638), no admission (N= 623). ¤= admission (N= 600), no admission (N=625).


28

4.6.3 Relationships: divergent thinking, Openness and interview ratings

The results indicated (Table 7) that there were significant associations between

divergent thinking and interview ratings (p<.001), and Openness and interview

ratings (p<.001).

For an additional point on divergent thinking tests, the odds of scoring high on

interview ratings were significantly increased by 4% (OR=1.04, p<.001), whereas an

additional point on Openness to experience, significantly increased the odds of

Table 5. Means, standard deviations, and correlations for all variables

N

Mean(±SD)

1

2

3

4

5

6

7

8

1. Fluency

r

1261

8.88(±1.65)

(.828)

2. Flexibility

r

1261 6.58(±1.83) .858** (.716)

3. Originality

r

1261 2.11(±1.86) .831** .698** (.689)

4. Total DT

r

1261 17.56(±6.79) .980** .907** .895** (.894)

5. Openness

r

1225 107.12(±16.30) .196** .259** .155** .214** (.703)

6. Interview rating

ρ

1262 4.13(±0.99) .149**

.168**

.088**

.149**

.133**

-

7. Admission

ρ

1375 .022

.059*

.010

.029

.046

.195**

-

8. Sex

ρ

1375

-.090**

-.118**

-.047

-.094**

-.156**

-.038

-.052

-

**p<.01. *p<.05. Admission 0=no admission; 1=admission, Sex 0=men; 1=women. r=Pearson’s, ρ=Spearman’s. Estimated Cronbach’s alpha in brackets on the diagonal.

Table 6. Means, standard deviations and correlations for personality and divergent thinking

variables

N

Mean(±SD)

1

2

3

4

5

6

1. Openness

r

1225

107.11(±16.30)

(.703)

2. Extroversion

r

1227 127.76(±14.94) .389** (.768)

3. Fluency

r

1261 17.75(±7.07) .196** .167** (.828)

4. Flexibility

r

1261 13.16(±3.66) .259** .185** .858** (.716)

5. Originality

r

1261 4.21(±3.73) .155** .111** .831** .698** (.689)

6. Divergent thinking

r

1261 35.12(±13.59) .214** .167** .980** .907** .895** (.894)


Table 7. Univariate binary logistic regression models, dependent

variable interview rating (0=low, 1=high)

Variables

OR

95% CI

P

Divergent thinking§***

1.04

1.02-1.06

<.001

Openness to

experience¤***

1.02

1.01-1.02

<.001

Sex#

Women

Men (ref)

1.21

-

.86-1.71

-

.275

-

***p<.001. §=N=1261. ¤=N=1225. #=1375.


29

scoring high on interview ratings with 2% (OR=1.02, p<.001). Sex was not found to

be significantly associated with interview ratings (p=.275). Divergent thinking was

not included in the following multiple binary logistic regression model (Table 8),

because this variable violated the assumption of linearity on the logits (section 4.5).

Accordingly, only the significant variable was included, which was Openness to

experience. Sex was included as a control variable. The multiple model (χ2:15.82,

p<.001) indicated that Openness was significantly associated with interview ratings

(p<.001), when controlling for sex. One additional point on measures of Openness

also significantly increased the odds of scoring high on interview ratings by 2%

(OR=1.02, p<.001).

The model did not fulfil the classification accuracy requirements, in that the

calculated PCA was found to be (336/1225)2+(889/1225)2= 0.075+0.526

=0.6016*100 =60.2%. 1.25*60.2% = 75.3%, whereas PCC was reported to 72.6%.

Cox and Snell was found to be 1.3%, and Nagelkerke R2 1.9%. Cooks distance values

were all <1.00, and all values of DfBeta were found to be within the range of ±1.00.

No standardised residuals had values >±2.00. Leverage was calculated and no cases

were found to be outside these values ((k+1)/n =3+1/187 =.014*3 =.042). Measures

of multicollinearity were examined using linear regression (VIF mean=1.03, and

Tolerance mean=.98) and found acceptable. Eigenvalue, condition index and residual

plots were inspected and found to be satisfactory.

4.6.4 Relationships: divergent thinking, Openness, interview ratings and

admission

The results indicated (Table 9) that the odds of being admitted were

significantly (p<.001) lower for applicants scoring low (0.5-3.5) on interview ratings

compared to those with high interview ratings (4.0-6.0). By scoring low on interview

ratings the odds of being admitted was decreased by 37% (OR=.63, p<.001).

Openness (p=.145), divergent thinking (p=.359), and sex (p=.406) were not

significantly associated with admission.

Table 8. Multiple binary logistic regression, dependent variable

interview rating (0=low, 1=high) (χ2: 15.822(2) p<.001) (N=1225)

OR

95% CI

P

Openness to

experience***

1.02

1.01-1.02

<.001

Sex

Women Men (ref)

1.03 -

.71-1.49 -

.879 -

***p<.001


30

In the multiple model (Table 10) the univariate significant variables Openness

and interview ratings were included, in addition to sex as control variable. The

multiple model (χ2:13.95, p=.003) indicated similarly to that of the univariate

regressions that interview ratings were significantly associated with admission

(p=.001). Scoring low on interview ratings lowered the odds of being admitted by

36% (OR=.64) compared to those scoring high. The variables sex and Openness were

found to be insignificant and less related to admission (p=.254).

The multiple model did not fulfil the classification accuracy requirements, in

that the calculated PCA was found to be (625/1225)2 +(600/1225)2 =0.26+0.24

=0.5*100= 50%. 1.25*50%= 62.5%, whereas PCC was reported to 54.0%. One case

was considered an outlier, given three times higher leverage values than allowed, and

thus removed. No changes in the estimates and PCA were observed after the removal.

Cox and Snell was found to be 1.1%, and Nagelkerke R2 1.5%. Cooks distance values

were all <1.00, and all values of DfBeta were found to be within the range of ±1.00.

No standardised residuals had values >±2.00. Measures of multicollinearity were

examined using linear regression (VIF mean=1.03, and Tolerance mean=.98) and

found acceptable. Eigenvalue, condition index and residual plots were inspected and

found to be satisfactory.

Table 9. Univariate binary logistic regression models, dependent variable

admission (0=no admission, 1=admission)

Variables

OR

95% CI

P

Divergent thinking§

1.01

.99-1.02

.359

Openness to experience¤

1.01 .10-1.01 .145

Sex#

Women Men (ref)

.88 -

.67-1.19 -

.406 -

Interview rating low/high¤***

Low

High (ref)

.63

-

.49-.80

-

<.001

-

***p<.001. §=N=1261. ¤=N=1225. #=1375.

Table 10. Multiple binary logistic regression models, dependent variable

admission (0=no admission, 1=admission) (χ2: 13.953(3) p=.003) (N=1225)

Variables

OR

95% CI

P

Openness to experience

1.01

.10-1.01

.254

Sex

Women

Men (ref)

.92

-

.67-1.27

-

.609

-

Interview rating low/high***

Low High (ref)

.64 -

.50-.83 -

.001 -

***p<.001


31

4.6.5 Moderation and mediation analyses

In order to evaluate the combined effect of divergent thinking/Openness, and

interview ratings on admission, moderation analyses were performed. Moderation

occurs when the relationship between two variables changes as a function of a third

variable (Field, 2013). Moderation is tested by creating an interaction term between

the moderator and the predictor and is present when this interaction term is significant

(Field, 2013). In moderation analyses the moderator may be either continuous or

dichotomous, and interview ratings was thus used as a dichotomous variable in line

with previous explanation (section 4.5). The predictor is commonly transformed in

moderation analyses by using grand mean centring, referring to the process of

transforming a variable into deviations around a fixed point (the grand mean) (Field,

2013). Centring was thus applied for the predictors (divergent thinking and Openness)

in the following moderation analyses. The results indicated (Table 11) that the

relationship between divergent thinking and admission was not moderated by

interview ratings, as indicated by the insignificant interaction term (B=.01, 95% CI -

.02-.05, p=.487).

The results (Table 12) for Openness also indicated that the relationship between

Openness and admission was not moderated by interview ratings either, as shown by

the insignificant interaction term (B=-.01, 95% CI .02-.02, p=.201). No significant

interaction terms were found and we could conclude that no moderation was present.

Mediation analyses were also performed in order to investigate whether or not

the relationship between the predictors (divergent thinking and Openness), and the

outcome variable (admission) could be explained by their relationship to a third

Table 11. Linear model of predictors of admission (0=no admission, 1=admission)

(N=1261)

Variables

B

SE B

Z

95% CI

P

Divergent thinking

(centred)

.00

.01

.35

-.01-.02

.723

Interview rating low/high

.61 .13 4.74 .36-.86

<.001

Divergent thinking x

interview rating low/high

.01

.02

.70

-.02-.05

.487

Table 12. Linear model of predictors of admission (0=no admission, 1=admission)

(N=1225)

Variables

B

SE B

Z

95% CI

P

Interview rating low/high

.43

.07

6.56

-.02-.02

<.001

Openness (centred)

.01 .00 .46 .34-.59

.643

Openness x interview rating

low/high

-.01

.00 -1.25 -.02-.02 .201


32

variable (interview ratings). Mediation analysis with a regression-based method

requires the mediator to be continuous (Hayes, 2013), and so interview ratings were

used as a continuous variable in this analysis. Effect size measures for indirect effects

(kappa-squared) are not available for models with dichotomous outcomes (Hayes,

2013), and are thus not reported in the following. The results indicated a significant

indirect effect of divergent thinking on admission through interview ratings (B=.01,

BCa CI .00-.01 (see appendix 6). However, there was no significant direct effect of

divergent thinking on admission (B=-.00, p=.970). Openness was also found to have a

significant indirect effect on admission through interview ratings (B=.00, BCa CI .00-

.01, p<.001) (appendix 6). But again, no significant direct effect of Openness on

admission was found (B=.00, p=.652).

Mediation is present when the strength of the relationship between the predictor

and the outcome variable is reduced by including a mediator, and so mediation

equates to the relationship between two variables being explained by a third (Field,

2013). Previously in the univariate analyses we found no relationships between

divergent thinking/Openness and admission, and no changes were found in the

mediation analyses either. So even if a significant indirect relationship is present in

the above analyses between the covariates and the outcome variable, we cannot

conclude that mediation is present, as there is no direct relationship to mediate in the

first place. Mediation was also tested by assessing the size of the indirect effect and

its confidence interval. Because the outcome variable was dichotomous, only the

confidence interval was assessed. If the confidence interval contains zero, we cannot

be confident that mediation is present (Field, 2013). Both mediation analyses

indicated that the confidence intervals contained zero. Consequently, we could

conclude that no mediation was present.

4.7 Discussion of results

The results of this study indicated that divergent thinking, including each sub-

scores (fluency, flexibility and originality) had higher positive correlations with

Openness than with Extroversion. This gave support to hypothesis 5 and justified the

decision to include Openness to experience into further analyses. The results also

indicated that the correlation between divergent thinking and Openness was

significant and positive, albeit assessed to be of small to medium effect size (Field,

2013). Hypothesis 6 was thus supported.

The results also indicated that Openness had a positive and significant

relationship to interview ratings, whereas divergent thinking did not meet the

assumptions for analysis, and could therefore not be evaluated further. Consequently,


33

hypothesis 7 was supported, whereas hypothesis 3 was not supported. The

relationship between interview ratings and admission into NCO training was also

assessed, and the results indicated that those scoring low on interview ratings had

significantly lower odds of being admitted, compared to those scoring high. Hence,

we could conclude that hypothesis 2 was supported. In contrast, we found no support

for the relationship between divergent thinking and admission into NCO training, and

so hypothesis 1 was not supported. Additionally, mediation and moderation models

were fitted. However, no support was found for either a mediating or moderating

effect of interview ratings on the relationships between divergent thinking/Openness,

and admission.

Further discussion of the results and implications of these will be covered under

general discussion (section 7.0).

To examine whether or not these findings remained persistent over time we

wanted to replicate the study using the same variables on a new representative sample

from a more recent NCO selection.

5.0 Study 2

The second study was performed as a replication of study one. While

replication studies are generally performed after the first studies have been completed

(Brandt et al, 2013) so as to e.g. re-examine relationships between constructs

(Mackey, 2012), there were both time limitations and practical reasons (NCO

selection only takes place twice a year), which made this impossible. Therefore, we

collected data in 2016 prior to our data analyses, but we hypothesised (in H3-H4) that

we would find a stronger relationship between divergent thinking and interview

ratings in study two. With regards to the other hypotheses, we expected the direction

of the estimates and associations to be the same for both studies.

Replications of studies within research are important elements of cumulative

science, and yet rather few attempts of replication are in fact reported in psychology

(Schmidt, 2009). This is generally due to the difficulty of carrying out exact

replications within the social sciences, where variations in psychological factors are

fairly common (Mackey, 2012). There are, however, different types of replications

and in our case an external replication was most suitable, because it involves

collecting data from a new sample at a different time than the original sample, and

can be conducted by the same persons as those who conducted the original study

(Drotar, 2010). The replication can take on several forms, but due to the difficulty of

performing exact replications we attempted a so called close replication, which

highlights that replications within psychology cannot be exact recreations of the


34

original studies (Brandt et al, 2013; Schmidt, 2009). Accordingly, we conducted a

close replication study by recreating the methods and procedures of study one as

closely as possible, so that the differences between them would be only the inevitable

ones, such as different participants (Brandt et al, 2013).

Since this study was a replication of study one, the method applied and data

analyses performed were as similar as possible to those described in study one.

Therefore, only the deviations from study one will be accounted for in the following,

and cross-referencing is used to avoid repetition.

5.1 Method

The proposed hypotheses tested in this study were 1, 2, 4, 5, 6, and 7. In the

following the study is presented with regards to design, setting, samples and

procedures, literature search, ethics, measurements and data analyses when deviations

are present. Results and discussions of results will be fully accounted for.

5.1.1 Design

Similar to study one, a cross-sectional study was designed. Data was collected

by us in cooperation with the Norwegian Defence College. In order to replicate study

one, the measures and procedures were identical (section 4.1.1).

5.1.2 Setting

There had been some changes made in the selection process since study one

with regards to the calculation of scores and the content of phase two. The selection

model, however, is the same and the main implications for our study is described

under selection interviews (section 5.2.1).

5.1.3 Sample and procedures

Data in 2016 was collected during the winter selection. The sample consists of

405 candidates, including data regarding sex, age, divergent thinking and admission

status. Of these 405 candidates, 86.9% (N=352) undertook personality tests, and only

77.5% (N=314) were interviewed. Inclusion in the 2016 study is explained in Figure

3 in appendix 1. The response rate was found to be 77.5% (N=314) and 22.5%

(N=91) of the candidates were considered non-responses. The procedures for the

administration of tests were similar to those described in section 4.1.3. During the

administration of tests some candidates had questions concerning the meaning of

words in the personality test. These were words that are not commonly used in

everyday language, e.g. “unprecedented”, which were then explained with more

common synonyms.


35

5.1.4 Literature

Literature search strategy was the same as for study one (section 4.1.4).

5.1.5 Ethics

All candidates in this study also received written and verbal information about

the study, and were informed that neither participation or performance would have

any influence on admission. The study was performed in line with the Norwegian

National Research Ethics Committees guidelines (NESH, 2016). The candidates were

given time to read through the information regarding the study and ask questions

before they agreed/not agreed to participate. The written information included:

purpose of study, procedures for storage, anonymity and destruction of data, follow

up studies, premises for informed consent and contact information to the researchers

responsible (see appendix 7). The study was approved by Norwegian Centre for

Research Data (NSD) (see appendix 8), and was part of a larger research project led

by the Norwegian Defence College, and thereafter approved as part of our project. All

data was completely anonymous so that no personal information was known to us.

5.2 Measurements

The exact same measurements where applied for study two as those for study

one, described in section 4.2.

5.2.1 The selection interview

Changes in the selection process between the two studies included differences

in scoring method used for interviews. The scale of the interview ratings was changed

to 1-9 points, where 1 indicated failure, 2 indicated lowest possible pass score and 9

indicated high leadership potential. The interview ratings scale contained 27 possible

scores. As in study one, however, the ratings still indicated leadership prognosis.

5.3 Reliability

The internal consistency using Cronbach’s alpha for divergent thinking

(α=.893) and all sub-scores are presented in Table 13.

Table 13. Means, standard deviation, correlations and

reliability for divergent thinking (N=405)

Mean(±SD)

1

2

3

4

1. Fluency

r

7.15(±2.98)

(.788)

2. Flexibility

r

5.65(±1.66) .887** (.677)

3. Originality

r

1.65(±1.62) .834** .707** (.670)

4. Total DT

r

14.45(±5.90) .982** .923** .894** (.893)



36

Overall, these were found to be somewhat questionable, to satisfactory (Field,

2013), ranging from α=.670 to .788. The internal consistency for the two tasks was

estimated to be α=.861 for task 1, and α=.879 for task 2 (Table 14). Internal

consistency was also measured for the six facets forming the Openness factor and

estimated to be α=.650. The internal consistency for each Openness facet ranged from

α=.634 to .728 (Table C in appendix 5). Internal consistency for facets forming the

Extroversion factor was found to be α=.788 (Table D in appendix 5). Reliability for

interview ratings is accounted for in section 4.3.

5.3.1 Interrater reliability

The intraclass correlation coefficient (ICC) was applied in line with section

4.3.1. The ICC among our flexibility ratings on each of the candidates were found to

be ICC=.879, and is presented in Table 15 along with means, standard deviations, and

Cronbach’s alpha.

5.4 Validity

Due to the cross sectional design of this study the external validity has been

emphasised similar to that of study one (see section 4.4). As in study one, the number

of non-responses was relatively low 22.5% (N=91) and so the impact of these non-

responses is likely to have low influence on the external validity of the study.

5.5 Data analyses

The same procedures for data analyses were performed as described for study

one in section 4.5.

Table 14. Means, standard deviation, correlations and

reliability for task 1 and 2 (N=405)

Mean(±SD)

1

2

3

1. DT total task 1

r

14.45(±6.09)

(.861)

2. DT total task 2

r

14.44(±6.95) .640** (.879)

3. DT total task 1-2

r

28.89(±11.81) .892** .918** (.893)


Table 15. Intraclass correlations coefficient and Cronbach’s

alpha for flexibility scores (N=405)

Mean(±SD)

1

2

3


r

5.62(±1.65)

(.671)


r

5.67(±1.71) .960** (.657)

3. Flexibility Total

r

5.65(±1.66) .990** .990** (.879)

** p<.01.


37

In order to test hypothesis 5 and 6 correlation analyses were performed to

explore covariation between continuous variables. To test hypothesis 4 and 7

univariate linear regressions were fitted in order to evaluate the relations of different

variables to interview ratings. Interview ratings in this study met the assumption of

linearity of the logits in logistic regression and was thus treated as a continuous

variable throughout all analyses. A multiple linear regression model was then fitted

for interview ratings, controlling for age and sex. All linear regression models were

carefully examined with respect to criteria for linear regression (i.e. linearity,

homoscedasticity, multicollinearity, normally distributed residuals) (Field, 2013).

Standardised regression coefficients are reported in β̂ (sample estimates), rather

than β (population estimates). Similar to study one, hypothesis 1 and 2 were tested by

fitting univariate binary logistic regression models with the outcome variable

admission (0=no admission, 1=admission), before a multiple model was fitted.

Furthermore, the indirect effects of divergent thinking and Openness on

admission through interview ratings were investigated, and mediation and moderation

analyses were thus performed.

5.6 Results

5.6.1 Sample characteristics

The descriptive statistics is presented in Table 16. The total number of

participants in the study was 405, which equals the total number of candidate

attendance on the first day of the selection process. In this sample 15.8% (N=64) were

women and 84.2% (N=341) were men. Amongst the candidates, 34.1% (N=138) were

admitted, of which 14.5% (N=20) were women and 85.5% (N=118) were men.

Table 16. Descriptive statistics over sample characteristics and selection variables

Sample

characteristics

Selection variables

Variables

Sex

Women N(%) Men N(%)

Age

Mean(±SD)$***

Divergent thinking

Mean(±SD)!

Openness to

experience

Mean(±SD)§

Interview rating

Mean(±SD)¤*

Total

(N=405)

64(15.8) 341(84.2)

21.11(±2.58)

14.44(±5.90)

122.71(±14.65)

5.95(±1.57)

Admission

(N=138)

20(14.5) 118(85.5)

20.21(±1.76)

14.16(±4.66)

123.92(±14.08)

6.17(±1.44)

No Admission

(N=267)

44(16.5) 223(83.5)

21.58(±2.82)

14.60(±6.46)

122.09(±14.94)

5.78(±1.65)

*** p<.001. *p<.05. $=admission (N=137), no admission (N=265). !=admission (N= 138), no admission (N=267). §=admission (N=121), no admission (N=231), ¤=admission (N=136), no admission (N=178).


38

The average age of the candidates was 21.11 (±2.58) years, although the

average age was significantly lower (20.21±1.76) for those admitted, compared to

those not admitted (21.58±2.82) (p<.001). The variable age contained three outliers,

detected as extreme values on Mahalanobis distance, and was thus removed from the

dataset. The outliers were age values of 41, 38 and 37 years, with only one

observation in each group. Only minor insignificant changes were observed after the

outliers were removed. The average scores on divergent thinking tests were 14.44

(±5.90) points, and no significant differences were found between candidates

admitted and not admitted. Divergent thinking scores ranged from 4.00 to 57.50.

Openness scores were on average 122.71(±14.65) points, and ranged from

86.00 to 166.00. No differences between the groups admitted or not admitted were

found. The candidates scored on average 5.95(±1.57) on interview ratings, but there

was a significant difference between those admitted who on average scored

6.17(±1.44), and those not admitted with average scores of 5.78(±1.65) (p<.05).

5.6.2 Correlations

Divergent thinking was found to be positively correlated with Openness

(r=.094, p=.077) (Table 17). Openness was found to be positively and significantly

correlated with interview ratings (rρ=.130, p<.05), and originality (r=.113, p<.05).

Divergent thinking was also found to be positively and significantly correlated with

Extroversion (r=.108, p<.05), including flexibility (r=.122, p<.05), and in fact more

correlated to divergent thinking than was Openness (see Table E in appendix 5).

5.6.3 Relationships: divergent thinking, Openness, and interview ratings

The results indicated (Table 18) that women achieved significantly, and slightly

higher interview ratings (β̂=0.11, p=.047) compared to men. Openness to experience

was also found to be significantly (when using two decimals) associated with

Table 17. Means, standard deviations and correlations for all variables

N

Mean(±SD)

1

2

3

4

5

6

7

8

1. Fluency

r

405

7.15(±2.98)

(.788)

2. Flexibility

r

405 5.65(±1.66) .887** (.677)

3. Originality

r

405 1.65(±1.62) .834** .707** (.670)

4. Total DT

r

405 14.45(±5.90) .982** .923** .894** (.893)

5. Openness

r

352 122.72(±14.65) .069 .101 .113* .094 (.650)

6. Interview rating

ρ

314 5.95(±1.57) .057 .070 .021 .060 .130* -

7. Admission

ρ

405 .020 .013 -.012 .015 .057 .120* -

8. Sex

ρ

405

.049 .082 .020 .054 .031 .108 -.026 -

** p<.01. * p<0.05. Admission 0=no admission; 1=admission, Sex 0=men; 1=women. r=Pearson’s, ρ=Spearman’s. Estimated

Cronbach’s alpha in brackets on the diagonal.


39

interview ratings (β̂=0.12, p=.053), whereas divergent thinking (p=.820) and age

(p=.599) were found to have no relationships to interview ratings.

The significant variables Openness to experience and sex were included in the

multiple model, in which age was controlled for. The multiple model (adjusted R2:

1.9%, p=.043) (Table 19) indicated that sex had the highest standardised coefficient

and was thus the most important covariate related to interview ratings (p=.025).

Women scored slightly higher (β̂=0.14, p=.025) on interview ratings compared

to men. Openness was found to have less importance, and a lower standardised

coefficient (β̂=.10, p=.109), whereas age was found to have no relationship to

interview ratings (p=.969). Diagnostics of the model showed that autocorrelation

measures Durbin Watson test, gave relatively low results (.57). Two cases were found

to be outside the calculated cut-off values for leverage (k+1)/n =3+1/187=.014*3

=.042), and considered outliers, and thus removed. No changes were observed in the

model after the removal of outliers. The multiple regression was performed forward

and backward, and the model was found to be stable in that the model estimates were

constant and no changes in the alpha level was detected. Cooks distance values were

all <1.00, and all values of DfBetas were found to be within the range ±1.00. No

standardised residuals had values >±2.00. The unstandardised residuals were

normally distributed, and plots of unstandardised predicted values and absolute values

Table 18. Univariate linear regression models, dependent variable

interview ratings

Variables

�̂�

95% CI

P

Divergent thinking#

-.01

-.03-.03

.820

Openness to experience§*

Sex#*

Women Men (ref)

.12

.11 -

.00-.02

.01-1.06 -

.053

.047 -

Age¤ -.04 -.09-.05 .599

*p<.05. §=(N=270). ¤=(N=311). #=(N=314).

Table 19. Multiple linear regression, dependent variable interview

rating (Adjusted R2: 1.9%, p=.043) (N=267)

Variables

�̂�

95% CI

P

Openness to experience

.102

-.00-.22

.109

Sex

Women Men (ref)

.141 -

.08-1.19 -

.025 -

Age -.003 -.07-.07 .969

Notes: Footnotes indicate standardised Beta-values, where 1=.64, 2=.01, 3=-.00


40

of unstandardised residuals were inspected with respect to homoscedasticity.

Measures of multicollinearity were examined (VIF mean=1.01, and Tolerance

mean=.99) and found acceptable. Eigenvalue, condition index and residual plots were

inspected and found to be satisfactory. Mahalanobis distance was found to be 14.42.

5.6.4 Relationships: divergent thinking, Openness, interview ratings and

admission

The results indicated (Table 20) that both interview ratings and age were

significantly associated with admission. Scoring high on interview ratings increased

the odds of being admitted compared to those not admitted, and for one additional

point on interview ratings the odds of being admitted was increased by 18%

(OR=1.18, p<.001). Age was also strongly associated with admission and for one

additional year of age the odds of being admitted was lowered with 24% (OR=.76,

p<.001). Openness (p=.267), divergent thinking (p=.477), and sex (p=.604) were

found to have insignificant relationships to admission.

In the multiple model (χ2: 32.12, p<.001) (Table 21) the univariate significant

variables interview ratings and age were included, in addition to the control variable

sex. The results indicated similarly as in the univariate models that interview ratings

was significantly (p=.020) associated with admission, when controlling for sex and

age. For one additional point on interview ratings the odds of being admitted

increased by 21% (OR=1.21, p=.020) compared to those not admitted. Age was also

significantly associated with admission in the multiple model, and for one additional

year of age the odds of being admitted decreased with 24% (OR=.76, p<.001). The

variable sex was found to have an insignificant relationship to admission (p=.802).

The PCA requirements for the model were not met, in that PCC was 60.8%,

whereas PCA was calculated to be (176/311)2+(135/311)2=0.32+0.188 =0.507=

50.7%. 1.25*50.7%= 63.5%. Cox and Snell was found to be 7.4%, and Nagelkerke R2


variable admission (0=no admission, 1=admission)

Variables

OR

95% CI

P

Divergent thinking#

.99

.95-1.02

.477

Openness to experience§

Interview rating ¤*

Sex#

Women Men (ref)

1.01

1.18

1.16 -

.99-1.02

1.02-1.37

.66-2.07 -

.267

.028

.604 -

Age$*** .76 .67-.85 <.001

***p<.001. *p<.05. #= (N=405). §=(N=352). ¤=(N=314). $=(N=402).


41

10.3%. Cooks distance values were all <1.00, and all values of DfBeta were found to

be within the range ±1.00. No standardised residuals had values >±2.00. Leverage

values were calculated and no extreme values were detected. Measures of

multicollinearity were examined by using linear regression (VIF mean=1.02, and

Tolerance mean=.98) and found acceptable. Eigenvalue, condition index and residual

plots were inspected and found to be satisfactory.

5.6.5 Moderation and mediation analyses

Moderation analyses were also performed in line with previous arguments and

procedures (section 4.6.5). The results indicated (Table 22) that the relationship

between divergent thinking and admission was not moderated by interview ratings, as

indicated by the insignificant interaction term (B=-.01, 95% CI -.02-.02, p=.820).

Similarly, the relationship between Openness to experience and admission was

not moderated by interview ratings, as indicated by the insignificant interaction term

(B=-.01, 95% CI -.02-.01, p=.401) (Table 23). No significant interaction terms were

found and we could therefore conclude that no moderation was present.


admission (0=no admission, 1=admission) (χ2: 32.115(3) p<.001) (N=311)

Variables

OR

95% CI

P

Interview rating*

1.21

1.03-1.41

.020

Sex

Women

Men (ref)

.91

-

.45-1.84

-

.802

-

Age*** .76 .67-.86 <.001

***p<.001. *p<.05.

Table 22. Linear model of predictors of admission (0=no admission, 1=admission) (N=314)

Variables

B

SE B

Z

95% CI

P

Interview rating

.17

.08

2.19

.02-.32

.028

Divergent thinking

(centred)

-.03 .02 -1.31 -.06-.01

.191

Divergent thinking x

interview rating

-.01

.01 -.23 -.02-.02 .820

Table 23. Linear model of predictors of admission (0=no admission, 1=admission) (N=270)

Variables

B

SE B

Z

CI

P

Interview rating

.21

.09

2.49

.05-.38

.013

Openness to

experience (centred)

.00 .01 .45 -.01-.02

.652

Openness x interview

rating

-.01

.01 -.84 -.02-.01 .401


42

Mediation analyses were also performed in line with previous arguments and

procedures (4.6.5). Here, an insignificant indirect effect of divergent thinking on

admission through interview ratings was found (B=-.00, BCa CI -.00-.01), but there

was no direct effect of divergent thinking on admission (B=-.03, p=.199) (see

appendix 6). Openness, on the other hand, was found to have a significant indirect

effect on admission through interview ratings (B=.00, BCa CI .00-.01), but there was

no direct significant effect of Openness on admission (B=.00, p=.695). In the previous

univariate analyses there was no relationship between divergent thinking or

Openness, and admission, and no changes were found in the mediation analyses. So

even if a significant indirect relationship is present between Openness and admission,

we cannot conclude that mediation is present as there was no direct relationship to

mediate in the first place. Mediation was also tested by assessing confidence intervals

of the indirect effect. Both mediation analyses indicated that the confidence intervals

contained zero. Consequently, we concluded that no mediation was present.


The results of the correlation analyses indicated that the correlation between

divergent thinking, including flexibility and fluency was positive and in fact higher

with Extroversion, than with Openness to experience. Originality, however, was

found to have a higher positive correlation with Openness. Consequently, no support

was found for hypothesis 5. The correlation analyses also indicated that divergent

thinking was positively but not significantly correlated with Openness, and so

hypothesis 6 was not supported.

Moreover, the results indicated that neither Openness or divergent thinking had

a positive and significant relationship to interview ratings when age and sex were

controlled for. Hence hypotheses 7 and 4 were not supported. The relationship

between interview ratings and admission into NCO training was also assessed, and

the results indicated that the relationship between interview ratings and admission

was positive and significant when controlled for age and sex. Consequently, we found

support for hypothesis 2. On the contrary, no support was found for the relationship

between divergent thinking scores and admission into NCO training, and so

hypothesis 1 was not supported. In addition, mediation and moderation models were

fitted and no support were found for either a mediating or moderating effect of

interview ratings on the relationship between divergent thinking or Openness to

experience, and admission.

Further discussion of the results and implications of these will be covered under

general discussion (section 7.0).


43

6.0 Study 3

The aim of this study was to compare the two previous samples and to gain a

broader, overall understanding of the NCO selection processes. Since we were

interested in investigating differences between the two samples and the general

selection process, we did not aim to test any hypotheses directly in this study.

Because study two is a close replication of study one, the circumstances and statistical

assumptions are fulfilled, and thus enables us to perform general and comparative

analyses of the two selection processes. This study builds on the methods, samples

and data from the two previous studies. To avoid repetition, we use cross referencing.

6.1 Method

The study builds on two cross-sectional studies, where all data used has been

collected in cooperation with the Norwegian Defence College. It builds exclusively

on data from study one and two, and no additional or new data has been added. The

method and design for study one and two also forms the basis for this study, and is

described in section 4.1 and 5.1.

6.1.1 Setting

The selection model is the same as for the previous studies, but as described in

study two, there were some changes with regards to the calculation of scores and the

content of phase two in the NCO selection process. Due to these differences, only

variables that have been identically scored in the previous studies are included in this

study. The main implications of these differences are described under section 6.2.

6.1.2 Sample and procedure

The data consists of two samples, where the first part was collected during the

summer selection in 2007 consisting of 1375 candidates. The second part of the data

was collected in 2016 during the winter selection consisting of 405 candidates. The

total sample size was 1780, and included data regarding sex, divergent thinking,

Openness and admission status. Of these 1780 candidates, data regarding sex and

admission was collected from the total sample with no missing values. 93.6%

(N=1666) of the candidates completed the divergent thinking test and 88.6%

(N=1577) of the candidates undertook the personality test. In total 86.5% (N=1539)

of the candidates participated and completed all tests. Only 13.5% (N=241) of the

candidates did not complete the tests, and because no data on them was recorded, they

were considered non-responses. Since age was only available in study two, it could

not be included as a variable in this study. For full description of the samples and

procedures used, see section 4.1.3 and 5.1.3.


44

6.2 Measurements

This study is based on the same measurements as described in section 4.2.

Because changes were made in the selection process between study one and two with

regards to the scale of interview ratings (section 5.2.1), these could not be included in

this study.

6.3 Reliability and validity

Due to the cross sectional design of study one and two, the external validity has

been emphasised. Since the total number of non-responses in the overall sample was

relatively low 13.5% (N=241), the impact of the non-responses is likely to have low

influence on the external validity of this study. The study also relies upon

measurements with various degrees of validity and will have the same implications as

those described in section 4.4. The estimated reliabilities for divergent thinking tests

and NEO PI-R will also be the same as for study one and two (section 4.3 and 5.3).

6.4 Data analyses

The same procedures for data analyses were performed as described in 4.5 and

5.5. No new correlation analyses were performed in this study. First descriptive

analyses were performed in order to compare the samples with respect to sample

characteristics. Interview ratings were not included in the descriptive analyses or in

the subsequent analyses due to the different scales that were used, i.e. study one (0.5-

6.0) and study two (1-9). Year of selection was added as a control variable and was

created as a dummy variable, where candidates from study one was coded 0 and

candidates from study two was coded 1. Candidates from study one was used as

reference group due to the considerably larger sample size.

As in the previous studies, univariate binary logistic regression models were

fitted for the outcome variable admission (0=no admission, 1=admission), before a

multiple model was fitted. Based on the lack of significant findings in the previous

mediation and moderation analyses (4.6.5 and 5.6.5), these analyses were not

performed.

6.5 Results

6.5.1 Descriptive statistics

The descriptive statistics for the study is presented for comparison in Table 24.

The total number of candidates included in this study was 1780. The percentage share

of men and women were approximately the same as for study one and two.

Significant differences were found between the two samples with respect to average


45

scores on divergent thinking tests, Openness and admission percentage. For divergent

thinking the average scores were significantly higher in study one (17.56±6.79),

compared to study two (14.45±5.90, p<.001). The average scores on Openness, on the

other hand, were significantly lower in study one (107.11±16.29 points), compared to

average scores in study two (122.09±14.94 points, p<.001). There were also

significant differences between the admission of candidates in the studies, where

significantly more candidates were admitted in study one (N=661), compared to study

two (N=138) (p<.001).

6.5.2 Relationships: divergent thinking, Openness and admission

The results indicated (Table 25) that the odds of being admitted were

significantly lower for candidates in study two compared to candidates in study one.

Participation in the study two selection decreased the odds of being admitted by

43% (OR=.57, p<.001). Neither divergent thinking (p=.096), Openness (p=.856), or

sex (p=.311) was significantly associated with admission in either of the two studies.

The variable divergent thinking was found to violate the assumption of linearity of

Table 24. Comparison of selection variables and characteristics variables Study 1 and Study 2

Sample

characteristics

Selection variables

Variables

Sex

Women N(%) Men N(%)

Divergent thinking

Mean(±SD)$***

Openness to

experience

Mean(±SD)§***

Admission***

Admitted N(%) Not admitted N(%)

Total

(N=1780)

271(15.2) 1509(84.8)

16.80(±6.72)

110.60(±17.21)

799(44.9) 981(55.1)

Study 1

(N=1375)

207(15.1) 1168(84.9)

17.56(±4.79)

107.12(±16.30)

661(48.1) 741(41.6)

Study 2

(N=405)

64(15.8) 341(84.2)

14.45(±5.90)

122.09(±14.94)

138(34.1) 267(65.9)

***p<.001. $=Study1(N=1261), Study2(N=405). §=Study1(N=1235), Study2(N=352).


variable admission (0=no admission, 1=admission)

Variables

OR

95% CI

P

Divergent thinking §

1.01

.99-1.03

.096

Openness to experience ¤

Sex #

Women

Men (ref)

Year of selection#***

2016

.99

.87

-

.57

.99-1.01

.67-1.14

-

.44-.70

.856

.311

-

<.001 2007(ref) - - -

***p<.001. §=(N=1666). ¤=(N=1577). #=(N=1780).


46

the logits, and was thus not included in the multiple model, despite a p-value below

the cut-off (p≤0.15).

The multiple model indicated (χ2:26.175, p<.001) (Table 26) that participating

in the 2016 selection significantly decreased the odds of being admitted by 44%

(OR=.56, p<.001), compared to the 2007 selection. Sex was found to be insignificant

in the multiple model (p=.328), and thus of less importance.

The PCA requirements for the model were not met, in that PCC was 55.1%,

whereas PCA was calculated to be (981/ 1780)2 +(799/1780)2 =0.30+0.20=.51

=50%*1.25= 62.5%. Leverage values were calculated and no extreme values were

detected. Cook’s distance values were all <1.00, and all values of DfBeta were found

to be within the range ±1.00. No standardised residual had values >±2.00. Cox and

Snell was found to be 1.5%, and Nagelkerke R2 2.0%. Measures of multicollinearity

were examined by using linear regression (VIF mean=1.00, and Tolerance

mean=1.00) and found acceptable. Eigenvalue, condition index and residual plots

were inspected and found to be satisfactory.


The analyses indicated that there were significant differences between the two

samples with respect to average scores on divergent thinking and Openness.

Candidates in study one scored significantly higher on divergent thinking tests

compared to candidates in study two, whereas candidates in study two scored

significantly higher on Openness compared to candidates in study one. However,

neither divergent thinking or Openness was found to be associated with admission in

the two studies.

The results also indicated a significant association between year of selection

and admission. However, the variable year of selection was included as a control

variable in these analyses, and these significant findings may indicate variations

between the two selections, because study one had more positions available compared

to study two.


admission (0=no admission, 1=admission) (χ2:26.175(2) p<.001) (N=1780)

Variables

OR

95% CI

P

Year of selection***

2016

2007 (ref)

.56

-

.44-.70

-

<.001

-

Sex

Women Men (ref)

.88 -

.67-1.14 -

.328 -

***p<.001


47

7.0 General discussion

Since several studies have indicated that divergent thinking is positively related

to leader performance (e.g. Connelly et al, 2000; Mumford et al, 1998; Vincent et al,

2002), and because NAF are guided by a directive control leadership philosophy –

which highlights the importance of engaging in creative thinking – we proposed that

they should also be interested in selecting those individuals who are likely to do so.

The three studies built on the existing research on divergent thinking onto two

Norwegian military samples in order to investigate whether the NAF are able, as part

of the NCO selection process, to identify those individuals who are likely to engage

in divergent thinking. We were interested in investigating both their ability to identify

these individuals, as well as to investigate whether or not the NAF had been able to

improve their NCO selection process between 2007 and 2016.

7.0.1 Replication Due to time limitations and for practical reasons that NCO

selection only takes place twice a year, we collected data in 2016 prior to our data

analyses. We hypothesised that we would find stronger relationships between

divergent thinking and interview ratings in our replication study. We payed close

attention to replicating the method and procedures as closely as possible, in order to

make our results comparable. The results, however, indicated variations in our main

findings. There might be several reasons for these differences and Bryman and Bell

(2011) point to the fact that replication in cross-sectional design studies may yield

different results due to variations and changes over time in samples, conditions,

organisation and procedures.

The samples in the two studies are quite different with regards to size (study

one (N=1375) and study two (N=405). But both studies had high response rates, and

were considered sufficient for the analyses performed. This may imply that the

sample sizes are not decisive for the differences in estimates (Field, 2013) of the

divergent thinking and Openness scores. The variations in samples of the two studies

can also be relevant (Bryman & Bell, 2011). The samples are similar with respect to

sex distribution in both studies, but age is only available in study two. This may be

considered a limitation since there are few background factors to evaluate the

similarity of the samples, and to control for confounders in the different models.

Other variables that have shown to affect performance on ability tests in previous

studies are anxiety level and level of warmth of the individual (Cooper, 2010). These,

however, were not recorded in either of the studies.

The context in which the testing of divergent thinking took place may be of

relevance for the significant differences in scores between the two samples


48

(Spielberger, 2010). Although the aim of testing was research and clearly stated for

the candidates prior to testing, the general context of the NCO selection process may

have contributed to an increased level of anxiety in the candidates (Cooper, 2010).

Wallach & Kogan (1965) also emphasised that the immediate environment (e.g. room

conditions and instructions) may in fact impede creative thinking. Because the

context of study one is not fully known, it is difficult to compare and evaluate the

context any further.

7.0.2 Reliability When using Cronbach’s alpha to estimate reliability it is

generally suggested that values between .7 to .8 are acceptable, whereas values that

are considerably lower often indicate unreliable scales, and that the measurement is

thus not suitable for measuring the specific construct in the chosen population (Field,

2013). This would imply that some of our reliabilities, such as the Openness construct

in study one (α=.650) and originality in both studies (α1=.689; α2=.670), could thus be

considered questionable. However, Kline (1999) argues that when dealing with

psychological constructs values below .7, can realistically be expected due to the

diversity being measured. It is in fact possible that because the two tasks were quite

different, i.e. one was a line and the other a pattern, the internal consistency between

them is influenced by one of them allowing the candidates to produce more

interpretations, or it is possible that some of the candidates did not entirely follow the

instructions, and so, spent more or less time on either of the two tasks.

This could explain the lower reliability between the tasks, but satisfactory

reliability between the raters reflected in interrater reliability above .8 (ICC1=.884;

ICC2=.879), and on the two tasks collectively (i.e. total divergent thinking = fluency,

flexibility and originality for both tasks) in study one and two (α1= .894; α2=.893), as

well as the tasks independent of each other (i.e. total divergent thinking per task)

(ranging between α=.850 to .879). These reliabilities in turn, seem to indicate that the

scoring manual we used had been appropriately developed and functioned well when

we independently distributed the scores among the candidates.

7.0.3 Correlations In both studies we hypothesised, in line with previous

research (King et al, 1996; McCrae, 1987; Silvia et al, 2008; Walker & Jackson,

2014), that divergent thinking including each sub-scores (fluency, flexibility and

originality) would have a significant, and higher positive correlation with Openness,

than with Extroversion. Taken at face value the results in study one indicated that

Openness and divergent thinking (r=.214) had indeed a higher positive correlation

than Extroversion and divergent thinking (r=.167). Since some previous studies have

found correlations reaching levels of r=.30 to .50 (e.g. McCrae, 1987; Chamorro-


49

Premuzic & Reichenbacher, 2008), we expected our correlations to be similar to

those. The correlations were found to be significant and supporting our hypothesis,

but were slightly lower than expected. In study two, however, the results were more

inconsistent, with a positive but insignificant correlation between Openness and

divergent thinking, and instead indicated that Extroversion had a significant, and

higher positive correlation with divergent thinking (r=.108), and flexibility (r=.122).

Although a few studies in the past have found higher correlations between

divergent thinking and Extroversion (e.g. Furnham & Nederstrom, 2010), the overall

more inconsistent results in the study two sample did raise some concerns. In fact,

when looking closer at the correlations of the facets forming the Openness construct

(Table C in app. 5) it illustrated that there was no correlation (r=.00, p<.001) between

facet 2 and 4. Since NEO PI-R builds on factor analysis (Cooper, 2010) we would

expect to find a correlation similar to those of the other facets for Openness, and

Extroversion in our matrices (between r=.161 to .599). This may well be linked to the

relatively lower reliabilities found for some facets of the Openness construct, as well

its overall reliability (α=.650), which is generally found to be somewhat higher (e.g.

for Openness to experience in the Norwegian version, α=.79) (Martinsen et al, 2005).

Consequently, the relatively low reliability for the Openness construct, the

inconsistent correlations between Openness and divergent thinking, as well as the

irregular correlation between facet O2 and O4 in study two, all add some caution to

our results and interpretations.

7.0.4 Scoring divergent thinking The failure to yield significant correlations

between Openness and divergent thinking (as in study two), however, has not been

completely uncommon, and can often be contributed to the method of assessing

divergent thinking (Batey et al, 2009b). Even though the three sub-scores of divergent

thinking (fluency, flexibility and originality) were found to be highly inter-correlated,

and often are in most studies of divergent thinking, various researches in the past

have in fact indicated that they are not interchangeable (Acar & Runco, 2015; Runco,

2008). So rather than using only one of them, e.g. fluency (which often seems to

dominate divergent thinking scores), this criterion alone would not be as important as

flexibility or originality if we aim to estimate the candidates’ creative potential

(Runco, 2008; Acar & Runco, 2015). This is due to previous research indicating that

when fluency scores have been statistically controlled for, the unique variance of

flexibility and originality scores from divergent thinking tests are actually found

reliable (Runco, 2008). In addition, the validity for the scoring system using the three

sub-scores have been found supported (Runco, 2008).


50

Moreover, given that the candidates were only allowed 4 minutes to complete

each divergent thinking task, it is possible that some would have been disadvantaged

had we not included each sub-scores, for reasons that some individuals are more

likely to focus on producing unique and unusual answers, as opposed to higher

quantity (Batey et al, 2009b). This would naturally decrease fluency, as novel

connections will take longer for individuals to produce. Consequently, we found it

justified to include all three sub-scores despite the somewhat high correlations

between them.

7.0.5 Relationships between divergent thinking, interview rating and

admission We proposed that there would be a positive relationship between interview

ratings and divergent thinking in study one, whereas a significant and positive

relationship between interview ratings and divergent thinking was hypothesised for

study two. For both studies, we proposed a positive relationship between divergent

thinking and admission into NCO training. In study one, the relationship between

divergent thinking and interview ratings could not be evaluated, due to the violation

of the assumption of linearity of the logits, whereas the relationship between

divergent thinking and admission was only tested in the univariate analyses (p=.359).

In study two, we found no relationship between divergent thinking and interview

ratings (p=.820), or divergent thinking and admission (p=.477). However, in study

three there was an interesting finding where candidates in study one, was on average

found to score significantly higher (17.56±4.79, p<.001) on the divergent thinking

test, compared to candidates in study two (14.45±5.90).

The lack of appropriate norm groups of the divergent thinking test makes it

very difficult to evaluate the scores in the two studies with regards to essential

questions, such as what constitutes high or low scores; what the practical relevance is

of a score; and changes in score over time. Previous studies have used this test on e.g.

children (Cheung et al, 2004), or undergraduates (Silvia, 2008), and with different

scoring methods (Runco et al, 1987). To our knowledge, no previously published

studies have used the test on NCO candidates, and any further meaningful assessment

of the scores is therefore limited.

Based on these findings we can answer our research question: What is the

relationship between divergent thinking, interview ratings and admission into non-

commissioned officer training? Neither of the three studies provided support for the

hypothesis that candidates scoring high on divergent thinking tests also performed

well in selection interviews, and were further admitted into NCO training. In addition,

no support was found for an indirect effect of divergent thinking on admission


51

through interview ratings in either of the studies. These findings indicate that

divergent thinking as measured by Wallach & Kogan’s (1965) test, is an ability that is

not evident in the NCO selection process.

As part of directive control leadership, we argued that divergent thinking is an

essential ability for military leaders to possess (e.g. Zaccaro et al, 2015). It is

therefore a particularly interesting finding that divergent thinking is not ‘detectable’

in the interview ratings or admission in study two, when directive control leadership

has in fact been enforced for 21 years. The results of the studies raise several

questions regarding aspects related to the selection process. First, how is the selection

interview designed with respect to detecting divergent thinking abilities in the

candidates? Second, is divergent thinking ability measured in any of the remaining

selection variables not included in these studies? And third, to what extent is the

abilities and characteristics related to directive control actually implemented through

selection criteria in the selection process?

The answers to these questions are beyond the scope of our thesis, but they are

important questions to raise as a result of the lack of support to our hypotheses (study

1: H1, H3; study 2: H1, H2, H4, H6, H7). Since the NCO selection is the entrance

into military leadership within the NAF, and the recruitment into higher leadership

positions is based mainly on internal recruitment, the selection criteria used – and the

admission decisions based on these – are vital, as some admitted NCO candidates will

also be recruited into positions as the NAF’s future military leaders (Rones & Fasting,

2011; Ellingsen et al, 2008). The implications for the selection process based on our

findings are further discussed under implications (section 9.0).

7.0.6 Divergent thinking tests The studies we found as part of our literature

review that had used military samples, measured divergent thinking as part of

complex problem-solving and thus provided their participants with relevant real-life

problems to which they were asked to provide solutions (e.g. Zaccaro et al, 2000;

2015). These participants were also already employed in the military, whereas our

samples were applying to join the military. This naturally relates to the distinction

between creativity as domain-specific vs. creativity as transferable across domains

(Reiter-Palmon et al, 2009). Since the NAF are interested in identifying individuals

with the greatest potential for becoming military leaders, it would perhaps be

reasonable to include measures of divergent thinking that focus on creative problem-

solving relevant for their profession. However, using more domain-specific measures

will also require a certain level of expertise or knowledge (Vincent et al, 2002), which

candidates applying to NCO training may not have. Using divergent thinking tests


52

instead, eliminates the need for expertise and thus makes it more of a cross-domain

measure of such ability. The fact that several researchers have found support for the

validity of divergent thinking tests (e.g. Runco, 2008; Kim, 2008; Guildford, 1965),

also support the use of such measures.

Nevertheless, it is of course possible that somewhat different results would

have been found if we had used other types of divergent thinking tests, or if we would

have scored them differently. Another interesting aspect is that previous studies have

shown that explicit instructions to be creative can in fact increase ideational fluency,

flexibility or originality (Matthew, 2009). This would then support the idea that

telling the candidates before the divergent thinking tests that they should be as

creative as possible, would in theory have generated either more responses in

quantity, number of categories, or novelty (Silvia et al, 2009), and possibly yielded

different results.

7.0.7 Relationship between Openness, interview rating and admission

We proposed that there would be a positive relationship between interview

ratings and Openness to experience in both studies. The results of study one provided

support for the hypothesis that candidates scoring high on Openness also performed

significantly better in the selection interviews (OR=1.02, p<.001). On the contrary,

Openness was not found to be significantly associated with admission (p=.254) in

study one. Study two provided no support for this hypothesis and no significant

relationship was found between Openness and interview ratings (p=.109), or

admission (p=267). Openness was not found to have a significant relationship to

admission (p=.856) in the third study either. There was, however, an interesting

finding that candidates in study two, on average, were found to score significantly

higher on Openness compared to candidates in study one. This is the opposite of the

scores of divergent thinking. There are several reasons for such contradicting

findings, some of which we stated in the beginning of the discussion (section 7.0.1).

In addition, we found no support for an indirect effect of Openness on admission

through interview ratings in either of the two studies. The main findings related to

Openness were similar to those of divergent thinking, in that neither of the two

variables were evident in the admission of candidates.

Although some studies within the leadership literature points to a linear

relationship between personality traits and leadership effectiveness, there are reasons

to believe that this relationship is in fact curvilinear (Yukl, 2013), and moderate

scores may thus be preferred in the selection of leaders (Moldjord et al, 2005), and in

the NCO selection (Vik, 2013). The results in our studies did not indicate that the


53

Openness scores were particularly high, and previous research has found that

individuals scoring low on Openness to experience during high school were more

likely to enter military training after graduation (Jackson et al, 2012). However, since

the study by Jackson et al (2012) was conducted on a German sample and only men

were included in the study, their conclusions may not be directly applicable to our

studies.

Although Openness in a Norwegian context has been found to be important in

military leadership – by supporting the ability to use creative and unconventional

tactics in ambiguous and uncertain environments, and a willingness to try new

approaches – there are also other personality traits that have been found to be

important for increased leadership performance, such as Conscientiousness and

Agreeableness (Johansen et al, 2014). It is clear that several traits are important and

need to be taken into account as part of the selection process. However, since we did

not investigate any other personality traits we cannot make any further conclusions or

assumptions regarding the relationship between these and admission. But for future

research it may be important to include a broader test battery, e.g. include other

personality traits in order to both assess the relationship between these traits and

admission, and to exclude them as cofounders in the fitted models.

Another attempt to explain the weak relationship between Openness and

interview ratings/admission is the ‘creative personality’ that generally scores high on

Openness, for which traits such as low emotional stability and low sociability are also

characteristic (Martinsen, 2011). These, however, may not necessarily be compatible

with other appreciated personality traits for military leaders (Johansen et al, 2014). As

with most military organisations there often exist strong and unique cultures that may

influence both attitudes and motivations that stimulate creative performance

(Matthew, 2009). If some candidates then have the idea that certain traits are less, or

not appreciated (e.g. fantasy and aesthetics), it is possible that this would influence

the way they responded on the NEO PI-R, as well as the divergent thinking test. The

latter because some may possibly fear to be seen as too artistic or original.

This may be related to a culture that still supports an idea of the stereotypical

military leader for which certain attributes are more or less valued (Huntington, 1957;

Rones, 2015), e.g. gregariousness (sociability) and positive emotions part of

Extroversion, which are generally considered more valued traits. This may be

grounded in the notion that military leaders need to demonstrate high sociability and

emotional stability (Martinsen, 2011; Johansen et al, 2014). While the doctrines aim

to change the norms and values of this culture (Høiback, 2011), such as encouraging

the use of creativity within the organisation as part of the directive control leadership


54

(Forsvarsstaben, 2014) it may well be that these deeply rooted ideas are still kept

alive and continue to obstruct an acceptance of the notion of military leaders as

creative.

7.0.8 Relationship between background variables, interview rating and

admission Interview ratings were found to have a positive relationship to admission

in both studies. Study one indicated that low interview ratings significantly decreased

the odds of being admitted (OR=.64, p<.001). Study two, on the other hand, indicated

that candidates scoring high on interview ratings tended to be admitted into NCO

training more often (OR=1.18, p=.028) compared to those not admitted. These

findings support our hypothesis that there is a positive relationship between interview

ratings and admission. Due to the scoring differences between the two studies,

however, the interview ratings could not be evaluated in study three.

Study one and two differed with respect to which covariates that were related to

interview ratings. As previously mentioned, interview ratings were found to be

significantly associated with Openness in study one (OR=1.02, p< 001), whereas

study two found sex to be significantly associated with interview ratings (β̂=0.14,

p=.025), in that women were more likely to achieve higher interview ratings

compared to men. The significant difference between men and women related to

interview ratings in study two may be explained by several reasons, such as women

performing better than men during interviews, or as a consequence of quotas

(Forsvarsdepartementet, 2007).

Age was also found to be significantly associated with admission in study two

(OR=.76, p<.001), but not with interview ratings (p=.969). The results indicated that

older candidates were less likely to be admitted into NCO training. Similar to the sex

differences found with regards to interview ratings, neither of the analyses

investigated the reasons for the observed age differences in admission. Once again,

there may be several reasons for this finding, such as lower performance related to

higher age groups in the sample, or unconscious selection criteria related to age (Ng

& Feldman, 2012).

The results in study three also indicated that year of selection was significantly

associated with admission, in that the odds of being admitted was considerably lower

for candidates in the study two selection (OR=.56, p<.001), compared to study one.

The differences between the two years of selection may be contributed the differences

in available positions in the two selections, which in turn may imply that year of

selection is a confounding factor, since it is not included in the fitted model.


55

Overall, the inconsistent findings in our studies suggest that our replication may

not have succeeded the way we expected. This may well be related to sample,

contingencies and setting (see 7.0.1). It is, however, not uncommon that replication

studies fail to reproduce findings (APA, 2015). In fact, in a recent study where 100

experimental and correlational psychological studies were attempted replication, only

39 of those studies were successfully replicated. In the 39 studies that were replicated,

the effects tended to be smaller and weaker compared to those in the original studies

(APA, 2015). The correlational tests also showed that when original studies had lower

original p-values or larger effect sizes, they were more likely to be replicated (APA,

2015). It is thus possible that even with the best attempts, we were not able to fully

replicate all the important aspects.

8.0 Limitations

Although the studies demonstrate interesting findings with regards to the NCO

selection, it is necessary to interpret the results with some caution. In the following,

the main limitations of our studies will be discussed.

8.1 Research design and material

8.1.1 A cross-sectional design was chosen in order to investigate the

relationship between different covariates and outcome variables. However, as with all

research designs a cross-sectional design has some limitations. First, the design only

allows us to investigate the relationship, or associations, between the variables, but no

causality or causal relationships can be confirmed or disproved (Bryman & Bell,

2011). Based on our studies, we can therefore only draw conclusions regarding the

associations and not the direction of effects or causal inferences (Johnson & Hall,

1988). If an experimental design had been applied, we could have assessed the effect

in a more direct manner, and the internal validity of the studies could also have been

improved by using an experimental design (Bryman & Bell, 2011).

8.1.2 NEO PI-R is a renowned and well-documented measure of personality

(Cooper, 2010; Martinsen et al, 2005). One of its limitations, however, is that it is a

self-report measure and thus open for faking due to e.g. social desirability bias, in

which candidates may have responded on the NEO PI-R in ways they hoped would be

viewed more positively (Cooper, 2010). This is a common type of method bias and

one of the main sources of measurement error, which may consequently threaten the

validity of the conclusions we make about the measures (Podsakoff et al, 2003).

Because there are facets in the Openness construct that measures e.g. fantasy and

aesthetics, it is possible that some of these aspects are perceived by the candidates as


56

somewhat lesser appreciated traits, which then encouraged them to answer

incoherently and/or not completely honest. This could possibly have contributed, at

least partly, to the lower reliabilities found within the Openness construct.

Extroversion, in contrast, includes facets measuring e.g. sociability and positive

emotions, which are generally known to be more valued traits, and so possibly made

candidates more inclined to score higher on these. Moreover, being instructed that

their performance on the tests would matter for admission, could also have influenced

their performance and responses on both tests.

8.1.3 Divergent thinking test and scoring Another important note to make

with regards to divergent thinking and creativity research in general, is the very

nature of the construct and how it is measured. Creativity is one of the most complex

human behaviours, and as part of creativity, divergent thinking in turn becomes a

complex construct to include in research (Matthew, 2009). Since it is considered to be

both spontaneous and novel, it suggests that the candidates’ performance on the

divergent thinking tests under the conditions present during the NCO selection

process, may be inaccurate from their real creative behaviour (Runco & Sakamoto,

1999). This spontaneity, or unpredictability of the construct stands in contrast to

control and hence the accuracy of predictions (Runco & Sakamoto, 1999). For these

reasons, there are researchers that have raised concerns with regards to the validity of

measurements and others enquiring if we actually can measure these abilities (e.g.

Silvia et al, 2009; Runco & Sakamoto, 1999). Assuming that we can measure them,

however, seem to suggest that the use of divergent thinking tests would be most

suitable, as these have received much support in the literature (Kim, 2008).

The scoring methods used, are another important limitation in our thesis, and in

research on divergent thinking in general. Because the tests are open-ended, the

scores will be influenced by interpretations and subjective evaluations. The scoring

procedure is a very time-consuming effort because responses (in our studies over

30.000 in total), must be sorted into alphabetical order and then each compared with

others to find the unusual responses (originality), and then divided into categories in

order to establish flexibility scores. Being not only a very tedious type of effort it also

requires a lot of judgement calls that must be made along the way: e.g. is a “worm”

different from a “caterpillar”; is a “brick path” different from a “brick walk-way” etc.

(see app. 2 for scoring procedures). Some will argue that making such judgements

will require expert raters (Silvia et al, 2009) because the interpretations we make also

influence the scores we distribute. Such as when a word has several meanings and

both raters see different things, while the candidate may have thought about


57

something completely different. Others, on the other hand, argue that expert raters

may confound the scores by focusing too much on their value (Runco & Mraz, 1992).

Moreover, trying to establish whether an answer is original also opens for the

negative aspects of such scores, where inappropriate or bizarre responses may be

assigned a point. All of these aspects of scoring methods may consequently lead to

the validity being threatened, and the data misinterpreted (Runco & Sakamoto, 1999).

Yet, scoring the responses is indeed a necessary evil within divergent thinking

research. We thus worked hard to establish scoring manuals and work together in

order to establish a joint understanding of how to distribute our scores, and our

satisfactory interrater reliability seem to support this.

8.1.4 Sample In study one and two, sex was recorded as a background

variable, whereas age was only recorded in study two. The lack of data regarding age

in study one is a limitation, as age could not be controlled for in the analyses of study

one and three. Age is generally considered to be an important control variable, and

when excluded in e.g. regression models, confounding associations between the

outcome and covariates may arise (Bryman & Bell, 2011). Generally, in all statistical

models age is a central background variable, and this also applies for research

regarding personality. Openness, in particular, has been found to decline in

individuals between 30-49 years and groups over 50 years (Cooper, 2010). This,

however, is a much higher age then the average age of the candidates included in our

studies. Despite this, the lack of age as a control variable may influence the regression

estimates in both study one and study three.

The samples in our studies were also similar with regards to sex distribution

(15.1% women in study one and 15.8% women in study two). Although the

representation of women in the samples is fairly low, they are in fact representative of

the actual sex distribution of candidates in NCO selections (Eide et al, 2014; Rones &

Fasting, 2011). The sample sizes of study one and two were also different due to the

natural differences between the winter and summer selections, in which the latter

have more NCO training positions that are recruited for (Forsvaret, 2016a). Ideally,

the data collection in study two should have taken place during the summer selection

in order to ensure a more similar sample and equal sample size. But for obvious

practical reasons (summer NCO selection is in June-July), this was not possible.

8.1.5 Selection of participants All candidates enrolled into the NCO

selection process in both study one and two were asked to voluntarily participate, and

the samples are therefore not based on random selection. The response rate in both

studies may be considered relatively high (Pallant, 2010): study one 89.1%, and study


58

two 86.9%. However, in cases of non-responses it is important to evaluate if they are

systematic or random (Ringdal, 2001). In the studies, the lack of responses was

mainly caused by unavailability of the candidates due to tight selection schedules, in

addition to a few candidates who refused to answer or withdrew during the study. In

study two, only one candidate withdrew, whereas data regarding withdrawal in study

one was not recorded. Due to a combination of reasons for non-responses, there are

no indication of a systematic pattern with respect to sex or age of the candidates that

did not participate in the studies. This is important with regards to data quality

(Bryman & Bell, 2011). Nevertheless, the lack of background data regarding the non-

responses in both studies is a limitation, because we are not able to investigate

potentially meaningful differences in, e.g. age and sex between responses and non-

responses. Since reasons for non-responses were not recorded, they could not be

examined any further.

8.1.6 Generalisation The findings in the studies apply to NCO selection and

their candidates, and generalisability beyond this context and population may be

fairly limited. Findings from the studies should also be treated with caution if applied

to selection processes at higher levels of military leadership education, because

additional requirements for those candidates may be more important in these selection

processes (Forsvaret, 2016c). Some cautions should also be taken if findings are to be

applied to other NCO selection programmes part of other nations’ Armed Forces, due

to e.g. national cultural differences (Bryman & Bell, 2011), and variations in the

military profession.

8.2 Setting

Another important limitation is the fact that we were not part of the data

collection in study one, or part of any of the selection interviews in either study one

or two. Although the reliability of these interviews have been estimated to be closer

to those of structured interviews (.84), we will never know exactly what questions are

asked, or which specific attributes and behaviours they look for (besides the five

leadership criteria in section 3.3) during these interviews. Even with interview guides

present, the very nature of semi-structured interviews leave room for both error and

interpretations by the interviewers which may influence our results (Schmidt &

Hunter, 1998). As the candidates of the NCO selection are highly motivated for

admission into NCO training (Rones & Fasting, 2011), it is possible that candidates

during the selection interviews, due to social desirability may present themselves in a

more favourable light, regardless of their true feelings about an issue or topic


59

(Podsakoff et al, 2003). Neither the interview guide or data regarding inter-rater

reliability were available to us in any of the studies, and could not be evaluated.

The scoring of the interviews also changed between the two studies, which

made them inadequate for us to compare in study three. Not being part of the data

collection in study one also affects our inability to know exactly what was said or

done during the divergent thinking and personality tests. This can make the

comparison between the samples difficult and may reduce both the reliability and

validity of our studies. There seems to be more overall elaborative responses in study

one, which could be a result of the data collection, but we can only speculate about

the reason for these differences. It does, however, illustrate the importance of being

involved in the research process to be able to properly discuss how it may affect our

results and the conclusions we draw.

8.3 Statistical analyses

8.3.1 Interview ratings In order to perform the statistical analyses required to

test the proposed hypotheses, the variable interview ratings had to be recoded in study

one. The ordinal variable interview ratings did not meet the assumption of linearity of

the logits and several statistical solutions were unsuccessfully fitted (section 4.5). The

interview ratings variable was therefore recoded into a dummy variable. However,

dummy coding may result in a reduction of data, and so some of the variation in the

data may have been reduced (Hair, 2010). Re-coding an ordinal variable into a

dummy variable may also cause less precise estimates, which should be taken into

account when results are interpreted.

8.3.2 Assumptions As previously argued, linearity of the logits is an essential

assumption in logistic regression (section 4.5). Because the divergent thinking

variable did not meet this assumption we could not include it in two of the multiple

models, regardless of satisfactory significance level in the univariate models (Field,

2013). Since the divergent thinking variable could not be included in the two multiple

models, the opportunity to evaluate several associations related to divergent thinking

were reduced. Being our main construct obviously makes this an important limitation

to our studies.

8.3.3 PCA requirements The PCA requirements were not fulfilled in any of

the multiple binary logistic regression models. When a calculated PCA value for a

multiple model is higher than the given PCC value, it indicates that the model does

not satisfactorily explain the associations in the model, which makes it less useful

(White, 2013). Though the variables in the model may still be significant and odds

ratio still be relevant (White, 2013). The lack of fulfilled PCA requirements in the


60

models of interview ratings in study one and admission in both studies, however, may

suggest that the models are not optimally fitted. Nonetheless, our primary aim was to

investigate associations, and the lack of a satisfactory PCA may thus be of less

importance in this context.

8.3.4 Excluded variables In addition to the selection interviews, high school

grades and officer ratings from the second phase are important components of the

final admission decision (Gimsø, 2014). It is a limitation that high school grades and

officer ratings were not included in the studies, because these variables may

potentially have contributed to explaining additional variance in the main outcome

variable admission. The two variables were not included due to differences in their

calculation, which was based on the branches of application. Because of the

inconsistencies in the evaluation of candidates they could not be directly compared,

and was thus excluded in all of the studies.

9.0 Practical and theoretical implications

Our two studies add to the previous literature on divergent thinking by using

divergent thinking tests in a military selection context, since this has to the best of our

knowledge not been done before, at least not in a Norwegian context. It also

contributes to the theory and research on the relationship between personality and

divergent thinking. With regards to practical implications, we realise that making

changes to the recruitment and selection system would require overcoming several

obstacles, as the existing systems are generally well-entrenched (Rumsey, 2014).

Proposing changes to the selection process would thus require much evidence of its

benefits and effectiveness, as well as to demonstrate feasibility (Rumsey, 2014).

Although we did not find the relationship we hypothesised between divergent

thinking, interview ratings and admission, there is much research to support the

importance of divergent thinking in military leaders. Due to the NAF’s closed

personnel systems; the directive control leadership philosophy necessitating creative

thinking; and because military officers higher on divergent thinking are also more

likely to continue with their military service for longer periods of time (Zaccaro et al,

2015) – suggest that being able to identify these individuals should be an objective.

While cognitive ability is often necessary for completing the academic

requirements of the NCO training programmes, it is undoubtedly so that their

effectiveness as military leaders will also be affected by their personality

(McCormack & Mellor, 2002). Not only has Openness to experience been found to

predict leader effectiveness (Judge et al, 2002), but it also facilitates both learning and

adaptability (Johansen et al, 2014), and supports the use of divergent thinking


61

(Mumford & Connelly, 1992), all of which are valuable assets for NCOs in training.

This would thus support the suggestion that a continuous use of NEO PI-R, or other

Big Five personality tests by NAF in their selection processes (Johansen et al, 2014),

could be recommended. It is possible that the use of these personality tests could help

the NAF to identify those individuals likely to complete their training and to engage

in divergent thinking. The use of personality tests may also be relevant for higher

education within the NAF, since higher levels of leadership are more likely to engage

in problem-solving in which divergent thinking will be necessary (Zaccaro, 2014).

Another interesting aspect with regards to divergent thinking is that it in

contrast to personality and intelligence, is in fact malleable as a result of continuous

and long-term training and developmental activities (Zaccaro et al, 2015). So rather

than changing the selection process, it may thus be possible that focusing on complex

problem-solving using tools that facilitate divergent thinking as part of the NCO

training, could in fact enhance the candidates’ capacities to solve problems in future

operational environments (Hansen, 2013). Certain alterations could also be made to

the interview procedures, such as looking for certain aspects linked to traits found

among candidates scoring high on Openness, or by including hypothetical problems

(relevant for their profession) to solve. Problem-solving is part of the second phase

during the NCO selection process, but it is possible that many of the other leadership

qualities wanted are placed more attention to during the officer’s evaluations (Rones

& Fasting, 2011). Hence, changing the procedures of the interviews and adding ways

to identify individuals high on Openness and are likely to engage in divergent

thinking, could be important implications to focus on.

10.0 Future research

The inconsistent results between study one and two suggest that more research

is needed in order to establish whether or not there is a relationship between divergent

thinking and the outcome variables interview ratings and admission. It would be

interesting to see if the same type of study could be performed by including a

different type of divergent thinking test, or tests more directed towards problem-

solving relevant for the military profession. The latter would require more expertise

than divergent thinking tests, but the use of another type of test could possibly yield

other results. The fact that divergent thinking is malleable makes research testing

divergent thinking skills prior to admission into the NAF, and after training/education

is completed, rather interesting. Because our results were inconsistent with regards to

the relationship between Openness/divergent thinking and interview ratings, it would

seem to indicate that more research should be done on how to identify Openness and


62

divergent thinking in NCO candidates. Since Openness to experience, as a personality

trait on its own, contributes to both adaptability and learning, would seem to suggest

that identifying these individuals is in fact important. To use Openness as a proxy for

divergent thinking, on the other hand, would require more research to establish such

connection.

11.0 Conclusion

Military leaders may not often be described as creative, but much research now

points to the importance of divergent thinking for military leaders to be effective.

Guided by directive control leadership, the NAF now encourages creative thinking at

all levels of the organisation. Therefore, we wanted to investigate whether or not the

selection interviews conducted during the NCO selection process were able to

identify those individuals who are likely to engage in divergent thinking. We were

also interested in investigating whether they had been able to improve their ability to

identify these individuals between the years of 2007 and 2016, and thus attempted a

close replication study. Although our results were found to be inconsistent between

study one and two, and in fact indicated that divergent thinking is not evident as part

of this process, Openness to experience was found to have a significant relationship to

interview ratings in study one.

As an important personality trait in its own right, being both related to

divergent thinking and has been found to predict leadership effectiveness in previous

research, would seem to support the use of Big Five personality tests as part of future

NCO selection processes. Since the results indicated that divergent thinking was not

evident in their current selection interviews, we offered some suggestions on how to

possibly improve their ability to identify these individuals, such as probing divergent

thinking abilities through problem-solving during the interviews. With the possibility

that the use of another type of divergent thinking test could have yielded different

results, we also suggested that future research should focus on using another type of

test. In the least, our studies provide a springboard into further investigation of

divergent thinking as part of military leadership in a Norwegian context. Indeed, the

inconsistent results of our studies seem to indicate that more research is needed to

establish whether or not divergent thinking is in fact evident in the selection process

of non-commissioned officers into the Norwegian Armed Forces.


63

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74

13.0 Appendices

Appendix 1 – Inclusion and exclusion: Figure 2 and 3

Appendix 2 – Divergent thinking test

Appendix 3 – Literature search

Appendix 4 – Scoring manual

Appendix 5 – Correlation matrices (study one and two)

Appendix 6 – Mediation analyses (study one and two)

Appendix 7 – Information to candidates for study two

Appendix 8 – NSD approval for study two

Appendix 1

Inclusion and exclusion of candidates in study one and two

Study one

Study two

Hedda Lærum Jacobsen

Appendix 2




Appendix 3

The following search-matrices display the different searches conducted and the number of hits

in each database (PsycI= PscykINFO, PyscA= PsyckARTICLES, BSC= Business Source

Complete, SP= Sage Premier).

All search terms

ID Search terms PsycI PsycA BSC SP 1 Divergent thinking 1835 113 214 1432

2 Creativity 31396 1876 38972 52607

3 Openness to experience 2910 249 520 1636

4 Fluency 18065 720 1148 12610

5 Flexibility 20704 869 53936 83868

6 Originality 15634 128 33442 12744

7 Selection interview 812 59 423 310

8 Interview score 1352 88 84 60

9 Interview ratings 3030 218 204 95

10 Officer selection 220 21 2394 139

11 Military selection 186 31 114 28

12 Non-commissioned officer 48 - 90 69

13 Military leadership training 24 3 22 8

14 Military leadership 529 65 1008 73

15 Officer candidate school 55 11 29 64

Combinations of search terms within each category

ID Search terms PsycI PsycA BSC SP 16 Divergent thinking AND creativity 1161 77 106 137

17 Divergent thinking AND openness

to experience

31 2 3 37

18 Divergent thinking AND fluency 292 21 14 23

19 Divergent thinking AND flexibility 214 6 16 61

20 Divergent thinking AND originality 236 12 15 38

21 Creativity AND openness to

experience

231 32 25 158

22 Divergent thinking AND fluency

AND flexibility

137 4 7 19

23 Divergent thinking AND fluency

AND flexibility AND originality

106 3 3 14

24 Creativity AND fluency AND

flexibility AND originality

358 11 11 25

25 Selection interview AND interview

score

35 3 9 2

26 Selection interview AND interview

ratings

70 8 114 28

27 Selection interview OR interview

ratings

3772 269 606 100

28 Interview score OR interview

ratings

4772 292 277 12

29 Officer selection AND non-

commissioned officer

4 - 3 -

30 Officer selection AND military

leadership training

- - - -

31 Non-commissioned officer AND

military leadership training

1 - - -

32 Officer selection AND military

leadership

7 4 3 1

33 Non-commissioned officer AND

Military selection

- - - -

Combinations of search terms between categories

ID Search terms PsycI PsycA BSC SP 34 Divergent thinking AND selection

interview

- - - -

35 Divergent thinking AND non-


- - - -

36 Selection interview AND non-


2 - - -

37 Divergent thinking AND officer

selection OR military selection

186 31 114 3

38 Divergent thinking AND interview

ratings

2 - - -

39 Divergent thinking AND interview

score

1 - - -

40 Divergent thinking AND military

leadership

- - - 1

41 Creativity AND military leadership 3 - - 15

42 Creativity AND interview score OR

interview ratings

3040 220 206 22

43 Creativity AND officer selection

OR military selection

187 31 118 4

44 Creativity AND non-commissioned

officer

- - - 1

45 Creativity AND selection interview 9 3 2 20

46 Creativity AND officer selection

OR non-commissioned officer

49 - 94 8

47 Openness to experience AND

military leadership

3 - 1 3


interview score OR interview

ratings

1355 88 84 5


officer selection OR military

selection

189 31 114 3

50 Openness to experience AND non-


1 - - -


selection interview

1 - - 4


officer selection OR non-


50 - 90 7

Appendix 4

Scoring manual

General

Because creative individuals are believed to be fluent, flexible and original the typical scores for

divergent thinking tests are fluency, flexibility and originality (Runco & Mraz, 1992)

Each task will be scored on each sub-indicator before summarised into one overall score

indicating divergent thinking ability

The data collected in both 2007 and 2016, will not be scored on elaboration as the responses are

mainly single words rather than descriptive ideas

In the 2007 data set we are uncertain about how unreadable responses were handled, but

responses in the raw data that are not readable or understandable in the 2016 data set will not be

included and scored

If date of birth is not readable the candidate will not be included in the data set for 2016

Since the data set in 2007 was not available as raw data, we cannot be sure that the spelling

errors stem from the respondents or those who typed it into Excel. Therefore, we will show

some level of good will and try to interpret spelling errors and vague responses in the

candidates’ best interest, e.g. “øyspære” could be “lyspære” due to typing error, as l and ø is

next to each other on the key board

Fluency – the number of ideas/responses

Rationale: Individuals with more divergent thinking abilities will generate more ideas compared to

individuals with less divergent thinking abilities (Runco & Mraz, 1992)

Procedure:

The total number of ideas given will be counted

Ideas written twice is only counted as one e.g. sun and the sun

Validation of ideas will not be conducted

Flexibility – number of categories, or themes, in the ideational pool

Rationale: flexibility is an important aspect of DT because an individual that has several ideas within

several categories has the ability to take on different perspectives (Runco & Mraz, 1992)

Procedure:

Categories are decided together prior to scoring, and often 10-20 categories are used, but due to

our large data set we are required to include 25-30 categories to cover as many responses as

possible

Scoring will be conducted individually

For each category used 1 point will be given, except when responses are undefinable (task 1:

AA; task 2: AC)

If a sentence includes two or more categories e.g. “car accident in a tunnel”, one point will be

given for car accident (explosion) and one point for tunnel (building). Note that only the most

primary categories will be used, that is car (transport) will not be given points

When there is a combination of words: e.g. “frustrated person”, the emotion is underlined and

given 1 point

When there is a sentence including more than just “sint kineser”, such as “en sint kineser med

bustete morgenhår”, we refer to both the emotion and the body part described as human and thus

gives the candidate 2 points

Originality – the number of unique/unusual ideas

Rationale: originality and creativity is strongly related, and what is original occurs seldom. What is

seldom is often considered new, and what is considered new and/or original is generally perceived as

creative (Martinsen, n.d.). Originality is defined as responses that are not usual, or common (Runco &

Mraz, 1992).

Procedure:

The scores for originality will be calculated together by both raters

An alphabetic list of all responses from each of the data sets 2007/2016 will be made in Excel

prior to scoring

Words with equal meaning or different synonyms will be conservatively defined and

alphabetically grouped

Next the frequency of each response will be calculated and given percentage of each prevalence

Cut-off levels for the responses are 5% for both data sets

Those responses below cut-off level will be given 1 point, whereas responses above cut-off level

are given 0 point

Sorting

All quotation marks, numbers, parentheses, and information regarding which way or direction

the figures were held during interpretation, are removed

One master list was created in Excel where all the responses for each of the task were sorted

alphabetically. Then sub-groups were created and responses were sorted into these

Then the remaining responses are evaluated for uniqueness, and calculated to check they are

below cut-off level before final scores are given in the main Excel-document

When there is combination of words: e.g. “angry sun” or “vampire teeth”, only one word will be

emphasised and given credits for originality

Potential limitations with scoring

Many responses may have different associations for different raters and thus create problems

when categorising them, e.g. “løypeprofil” as related to either curves (stigning) or path/direction

(map)

Other problems may also arise when scoring flexibility in terms of interpretations of responses:

e.g. «Bilbane» (Hedda: kjørebane, Ulrika: Rakkestad, Respondent: lekebil bane(?), «Sene»

(fiske sene eller sene i kroppen)

Example from the data set illustrating the difficulty and complexity involved in the scoring of

responses: Synkronsvømming, soloppgang, forsvarsverk av bakketopp tegnet ovenfra (1800ish),

en maur/annet innsekt med følehorn på vei over en bakketopp med en stigende sol i ryggen,

øyevipper, smilefjes og nesebor (ID 10979)

Flexibility categories

Task One (Mountain)

A) animal(s) (e.g. mark, crocodile teeth, nebb, øgle, animal parts, hoggtenner, horn, dinosaur)

B) nature/landscape (e.g. the Alps, mountains, fjellkjede, skog, trær, Sveits, earth, Lofoten,

flowers, plants, sand, grass, stones, isbre (glacier), grottetak, havbunn, utsikt, horisont, bakker)

C) graphs/diagrams/curves (e.g. graf, diagram, kurve, levels, elevation, incline, decline, changes,

variations, løypeprofil, stigning, høyde, høydeforskjell)

D) human(s) (e.g. teeth, haircut, ansikt, Simpsons hair, menneske, profil)

E) path/direction (e.g. path, way, road, borders, map, løype, tur, rute, tråkk, fotspor/hjulspor)

F) pattern(s) (e.g. lines, stripes, seam, sick-sack, søm, mønster, sying, sting, arr, kutt, bitemerker,

bord, riper, trekanter, firkanter, streker)

G) water (e.g. icicles, waves (bølger), ocean, rain, is, isfjell, istagger, istapper, vanndråper,

vannfontene, snøkrystaller, krystaller, tsunami)

H) building(s) (e.g. cabin, tent, pyramids, tipi, lavvo, walls, roof, sandslott, by, bygning, hustak)

I) emotions (e.g. mood, lykke, kjedelig, hat, aggressivitet)

J) letters/ logos/signatures (e.g. pencil movement, autograph, alphabets, scripts, commercials,

tattovering, reklameskilt, skilt)

K) music (e.g. lydbølger, lydfrekvens, radio frequence, radio, lyd, trekkespill, gitarr)

L) transport (e.g. car, wagon, roller coaster, sail, vehicles, wheels, tog, vogn, sykkehjul)

M) supernatural/religious phenomena and cartoons (e.g. ghosts, vampires, Bible, nisser, Santa,

giants, dwarfs, monster, navngivne cartoons: postman pat, pacman)

N) furniture/interior (e.g. stairs, curtains, vegger, tepper, spikermatter, toalett)

O) economics/mathematics/statistics (e.g. finance, wall street, money, currency, statistics, matte,

kalkulatorskjerm, trekantpuls, vinkler, geometri)

P) sports/sport equipment (e.g. slope, slalom, surfboard, crossbane, obstacle course/ hinderløype,

climbing, tour de France, Giro d’Italia, slalomløype, orienteering, formkurve, intervalltrening,

treningsprogram, intensitetskurve, akkebakke, kulekjøring)

Q) tools/weapons (e.g. saw, knife, pencil, arrows, felle, kjegler, jekk, øks)

R) scientific measurement/instruments (e.g. seismograph, lie detector, polygraph, power,

electricity, EKG (heart rate, pulse), medical equipment, analog, oscilloscope, tv signals, frekvens

(heart), bølgelengde, oscilloskop)

S) food and drinks (e.g. pizza, sukkertopper, eggskall, iskjeks, melon, kakeform)

T) art/images/photos (e.g. painting, decorations, tegning, tegneserie…, skulptur, statue, skisse)

U) clothing and accessories (e.g. hats, crown, smykke, beltespenne, diamant, skolisse, sko,

skosåle, bukse, kjole, skjorte, bukserift)

V) areas (e.g. graveyard, tivoli, brygge, Disneyland, parkeringsplass, område)

W) entertainment (e.g. cards, tv-shows, toys, playing, badesklie, Grey’s anatomy, flåklype)

X) games (e.g. laptop, PC, computer, elastomania, Nintendo/PS, MS paint, data)

Y) abstract (e.g. ideas, liv/livslinje, ujevnheter/ulikheter, skarp, beskrivelse, spenning, turbulens)

Z) formation (e.g. formasjon, oppstilling, forsamling, familie, flere mennesker/dyr i samling)

AA) materials (e.g., glasskår, knust/knekt material, rivet/oppklippet…, bit/del av…, sprekk

(independent of object), brettet papir, tøyhaug, bruddskader, hakk)

AB) natural phenomena (e.g. light, day, flash, wind, thunder, lyn, mane, sol, flammer,

stjernebilde, eksplosjon, stråler, bål, lys)

AC) 0 points: non-definable/non-readable/non-existent word after adjusting for possible errors

Task Two (sun):

A) animal(s) (e.g. porcupine, hedgehog, innsektsben, kråkebolle)

B) nature/landscape/geography (e.g. sun, sunset, sunrise, rainbow, desert, water Sahara, avgrenset område,

stokker, kvister, pinner, horisont, måne, atmosfære, is, vannsprut, holme, nes, badestrand, innsjø, elv, foss,

bekk, bevegelse i vann, morgen, sommer, syden, solstråler, sopp)

C) carrying things (e.g. bag, basket)

D) furniture/household things/interior (e.g. bowl, sink, fork, table, håndtak, inngangsparti, gang, vindu,

balking, vifte)

E) protection (e.g. shield, armour, helmet, force field, forsvar, forsvarsstilling)

F) equipment/machinery (e.g. tannhjul, turbiner, satellites, propeller, anchor, skovlejul)

G) scientific measurement/instruments (e.g. analog, oscilloscope, tv signals, frekvens (heart, frequence),

signal, telescope, speed indicator, compass, graf, microbølger, trykkbølger, voltmeter, ampermeter,

ohmmeter, turteller, fartsmåler, meter, måleinstrument, heisklokke/etasje viser)

H) tools/weapons/materials (e.g. watch, arrows, kikkert, bue, magnet, ledning, kabel, ståltråd, sag, sagblad,

tau, vannspreder)

I) art/logo/commercials (e.g. cartoons(navngitte e.g. karius og baktus, tommy og tigern, carman i south

prak), letters, alphabet, tattovering, statue, symboler, omriss)

J) pattern(s) (e.g. fingermerker, halvsirkel, strekk kode, foot print, sprekker, streker, pigger, sysøm, flenge i

ball)

K) light source(s) (e.g. lamp, light bulb, candle, laser, light, lyn, foton, lysstolpe, lommelykt, stearinlys,

lysstråler)

L) heat source(s) (e.g. heat, fire, fireplace, cigarettes (smoke), leirbål, glødning, brente fyrstikker,

hetetbølge)

M) theatre/cinema/audience/crowd/stage (e.g. Stortinget, military formation, animals in formation, objects

in formation, konferanserom, angrep, leder/lærer med elever, oppstilling, kor, bryllup)

N) human (e.g. face, hair, beard, nose, hårfrisyre, dårlig hårdag, rastafletter, svette)

O) emotion(s) (e.g. anger, happiness, tiredness, smiley/smilefjes, states, moods, ansiktsuttrykk, sinna taggen,

hissig, temperament, frustert, lykkelig, glad)

P) religious/supernatural phenomenon (e.g. troll, monster, alien, lykketroll, jesus og disiplene, djevel)

Q) biology (e.g. cells, bacterias, semen, føflekk med hår, brain, genitals, fetus, værhår, organisme, DNA

kveiler)

R) food and drinks (e.g. vannmelonfrø, banana, tomato, alle typer frukt, pommes fries)

S) power (e.g. påvirkingskraft, utstrålning, explosion, implosjon, stråler, nuclear, energy, fireworks,

electricity, elektroner, elektoder, spenning, stjerneskudd, personer som får støt/strøm)

T) path/direction (e.g. path, way, road, borders, map, løype, himmelretning, veiskilt)

U) clothing and accessories (e.g. hats, crown, jewellery, hårbørste, tråd, hissing, parasol, parply, smykker,

medaljon)

V) building(s) (e.g. bridge, tunnel, FBI HQ, p-plasser, parkeringshus, oversikt over hus, trafikk, båser,

gjerde, innheining)

W) transport/vehicles (e.g. cars, motorbikes, wheels, spaceship, fly, togbane, jernbane, retningsviser,

bilratt)

X) sound/music/electronics (e.g. stereo, music, høytaler, speaker, trekkspill, lydbølger, volum, noen roper,

smell, sang, ulike musikk typer/stiler, vibrasjoner, torden, radiobølger/signaller/skjerm, instrumenter, TV)

Y) games/entertainment (e.g. laptop, PC, computer, Nintendo/PS, domino, ulike typer barneleker, leke,

bamse, paint i word, bok, film)

Z) sports/sportsmen/sports equipment/sports area (e.g. swimmer, Holmenkollen, climbing wall, 100 m

hekk i en sving, hinderløype, ball)

AA) smell (e.g. vond lukt, lukter vondt, noe som lukter, gass, bæsj)

AB) abstract (e.g. war, thoughts, ideas, life, taktikk, urettferdighet, flukt, spredning, plan, skygge)

AC) 0 points: non-definable/non-readable/non-existent word after adjusted for possible errors

References

Martinsen, Ø. L. (n.d.). Skåringsmanual Divergent tenkning – Kreativitet. Seksjon for Psykometri.

Universitetet i Bergen, 1-33.

Runco, M. A., & Mraz, W. (1992). Scoring divergent thinking tests using total ideational output and a

creativity index. Educational and Psychological Measurement, 52(1), 213-221.

Torrance, E. P. (1990). Manual for scoring and interpreting results. Scholastic testing Service.

Appendix 5

Correlation matrices

Table A. Study one Means, standard deviations and correlations for Openness to experience

N

Mean(±SD)

1

2

3

4

5

6

7

1. Facet O1

r

1135

17.08(±4.58)

(.748)

2. Facet O2

r

1120 14.73(±5.30) .377** (.752)

3. Facet O3

r

1124 19.02(±3.84) .398** .426** (.732)

4. Facet O4

r

1138 17.20(±3.49) .133** .246** .163** (.690)

5. Facet O5

r

1221 18.87(±4.95) .295** .500** .290** .279** (.759)

6. Facet O6

r

1221 20.34(±3.17) .180** .207** .206** .244** .304** (.677)

7. Openness

r

1225 107.37(±16.45) .645** .770** .646** .494** .715** .483** (.703)

**p<.01. Estimated Cronbach’s alpha in brackets on the diagonal.

Table B. Study one Means, standard deviations and correlations for Extroversion

N

Mean(±SD)

1

2

3

4

5

6

7

1. Facet E1

r

1129

2.91(±.31)

(.749)

2. Facet E2

r

1102 2.79(±.49) .532** (.770)

3. Facet E3

r

1129 2.32(±.47) .364** .257** (.772)

4. Facet E4

r

1139 2.43(±.41) .370** .315** .410** (.625)

5. Facet E5

r

1121 2.68(±.45) .304** .410** .159** .216** (.641)

6. Facet E6

r

1113 2.84(±.50) .537** .413** .290** .401** .356** (.768)

7. Extroversion

r

1223 127.76(±14.94) .756** .730** .611** .645** .599** .744** (.768)


Table C. Study two Means, standard deviations and correlations for Openness to experience

N

Mean(±SD)

1

2

3

4

5

6

7

1. Facet O1

r

383

16.86(±4.53)

(.724)

2. Facet O2

r

389 20.99(±4.77) .237** (.634)

3. Facet O3

r

379 21.96(±3.47) .234** .225** (.697)

4. Facet O4

r

381 18.15(±3.43) .192** .000 .171** (.672)

5. Facet O5

r

386 23.76(±4.52) .314** .296** .197** .329** (.728)

6. Facet O6

r

383 21.00(±3.33) .206** .202** .244** .347** .415** (.656)

7. Openness

r

352 122.72(±14.65) .627** .584** .545** .526** .724** .622** (.650)


Table D. Study two Means, standard deviations and correlations for Extroversion

N

Mean(±SD)

1

2

3

4

5

6

7

1. Facet E1

r

384

27.47(±3.49)

(.732)

2. Facet E2

r

386 21.10(±3.92) .599** (.719)

3. Facet E3

r

387 19.83(±3.76) .454** .310** (.718)

4. Facet E4

r

382 21.87(±3.35) .495** .347** .359** (.667)

5. Facet E5

r

379 26.69(±3.71) .249** .264** .161** .230** (.675)

6. Facet E6

r

381 24.28(±4.05) .596** .471** .349** .455** .333** (.724)

7. Extroversion

r

348 141.14(±15.56) .809** .727** .642** .674** .538** .796** (.788)


Table E. Study two Means, standard deviations and correlations for personality and

divergent thinking variables

N

Mean(±SD)

1

2

3

4

5

6

1. Openness

r

352

122.72(±14.65)

(.650)

2. Extroversion

r

348 141.14(±15.56) .405** (.788)

3. Fluency

r

405 14.29(±5.95) .069 .093 (.788)

4. Flexibility

r

405 11.30(±3.32) .101 .122* .905** (.677)

5. Originality

r

405 3.30(±3.24) .113* .095 .751** .671** (.670)

6. Divergent thinking

r

405 28.89(±11.81) .094 .108* .979** .941** .831** (.893)

**p<.01. *p<0.05. Estimated Cronbach’s alpha in brackets on the diagonal.

Appendix 6

Mediation analyses

Study 1

Model of divergent thinking as a predictor of admission, mediated by

interview rating (N=1222)

X= Divergent thinking

M= Interview rating

Y= Admission

Divergent thinking interview rating: b=.02, p<.001.

Divergent thinking admission: b=-.00, p=.970.

Interview rating admission: b=.47, p<.001.

There is a significant indirect effect of divergent thinking on admission through

interview rating, b=.01, BCa CI (.00-.01). There is no direct effect of divergent

thinking on admission. Effect size (K2) could not be produced.

Direct effect, b=-.00, p=.970. Indirect effect, b=.01, 95%CI (.00- .01).

Model of Openness to experience as a predictor of admission, mediated by


X= Openness to experience

M= Interview rating

Y= Admission

Openness to experience interview rating: b=.01, p<.001.

Openness to experience admission: b=.00, p=.652.

Interview rating admission: b=.43, p<.001.

There is a significant indirect effect of Openness on admission through interview

rating, effect b= .00, BCa CI (.00- .01). There is no direct effect of Openness to

experience on admission. Effect size (K2) could not be produced.

Direct effect, b=.00, p=.652. Indirect effect, b=.00, 95% CI (.00- .00).

Study 2

Model of divergent thinking as a predictor of admission, mediated by


X= Divergent thinking

M= Interview rating

Y= Admission

Divergent thinking interview rating: b=-.00, p=.819.

Divergent thinking admission: b=-.03, p=.199.

Interview rating admission: b=.17, p=.029.

There is an insignificant indirect effect of divergent thinking on admission through

interview rating, b=-.00, BCa CI(-.01-.01). There is no direct effect of divergent

thinking on admission. Effect size (K2) could not be produced.

Direct effect, b=-.03, p=.199. Indirect effect, b=-.00, 95% CI (-.01- .01).

Model of Openness to experience as a predictor of admission, mediated by


X= Openness to experience

M= Interview rating

Y= Admission

Openness to experience interview rating: b=.01, p=.053.

Openness to experience admission: b=.00, p=.695.

Interview rating admission: b=.21, p=.016.

There is a significant indirect effect of openness on admission through interview

rating, b= .00, BCa CI (.00-.01). There is no direct effect of Openness to

experience on admission. Effect size (K2) could not be produced.

Direct effect, b=.00, p=.695. Indirect effect, b= .00, 95% CI (.00- .01).


Appendix 7




Rino Bandlitz JohansenForsvarets stabsskole Forsvarets HøgskolePostboks 800, Postmottak2617 LILLEHAMMER Vår dato: 14.12.2015 Vår ref: 45936 / 3 / HJP Deres dato: Deres ref: TILBAKEMELDING PÅ MELDING OM BEHANDLING AV PERSONOPPLYSNINGER Vi viser til melding om behandling av personopplysninger, mottatt 02.12.2015. Meldingen gjelderprosjektet:

Personvernombudet har vurdert prosjektet, og finner at behandlingen av personopplysninger vil væreregulert av § 7-27 i personopplysningsforskriften. Personvernombudet tilrår at prosjektetgjennomføres. Personvernombudets tilråding forutsetter at prosjektet gjennomføres i tråd med opplysningene gitt imeldeskjemaet, korrespondanse med ombudet, ombudets kommentarer samtpersonopplysningsloven og helseregisterloven med forskrifter. Behandlingen av personopplysningerkan settes i gang. Det gjøres oppmerksom på at det skal gis ny melding dersom behandlingen endres i forhold til deopplysninger som ligger til grunn for personvernombudets vurdering. Endringsmeldinger gis via eteget skjema, http://www.nsd.uib.no/personvern/meldeplikt/skjema.html. Det skal også gis meldingetter tre år dersom prosjektet fortsatt pågår. Meldinger skal skje skriftlig til ombudet. Personvernombudet har lagt ut opplysninger om prosjektet i en offentlig database,http://pvo.nsd.no/prosjekt. Personvernombudet vil ved prosjektets avslutning, 13.01.2020, rette en henvendelse angåendestatus for behandlingen av personopplysninger. Vennlig hilsen

Kontaktperson: Hanne Johansen-Pekovic tlf: 55 58 31 18Vedlegg: Prosjektvurdering

45936 Lederkandidatundersøkelsen ved Forsvarets utdanning. En studie avkultur, profesjonsidentitet og individuelle prestasjonsfaktorer

Behandlingsansvarlig Forsvarets høgskole, ved institusjonens øverste lederDaglig ansvarlig Rino Bandlitz Johansen

Katrine Utaaker SegadalHanne Johansen-Pekovic

http://www.nsd.uib.no/personvern/meldeplikt/skjema.html


Appendix 8



http://pvo.nsd.no/prosjekt

Personvernombudet for forskning Prosjektvurdering - Kommentar

Prosjektnr: 45936 Prosjektet er en videreføring av prosjektnummer 43533. FORMÅLProsjektets formål er å undersøke hva som kan kjennetegne en god lederkandidat som blir tatt opp til utdanningved befals- og høyskolene i Forsvaret. METODEProsjektet er utformet slik at det består av tre spørreundersøkelser og registerdata fra forsvarets register P3/SAP. Spørreskjemaene inneholder spørsmål som omhandler motivasjon, profesjonsidentitet, kultur,personlighetstrekk og verdier. Disse vil deles ut til informantene på tre tidspunkt: under opptaksukene, motslutten av befalsskolen og mot slutten av plikttjenesteåret. Datamaterialet som hentes fra Forsvarets register P3/SAP vil inkludere- resultater fra opptaksprøvene, herunder vitnemål fra videregående, resultater fra forsvarets evnetester,personlighetstester, fysiske tester, intervju og feltvurdering- resultater fra tjenesteresultater, herunder tjenesteresultater fra skole og plikttjeneste, skoleresultater ogresultater fra ledervurderingen 360 Mil. Personvernombudet forutsetter at det er søkt om godkjenning fra nødvendige instanser innad i Forsvaret fortilgang til registerdata. SAMARBEIDSSTUDIEDet er mulig at prosjektet kan bli en nasjonal samarbeidsstudie med BI eller Høgskolen i Oslo og Akershus.Forsvarets høgskole er behandlingsansvarlig institusjon. Personvernombudet forutsetter at ansvaret forbehandlingen av personopplysninger vil bli avklart mellom institusjonene. Vi anbefaler at det inngås en avtalesom omfatter ansvarsfordeling, ansvarsstruktur, hvem som initierer prosjektet, bruk av data og eventuelteierskap. INFORMASJON OG SAMTYKKEUtvalget informeres skriftlig og muntlig om prosjektet og samtykker til deltakelse. Informasjonsskrivet er godtutformet. SENSITIVE OPPLYSNINGERDet behandles sensitive personopplysninger om helseforhold. I innsendt meldeskjema var dette punktet ikkekrysset av for. Da registerdata inneholder informasjon fra blant annet fysiske tester finner Personvernombudet

at det samles inn sensitive personopplysninger, og har endret dette punktet i meldeskjemaet. INFORMASJONSSIKKERHETPersonvernombudet legger til grunn at forsker etterfølger Forsvarets høgskole sine interne rutiner fordatasikkerhet. PROSJEKTSLUTT OG ANONYMISERINGForventet prosjektslutt er 13.01.2020. Ifølge prosjektmeldingen skal innsamlede opplysninger da anonymiseres.Anonymisering innebærer å bearbeide datamaterialet slik at ingen enkeltpersoner kan gjenkjennes. Det gjøresved å:- slette direkte personopplysninger (som navn/koblingsnøkkel)- slette/omskrive indirekte personopplysninger (identifiserende sammenstilling av bakgrunnsopplysninger somf.eks. bosted/arbeidssted, alder og kjønn)

BI Norwegian Business School Master Thesis · GRA 19003 Master Thesis 01.09.2016 ii Abstract The...

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