thesis manuscript

CHARACTERISTICS OF UNIVERSITY STUDENT LEADERS

by

CHRISTINE KAY ANDERSON, B.S. (Northern Illinois University) 2012

EMILY SUZANNE APITZ, B.S. (Eastern Illinois University) 2012

JENNIFER ROSE CONTERIO, B.S. (Purdue University) 2010

COLLEEN ANNE GANDOLFI, B.S. (Benedictine University) 2012

KRISTIN PAGE LAWLER, B.S. (Northern Illinois University) 2012

CARLY MARIE SMITHERMAN, B.S. (Northern Illinois University) 2012

RESEARCH MANUSCRIPT

Submitted in partial fulfillment of the requirements for the degree of

MASTER OF SICENCE in NUTRITION AND WELLNESS

in the College of Education and Health Services,

Benedictine University, Lisle, Illinois

Research Advisor:

Catherine Arnold, M.S., Ed.D.

November 2013

A MIXED METHOD STUDY OF STUDENT LEADERS

RESEARCH MANUSCRIPT

by

CHRISTINE ANDERSON

EMILY APITZ

JENNIFER CONTERIO

COLLEEN GANDOLFI

KRISTIN LAWLER

CARLY SMITHERMAN

The Research Manuscript submitted has been read and approved by the Research

Advisor. It is hereby recommended that this Research Manuscript be accepted as

fulfilling part of the Master of Science in Nutrition and Wellness graduate degree in the

College of Education and Health Services at Benedictine University, Lisle, Illinois:

_________________________________ ___________________________________Signature of Catherine Arnold, M.S., Signature of Karen Plawecki, M.S., Ph.D. Ed.D. Director, M.S. in Nutrition and WellnessResearch Advisor APPROVED FOR BINDING

___________________________________Signature of Catherine Arnold, M.S., Ed.D.Chairperson, Nutrition DepartmentAPPROVED COMPLETION OF RESEARCH REQUIREMENT

___________________________________Signature of Alan Gorr, Ph.D., M.P.H.Dean, College of Education and HealthServices

_________________________________ December, 2013 __Date of Oral Defense Intended Graduation Date (Month, Year)

ii

I authorize Benedictine University, 5700 College Road, Lisle, IL 60532, to lend this

Research Report, or reproductions of it, in total or in part, at the request of other

institutions or individuals for the purpose of scholarly research.

________________________________ Student Name (Print)_______________

_________________________________Student Signature and Date___________

________________________________Student Name (Print)_______________

________________________________Student Name (Print) __________ ________________________________Student Name (Print)_______________



________________________________Research Advisor Name (Print)_______

________________________________Student Signature and Date__________





________________________________Research Advisor Signature and Date__

iii

© Copyright by

Christine Kay Anderson, Emily Suzanne Apitz, Jennifer Rose Conterio, Colleen Anne Gandolfi, Kristin Page Lawler, Carly Marie Smitherman

2013: All Rights Reserved

iv

TABLE OF CONTENTS

Page

LIST OF TABLES viii

LIST OF FIGURES x

ACKNOWLEDGEMENTS xi

STRUCTURED RESEARCH ABSTRACT xii

CHAPTER 1: INTRODUCTION 1Context of the Study 1Purpose and Research Question 3Methods 4Definition of Terms 4Hypotheses 6

CHAPTER 2: LITERATURE REVIEW 9Leadership Theories by Jennifer Conterio 9Leadership & Volunteerism by Christine Anderson 11Family Dynamics/Environment & Leadership by Colleen Gandolfi 13Leadership & Religious Affiliation by Emily Apitz 18Self-efficacy & Leadership by Carly Smitherman 20Gender & Leadership by Kristin Lawler 24

CHAPTER 3: METHODOLOGY 27Research Study Design 27Participants 27Data Collection Methodology 28Measurement Tools 29Statistical Procedures 41

CHAPTER 4: FINDINGS: IN-CLASS SURVEYS 42Outliers Treatment of the Data 42Descriptive Profile of Participants 42Leadership & Gender (Hₒ1) by Kristin Lawler 44Leadership & Gender (Hₒ2) by Kristin Lawler 47Leadership & Gender (Hₒ3) by Kristin Lawler 47Leadership & Gender (Hₒ4) by Kristin Lawler 47Leadership & Gender (Hₒ5) by Kristin Lawler 47Leadership & Gender (Hₒ6) by Kristin Lawler 47Leadership & Gender (Hₒ7) by Kristin Lawler 48Leadership & Gender (Hₒ8) by Kristin Lawler 48

v

Leadership & Gender (Hₒ9) by Kristin Lawler 48Leadership & Gender (Hₒ10) by Kristin Lawler 48Leadership & Gender (Hₒ11) by Kristin Lawler 49Leadership & Gender (Hₒ12) by Kristin Lawler 50Leadership & Gender (Hₒ13) by Kristin Lawler 50Leadership & Gender (Hₒ14) by Kristin Lawler 51Leadership & Family (Hₒ15) by Colleen Gandolfi 52Leadership & Family (Hₒ16) by Colleen Gandolfi 54Leadership & Religion (Hₒ17) by Emily Apitz 56Leadership & Religion (Hₒ18) by Emily Apitz 58Leadership & Volunteerism (Hₒ19) by Christine Anderson 59Leadership & Volunteerism (Hₒ20) by Christine Anderson 60Leadership & Volunteerism (Hₒ21) by Christine Anderson 63Leadership & Volunteerism (Hₒ22) by Christine Anderson 64Leadership & Volunteerism (Hₒ23) by Christine Anderson 64Leadership & Volunteerism (Hₒ24) by Christine Anderson 64Leadership & Volunteerism (Hₒ25) by Christine Anderson 65Leadership & Leadership Styles (Hₒ26) by Jennifer Conterio 65Leadership & Leadership Styles (Hₒ27) by Jennifer Conterio 67Leadership & Leadership Styles (Hₒ28) by Jennifer Conterio 67Leadership & Leadership Styles (Hₒ29) by Jennifer Conterio 70Leadership & Leadership Styles (Hₒ30) by Jennifer Conterio 71Leadership & Leadership Styles (Hₒ31) by Jennifer Conterio 73Leadership & Leadership Styles (Hₒ32) by Jennifer Conterio 75Leadership & Leadership Styles (Hₒ33) by Jennifer Conterio 77Leadership & Self-efficacy (Hₒ34) by Carly Smitherman 81Leadership & Self-efficacy (Hₒ35) by Carly Smitherman 83Leadership & Self-efficacy (Hₒ36) by Carly Smitherman 84Leadership & Self-efficacy (Hₒ37) by Carly Smitherman 84Leadership & Self-efficacy (Hₒ38) by Carly Smitherman 85Leadership & Self-efficacy (Hₒ39) by Carly Smitherman 85Leadership & Self-efficacy (Hₒ40) by Carly Smitherman 85

CHAPTER 5: DISCUSSION 87Conclusions 87Applications 87Generalizability 89Limitations 89Recommendations 90

REFERENCES 91

APPENDIX A:Permission to use Leadership Self-Efficacy Scale 93APPENDIX B:Leadership Survey plus SLPI (Pretest) 94APPENDIX C:Leadership Survey plus SLPI (Posttest) 97

vi

APPENDIX D:Interview lead and follow-up questions 98APPENDIX E: Letter of Consent 99

vii

LIST OF TABLES

Table Page

1. Impact of Others……………………………………………………........ 30

2. Total Variance Explained……………………………………………….. 30

3. Rotated Component Matrix……………………………………………... 31

4. Cronbach’s Alpha……………………………………………………….. 31

5. Cronbach’s Alpha……………………………………………………….. 32

6. Reliability Statistics……………………………………………………… 32

7. Impact of Participation Before College………………………………….. 33

8. Total Variance Explained………………………………………………... 33

9. Rotated Component Matrix……………………………………………… 34



12. Impact of Previous & Current Experience……………………………….. 36

13. Total Variance Explained………………………………………………… 37

14. Rotated Component Matrix………………………………………………. 39

15. Reliability Statistics………………………………………………………. 39

16. Reliability Statistics………………………………………………………. 40

17. Gender Descriptives………………………………………………………. 43

18. SLPI Results between Males and Females………………………………... 45

19. Independent t-Test between Males and Females…………………………. 46

20. Leadership Self-efficacy Survey of Males and Females………………….. 49

21. Independent t-Test of Leadership Survey between Males and Females….. 49

22. Pearson Correlation-Mother/Father Education and SLPI………………… 53

23. Pearson Correlation-Family Influence and SLPI…………………………. 54

viii

24. Information from Interviews……………………………………………… 56

25. Pearson Correlation-Attendance of Religious Services and Pre-Test SLPI. 57

26. Pearson Correlation-Prayer/Meditation and Pre-Test SLPI………………. 58

27. Spearman-rho-Prayer/Meditation and Pre-Test SLPI…………………...... 59

28. Pearson Correlation-Before College Community Service/Events………... 59

29. Pearson Correlation-Before College and In College…………………….... 61

30. Correlations-SLPI…………………………………………………………. 66

31. Pearson Correlation-Leadership and SLPI………………………………... 68

32. Descriptive Statistics-GPA and SLPI……………………………………... 72

33. Grand Mean……………………………………………………………….. 72

34. Multivariate Tests………………………………………………………… 73

35. Paired Samples Statistics…………………………………………………. 74

36. Paired Samples t-Test……………………………………………………... 74

37. Paired Samples Statistics Male…………………………………………..... 76

38. Paired Samples Test Male………………………………………………… 76

39. Paired Samples Statistics Female…………………………………………. 78

40. Paired Samples Test Female……………………………………………… 79

41. Independent Sample Test-Variance……………………………………….. 82

42. Independent Sample Test-Comparison of Experimental and Match Group. 83

43. Pearson Correlation-Self-Efficacy and Age………………………………. 84

44. Pearson Correlation-Self-Efficacy Posttest and Age……………………... 84

45. Pearson Correlation-Pre and Posttest Self-Efficacy……………………… 85

46. Paired Samples Test-Pre and Posttest Self-Efficacy……………………… 86

LIST OF FIGURES

ix

Figure Page

1. Gender……………………………………………………………………. 43

2. Ethnicity…………………………………………………………………... 44

3. Mother Education Level…………………………………………………... 51

4. Father Education Level……………………………………………………. 52

5. Model the Way…………………………………………………………….. 80

6. Challenge the Process……………………………………………………… 81

ACKNOWLEDGMENTS

x

ABSTRACT OF THE RESEARCH MANUSCRIPTA Mixed Method Study of Student Learners

ByChristine Kay Anderson

Emily Suzanne ApitzJennifer Rose ConterioColleen Anne Gandolfi

Kristin Page LawlerCarly Marie Smitherman

Master of Science in Nutrition and WellnessBenedictine University, Lisle, Illinois

November 2013 Research Advisor: Catherine Arnold

Objectives: To determine the qualities present in student leaders at a Midwestern

university and also the factors and traits that contribute to a person becoming a leader.

Design: A mixed method design using both quantitative and qualitative data was used.

Measures: Quantitative data was gathered using the Student Leadership Practice

Inventory (SLPI) and supplemental surveys. Analysis of the pretest and posttest SLPI

scores and self-efficacy were examined using SPSS. The qualitative data was gathered

through pair interviews examining multiple aspects of leadership.

Subjects: Forty-two undergraduate students identified as student leaders from a

Midwestern university were analyzed (24 females, 18 males).

Statistical Analysis: Pearson Correlations were calculated to determine correlations

between SLPI scores and factors such as family influence, religion, volunteerism and

self-efficacy. When comparing means between genders, between pre-test and posttest

SLPI scores and between experimental and match leadership groups, t-tests were used. A

Spearman rho correlation was calculated to determine the relationship between aspects of

religion and SLPI scores. A one-way MANOVA was calculated to determine the effect of

GPA on pre-test SLPI scores.

Results: Data collected showed that females were significantly higher than males in the

ability to, “enable others to act” and “modeling the way” (t(41) = 1.26, p = .02, d = .20.

No significance was found between parent education level or family influence on SLPI

responses. However, qualitative results support the role of family in leadership

xi

development. There was a significant correlation found between frequency of attending

religious services and SLPI and for pray/meditation and SLPI. Significant correlations

were found between volunteerism before college and event participation before college.

Significant correlations were found between participation in external organizations,

events, college volunteerism and leadership. Community service before college had a

significant correlation with SLPI scores, and the leadership training program had a

significant effect on SLPI scores for “model the way” and “challenge the process”. There

was no significance between experimental and match groups in self-efficacy

characteristics. There was also no significance between self-efficacy pre and posttest

scores and age or pre and posttest self-efficacy characteristic scores.

Conclusions: Gender, religion and volunteerism appear to be major factors in

identifying leadership qualities and in determining who will become leaders. Further

research is needed, but these findings could play an important role in choosing students

for graduate programs as well as dietetic internship programs.

xii

CHAPTER 1

INTRODUCTION

Context of the Study

The question of whether leaders are born or made has been assessed ten times

over by researchers and scientists alike. Originally, it was believed that individuals were

born with certain innate characteristics or traits favorable for leadership and that these

individuals would become successful leaders (1). Although the answer to this question is

still not definitive, a great deal has been discovered about specific traits and

characteristics that may be learned by individuals to become leaders and the factors that

contribute to leadership development (2, 3). The idea that leadership is a learnable skill

creates the possibility for anyone to obtain these traits and characteristics, opposed to a

select few leaders who are "born that way" (1). However, having these traits does not

automatically make someone a leader. It is known that one must make decisions and take

certain actions throughout their life in order to become an effective leader (2, 3).

There are various factors, or themes, associated with leadership discussed

throughout the length of this report. Prominent leadership theories, volunteerism, family

dynamics/environment, religious affiliation, self-efficacy, and gender play a role in

leadership development and therefore were included in the research for this study. This

study was meant to provide the research team with valuable information regarding

student leaders and how these specific themes contributed to their personal decisions to

lead.

Two main leadership theories were common amongst the literature; constructive

developmental theory and transformational leadership theory. These theories help us to

understand the processes involved in leadership development along with the

characteristics favorable for leadership, essentially providing a framework for success.

Leaders exhibit characteristics such as being proactive, being innovative, and being a

visionary. Volunteerism and leadership often go hand in hand. For many leaders,

1

volunteering allows them to utilize these characteristics in a way that not only benefits

themselves, but others as well. Family upbringing (including parental morals/values,

parental leadership styles, parental support, family conflict) and the social environment

one grows up in (socioeconomic status, parental support, parental conflict) have been

known to shape multiple aspects of an individual as well as influence their motivation to

lead and their leadership style. Religious affiliation is often an important characteristic

for many people. Religion and religious beliefs can be influential in the way one lives,

including their decision to lead. Self-efficacy strongly correlates with leadership as seen

in multiple studies. Further investigations regarding leadership and self-efficacy will

continue to divulge how the skills and attributes of one, impact the other. Gender

stereotypes have previously idealized males as a stronger leader than females and the

percentage of current female managers is shockingly low. Characteristics of feminine

personalities are associated with traits necessary for a transformational leader and

evidence that transformational leadership is effective in the management world continues

to accumulate.

The concept of higher education institutions and their role in developing socially

responsible leaders began gaining much attention in the early 1990's (3). Since then,

campus leadership practices have expanded from approximately 700 leadership

programs existing on college campuses to over 1,000 programs nationally today (3).

Research suggests that throughout colligate years, students are capable of, and often do,

hone their leadership skills (3). In fact, the findings from a national study conducted by

Dugan and Komives demonstrated that college experiences accounted for 7% to 14% of

the overall variance in leadership outcomes (3). Many factors are thought to contribute to

this phenomenon. Environmental factors such as living away from home, student-student

interactions, student-faculty interaction, campus involvement, intramural sports,

volunteer work, acting as a tutor, group projects, and class presentations are all thought to

positively impact leadership development (2). Background factors such as age, sex, grade

point average, and personality factors such as intelligence, self-efficacy, extroversion,

and self-confidence are also influential elements for student leadership development (2).

Colleges and universities aim to provide students with a variety of learning and service

opportunities in order to enhance their leadership abilities and qualities (1).

2

Dugan and Komives thoroughly examined the factors associated with leadership

development in college students using a multi-institutional national study involving 55

universities and over 165,000 students (3). One aspect of this study was to examine how

students' perceptions on leadership changed over time. The students' perceptions of

leadership positively increased for consciousness of self, congruence, collaboration,

common purpose, citizenship, change, and leadership efficacy; with the greatest

magnitudes of change being consciousness of self and leadership efficacy (3). Although

these changes occurred during the college years, it is difficult to say whether these

changes were the result of the college environment or other influences. This study also

assessed the role and degree to which demographics, pre-college experiences, and college

experiences such as mentoring, campus involvement, acts of service, holding positional

leadership roles, and formal leadership programs have on leadership development (3).

From this study, it was determined that short, moderate, and long-term leadership training

experiences all had significant effects on leadership efficacy (in comparison with no

training) (3).

Purpose and Research Question

Research has shown that leadership characteristics and traits are becoming

increasingly important for an individual to possess. The National Association of Colleges

and Employers’ Job Outlook 2012 survey, as cited in the IRB, noted that nearly 80

percent of respondents “search for evidence that the potential employee can work in a

team", and more than three-quarters indicated they "want the résumé to show the

candidate has leadership abilities.” Our study will be able to determine which qualities

are present in students currently identified as leaders by our university. Using the data

obtained, we may then be able to promote the development of leadership in

nutrition/dietetics students, as well as students of other fields. The purpose or goal of our

study is to explore the primary guiding question:

o How do university students develop as leaders?

Additionally, we will explore numerous variables that may impact development

and current leadership scores of the student leaders, to answer questions such as:

o Do males and females differ? Do leaders differ across other demographic

characteristics?

3

o Is there a relationship between self-efficacy and leadership?

o Is there a connection between campus involvement, volunteerism, and

leadership?

o Can past involvement activities (or pre-college participation in clubs, teams,

or activities), volunteerism, and/or leadership experiences predict leadership

attributes and/or leadership self-efficacy?

o What are common experiences prior to college that influence leadership?

o What is the influence of family or faith on leadership?

Methods

Our experimental group was comprised of current students from the selected

Midwestern University identified as leaders who participated in a leadership- training

program in April 2013 by invitation from the university's Director of Student

Engagement and Leadership. This leadership program targets the development of

leadership skills measured on the Student Leadership Practice Inventory (SLPI), and was

delivered by this director. Current university students identified as leaders who were not

participating in a leadership training program in April were the match group.

There was two types of data analyzed, qualitative and quantitative data.

Quantitative data was gathered using the Student Leadership Practice Inventory and

supplemental surveys. Analysis of the pretest and posttest SLPI scores and self-efficacy

were examined using SPSS.

The qualitative method used in our research was pair interviewing. This

qualitative method was used to gain a better understanding of participant's experiences in

life and why they chose to become a leader. Pair interviewing was used for increased

validity and word credibility. Interviews were also voice recorded by the interviewing

pair, or graduate students. Data was gathered encompassing multiple aspects of

leadership and comparison of data and methods was performed at several intervals during

data collection.

Definition of Terms

Several terms used throughout the study are described here so that the reader will

understand topics being referenced. The terms and their definitions are listed below.

4

Leadership:"the ability to inspire and guide others toward building and achieving

a shared vision. Association leaders shall model the way with a mindset for

transformation, innovation, invention, adaptability, empowerment and risk-taking. This

leadership mindset will enable the Association and its members to embark on a path

toward a successful future"(The Academy of Nutrition and Dietetics).

Leadership Program:"college-sponsored experience with student participants who

attend in order to learn about and develop individual leadership traits and characteristics"

Transformation leadership: "leadership by empowerment. Comprised of four

components consisting of idealized influence, inspirational motivation, intellectual

stimulation, and individualized consideration" (Walumbwa 2011, Zacharatos, 2000).

Leadership Role Occupancy: "the extent to which individuals have occupied or

are now occupying positions of formal leadership in organizational settings" (Zhang,

2009).

Socioeconomic Status (SES): "describes an individual's or a family’s ranking on

hierarchy according to access or control over a combination of valued commodities such

as wealth, power, and social status. This also serves as an overall measure of the level of

possible resources available to adolescents when they grow up" (Zhang, 2009).

Family Environments: "include the level of financial resources and the parental

support offered via emotional understanding, family involvement in the individual's

activities, and financial funding of interests of the individual" (Zhang, 2009).

Social Environments: "include neighborhood, school, peers, safety, and

availability of leadership programs and involvement opportunities" (Zhang, 2009).

Enriched Environments: "having a higher family socioeconomic status, higher

perceived parental support, and lower perceived conflict with parents or social

environments" (Zhang, 2009).

Inspirational Motivation: "the ability to inspire and motivate others to

demonstrate appropriate behavior" (Sahgal, 2007).

Supportive Parenting: "providing careful attention, guidance, and support which

instills and sets the foundation in children that they can be special and feel valued"

(Sahgal, 2007).

5

Self-efficacy: "defined as the belief in oneself to have the personal capabilities

and resources to meet the demands to perform specific tasks" (McCormick 2002).

Occupational self-efficacy: "reflects the belief of a person that he/she can execute

behaviors relevant to complete their own work" (Schyns 2010).

Gender: "male or female based on possession of male or female reproductive

organs"

Fortune 500 company: "yearly list of the largest 500 industrial companies in the

U.S

“Manager, Leader, and Boss will be used interchangeably in this report"

Hypotheses

Hₒ1: There is no significant difference between self-reported skills of “modeling the

way” between males and females based on the SLPI.

Hₒ2: There is no significant difference between self-reported skills of “inspiring a shared

vision” between males and females based on the SLPI.

Hₒ3: There is no significant difference between self-reported skills of “challenging the

process” between males and females based on the SLPI.

Hₒ4: There is no significant difference between self-reported skills of “enabling others to

act” between males and females based on the SLPI.

Hₒ5: There is no significant difference between self-reported skills of “encouraging the

heart” between males and females based on the SLPI.

Hₒ6: There is no difference between the percentile score for “modeling the way” between

males and females.

Hₒ7: There is no difference between the percentile score for “inspiring a shared vision”

between males and females.

Hₒ8: There is no difference between the percentile scores for “challenging the process”


Hₒ9: There is no difference between the percentile scores for “enabling others to act”


Hₒ10: There is no difference between the percentile scores for “encouraging the heart”


6

Hₒ11: There is no difference between the self-efficacy levels of ability to perform

managerial leadership tasks reported between males and females.

Hₒ12: There is no difference between the self-efficacy levels of the ability to perform

charismatic leadership tasks reported between males and females.


leadership tasks that require taking action reported by males and females.


personalization leadership tasks reported by males and females.

Hₒ15: Mother and father education level is not related to the ability to “model the way”,

“inspire a shared vision”, “challenge the process”, “enable others to act”, or

“encourage the heart” in terms of leadership.

Hₒ16: Family influence is not related to the ability to “model the way”, “inspire a shared

vision”, “challenge the process”, “enable others to act”, or “encourage the heart” in

terms of leadership.

Ho17: Attending religious services is not related to the ability to “model the way”,



Ho18: Participating in prayer and/or meditation is not related to the ability to “model the

way”, “inspire a shared vision”, “challenge the process”, “enable others to act”, or


Ho19: There is no relationship between community service participation before college

and event participation before college.

Ho20: There is no relationship between community service participation in elementary

school and participation in college sports.

Ho21: There is no relationship between participation in external organizations in college

and participation in community service before college.


and community leadership in college.

Ho23: There is no relationship between participation in events (sports/activism) before

college and participation in college sports.

7

Ho24: There is no relationship between school-related community service and

community leadership in college.


community leadership before college.

Hₒ26: There is no relationship between participating in community service activities

prior to college and SLPI response scores.

Hₒ27: There is no relationship between participating in sporting/activism events prior to

college and SLPI response scores.

Hₒ28: There is no relationship between frequency of seeking out leadership opportunities

and SLPI response scores.

Hₒ29: There is no relationship between frequency of acting as a group leader and SLPI

response scores.

Hₒ30: Individuals’ GPA does not have any effect on SLPI scores.

Hₒ31: The leadership training program will have no effect on pre-test to posttest SLPI

scores.


scores in males.


scores in females.

Hₒ34: There is no difference between Group 111 (experimental group) and Group 222

(match group) and self-efficacy scores.

Hₒ35: There is no relationship between the self-efficacy pre-test scores and age.

Hₒ36: There is no relationship between the self-efficacy posttest scores and age.

Hₒ37: There is no difference between the pre and posttest scores for SE1:

managerial/administrative in relation to leadership.

Hₒ38: There is no difference between the pre and posttest scores for SE2: charisma in

relation to leadership.

Hₒ39: There is no difference between the pre and posttest scores for SE3:taking action in


Hₒ40: There is no difference between the pre and posttest scores for SE4:personalization

in relation to leadership.

8

CHAPTER 2

LITERATURE REVIEW

Leadership Theories

As the definition of leadership continues to develop and change over time, so do

the theories and models used to describe and categorize leadership behaviors and

processes (4). The Academy of Nutrition and Dietetics defines leadership as, "the ability

to inspire and guide others toward building and achieving a shared vision. Association

leaders shall model the way with a mindset for transformation, innovation, invention,

adaptability, empowerment and risk-taking. This leadership mindset will enable the

Association and its members to embark on a path toward a successful future" (5). While

this definition provides ideal leadership characteristics, it does not identify the leadership

processes used to provide this end result. When looking at the literature, the amount on

leadership alone seems to be unlimited while leadership as it relates to the field of

dietetics is minimal. Through our extensive research, we were able to find two main

leadership theories that seem to be the most prominent within the dietetics profession;

Constructive Developmental Theory and Transformational Theory (4, 5, 6, 7).

Constructive Developmental Theory

Constructive developmental theory focuses on the mindset of the individual, not

specific traits or characteristics of the individual. Constructive developmental theorists

believe that "persons move through qualitatively different ways of knowing who they are,

how the world works, and how they know what they know" and that "leaders as

individuals develop over the life course and do so in predictable ways" (6). The origin of

the constructive developmental theory is Jean Piaget's theory of cognitive development

(6). The process of how human beings "come to know" and the stages of mental growth

we travel through acquiring this ability of "abstract symbolic reasoning" is what this

theory is centered upon (6). Human development is both horizontal and vertical (6).

Horizontal growth is what we see most in adults and consists of learning new skills, new

9

methods, new facts, or pursuing advanced degrees (6). A person may grow horizontally

in knowledge acquisition, while their vertical development remains the same (6). Vertical

growth focuses on how people tend to reason and behave in response to their experiences.

Vertical development is illustrated as a spiral of developmental stages. An individual

lives through the earlier stages before progressing to the later stages and once one has

journeyed through a stage, it becomes part of that individual (6). However, most humans

do not grow through the entire spiral and will settle in the stage that is most comfortable

for them (6). Developmental psychologists agree that the stage of vertical development is

what differentiates leaders, rather than their personality or philosophy of leadership (6).

The stages of vertical development can better be described as Action Logics. The Action

Logics model is separated into three tiers, pre-conventional, conventional, and post-

conventional. The pre-conventional tier contains the earlier stages of change and the post-

conventional tier contains the later stages of change (6). In the field of dietetics,

individuals in the later post-conventional stages can provide proficient leadership to the

profession and serve as leadership mentors (6). Conventional leadership theory can

identify the stage of vertical development in leaders within the profession to help to

understand the factors that contribute to the movement from one stage to the next (6).

Transformational Theory

New leadership theories have begun to emerge within the last decade,

transformational theory being one of them. Transformational leadership does not replace

the well-known theory of transactional leadership, but enhances it (5). The characteristics

of a transformational leader are described as one who is inspiring, energetic, is

enthusiastic in nature, has a vision, and is passionate (4, 5, 7, 8). Charisma is another

known trait of a transformational leader. However, a charismatic leader is not always

transformational as they may not place emphasis on the development of their followers.

A transformational leader supports the development of self-reliance with the main goal of

transforming their followers and the organization itself (8). Avolio and Bass described

the skills of a transformational leader as the four I's: idealized influence, inspirational

motivation, intellectual stimulation, and individualized consideration (8). Idealized

influence represents the followers' confidence and appreciation which is necessary for the

acceptance of changes within the organization (8). Inspirational motivation is the ability

10

to inspire and motivate followers to demonstrate appropriate behaviors (8). Intellectual

stimulation is the process of stretching the followers' competencies in order to drive

change in their way of thinking about issues and their performance (8). Individualized

consideration is the leader's ability to observe, analyze and predict the needs and wishes

of followers (8). Although there is not much literature on leadership relating to the field

of dietetics, the existing literature shows that dietetic students as well as registered

dietitians exhibit many qualities of a transformational leader (4, 5, 7).

Leadership & Volunteerism

Volunteerism is a trait exhibited by many leaders. It is thought to be an important

factor both in determining what makes a good leader, and also in determining the types of

individuals who will take on leadership roles at some point in their lives. Many factors

can contribute to a person’s decision to become a volunteer, including their familial

influence, their religion, and the culture in which they live. It is important to note that

these factors are often introduced during childhood or adolescence and will continue to

influence a person throughout their entire life. Another thing that might influence a

person’s decision to become a volunteer is school. Many colleges and universities are

now requiring their applicants to have some volunteer experience to even be considered

for admission. A further look into some of these factors can help identify what leads to

volunteerism and how it is related to leadership.

Family Influence and Youth Volunteerism

Many studies have been done to help determine why a person makes the decision

to become a volunteer. According to studies conducted by Dunham et al., many people

who become volunteers were raised in a household where one or both parents were

volunteers. Therefore, the parents served as role models for youth volunteerism.

Oftentimes, these parents would participate in volunteer activities with their children.

This taught them at a young age to become community oriented (9, 10).

Many children and adolescents are involved in groups such as 4-H. Children who

are involved with these types of groups at a young age are more likely to take on

leadership roles and are more likely to be involved in volunteer activities as they move

into adulthood (11).

Religion and Culture

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Cultural beliefs are often based on religion, and both are linked to volunteerism.

Some cultures are more egocentric, whereas others are more altruistic. Cultures that focus

more on the society as a whole tend to have ideals that are more in line with those seen in

volunteerism (12). People who are members of an organized religion are more likely to

become volunteers than people who are not affiliated with a religion. An article from

Louis Penner states that 80% of people who were organized religion members

participated in volunteer activities, while only 62% of people who were not members of a

particular religion participated in volunteer activities. Another interesting finding in this

study was that volunteers scored higher on a religiosity measure than non-volunteers,

meaning they considered themselves to be more religious.

Religion was also significantly correlated with other factors, such as the number

of organizations they volunteered for and also the length of time they spent volunteering

for these organizations. The higher a person scored on the religiosity measure, the more

organizations they tended to be involved with and the more time they spent at these

organizations. Religion, although not the focus of this particular study, showed the

strongest correlation with volunteer activities when compared with factors like

personality or socio-economic status. Therefore, it is noted that religion should continue

to be looked at in future studies involving volunteerism (13).

Demographics of Volunteers

According to the Bureau of Labor Statistics from 2012, there was little change in

the total number of volunteers for the year. Women continue to volunteer more than men

(29.5% vs. 23.2%) and this was true for all ages, levels of education, and other

demographics. The age group that is most likely to volunteer is the 35-44 year old group.

The group with the lowest volunteer rates was the 20-24 year old group. Also, after age

45, the volunteer rate began to taper off. When looking at race, whites volunteer at a rate

higher than blacks, Hispanics, and Asians, with little change in the rates of each group

over the year. Also interesting to note was that married people tend to volunteer at a

higher rate than those of other marital statuses (14).

Motivation

People tend to have particular motivators that play a role in their decision to

volunteer. A study by Clary and Snyder explored different motivators people have, and

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how these motivators can impact the length of volunteerism. They broke it down into six

“functions” served by volunteering: values, understanding, enhancement, career, social

and protective. Some of these are based on the desire to help oneself, and some are based

on the selfless desire to help others. Based on responses to a survey asking people to

indicate their personal motivators, the researchers discovered that most people’s

motivators for volunteerism are multifaceted. People want to do something to help others,

but at the same time may be required to volunteer for school or may use it as an escape

from their own troubles. With this in mind, it is important for recruiters to target their

messages to people whose motivators are in line with the nature of the volunteer work.

The researchers also found that college students who felt that their volunteer work

fulfilled a particular motivation or function were more likely to continue volunteering

(15).

The Organization

The organization itself plays an important role in volunteerism. First of all, the

majority of volunteers are part of an organization. It is far less common for individuals

outside of an organization to engage in volunteerism that is sustained for a significant

amount of time. It is thought that as many as 85% of volunteers are part of an

organization, so how the organization is run has a huge impact on determining if and for

how long they will have volunteers (12). The recruitment process is only the beginning.

Motivators and functions, which were previously mentioned, are not concrete. They may

change over time, and an organization needs to be aware of this in order to maintain its

volunteers. It is also important for the organization to continuously encourage its

volunteers and to remind them that the goal of volunteerism is to better society as a whole

(16).

Family Dynamics/Environment & Leadership

Family structure and dynamics have been shown to shape the way a child grows

and matures throughout his or her life. However, do family dynamics and upbringing

specifically influence the child’s leadership skills or lack thereof? Several studies have

been conducted to address this issue by examining leadership skills as related to family

environment vs. genetic influences, the influence of parent’s leadership skills on the

child’s motivation to lead, and the influence of life experiences in shaping leaders today.

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The first study conducted by Zhang et al., addresses the controversial question

surrounding the nature of genetic influences on leadership and whether the genetic effects

establish constraints on the effectiveness of leadership development efforts in

organizations and in earlier life. Specifically, it examines whether the heritability of

leadership at work is moderated by individuals’ developmental environment in

adolescence (17).

The study presented two distinct conceptual, yet opposite, arguments for the

moderating effects of the social environment on leadership. First, a more enriched

environment would allow greater influence of genetic differences in leadership capacity,

thus strengthening the heritability of leadership emergence. The second argument is

based on the leadership theory that links overcoming adversity and crises to leadership

emergence. Therefore, a more impoverished social environment, like those involving

interpersonal conflict, would allow the greater influences of genetic differences in

leadership capabilities.

The study examined three family social environmental variables; the first being

family socioeconomic status (SES) including wealth, power, and social status. Second

was perceived parental support (PPS), and last was perceived conflict with parents (PCP).

The subjects were male twins who completed three different surveys including a

background questionnaire, a parental environmental questionnaire, and a leadership

survey (17).

The study reported that the presence of adversity and conflict facilitates the

greater influence of genetic leadership potential. This is also true of individuals from low

SES families. Therefore, “leadership genes” that one is born with, will have a greater

influence on one’s leadership potential in an environment of low SES, negative parental

support, and greater parental conflict. The flip side of this result was also true in that

environments characterized by higher SES, higher levels of perceived parental support,

and lower perceived conflict with parents were associated with a lower heritability of

leadership role occupancy (17).

The study showed that the family economic and social environments experienced

by adolescents have important effects on the magnitude of genetic influences on

leadership exhibited later in life. When an individual came from a family with higher

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SES, higher parental support or lower conflict with parents, his/her opportunities of

becoming a leader in the workplace were determined more by environmental factors

rather than genetic factors. Therefore, even those born without the “leadership genes”

have the opportunity to become leaders by experiencing an enriched family environment

during their adolescent years (17).

The next study conducted by Hartman et al. examined how parental influence

may shape the leadership process. The study emphasized the ideas offered by behavioral

modeling which suggests that children have the opportunity to observe their parents’

leadership style and adopt the style demonstrated by an admired parent, but reacts against

a parent who is not admired.

The study utilized 195 college students majoring in business administration from

two universities. Each completed the Leadership Behavior Description Questionnaire to

describe their management style. They then completed the same questionnaire to describe

their perceptions of the management style used by a nominated person as an important

early influence (i.e. parent). Finally, the nominated person (i.e. parent) completed the

questionnaire. Correlations among the completed questionnaires were examined. The

researchers hypothesized that students’ reported leadership styles will be positively

correlated with both their perceptions of the parents’ leadership styles and with their

parents’ self-reports of their styles. It was also hypothesized that the students’ perceptions

of their parents’ style will be more closely related to the students’ style than will parents’

self-reports of their own styles (18).

Correlations were positive, indicating that students’ scores were similar to

parents’ scores, supporting the first hypothesis. Correlations were higher between

parents’ perceived scores and students’ scores than between parents’ reported scores and

student’s scores, which supports the second hypothesis. Therefore, the results indicated

that parents’ leadership styles, especially their styles as perceived by their children, were

related to their children’s leadership styles. This suggested that the students learned at

least some aspects of leadership from their parents early in life (18).

A study conducted by Sahgal et al. used a developmental approach to examine the

life experiences that have shaped the lives of leaders who have successfully transformed

organizations. The study attempted to answer these questions: How do leaders develop?

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Do life experiences or specific events/circumstances make a leader? What are leaders’

self-perceptions and the drivers for their success? (8).

The group consisted of 10 Indian leaders serving in various leadership positions.

Each individual was interviewed and an analysis of the qualitative data was conducted

and classified into nine broad areas (four of these areas being family related, including

supportive parenting, inspiration of the father, relentless pursuit of values, and rising

above adversity) (8).

For supportive parenting, the subject leader received encouragement and positive

reinforcement from parents and significant family members. There was relatively low

direction on achievement of long-term career goals and greater emphasis on family

values and discipline that seemed to have a lasting impact. There was a focus on building

inner strength and confidence. The warmth and support extended by family members

helped in developing respect for elders, tolerance and adaptability. The subjects did not

experience any family pressure to achieve academic excellence or a particular career path

(8).

Most of the subjects stated that their fathers played a key role in their upbringing

and the formation of their core values and principles. While the subjects closely held

humanistic values that had been ingrained in them either by their father or other family

members, there were other instances where early life experiences and hardships also

contributed to their code of values. The respondents shared early personal limitations

such as having to compete with others who were more educated than themselves, coping

with their village/small town background, overcoming family financial constraints, and

facing the trauma of losing loved ones early in life. The leaders were able to withstand

the pressures because of their inherent confidence, unwillingness to compromise with

injustice, and their belief in the value of hard work. All of these values they learned

through early personal experiences at home and contribute to the theme of rising above

adversity. This study concluded that life experiences play a significant role in the

development of leadership (8).

The aim of the study conducted by Zacharatos et al. was to further the

understanding of the development of leadership, transformational leadership in particular,

in children. It was the first stage of a research program to develop an understanding of the

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origin, development, and emergence of adult leadership behavior. The hypothesis was

that adolescents perceive the extent to which their parents exhibit transformational

behaviors (namely, inspirational motivation, idealized influence, intellectual stimulation

and individualized consideration) during parent-child interactions and adopt similar styles

themselves (19).

To test their hypothesis, the study focused on the leadership behaviors exhibited

by adolescents while participating on sports teams, which provided a naturalistic setting

for examining leadership behaviors. The subjects consisted of 112 athletes who

completed the Multifactor Leadership Questionnaire’s (MLQ) sections pertaining to

transformational leadership. They completed the MLQ separately for their mothers’ and

fathers’ behaviors and completed evaluations of themselves and their teammates (19).

Results of this study confirmed that there were no sex differences with respect to

the perceptions of parents’ transformational behaviors or self, coach, and peer ratings of

transformational leadership. Also, perceptions of their fathers’ transformational

leadership affected the children’s transformational leadership, but not that of their

mothers’. Adolescents perceive the extent to which their fathers use behaviors consistent

with transformational leadership when interacting with them and, in turn, manifest these

behaviors themselves when interacting with peers. Adolescents exhibiting

transformational leadership behaviors appear to be capable of evoking effort from their

peers and of being perceived as effective leaders (19).

In conclusion, all of these studies confirmed that there were strong links between

early family experiences and ultimate leadership qualities and skills. Although these

studies indicated that family influence is not the only factor in the development of

leadership skills, it plays an important role. The results of the various questionnaires

completed in these studies demonstrate that there are strong links between parental

leadership styles and the leadership styles of their children.

Leadership & Religious Affiliation

Several studies have been accounted for regarding religious leadership, but the

question remains whether or not there is a connection between leadership and religious

affiliation. Scholars have previously focused their efforts into studying various types of

leadership styles, which can be based upon a person’s ethical and moral judgment. Webb

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studied the leadership behaviors of presidents of Christian colleges in North America that

belonged to the Council for Christian Colleges and Universities (CCCU). The degree to

which three different leadership styles were practiced by the presidents of these colleges

was considered as well as the degree of which these leadership styles promoted higher

job satisfaction. The styles considered included transformational leadership, transactional

leadership, and laissez-faire leadership (20). These leadership styles theoretically inspire

followers and enable them to create change within a system (20).

Transformational leaders embody the character of an individual who shows

confidence and positivity towards their followers’ capacity, provides a concise vision of

group goals, encourages creativity through assigning benefits, sets high expectations,

creates an environment that promotes meaning, and forms relationships with their

followers (20). This type of leadership led to the highest job satisfaction within the study.

Each leadership style was measured by the Multifactor Leadership Questionnaire.

Webb argued that transformational leadership involved motivating followers by

producing an exciting environment and persuading followers to act in the best interest of

the group, despite their own interests. In transactional leadership, leaders facilitated an

exchange of equal value to complete assigned duties regardless of the presence political,

psychological or economical motivators. In Laissez-faire leadership, Webb argues that

the leaders hold neither a negative nor positive attitude and avoid any direct personal

interaction or interference (20). These leadership styles were also studied to determine

any successful combination styles of leadership (20).

Webb’s results concluded that followers indicated more job satisfaction and

motivation when following leaders who demonstrated energy, high levels of self-

confidence, strong beliefs and ideals, assertion, and who promoted personal confidence

within their followers (20). It was found that a combination of transactional and

transformational leadership further enhanced satisfaction among employees (20).

Oh, a scholar who has studied the dynamics of leadership, looked closely at the

Motivation to Lead (MTL) concept. MTL assumes that individual traits and sociocultural

values are influential in the performance of leadership behaviors (21). A second concept

that Oh studied is Need for Closure (NFC). This is a person’s need for an immediate

answer rather than ambiguity about a certain topic (21). Oh states that a person with a

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low need for closure will ponder over and discuss certain decisions. On the other hand, a

person with a high need for closure that will make a snap decision to ease stress and will

not abandon their decision (21).

One of Oh’s hypotheses came from his belief that a person with a higher need for

closure, one that prefers predictability and is uncomfortable with ambiguity, will be

highly motivated to accept a leadership role. He also believes this type of person will

assume a leadership role due to a strong need for structure and predictability, even though

most people look to avoid the responsibility accompanied with a obtaining a leadership

role (21).

In his study, Oh assigned 136 full-time, first year graduate students earning a

Master’s of Business Administration to 40 independent leaderless work teams. After two

months of working in these groups, the students took an online survey that was

comprised of MTL and NFC scales (21). The results showed positive relationships for

each of the variables measured in the study. A higher NFC was correlated with a higher

MTL (21).

An article review by Sweeney and Fry titled, Character Development through

Spiritual Leadership contained many arguments that showed a connection between

leadership and spirituality. The basis of the article inquired about the origin of a leader’s

characteristics (22). It is first noted that character is established through making moral

and ethical decisions in all types of situations. Secondly, it is noted that the actions of

leaders is used to infer values and beliefs of the followers. Thirdly, it was noted that the

groups’ beliefs about virtues and values has a direct effect on their perceptions and

judgments concerning moral and ethical issues. People use their moral values as a

foundation for establishing goals and rules on how to live their lives (22).

Self-efficacy & Leadership

A strong correlation exists between self-efficacy and leadership, as each has been

shown to directly impact the other. It seems what researchers have been characterizing as

effective leadership could also be known as high self-efficacy. Recent studies have been

conducted regarding the impact of self-efficacy and the role it has in leadership and vice

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versa. Several issues were examined regarding self-efficacy and leadership including

motivation, persistence, goal orientation, resilience, cognitive abilities, resourcefulness,

problem solving, providing feedback, positive reinforcement, and the ability to work well

under pressure.

The first study reviewed by McCormick et al. addressed the concern that high

leadership self-efficacy was needed for leadership performance. The study argued and

discovered that leadership self-efficacy was a deciding factor to determine leaders from

non-leaders. It also addressed topics from prior leadership experience and behavior in

predicting future leaders. The last two decades have shown a consistent trend between

high self-efficacy and individual work performance. Efficacy theory suggests that

personal efficacy impacts the goals people pursue and therefore determines their

leadership capability (23).

Bandura first introduced the concept of self-efficacy in 1977. It was defined as

“the belief one has the personal capabilities and resources to meet the demands of a

specific task” (23). Efficacy theory has found that personal efficacy influences individual

goals based on aspirations, the amount of effort they put into a task, how much time and

effort were put into resolving the given difficulties, obstacles, and disappointments. One

can say that efficacious individuals are highly motivated, persistent, goal oriented,

resilient, and maintain clear and concise thoughts when under pressure. It was no

coincidence that individuals who are successful leaders have been described in similar

manners.

During investigations of effective leaders, characterizations of being committed,

determined, resilient, resourceful, an effective problem solver, and goal oriented were

commonly highlighted. McCormick stated that “regarding these leadership findings in

light of what is known about highly effective efficacious individuals suggest that what

leadership researchers have been describing for years is a person with high self-efficacy”

(23). All major reviews have self-confidence as an essential tool to being an effective

leader. This is also a needed trait in the transformational leadership theory.

While self-confidence and self-efficacy are not identical, self-confidence is a

generalized sense of competence, which is considered a personal trait. Self-efficacy is a

personal belief or self-judgment about one’s specific ability. This, in turn, makes these

20

characteristics closely allied with one another and related to some extent. This means a

highly confident person in a leadership role is influenced by their self-confidence and

thus possesses a high level of self-efficacy. While self-confidence does not guarantee a

successful leader, it is a belief in their ability to complete or perform in a leadership role

that is the key factor.

In his study, McCormick found that participants high in leadership self-efficacy

reported a much higher frequency of taking on a leadership role than participants

categorized as having low leadership self-efficacy. These results indicated that high self-

efficacy could be the key leadership factor. All participants were assessed using an eight-

item questionnaire to rate the self-efficacy with response options ranging from one (no

confidence) to seven (high confidence). They also confirmed the number of leadership

role experiences that had a positive effect on their leadership self-efficacy assessment

(23).

The second study by Walumbwa et al. examined the relationship between

transformational leadership and self-efficacy. The study used employees to gauge

individual’s willingness to take on challenges, ability to be creative, innovative, and

inspiring to achieve the goals of the organization. It specifically reviewed the mediated

relationship between transformational leadership and self-efficacy (23).

It has been found that transformational leadership is related to follower levels of

self-efficacy. The important aspect of this study was to determine the cause for the

followers of transformational leaders’ that show an increased level of self-efficacy. They

proposed that the effect of transformational leadership on follower performance is

realized through employees who come to identify with transformational leaders, and in

turn, show greater self-efficacy and an increase their performance (24). Transformational

leaders influence their followers by instilling and providing them with confidence to

perform beyond their implicit or explicit expectations.

This study hypothesized the relationship as follows: transformational leadership,

to rational identification, to self-efficacy, will affect the followers’ performance.

Transformational leadership consists of leadership by empowerment. It is conceptualized

that transformational leaders include four dimensions: charisma, inspirational motivation,

intellectual stimulation, and individual consideration. Bandura argued that individuals

21

increase self-efficacy through role-modeling (24). Rational identification comes into play

by enabling employees to enact behaviors that are consistent with their abilities, opposed

to mimicking supervisor behavior. Simplified, it allows them to learn from their leader

and acquire new skills, thereby enhancing their self-efficacy.

Previous studies have found a positive correlation between self-efficacy and work

related performance. The reason self-efficacy is positively related to important

organizational outcomes stems from the efficacy beliefs that influence individual’s goal

choices and goal-directed activities, reactions, and persistence in the face of challenges

and/or obstacles (24). This determines individual’s selection of a challenge they believe

they can accomplish. The higher the self-efficacy the more likely they will enter into a

situation in which performance expectation is high. Likewise, a low self-efficacy will

predict an individual’s performance into a lower performance expectation. Therefore,

transformational leaders expect followers with high self-efficacy to accept challenges as

they instill confidence and provide encouragement.

The study utilized 426 employees and their supervisors. Questionnaires and

assessments were utilized to gauge employees’ self-efficacy on a ten-point Likert scale.

The results showed that transformational leadership was positively related to self-efficacy

and performance. Transformational leaders enhanced efficacy by providing opportunities

to learn, providing feedback, delegating duties, and challenging followers to come up

with new solutions. This self-efficacy leads to better performance and supports the

leadership and self-efficacy relationship (24).

The next study by Anderson et al. involved the development of structured

leadership self-efficacy and the reactions to leadership effectiveness. The study derived

key leadership behaviors from executives to serve as a basis for measuring leadership

effectiveness. It was proposed that leaders with higher self-efficacy will enact key

leadership skills and engage more often and with greater effectiveness than those who

possess lower self-efficacy. This study is supported by recent studies conducted by Paglis

and Green that links self-efficacy to effective leadership. Findings in their literature

suggest that people with strong self-efficacy beliefs are likely to be more motivated,

contribute more towards actions, and preserve to a greater degree when faced with

difficulty (25).

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The key behaviors were chosen from 44 senior to mid-level executives and

managers. A total of 251 participants were selected to participate in the current study.

The study showed the importance and effectiveness of a well-defined leadership self-

efficacy in expanding our understanding of leadership effectiveness. It was determined

that certain leadership measurements can predict and lead to leadership self-efficacy

performance. Such factors included innovation, creativity, problem solving, influential

leadership, and communication (25).

The last study, conducted by Schyns, was the exploration of the relationship

between leadership-relevant attributes and occupational self-efficacy. It is hypothesized

that leadership-relevant attributes are related to high self-efficacy beliefs. Self-efficacy

has been widely applied in the organizational context and is believed to play a central

role to the organization’s performance. Occupational self-efficacy is extremely similar to

self-efficacy, except occupational efficacy behaviors are specific to one’s work (26).

Prior research has found that self-efficacy is positively related to a performance

increase. According to a study by Hannah, effective leadership requires high levels of

agency and confidence; therefore self-efficacy is important for becoming a successful

leader in the future (26). The study was interested in self-efficacy prior to job experience,

which is why the study targeted business majors. They believe that students higher in

occupational self-efficacy will find it much easier to succeed and achieve their desired

tasks. This suggests the development of self-efficacy is mainly linked to mastery

experience and would further support transformational leadership.

The study was composed of 136 students who were assessed for their leadership

attributes. A total of 34 attributes were tested on a four-point scale. Occupational self-

efficacy was then assessed using a self-efficacy scale. The results of the study confirmed

the hypothesis that leadership attributes are positively related to occupational self-

efficacy. Self-efficacy is an important personal resource, and plays a vital role in career

development. The study used self-description scales and assessments. These scales were

of the most importance to people who believed themselves to be confident and motivated

and were likely to rate themselves as highly motivated and confident (26).

The studies confirmed a positive relationship exists between leadership and self-

efficacy. Individuals who are high in self-efficacy will have higher leadership skills.

23

Several common skills or attributes were present in all the studies on the composition of

leadership self-efficacy. Common skills and attributes included motivation, innovation,

critical thinker, problem solver, accepted challenges, etc. (26). Leaders who are

efficacious will also produce and help their followers become more efficacious as well.

It seems apparent that self-efficacy and leadership run hand in hand, as one will directly

influence the other.

Gender & Leadership

Gender equality is a continued battle, even in contemporary America. Currently,

females represent a greater percentage in the workplace in comparison to men (27). It

could be said that the presence of women in the healthcare field is over-powering.

Women are 78% of the healthcare workforce; 92% of nurses, and 48% of physicians. A

staggering 81% of graduate degrees attained in the health fields are received by women

(27). The large number of women qualified to take on a leadership role is one of the

characteristics that strengthens the field (27, 28). Unfortunately, the percentage of

females in leadership positions in the healthcare field is not representative of the vast

majority of females currently working in the field. Research shows that women are more

likely to remain in a middle-management position, proven by the fact that in 2011 a mere

25% of women held chief executive officer (CEO) positions in hospitals (27, 28). This

disparity is not isolated to the healthcare profession; Fortune 500 companies’ executive

positions are comprised of 86% male (28). In fact, 60 Fortune 500 companies do not have

a single female on their board, and 136 do not have a female in their top five executives

(28). Bringing women to the top of the corporate ladder will require development of

leaders and a focus on women leaders (27, 28). Board studies have shown that health

systems perform higher in proportion to having women on the board of executives (27).

A study conducted by Elsesser and Lever found that 8% of women and 21% of men have

never reported to a female boss, in comparison to 3% of women and 1% of men who

have never reported to a male boss (29). Additionally, it is found that women who

achieve an executive position are more likely to mentor their colleagues and aide in

developing future leaders (27, 28, 30). A young woman with aspirations for leadership

should look for at least one mentor and develop leadership skills whenever possible, so

that she may be prepared to seize a leadership position when one arises (28, 30, 31).

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Gender bias may be one large barrier to women gaining executive positions.

Stereotypically, men are direct, aggressive, assertive, and ambitious, which have

previously also been associated with desirable leadership characteristics (30, 31, 32). On

the other hand, women have personality traits associated with being communal,

nurturing, caring, and sensitive (29, 30, 32). Research shows that more time spent with an

individual results in less stereotyping, however hypothetical situations still show that a

gender bias stereotype exists (29). In a study conducted, there was minimal difference

between genders when workers were asked to rate the leadership skills of their own

bosses, however in a hypothetical situation; the male bosses were preferred (29). A cross-

gender difference was also found between male and female workers (29). Elsesser and

Lever found that women were more likely to prefer a male boss, and individuals who

have previously had a female boss are more likely to admit to preferring to have a female

boss (29). Essay responses to the question ‘why do you prefer a female boss?’ included

desiring an understanding boss that was easier to communicate with, whereas, common

reasons for desiring a male boss included negative adjectives for women opposed to

highlighting the quality of a male boss (29). Other themes that appeared from the study

included women who believed they could use their gender to attain sympathy from their

male bosses and workers and disliking bosses of the gender with which they compete in

their work (29). In the future, women will need to empower each other to climb the

corporate ladder and begin to take charge of leadership positions (27, 28, 29, 30).

Many leadership theories have arrived over the recent years, with

transformational leadership appearing as an effective approach for leaders of the future

(27, 32). Female characteristics fit this leadership style effectively, creating an open and

innovative work atmosphere for employees (27, 32). The leadership path for women was

previously thought of as a labyrinth, with many competing interests and stereotypes that

prevented a female from becoming a leader in her career (27, 28, 32). This labyrinth has

been reshaped into a circular model, where individuals may enter towards leadership

through characteristics of competence, connectivity, service, awareness, creation,

renewal, and wisdom, which have been identified as effective leadership qualities (27, 28,

32). This flattened model has allowed for females to balance their work-life priorities and

become an option for leadership positions that they have previously remained

25

unconsidered (27, 28, 32). The path for females into leadership positions allows for a

future of diverse leadership positions, which will promote creative thinking, innovation,

and improve patient care in the healthcare field in the future (27, 28, 30, 32).

CHAPTER 3

METHODOLOGY

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Research Study Design

The research design utilized for this study was a quasi-experimental

pretest/posttest design. Tests were conducted before and after a four-week period, where

student leaders attended a weekly leadership program.

The Institutional Review Board Application was approved at an expedited level

with an informed consent in March of 2013. This expedited IRB was also qualified for

category 6 and 7. Category 6 allows for data collection from voice, video, digital or

image recordings made from the research process. Category 7 allows for research on

individual or group characteristics or behavior and research employing survey, interview,

oral history, focus group, program evaluation, human factors evaluation, or quality

assurance methodologies.

Participants

There were two groups involved in this study. The experimental group contained

current Benedictine University students that were identified as leaders. These students

participated in a leadership-training program in April 2013 by invitation from the

Benedictine Director of Student Engagement and Leadership. This leadership program

targets development of leadership skills measured on the Student Leadership Practice

Inventory (SLPI) and is delivered by the Director of Student Engagement and

Leadership. A posttest SLPI was administered to the experimental group following four

leadership training programs. The control group contained current Benedictine University

students identified as leaders who were not participating in a leadership-training program

during this time. The control group was not administered a posttest SLPI.

Student recruitment began with the Director of Student Engagement and

Leadership providing names and contact information for students willing to be involved

in this study. Selection was amongst those receiving leadership scholarships at

Benedictine University. Contact information was received during the last week of March,

where a time for data collection was selected. Students provided written consent prior to

responding to survey or interview questions. Qualitative interviewing and administration

of the quantitative surveys occurred at the beginning of the training sessions. A posttest

SLPI was administered following the fourth training session.

27

The role of students in the study consisted of completion of surveys and

interviews (refer to appendices for question sets). All participants were asked to complete

the self-administered pretest and participate in a semi-structured interview during weeks

1-3. The experimental group was asked to complete the self-administered posttest after

four leadership-training sessions. The SLPI and other items on the quantitative pretest

survey were estimated to take 18-20 minutes to complete. The interviews were estimated

to last for about 30 minutes, depending on the length of individual answers. The final

posttest was estimated to take 10-12 minutes to complete. Those in the experimental

group attended a leadership-training workshop on campus, led by the Director of Student

Engagement and Leadership. The theme was Five Practices of Exemplary Student

Leadership.

A consent form asking for the participant’s signature was provided and collected

before collecting data. Each student responded to the pretest SLPI and a survey

containing the Leadership Self-Efficacy scale developed by Ng, Ang, and Chan (2008)

and questions developed by our research team. Student interviews were conducted in

pairs. The interview times were coordinated between the student and interview pairs and

were offered in person or via Skype. Interviews were recorded and transcribed by the

research pairs.

Data Collection Methodology

Baseline data was collected from March 26, 2013 to April 8, 2013. At this time,

participants completed the SLPI and survey questionnaires. Students in the experimental

group began attending the weekly leadership-training program.

Interviews were conducted from April 9, 2013 through April 16, 2013. Pairs of

graduate students in the research group conducted interviews. All interviews were

completed in person and on the Benedictine University campus, with the exception of one

Skype interview. Interviews were recorded and transcribed verbatim by the interviewers.

The posttest SLPI was administered to the experimental group during the week of

April 30, 2013 following four leadership-training sessions.

The site for this study was the Benedictine University campus. Pre and posttesting

sessions took place in the leadership classrooms. In-person interviews took place in a

campus building and the Skype interview took place in the homes of the participants.

28

Confidentiality was maintained during the testing. Mobile phone communication was the

primary source of communication to confirm interview times between interviewers and

participants. Refer to appendices for interview, pre and posttest questions.

Measurement Tools

Student Leadership Practices Inventory (SLPI)

The SLPI is a 30-item self-instrument which measures leadership practices in five

areas: (a) Challenging the Process (search for opportunities, experiment, and take risks);

(b) Inspiring a shared vision (envision the future, enlist others); (c) Enabling Others to

Act (foster collaboration, strengthen others); (d) Modeling The Way (set the example,

plan small wins); and (e) Encouraging the Heart (recognizing individual contribution,

celebrate accomplishments). The instrument contains six items in each category and uses

a 5-point Likert scale (rarely to very frequently). The reliability and validity is high,

including the predictive validity: “The results make sense to people and, over time, have

proven to predict high-performing leaders and moderate- and low-performing ones”

(source: http://wwww.studentleadershipchallenge.com/Assessment/assessment-

studentLPI-print.aspx). Permission was granted to use this instrument. The university had

purchased paper copies to utilize in this study.

For this data set, the KMO statistic is .47, which is considered an unacceptable

value (greater than 0.5 being acceptable). Further data should be collected.

For this data set, the Bartlett’s test is highly significant (p < .001), and therefore

factor analysis is appropriate (Table 1).

Table 1: Impact of Others

KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy..47

Bartlett's Test of Approx. Chi-Square 60.93

29

SphericityDf 28

Sig. <.01

After rotation the three components together account for 73% of the total variance

(Table 2).

Table 2: Total Variance Explained

Compone

nt

Initial Eigenvalues Extraction Sums of

Squared Loadings

Rotation Sums of

Squared Loadings

Tot

al

% of

Varian

ce

Cumulati

ve %

Tot

al

% of

Varian

ce

Cumulati

ve %

Tot

al

% of

Varian

ce

Cumulati

ve %

13.1

038.68 38.68

3.1

038.68 38.68

2.4

230.25 30.25

21.5

419.29 57.97

1.5

419.29 57.97

1.8

923.63 53.88

31.2

015.05 73.02

1.2

015.05 73.02

1.5

319.15 73.02

4.75

39.413 82.44

5 .60 7.47 89.91

6 .40 4.98 94.89

7 .31 3.92 98.81

8 .10 1.19 100.00

Extraction Method: Principal Component Analysis.

This output allowed us to group these eight variables into three groupings: Group

1 = Teacher, Church, Work Supervisor; Group 2 = Family (Father, Mother, Siblings);

Group 3 = Significant Others, Friends) (Table 3).

Table 3: Rotated Component Matrix

Component

30

Reliability Statistics

Table 4: Cronbach’s Alpha

Cronbach's

Alpha

Cronbach's

Alpha Based

on

Standardized

Items

N of

Items

.81 .82 3

The Cronbach’s Alpha for Group 1 (Teacher, Church, Work Supervisor) is .81, which

indicates good internal consistency among the three items assigned.


Table 5: Cronbach’s Alpha

Cronbach's

Alpha

Cronbach's

Alpha Based

on

Standardized

Items

N of Items

.78 .78 3

The Cronbach’s Alpha for Group 2 (Father, Mother, Siblings) is .78, which indicates

acceptable internal consistency among the three items assigned.


Table 6: Reliability Statistics

31

Cronbach's

Alpha

Cronbach's

Alpha Based

on

Standardized

Items

N of Items

.21 .23 2

The Cronbach’s Alpha for Group 3 (Friends, Significant Others) is .21, which indicates

unacceptable internal consistency among the two items assigned.

For this data set, the KMO statistic is .78, which is considered a middling value

but still acceptable (> 0.5 = acceptable; 0.7 < KMO = middling).

For this data set, the Bartlett’s test is highly significant (p < .001, and therefore

factor analysis is appropriate (Table 7).

Table 7: Impact of Participation Before College


Kaiser-Meyer-Olkin Measure of Sampling

Adequacy..78

Bartlett's Test of

Sphericity

Approx. Chi-Square 128.44

Df 28

Sig. <.01

After rotation the two components together account for 67% of the total variance

(Table 8).


Compone

nt

Initial Eigenvalues Extraction Sums of

Squared Loadings

Rotation Sums of

Squared Loadings

32

Tot

al

% of

Varian

ce

Cumulati

ve %

Tot

al

% of

Varian

ce

Cumulati

ve %

Tot

al

% of

Varian

ce

Cumulati

ve %

1 3.81 47.58 47.58 3.81 47.58 47.58 3.52 43.98 43.98

2 1.54 19.21 66.79 1.54 19.21 66.79 1.83 22.81 66.79

3 .69 8.64 75.43

4 .65 8.08 83.51

5 .44 5.46 88.97

6 .37 4.66 93.63

7 .30 3.72 97.35

8 .21 2.65 100.00


This output allowed us to group these seven variables into 2 groupings (Group 1 =

Amount of community service before college, Participation in clubs/groups/honor

societies before college, Leadership position in community before college, Leadership

position in school before college, Participation in community organizations; Group 2 =

Participation in varsity sports before college, Participation in intramural sports before

college, Participation in activism before college (Table 9).

Table 9: Rotated Component Matrix

Component

1 2

How often before college did

you volunteer or community

service

.86 -.05

Before college how often did

you participate in student clubs,

groups, honor societies

.83 .14

33


you have a leadership position

in the community

.80 .08

Before college, how often did

you participate in leadership

positions at school?

.79 .13


you participate in community

organizations (choir, scouts,

youth group)

.73 .19

__________________________

____________

__________

____

__________

____


you play intercollegiate or

varsity sports

<.01 .88


you play intramural sports.11 .82


you participate in activism

(petition, rally, protest)

.54 .55


Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 3 iterations.


Cronbach's

Alpha

Cronbach's

Alpha Based

on

Standardized

Items

N of

Items

34

.89 .90 6

The Cronbach’s Alpha for Group 1 (Amount of community service before college,

Participation in clubs/groups/honor societies before college, Leadership position in

community before college, Leadership position in school before college, Participation in

community organizations) is .89, which indicates good internal consistency among the

thesix items assigned.


Cronbach's

Alpha

Cronbach's

Alpha Based

on

Standardized

Items

N of

Items

.68 .69 2

The Cronbach’s Alpha for Group 2 (Participation in varsity sports before college,

Participation in intramural sports before college, Participation in activism before college)

is .68, which indicates questionable internal consistency among the two items assigned.

For this data set, the KMO statistic is .61, which is considered a mediocre value

but still acceptable (> 0.5 = acceptable; < 0.5 < KMO < 0.7 = mediocre).

For this data set, the Bartlett’s test is highly significant (p < .001, and therefore factor

analysis is appropriate (Table 12).

Table 12: Impact of Previous & Current Experience


Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .61

Bartlett's Test of Sphericity Approx. Chi-Square 64.85

Df 21

Sig. <.01

35

After rotation the two components together account for 56% of the total variance

(Table 13).


Compon

ent

Initial

Eigenval

ues

Extracti

on

Sums of

Squared

Loadin

gs

Rotation

Sums of

Squared

Loading

s

Total % of

Varianc

e

Cumulat

ive %

Tot

al

% of

Varian

ce

Cumulat

ive %

Tot

al

% of

Varian

ce

Cumulat

ive %

36

1 2.69 38.49 38.492.6

938.49 38.49

2.1

230.27 30.27

2 1.20 17.19 55.681.2

017.19 55.68

1.7

825.41 55.68

3 .96 13.69 69.37

4 .83 11.78 81.15

5 .62 8.88 90.02

6 .47 6.67 96.70

7 .23 3.30 100.00

Extractio

n

Method:

Principal

Compon

ent

Analysis

.

This output allowed us to group these seven variables into two groupings (Group

1 = Number of organizations, Number of volunteer experiences, Number of work

experiences; Group 2 = Number of leadership/professionalism training programs

attended, Number of professional organization/association meetings attended, Number of

courses taken requiring volunteerism, Number of awards/honors/scholarships received

(Table 14).

37

Table 14: Rotated Component Matrixa

Component

1 2

How many organizations have you been involved .84 .11

How many volunteer experiences have you been involved .83 .22

How many different work experiences have you obtained .50 .49

How many times did you attend leadership and/or professionalism training

programs-.43 .72

How many times did you attend a meeting of a professional organization or

association.25 .67

How many courses have you taken in which you completed a community

service or service learning component.31 .51

How many awards, scholarships, and honors received .38 .50


38

Rotation Method: Varimax with Kaiser Normalization.

a. Rotation converged in 3 iterations.


Cronbach's

Alpha

Cronbach's

Alpha Based

on

Standardized

Items

N of

Items

.72 .72 3

The Cronbach’s Alpha for Group 1 (Number of organizations, Number of volunteer

experiences, Number of work experiences) is .72, which indicates acceptable internal

consistency among the three items assigned.


Cronbach's

Alpha

Cronbach's

Alpha Based

on

Standardized

Items

N of Items

.45 .51 4

The Cronbach’s Alpha for Group 2 (Number of leadership/professionalism training

programs attended, Number of professional organization/association meetings attended,

Number of courses taken requiring volunteerism, Number of awards/honors/scholarships

received) is .45, which indicates unacceptable internal consistency among the 4 items

assigned.

Leadership Self-Efficacy scale

39

The Leadership Self-Efficacy scale was established by Ng, Ang, and Chan (2008)

to assess leadership self-efficacy. Permission was received from the authors to use this

questionnaire. The questionnaire asked respondents to report their confidence in the

ability to perform several aspects of leadership on a Likert scale ranging from 1 to 7,

where 1 indicated ‘not at all confident’ and 7 indicated ‘extremely confident’. Examples

of leadership aspects included: planning, communicating, delegating, and leading a team.

Reliability for leadership self-efficacy mean score was .93.

Survey Questions

Our research group developed additional survey questions based on research

obtained from literature reviews. Questions were selected to highlight themes from

previous leadership research to determine if these themes were consistent amongst our

leadership participants and to uncover potential new themes. To increase the reliability of

the study, all surveys were collected while students were at the same level of completion

of the leadership-training program. All surveys were self-administered per instruction.

Statistical Procedures

Analysis of SLPI using SLPI scoring software was used to print reports providing

an interpretation of individual SLPI results. The statistical software utilized to compute

all statistical procedures was SPSS, including the analysis of pretest and posttest scores

(SLPI and self-efficacy) as well as analysis of variables against SLPI and self-efficacy

scales. The tests used for comparing leadership groups included a paired t-test, Pearson

Correlation, repeated measurement ANOVA, and one-way MANOVA.

40

CHAPTER 4

FINDINGS: IN-CLASS SURVEYS

Outliers Treatment of the Data.

Before running in-depth analysis of the data collected, exploratory and descriptive

data analyses were run to look for errors and outliers. Descriptive statistics were

computed on variables such as ethnicity, age, gender, and the 30 questions of the SLPI

surveys. Examination of the frequencies and descriptive statistics tests that were

performed within the aforementioned parameters were mean, range, and standard

deviation. Some questions in the SLPI were missing pieces of information. These areas

were coded as “999”.

Descriptive Profile of Participants

41

These participants were all identified as student leaders at a selected Midwestern

university. The student leaders were placed into two separate groups, “group 111” and

“group 222.” An SLPI survey was administered to all participants in April 2013. The

SLPI was also administered four weeks later the experimental group received leadership

education. All participants were undergraduate students of various majors. There were

more females then males, a total of 24 (57%) and 18 (43%), respectively (Figure 1). The

age ranged from 18-56 years old(n= 43, m = 22.10, sd = 6.97). The mode for age was 18

years old (n = 10, 25.6%) and the mean age was 22.10 years old. There were 21 students

in the experimental and match groups. Of the 21 students in the experimental group that

filled out the original SLPI, a total of 9 post-SLPI surveys were returned four weeks later.

Figure 1: Gender

42

Table 17: Gender Descriptives

NValid 41

Missing 2

Mean 1.56

Mode 2.00

Std. Deviation .50

The majority of the participants were identified as being of White and Asian

ethnicity (12 of 43, 27.9%). The remaining 19 participants considered themselves to be

either Hispanic (n = 2, 4.65%), Black or African American (n = 6,14%), White Middle

Eastern (n =12, 27.9%), American Indian, Alaskan Native (n = 1,2.33%), or of the mixed

43

minority (n = 3,6.98%) (Figure 2).There were no differences found in the responses of

the SLPI between ethnicities.

Figure 2: Ethnicity

Leadership & Gender

Hₒ1: There is no significant difference between self-reported skills of “modeling the

way” between males and females based on the SLPI.

An independent t-test was used to compare the mean score of modeling the way

scores between males and females. There was no significant difference between modeling

the way skills reported by males and females t(41) = .80, p = .13, d = 0.13. The mean for

females was non-significantly higher than males (Table 18). The null hypothesis is

accepted (Table 18 & 19).

Table 18: SLPI Results between Males and Females

44

Gender N Mean Std. Deviation

Self- Model the Way male 18 23.28 3.91

female 23 24.17 3.30

Self- Inspire a shared vision male 18 24.06 3.40

female 23 24.74 3.82

Self- Challenge the Process male 18 23.78 3.64

female 23 24.96 3.07

Self- Enable Others to Act male 18 25.50 3.24

female 23 26.09 1.78

Self- Encourage the heart male 18 24.61 3.76

female 23 25.39 3.19

Percentile Model the way male 18 54.72 32.82

female 23 66.17 25.59

Percentile Inspire a shared vision male 18 71.00 23.32

female 23 74.35 25.58

Percentile Challenge the process male 18 72.06 25.49

female 23 81.39 21.37

Percentile Enable Others to act male 18 66.56 30.17

female 23 75.43 15.96

Percentile Encourage the Heart male 18 62.22 27.88

female 23 67.61 26.31

Table 19: Independent t-Test between Males and Females

45

Levene's Test for Equality of Variances

F Sig. t Df

Self- Model the Way

Equal variances assumed 2.45 .13 -.80 39

Equal variances not assumed -.78 33.25

Self- Inspire a shared vision

Equal variances assumed .47 .50 -.60 39


Self- Challenge the Process

Equal variances assumed 1.35 .25 -

1.13 39

Equal variances not assumed

-1.10 33.22

Self- Enable Others to Act

Equal variances assumed 7.65 .01 -.74 39


Self- Encourage the heart



Percentile Model the way


1.26 39


-1.22 31.51

Percentile Inspire a shared vision



Percentile Challenge the process


1.28 39


-1.25 33.11

Percentile Enable Others to act


1.21 39


-1.13 24.36

Percentile Encourage the Heart



46

Hₒ2: There is no significant difference between self-reported skills of “inspiring a shared

vision” between males and females based on the SLPI.

An independent t-test was used to compare means between the self-reported skills

of modeling the way between males and females. There was no significant difference

between inspiring a shared vision between males and females, t(41) = .60, p = .50,d = .10.

There was a non-significant higher mean score for females (Table 18). The null

hypothesis is accepted (Table 18& 19).

Hₒ3: There is no significant difference between self-reported skills of “challenging the

process” between males and females based on the SLPI.

An independent t-test was used to compare means between the skills of

challenging the process between males and females. There was no significant difference

between the mean scores for challenging the way between males and females, t(41) =

1.13, p = .25, d = .18. There was a non-significant higher mean score for females than

males (Table 18). The null hypothesis is accepted (Table 18 & 19).

Hₒ4: There is no significant difference between self-reported skills of “enabling others to

act” between males and females based on the SLPI.

An independent t-test was used to compare means between skills reported for

enabling others to act between males and females. There was a significant difference

between the ability of males and females to enable others to act, t(41) = .74, p = .01, d

= .12. The mean score for males and females (Table 18). The null hypothesis is rejected

(Table 18 & 19).

Hₒ5: There is no significant difference between self-reported skills of “encouraging the

heart” between males and females based on the SLPI.

An independent t-test was used to compare means between skills of encouraging

the heart between males and females, t(41) = .72, p = .80,d = .11. There was no

significant difference between scores for encouraging the heart between males and

females. There was a non-significant higher mean score for females than males (Table

18). The null hypothesis is accepted (Table 18 & 19).

Hₒ6: There is no difference between the percentile score for “modeling the way” between

males and females.

47

An independent t-test was used to compare means between percentile scores of

modeling the way between males and females. There was a significant difference

between the percentile scores of modeling the way between males and females, t(41) =

1.26, p = .02,d = .20. The mean score was higher for females than males (Table 18). The

null hypothesis is rejected (Table 18 & 19).

Hₒ7: There is no difference between the percentile score for “inspiring a shared vision”


An independent t-test was used to compare means between the percentile scores

of inspiring a shared vision between males and females. There was no significant

difference between the percentile scores between males and females, t(41) = .43, p = .69,

d = .07. There was a non-significant higher mean score for females than males (Table

18). The null hypothesis is accepted (Table 18 & 19).

Hₒ8: There is no difference between the percentile scores for “challenging the process”


An independent t-test was used to compare means between percentile scores for

challenging the process between males and females. There was no significant difference

between the percentile scores for challenging the process between males and females,

t(41) = 1.28, p = .15,d = 0.2. There was a non-significant higher mean score for females

than males (Table 18). The null hypothesis is accepted (Table 18 & 19).

Hₒ9: There is no difference between the percentile scores for “enabling others to act”


An independent t-test was used to compare the means between the percentile

scores for enabling others to act between males and females. There was a significant

difference between the percentile score for enabling others to act between males and

females, t(41) = 1.21, p = .01,d = .19. The mean score was higher for females than males

(Table 18). The null hypothesis is rejected (Table 18 & 19).

Hₒ10: There is no difference between the percentile scores for “encouraging the heart”


An independent t-test was used to compare means between the percentile scores

for encouraging the heart between males and females. There was no significant difference

between the percentile scores between males and females, t(41) = .63, p = .89,d = .10.

48

There was a non-significant higher mean score for females than males (Table 18). The

null hypothesis is accepted (Table 18 & 19).

Hₒ11: There is no difference between the self-efficacy levels of ability to perform

managerial leadership tasks reported between males and females.

An independent t-test was used to compare means between the ability to perform

managerial leadership tasks between males and females. There was no significant

difference between the managerial leadership tasks between males and females, t(39) =

2.0, p =.28, d = .31. There was a non-significant higher mean score for females than

males (Table 20). The null hypothesis is accepted (Table 20 & 21).

Table 20: Leadership Self-Efficacy Survey of Males and Females

Gender N Mean Std. Deviation

SE1- Managerial/administrative male 17 5.3882 1.03071

female 22 5.9818 .85503

SE2- Charisma male 17 5.5000 .96014

female 23 5.9130 .89382

SE3- Taking action male 17 5.9412 .91466

female 23 5.8406 1.05825

SE4- Personalization male 17 4.6471 .84344

female 23 5.3261 1.14424

49

Table 21: Independent t-Test of Leadership Survey between Males and Females


F Sig. t Df

SE1- Managerial/administrative


1.97 37


-1.92

30.89

SE2- Charisma

Equal variances assumed <.01 .93 -

1.40 38


-1.39

33.17

SE3- Taking action

Equal variances assumed .17 .68 .31 38

Equal variances not assumed .32 36.9

9

SE4- Personalization


2.06 38


-2.16

38.00


charismatic leadership tasks reported between males and females.

An independent t-test was used to compare the means between the self-efficacy

level of performing charismatic leadership tasks between males and females. There was

no significant difference between the self-efficacy level of males and females, t(39) = 1.4,

p = .93, d = .22. There was a non-significant higher mean score for females than males

(Table 20). The null hypothesis is accepted (Table 20 & 21).


leadership tasks that require taking action reported by males and females.

An independent t-test was used to compare the means between the self-efficacy

levels of the ability to perform leadership tasks that require taking action. There was no

significant difference between the self-efficacy levels between males and females, t(39) =

.31, p = .68,d = 0.05. There was a non-significant higher mean score for males than

females (Table 20). The null hypothesis is accepted (Table 20 & 21).

50


personalization leadership tasks reported by males and females.

An independent t-test was used to compare the mean self-efficacy levels between

the ability to perform personalization leadership tasks between males and females. There

was no significant difference between males and females, t(39) = 2.06, p = .18, d = .32.

There was a non-significant higher mean score for females than males (Table 20). The

null hypothesis is accepted (Table 20 & 21).

Leadership & Family

Frequency Distribution

The majority of the participants identified their mother’s highest education level

as being a bachelor’s degree (12 of 43, 27.9%). The remaining participants identified

their mother’s highest education level to be either some college or associates degree

(n=11, 25.6%), high school, GED, or less (n=8, 18.6%), master’s degree (n=4, 9.3%),

some graduate coursework (n=3, 7.0%), or doctorate, J.D., MD, or pharm D (n=2, 4.7%)

(Figure 3).

Figure 3: Mother Education Level

51

The majority of the participants identified their father’s highest education level as

being a bachelor’s degree (12 of 43, 27.9%). The remaining participants identified their

father’s highest education level to be either some college or associates degree (n=8,

18.6%), high school, GED, or less (n=7, 16.3%), master’s degree (n=6, 14.0%),

doctorate, J.D., MD, or pharm D (n=5, 11.6%), or some graduate coursework (n=2,

4.7%). (Figure 4).

Figure 4: Father Education Level

Hₒ15: Mother and father education level is not related to the ability to “model the way”,



A Pearson correlation coefficient was calculated for the relationship between

mother highest education level and SLPI pre-test responses (model the way, inspire a

shared vision, challenge the process, enable others to act, and encourage the heart). No

significant correlations (p > .05) were found examining the relationship between mother

highest education level and SLPI responses of model the way (r(40) = .60), inspire a

52

shared vision (r(40) = .68), enable others to act (r(40) = .51), encourage the heart(r(40)

= .60), and challenge the process (r(40) = .95).


father highest education level and SLPI responses (model the way, inspire a shared

vision, challenge the process, enable others to act, and encourage the heart). No

significant correlations (p > .05) were found examining the relationship between father

highest education level and SLPI responses of model the way (r(40) = .90), inspire a

shared vision (r(40) = .97), enable others to act (r(40) = .20), encourage the heart (r(40) =

.26), and challenge the process (r(40) = .70) (Table 22).

Based on the results of this data output, the null hypothesis: there is no

relationship between maternal level of education and SLPI response scores is accepted.

The null hypothesis: there is no relationship between paternal level of education and

SLPI response scores is also accepted.

Table 22: Pearson Correlation-Mother/Father Education and SLPI

Mother highest education level

Father highest education level

Self- Model the Way

Pearson Correlation -.09 .02

Sig. (2-tailed) .60 .89N 40 40


Pearson Correlation -.07 -.01

Sig. (2-tailed) .68 .97N 40 40


Pearson Correlation .01 .06

Sig. (2-tailed) .95 .70N 40 40



Sig. (2-tailed) .51 .20N 40 40



Sig. (2-tailed) .60 .26N 40 40

53

Mother highest education level

Pearson Correlation 1 .58**

Sig. (2-tailed) <.01N 40 39

Father highest education level

Pearson Correlation .58** 1

Sig. (2-tailed) <.01N 39 40

**. Correlation is significant at the 0.01 level (2-tailed).

Hₒ16: Family influence is not related to the ability to “model the way”, “inspire a shared

vision”, “challenge the process”, “enable others to act”, or “encourage the heart” in

terms of leadership.


family influence and SLPI responses (model the way, inspire a shared vision, challenge

the process, enable others to act, and encourage the heart).

No significant correlations (p > .05) were found when examining the relationship

between family influence on ability to model the way (r(24) = .56), challenge the process

(r(24) = .64), inspire a shared vision (r(24) = .96), enable others to act (r(24) = .76), and

encourage the heart (r(24) = .89).


relationship between family influence and SLPI response scores is accepted.

Table 23: Pearson Correlation-Family Influence and SLPI

Family

Self- Model the Way

Pearson Correlation -.12

Sig. (2-tailed) .56N 24


Pearson Correlation .01





54







Family

Pearson Correlation 1

Sig. (2-tailed)N 24

**. Correlation is significant at the 0.01 level (2-tailed).

After interviewing and transcribing the interviews of the students in the

experimental group, common themes were found in their responses regarding the

individual(s) who impacted the student’s development as a leader. The specific questions

that provided the answers to this are as follows: “Did others believe that you would

achieve? If so, who were those people?” “What role does family play in your

development as well as the development of your values?” “How did family impact your

confidence?” “Explain your family’s influence, if any, on your choice to volunteer or on

your choice to lead?” “What role, if any, does friends or significant others play in your

choice to volunteer and to lead?” “Who do you admire or emulate or from whom do you

get your inspiration from?”

As gathered from the interviews, the percentage of students who responded that

their mother influenced their leadership development was 88.9%. The percentage of

students who responded that their father influenced their leadership development was

77.8%. The percentage of students who responded that their mother and father both

influenced their leadership development was 77.8%.The percentage of students who

responded that their grandparents/uncles/aunts/cousins influenced their leadership

development was 22.2%.The percentage of students who responded that their sibling(s)

influenced their leadership development was 16.7%.The percentage of students who

responded that their friend(s) influenced their leadership development was 50%.The

percentage of students who responded that their significant other influenced their

55

leadership development was 0.00%.The percentage of students who responded that their

husband/wife/children influenced their leadership development was 11.1% (Table 24).

Table 24: Information from Interviews

Individual who influenced leadership development

Number of People (as gathered from interviews)

Mother Influence 16/18 (88.9%)Father Influence 14/18 (77.8%)Mother & Father Influence 14/18 (77.8%)Grandparents/Uncles/Aunts/Cousins Influence 4/18 (22.2%)Sibling Influence 3/18 (16.7%)Friend Influence 9/18 (50%)Significant Other Influence 0/18 (0.00%)Husband/Wife/Children Influence 2/18 (11.1%)

Leadership & Religion

Ho17: Attending religious services is not related to the ability to “model the way”,



A Pearson correlation coefficient was calculated for the relationship between how

often participants attend religious services and SLPI pre-test responses (model the way,

inspire a shared vision, challenge the process, enable others to act, and encourage the

heart).

A strong positive correlation (p < .05) was found between the frequency of

attendance to religious services and self-model the way (r(39) = .35), self-inspire a shared

vision (r(39) = .38), self-challenge the process (r(39) = .37), self-enable others to act

(r(39) = .32), self-encourage the heart (r(39) = .46, p < .01).


relationship between the frequency of attending religious services and the influence to

lead is rejected (Table 25).

56

Table 25: Pearson Correlation-Attendance of Religious Services and Pre-Test SLPI

How often attend

religious services

Self- Model the Way

Self- Inspire

a shared vision

Self- Challenge

the Process



How often attended religious services

Pearson Correlation

1 .35* .38* .37* .32* .46**

Sig. (2-tailed)

.02 .01 .02 .04 <.01

N 41 41 41 41 41 41

Ho18: Participating in prayer and/or meditation is not related to the ability to “model the

way”, “inspire a shared vision”, “challenge the process”, “enable others to act”, or


A Pearson correlation coefficient was calculated to determine the relationship

between how often a participant prays or meditates and SLPI pre-test responses (model

the way, inspire a shared vision, challenge the process, enable others to act, and

encourage the heart).

A strong negative correlation (p < .05) was found for the frequency of prayer

and/or meditation and self-model the way (r(39) = -.32), self-inspire a shared vision

(r(39) = -.40), self-challenge the process (r(39) = -.42, p < .01), self-enable others to act

(r(39) = -.35), self-encourage the heart (r(39) = -.52, p < .01).


relationship between the frequency of prayer and/or meditation and the influence to lead

is rejected (Table 26).

57

Table 26: Pearson Correlation- Prayer/Meditation and Pre-Test SLPI

How often do you pray

or meditate

Self- Model

the Way

Self- Inspire

a shared vision

Self- Challenge

the Process



How often do you pray or meditate

Pearson Correlation

1 -.32* -.40* -.42** -.35* -.52**

Sig. (2-tailed)

.043 .010 .006 .026 .001

N 41 41 41 41 41 41

A Spearman rho correlation coefficient was calculated to determine the

relationship between how often prays or meditates and SLPI pre-test responses (model

the way, inspire a shared vision, challenge the process, enable others to act, and

encourage the heart).

A moderate negative correlation (p > .05) was found for the frequency of prayer

and/or meditation and self-model the way (rho (39) = -.46), self-inspired a shared vision

(rho (39) = -.60), self-enable others to act (rho (39) = -.58), and self-encourage the heart

(rho (39) = -.58).

Correlations greater than 0.7 are considered strong, correlations less than 0.3 are

considered weak, and correlations between 0.3 and 0.7 are considered moderate. (Table

27).

Table 27: Spearman rho-Prayer/Meditation and Pre-Test SLPI

58

How often do

you pray or meditat

e

Self- Model the Way

Self- Inspir

e a shared vision

Self- Challeng

e the Process

Self- Enabl

e Others to Act

Self- Encourag

e the heart

Spearman's rho

How often do you pray or meditate

Correlation Coefficient

1.00 -.46 -.60* -.25 -.58* -.58*

Sig. (2-tailed)

. .129 .039 .425 .048 .048

N 41 12 12 12 12 12

Leadership and Volunteerism

Influence of Volunteerism on Participation in Other Activities Before College

Ho19: There is no relationship between community service participation before college

and event participation before college.


between community service activities prior to college and pre-test SLPI response (before

college events) scores.

A positive correlation was found between the two variables, r(40) = .36, p < .05.

Overall, there was a moderate positive correlation between participation in community

service before college and participation in events (sports/activism) before college (Table

28).

Based on the results of the data output, the null hypothesis: there is no

relationship between community service participation before college and event

participation before college is rejected.

Table 28: Pearson Correlation-Before College Community Service/Events

Self- Mod

el the

Way

Self- Inspire a

shared

visio

Self- Challenge the

Process

Self- Enab

le Others to Act


Before college

community

service

Before college events

(sports/activism)

59

nBefore college community service

Pearson Correlation

.51** .48** .55** .56** .49** 1 .36*

Sig. (2-tailed) <.01 <.01 <.01 <.01 <.01 .02

N 40 40 40 40 40 40 40

Before college events (sports/activism)

Pearson Correlation

.16 .16 .11 .30 .21 .36* 1

Sig. (2-tailed) .31 .32 .49 .06 .19 .02

N 41 41 41 41 41 40 41

Influence of Volunteerism Throughout Life on Participation in Various College Activities

Ho20: There is no relationship between community service participation in elementary

school and participation in college sports.


between participation in required community service in elementary school and

participation in college sports.

A negative correlation was found between the two variables, r(42) = -.38, p < .05.

Overall, there was a moderate negative correlation between participation in required

community service in elementary school and participation in college sports (Table 29).

Based on the results in the data output, the null hypothesis: there is no relationship

between community service participation in elementary school and participation in

college sports is rejected.

Table 29: Pearson Correlation-Before College and In College

Did your

elementary

Did your high

school

Did any of your

course

Before college commu

nity

Before college events

(sports/a

In college

, commu

In college, exte

In college

,

In college, sport

60

school require commu

nity service

require

community servic

e

s at BU

require

community servic

es

service ctivism) nity leaders

hip

rnal organization

school related

s

Did your elementary school require community service

Pearson Correlation

1 .26 -.13 .02 -.20 -.15 -.12 .28 -.38*

Sig. (2-tailed)

.09 .40 .90 .20 .35 .44 .07 .01

N 42 42 42 40 41 42 42 42 42

Did your high school require community service

Pearson Correlation

.26 1 .14 -.26 .09 -.01 -.06 -.03 -.07

Sig. (2-tailed)

.09 .39 .01 .56 .96 .73 .84 .66

N 42 42 42 40 41 42 42 42 42

Did any of your courses at BU require community service

Pearson Correlation

-.13 .14 1 -.24 -.08 -.09 -.23 -.28 .11

Sig. (2-tailed)

.40 .39 .14 .63 .55 .14 .07 .50

N 42 42 42 40 41 42 42 42 42

61

Before college community service

Pearson Correlation

.02 -.26 -.24 1 .36* .31 .41** .32* .25

Sig. (2-tailed)

.90 .01 .14 .02 .05 .01 .05 .12

N 40 40 40 40 40 40 40 40 40


Pearson Correlation

-.20 .09 -.08 .36* 1 .21 .25 .19 .49**

Sig. (2-tailed)

.20 .60 .63 .02 .19 .12 .23 <.01

N 41 41 41 40 41 41 41 41 41

In college, community leadership

Pearson Correlation

-.15 -.01 -.09 .31 .21 1 .51** .31* -.05

Sig. (2-tailed)

.35 .96 .55 .05 .19 <.01 .04 .77

N 42 42 42 40 41 42 42 42 42

In college, external organization

Pearson Correlation

-.12 -.06 -.23 .41** .25 .51** 1 .26 .09

Sig. (2-tailed)

.443 .7 .14 <.01 .12 <.01 .101 .59

N 42 42 42 40 41 42 42 42 42

In college, school related

Pearson Correlation

.28 -.03 -.28 .32* .19 .31* .26 1 -.03

Sig. .07 .84 .07 .05 .23 .04 .10 .88

62

(2-tailed)

N 42 42 42 40 41 42 42 42 42

In college, sports

Pearson Correlation

-.38* -.07 .11 .25 .49** -.05 .09 -.03 1

Sig. (2-tailed)

.01 .66 .50 .12 <.01 .77 .59 .88

N 42 42 42 40 41 42 42 42 42


and participation in community service before college.


between participation in external organizations in college and participation in community

service before college.


Overall, there was a moderate positive correlation between participation in external

organizations in college and participation in community service before college (Table

29).


relationship between participation in external organizations in college and participation in

community service before college is rejected.


and community leadership in college.


between participation in external organizations in college and community leadership in

college.


Overall, there was a moderate positive correlation between participation in external

organizations in college and community leadership in college (Table 29).

63


relationship between participation in external organizations in college and community

leadership in college is rejected.

Ho23: There is no relationship between participation in events (sports/activism) before

college and participation in college sports.


between participation in events (sports/activism) before college and participation in

college sports.


Overall, there was a moderate positive correlation between participation in events

(sports/activism) before college and participation in college sports (Table 29).

Based on the results of the data output, the null hypothesis: there is relationship

between participation in events (sports/activism) before college and participation in

college sports is rejected.


community leadership in college.


between participation in school-related community service in college and community

leadership in college.


Overall, there was a moderate positive correlation between participation in school-related

community service in college and community leadership in college (Table 29).


relationship between school-related community service and community leadership in

college is rejected.


community leadership before college.


between participation in school-related community service in college and community

service before college.

64


Overall, there was a moderate positive correlation between participation in school-related

community service in college and community leadership before college (Table 29).

Based on the results of the data set, the null hypothesis: there is no difference

between school-related community service and community leadership before college is

rejected.

Leadership & Leadership Styles

Hₒ26: There is no relationship between participating in community service activities

prior to college and SLPI response scores.


between participating in community service activities prior to college and pre-test SLPI

response (model the way) scores. A strong positive correlation was found (r(40) = .51, p

< .05) (Table 30).

Table 30: Correlations-SLPI

Self- Model the Way

Self- Inspir

e a share

d visio

n

Self- Challenge the

Process

Self- Enabl

e Others to Act


Before college

community

service

Before college events (sports/activis

m)

Before college community service

Pearson Correlation .51** .48** .55** .56** .49** 1 .36*

Sig. (2-tailed) .001 .002 <.001 <.001 .001 .023

N 40 40 40 40 40 40 40

65


Pearson Correlation .16 .16 .11 .30 .21 .36* 1

Sig. (2-tailed) .310 .315 .488 .057 .193 .023

N 41 41 41 41 41 40 41



response (inspire a shared vision) scores. A strong positive correlation was found (r(40) =

.48, p < .05)(Table 30).



response (challenge the process) scores. A strong positive correlation was found (r(40)

= .55, p < .05)(Table 30).



response (enable others to act) scores. A strong positive correlation was found (r(40)

= .56, p < .05)(Table 30).



response (encourage the heart) scores. A strong positive correlation was found (r(40)

= .49, p < .05) (Table 30).


relationship between participating in community service activities prior to college and

SLPI response scores is rejected for model the way, inspire a shared vision, challenge the

process, enable others to act, and encourage the heart.

Hₒ27: There is no relationship between participating in sporting/activism events prior to

college and SLPI response scores.


between participating in sporting/activism events prior to college and pre-test SLPI

66

response (model the way, inspire a shared vision, challenge the process, enable others to

act, encourage the heart) scores. A weak, non-significant correlation was found for model

the way (r(41) = .16, p > .05), inspire a shared vision (r(41) = .16, p >.05), challenge the

process (r(41) = .11, p > .05), enable others to act (r(41) = .30, p > .05), encourage the

heart (r(41) = .21, p > .05)(Table 30).


relationship between participating in sporting/activism events prior to college and SLPI

response scores is accepted.

Hₒ28: There is no relationship between frequency of acting as a group leader and SLPI

response scores.


between SLPI pre-test response (model the way, inspire a shared vision, challenge the

process, enable others to act, encourage the heart) scores and the frequency of acting as a

group leader. A weak, non-significant correlation was found for model the way (r(42)

= .20, p > .05), inspire a shared vision (r(42) = .20, p > .05), challenge the process (r(42)

= .31, p > .05), enable others to act (r(42) = .13, p > .05), encourage the heart (r(42)

= .22, p > .05) (Table 31).


relationship between frequency of acting as a group leader and SLPI response scores for

model the way, inspire a shared vision, challenge the process, enable others to act, and

encourage the heart is accepted.

67

Table 31: Pearson Correlation-Leadership and SLPI

Self- Model the Way

Self- Inspir

e a share

d vision

Self- Challeng

e the Process

Self- Enabl

e Others to Act

Self- Encourag

e the heart

How often did you act in the role of

a group leader

responsible for

organizing,

directing, and

motivating others

How often did you seek to be a group leader when the opportunity presents

How often did you

Pearson Correlatio

.20 .20 .31 .13 .22 1 .40**

68

act in the role of a group leader responsible for organizing, directing, and motivating others

n

Sig. (2-tailed) .21 .22 .05 .41 .16 <.01

N 41 41 41 41 41 41 41

How often did you seek to be a group leader when the opportunity presents

Pearson Correlation

.43** .31* .46** .04 .33* .43** 1

Sig. (2-tailed) <.01 .05 <.01 .82 .04 <.01

N 41 41 41 41 41 41 41

Hₒ29: There is no relationship between frequency of seeking out leadership opportunities

and SLPI response scores.


between SLPI pre-test response (model the way) scores and the frequency of seeking to

act as a group leader. A strong positive correlation was found for model the way (r(42)

= .43, p < .05)indicating a significant linear relationship between the two variables (Table

31).


between SLPI pre-test response (inspire a shared vision) scores and the frequency of

seeking to act as a group leader. A strong positive correlation was found for model the

69

inspire a shared vision (r(42) = .31, p < .05)indicating a significant linear relationship

between the two variables (Table 31).


between SLPI pre-test response (challenge the process) scores and the frequency of

seeking to act as a group leader. A strong positive correlation was found for challenge the

process (r(42) = .46, p < .05)indicating a significant linear relationship between the two

variables (Table 31).


between SLPI pre-test response (encourage the heart) scores and the frequency of seeking

to act as a group leader. A strong positive correlation was found for encourage the heart

(r(42) = .40, p < .05) indicating a significant linear relationship between the two variables

(Table 31).

A Pearson correlation coefficient was calculated examining the relationship

between SLPI pre-test response (enable others to act) scores and the frequency of seeking

to act as a group leader. A weak, non-significant correlation was found for enable others

to act (r(42) = .04, p > .05) (Table 31).


relationship between frequency of seeking out leadership opportunities and SLPI

response scores is rejected for model the way, inspire a shared vision, challenge the

process and encourage the heart but is accepted for enable others to act.

Hₒ30: Individuals’ GPA does not have any effect on SLPI scores.

A one-way MANOVA was calculated to determine the effect of GPA and pre-test

SLPI response (model the way, inspire a shared vision, challenge the process, enable

others to act, encourage the heart) scores. No significant effect was found (Lambda (15,

91.5) = .71, p > .05) (Table 34).

Based on the results of this data output, the null hypothesis individuals’ GPA does

not have any effect on SLPI scores is accepted.

An interesting point to note is the GPA range of 33.49 had the highest mean

across all SLPI sections although no significance was seen.

70

Table 32: Descriptive Statistics-GPA and SLPI

Grade point average

Mean Std. Deviation

N

Self- Model the Way

3.5-4 23.90 3.18 213-3.49 24.00 3.22 112.5-2.99 23.33 4.46 62-2.49 23.00 7.00 3Total 23.78 3.56 41


3.5-4 24.14 3.68 213-3.49 25.00 2.90 112.5-2.99 24.33 3.08 62-2.49 24.67 7.57 3Total 24.44 3.61 41


3.5-4 24.52 3.53 213-3.49 24.55 2.77 112.5-2.99 24.17 3.54 62-2.49 24.00 5.29 3Total 24.44 3.34 41

71


3.5-4 25.29 2.67 213-3.49 25.91 2.55 112.5-2.99 27.33 1.51 62-2.49 26.33 2.52 3Total 25.83 2.51 41


3.5-4 24.76 3.77 213-3.49 25.82 2.23 112.5-2.99 24.50 3.62 62-2.49 25.33 5.51 3Total 25.05 3.43 41

Table 33: Grand Mean

Dependent Variable Mean

Std. Error

95% Confidence IntervalLower Bound

Upper Bound

Self- Model the Way 23.56 .74 22.07 25.05Self- Inspire a shared vision 24.54 .75 23.02 26.05

Self- Challenge the Process 24.31 .69 22.91 25.71Self- Enable Others to Act 26.22 .50 25.20 27.23Self- Encourage the heart 25.10 .70 23.68 26.53

Table 34: Multivariate Tests

Effect Value F Hypothesis df

Error df

Sig. Partial Eta Squared

Intercept Pillai's Trace .99 503.46b 5.00 33.00 <.001 .98

Wilks' Lambda .01 503.46b 5.00 33.00 <.001 .99

Hotelling's Trace 76.28 503.46b 5.00 33.00 <.001 .99

Roy's Largest Root 76.28 503.46b 5.00 33.00 <.001 .99

T18A Pillai's Trace .31 .80 15.00 105.00 .68 .10

Wilks' Lambda .71 .80 15.00 91.50 .68 .11

Hotelling's Trace .38 .80 15.00 95.00 .68 .11

Roy's Largest .28 1.96c 5.00 35.00 .11 .22

72

Root


scores.

The pre-test for model the way (M = 23.83, sd = 4.09)and the post-test for model

the way (M = 26.33, sd= 3.60). A significant increase from pre-test SLPI scores to

posttest SLPI scores was found (t(11) = 3.51, p < .05).(Table 36)

A paired-sample t -test was calculated to compare the mean pre-test SLPI

response (challenge the process) scores to the mean posttest SLPI response scores. The

pre-test for challenge the process (M = 24.50, sd= 2.94) and the post-test for challenge

the process (M = 26.17, sd= 3.10). A significant increase from pre-test SLPI scores to

posttest SLPI scores was found (t(11) = 2.64, p < .05). (Table36)

A paired-sample t-test was calculated to compare the mean pre-test SLPI response

(inspire a shared vision, enable others to act, encourage the heart) scores to the mean

posttest SLPI response scores. The pre-test for inspire a shared vision (M = 24.92, sd =

3.32), enable others to act (M = 25.75, sd= 2.53), encourage the heart (M = 25.33, sd=

3.08) and the posttest for inspire a shared vision (M = 26.08 sd= 2.91), enable others to

act (M = 26.50, sd= 3.15), encourage the heart (M = 25.92, sd= 4.48). No significant

difference from the pre-test to the posttest was found for inspire a shared vision (t(11) =

2.18, p > .05), enable others to act (t(11) = -.96, p >.05), encourage the heart (t(11) =

-.85, p > .05)(Table 36).

Based on the results of this data output, the null hypothesis: the leadership course

will have no effect on pre-test to posttest SLPI scores is rejected for model the way and

challenge the process but is accepted for inspire a shared vision, enable others to act, and

encourage the heart.

Table 35: Paired Samples Statistics

Mean N Std. DeviationStd. Error Mean

Pair 1 Self- Model the Way 23.83 12 4.09 1.18

Self- Model the Way 26.33 12 3.60 1.04

Pair 2 Self- Inspire a shared vision 24.92 12 3.32 .96

73

Self- Inspire a shared vision 26.08 12 2.91 .84

Pair 3 Self- Challenge the Process 24.50 12 2.94 .85

Self- Challenge the Process 26.17 12 3.10 .89

Pair 4 Self- Enable Others to Act 25.75 12 2.53 .73

Self- Enable Others to Act 26.50 12 3.15 .91

Pair 5 Self- Encourage the heart 25.33 12 3.08 .89

Self- Encourage the heart 25.92 12 4.48 1.29

Table 36: Paired Samples t-Test

Paired Differences Mean Std. Deviation t df Sig. (2-

tailed)Pair 1

Self- Model the Way - Self- Model the Way -2.50 2.47 -3.51 11 .005

Pair 2

Self- Inspire a shared vision - Self- Inspire a shared vision -1.17 1.85 -2.18 11 .052

Pair 3

Self- Challenge the Process - Self- Challenge the Process -1.67 2.19 -2.64 11 .023

Pair 4

Self- Enable Others to Act - Self- Enable Others to Act -.75 2.70 -.96 11 .357

Pair 5

Self- Encourage the heart - Self- Encourage the heart -.58 2.39 -.85 11 .416


scores in males.

A paired-samples t-test was calculated to compare the mean pre-test SLPI

response (model the way) scores to the mean posttest SLPI response scores for males.

The pre-test for model the way (M = 22.40, sd= 5.50) and the posttest for model the way

(M = 26.00, sd= 3.74). A significant increase from pre-test SLPI scores to posttest SLPI

scores was found (t(4) = 3.50, p < .05)(Table 38).


response (challenge the process) scores to the mean posttest SLPI response scores for

males. The pre-test for challenge the process (M = 23.40, sd= 4.16) and the posttest for

challenge the process (M = 25.80, sd= 3.90). A significant increase from pre-test SLPI

scores to posttest SLPI scores was found (t(4) = 2.95, p < .05) (Table 38).

74


response (inspire a shared vision, enable others to act, encourage the heart) scores to the

mean posttest SLPI response scores for males. The pre-test for inspire a shared vision (M

= 23.60, sd = 3.36), enable others to act (M = 25.40, sd= 3.64), encourage the heart (M =

25.40, sd= 2.79) and the posttest for inspire a shared vision (M = 26.00, sd= 2.83), enable

others to act (M = 27.40, sd= 2.79), encourage the heart (M = 26.60, sd= 3.85). No

significant difference from the pre-test scores to the post-test scores was found for inspire

a shared vision (t(4) = 2.59, p > .05), enable others to act (t(4) = 1.58, p > .05),

encourage the heart (t(4) = 1.00, p > .05) (Table38).

Based on the results of this data output, the null hypothesis: the leadership course

will have no effect on pre-test to posttest SLPI scores in males is rejected for model the

way and challenge the process but is accepted for inspire a shared vision, enable others to

act, and encourage the heart.

Table 37: Paired Samples Statistics Male

Mean N Std. Deviation Std. Error Mean



Pair 2 Self- Inspire a shared vision 23.60 5 3.36 1.50

Self- Inspire a shared vision 26.00 5 2.83 1.26

Pair 3 Self- Challenge the Process 23.40 5 4.16 1.86

Self- Challenge the Process 25.80 5 3.90 1.74

Pair 4 Self- Enable Others to Act 25.40 5 3.65 1.63

Self- Enable Others to Act 27.40 5 2.79 1.25

Pair 5 Self- Encourage the heart 25.40 5 2.79 1.25Self- Encourage the heart 26.60 5 3.85 1.72

75

a. Gender = male

Table 38: Paired Samples Test Male

Paired Differences Mean Std. Deviation t df Sig. (2-

tailed)

Pair 1 Self- Model the Way - Self- Model the Way -3.60 2.30 -3.50 4 .025

Pair 2 Self- Inspire a shared vision - Self- Inspire a shared vision -2.40 2.07 -2.59 4 .061

Pair 3 Self- Challenge the Process - Self- Challenge the Process -2.40 1.82 -2.95 4 .042

Pair 4 Self- Enable Others to Act - Self- Enable Others to Act -2.00 2.83 -1.58 4 .189

Pair 5 Self- Encourage the heart - Self- Encourage the heart -1.20 2.68 -1.00 4 .374

a. Gender = male

Hₒ33: The leadership training program will have no effect on pre-test to post-test SLPI

scores in females.

A paired- samples t- test was calculated to compare the mean pre-test SLPI

response (model the way, inspire a shared vision, challenge the process, enable others to

act, encourage the heart) scores to the mean posttest SLPI response scores for females.

The pre-test for model the way (M = 24.86, sd= 2.73), inspire a shared vision (M = 25.86,

sd = 3.18), challenge the process (M = 25.29, sd= 1.60), enable others to act (M = 26.00,

sd= 1.63), encourage the heart (M = 25.29, sd= 3.50) and the posttest for model the way

(M = 26.57, sd= 3.78), inspire a shared vision (M = 26.14, sd= 3.18), challenge the

process (M = 26.43, sd= 2.70), enable others to act (M = 25.86, sd= 3.44), encourage the

heart (M = 25.43, sd= 5.13). No significant difference from the pre-test scores to the

posttest scores was found for model the way (t(6) = 1.87, p > .05), inspire a shared vision

(t(6) = -.68, p > .05), challenge the process (t(6) = 1.26, p > .05), enable others to act (t(6)

= .16, p > .05), encourage the heart (t(6 )= -.17, p > .05) (Table 40).

76

Based on the results of this data output, the null hypothesis: the leadership

training program will have no effect on pre-test to posttest SLPI scores in females is

accepted.

Table 39: Paired Samples Statistics Female

Mean N Std. Deviation

Std. Error Mean



Pair 2 Self- Inspire a shared vision 25.86 7 3.18 1.20

Self- Inspire a shared vision 26.14 7 3.18 1.20

Pair 3 Self- Challenge the Process 25.29 7 1.60 .61

Self- Challenge the Process 26.43 7 2.70 1.02

Pair 4 Self- Enable Others to Act 26.00 7 1.63 .62

Self- Enable Others to Act 25.86 7 3.44 1.30

Pair 5 Self- Encourage the heart 25.29 7 3.50 1.32Self- Encourage the heart 25.43 7 5.13 1.94

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a. Gender = female

Table 40: Paired Samples Test Female

Paired Differences

Mean Std. Deviation t df Sig. (2-tailed)

Pair 1

Self- Model the Way - Self- Model the Way

-1.71 2.43 -1.87 6 .111

Pair 2

Self- Inspire a shared vision - Self- Inspire a shared vision

-.29 1.11 -.68 6 .522

Pair 3 Self- Challenge the Process - Self-

-1.14 2.41 -1.26 6 .256

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Challenge the Process

Pair 4

Self- Enable Others to Act - Self- Enable Others to Act

.14 2.41 .16 6 .881

Pair 5

Self- Encourage the heart - Self- Encourage the heart

-.14 2.27 -.17 6 .873

a. Gender = female

Figure 5: Model the Way

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Figure 6: Challenge the Process

Leadership & Self-Efficacy

Hₒ34: There is no difference between Group 111 (experimental group) and Group 222

(match group) and self-efficacy scores.

An independent sample t-test was used to compare the mean scores of self-

efficacy for managerial/administrative, charisma, taking action, and personalization

between the experimental and match leadership groups. The (Sig) p value is greater

than α for all four independent t-tests (SE1 – SE4). We assume the variances are equal

(Table 41).

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Table 41: Independent Sample Test-Variance


t-test for Equality of Means

F Sig. T df Sig. (2-tailed)


Equal variances assumed

.02 .90 -.42 38


-.42 38.00

SE2- Charisma Equal variances assumed

1.03 .32 .21 39


.21 37.63

SE3- Taking action


.11 .74 .04 39


.04 36.66



.02 .90 -.62 39


-.62 38.38

A t-test failed to reveal a statistically significant difference between the mean

number of SE1 that the experimental group had (M = 5.69, sd = .98) and that the match

group had (M = 5.82, sd = 1.0), t(38) = .42, p = .68, α = .05. A t-test failed to reveal a

statistically significant difference between the mean number of SE2 that the experimental

group had (M = 5.80, sd = .83) and that the match group had (M = 5.74, sd = 1.06), t(39)

= .21, p = .84, α = .05. A t-test failed to reveal a statistically significant difference

between the mean number of SE3 that the experimental group had (M = 5.92, sd= .84)

and that the match group had (M = 5.91, sd = 1.14), t(39) = .04, p = .97, α = .05. A t-test

failed to reveal a statistically significant difference between the mean number of SE4 that

the experimental group had (M = 4.98, sd = 1.15) and that the match group had (M =

5.19, sd = 1.07), t(39) = .62, p = .54, α = .05 (Table 42).

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Table 42: Independent Sample Test-Comparison of Experimental and Match Group

Group # N Mean Std. Deviation Std. Error Mean

SE1- Managerial/administrative 111.00 20 5.69 .98 .22

222.00 20 5.82 .99 .22

SE2- Charisma 111.00 20 5.80 .83 .19

222.00 21 5.74 1.06 .23

SE3- Taking action 111.00 20 5.92 .84 .19

222.00 21 5.90 1.14 .25

SE4- Personalization 111.00 20 4.98 1.15 .26

222.00 21 5.19 1.07 .23

Hₒ35: There is no relationship between the self-efficacy pre-test scores and age.


between self-efficacy pre-test scores and age (SE1: managerial/administrative, SE2:

charisma, SE3: taking action, and SE4: personalization). No significant correlations (p

< .05) were found when examining the relationship between self-efficacy pre-test scores

and age responses of SE1: managerial/administrative (r(37) = .65), SE2: charisma (r(38)

= .69), SE3: taking action (r(38) = .13), and SE4: personalization (r(38) = .96) (Table

43).


relationship between the self-efficacy pre-test scores and age is accepted.

Table 43: Pearson Correlation-Self-Efficacy Pre-Test and Age

Age


SE2- Charisma

SE3- Taking action


Age

Pearson Correlation

1 .08 .07 .25 -.01

Sig. (2-tailed)

.65 .69 .13 .96

N 39 37 38 38 38

83

Hₒ36: There is no relationship between the self-efficacy posttest scores and age.

A Pearson correlation coefficient was calculated for the relationship between self-

efficacy posttest scores and age (SE1: managerial/administrative, SE2: charisma, SE3:

taking action, and SE4: personalization). No significant correlations (p < .05) were found

when examining the relationship between self-efficacy posttest scores and age responses

of SE1: managerial/administrative (r(8) = .94), SE2: charisma (r(8) = .70), SE3: taking

action (r(8) = .77), and SE4: personalization (r(8) = .97) (Table 44).


relationship between the self-efficacy posttest scores and age is accepted.

Table 44: Pearson Correlation- Self-Efficacy Posttest and Age

Age

pSE1- Managerial/administrative

pSE2- Charisma

pSE3- Taking action

pSE4- Personalization

Age

Pearson Correlation

1 .03 .17 .13 -.02

Sig.(2-tailed)

.94 .70 .77 .97

N 39 8 8 8 8

Hₒ37: There is no difference between the pre and posttest scores for SE1:

managerial/administrative in relation to leadership.

A paired-samples t-test was used to compare the mean pre and posttest scores for

self-efficacy (SE1: managerial/administrative). The pre-test for SE1:

managerial/administrative (M = 5.66, sd = 1.19) and posttest for pSE1:

managerial/administrative (M = 6.11, sd =1.19) (Table 45).

Based on the results of this data output, the null hypothesis: there is no difference

between the pre and posttest scores for SE1: managerial/administrative in relation to

leadership is accepted.

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Table 45: Pearson Correlation-Pre and Posttest Self-Efficacy

Mean N Std. Deviation

Pair 1


5.66 7 1.19

pSE1- Managerial/administrative

6.11 7 1.19

Pair 2 SE2- Charisma 5.82 7 1.03pSE2- Charisma 6.00 7 .84

Pair 3 SE3- Taking action 5.90 7 .88pSE3- Taking action 5.86 7 .92

Pair 4 SE4- Personalization 5.14 7 1.07pSE4- Personalization 5.79 7 .99

Hₒ38: There is no difference between the pre and posttest scores for SE2: charisma in



self-efficacy (SE2: charisma). The pre-test for SE2: charisma (M = 5.82, sd = 1.03) and

posttest for pSE2: charisma (M = 6.00, sd = .84) (Table 45).


between the pre and posttest scores for SE2: charisma in relation to leadership is

accepted.

Hₒ39: There is no difference between pre and posttest scores for SE3: taking action in



self-efficacy (SE3: taking action). The pre-test for SE3: taking action (M = 5.90, sd = .88)

and posttest for pSE2: charisma (M = 5.86, sd = .92) (Table 45).


between the pre and posttest scores for SE3: taking action in relation to leadership is

accepted.

Hₒ40: There is no difference between the pre and posttest scores for SE4: personalization

in relation to leadership.

85


self-efficacy (SE4: personalization). The pre-test for SE4: personalization (M = 5.14, sd =

1.07) and posttest for pSE2: personalization (M = 5.79, sd = .99) (Table 45).


between the pre and posttest scores for SE4: personalization in relation to leadership is

accepted.

Table 46: Paired Samples Test-Pre and Posttest Self-Efficacy

Paired Differences t df

Sig. (2-

tailed)Mean Std.

DeviationStd.

Error Mean

95% Confidence

Interval of the Difference

Lower Upper

Pair 1

SE1- Managerial/administrative - pSE1- Managerial/administrative

-.46 .36 .14 -.79 -.12 -3.36 6 .02

Pair 2

SE2- Charisma - pSE2- Charisma

-.18 .19 .07 -.35 -.01 -2.5 6 .05

Pair 3

SE3- Taking action - pSE3- Taking action

.05 .63 .24 -.54 .63 .20 6 .85

Pair 4

SE4- Personalization - pSE4- Personalization

-.64 .63 .24 -1.22 -.06 -2.7 6 .04

86

CHAPTER 5

DISCUSSION

Conclusions

“How do university students develop as leaders?” was the primary guiding

question that initiated our research. To answer this question we focused our research on

current leaders at a university and asked them several questions regarding their age and

gender, as well as questions concerning campus involvement, volunteerism, religion, and

their parent’s involvement in their lives. The nature of our mixed methods approach

offered easy documentation through journal articles, books, and special interest groups

(33). The importance of our study lies in the data collected and analyzed using the SPSS

software.

There were many significant factors encompassing the themes researched that had

an impact on the development of the university leaders. There were significant gender

differences in the self-reported skills of “enabling others to act” as well as the percentile

scores for “modeling the way” and “enabling others to act.” There was a significant

correlation between the attendance frequency of religious services and all of the

leadership categories in the SLPI. Coinciding with their attendance at religious services is

the frequency of prayer and/or meditation, which also had a strong significance for each

leadership category. Also, there is a significant relationship between school-related

community service and community leadership in college.

Applications

All across the country, universities are sifting through applications from graduate

school hopefuls as well as students who are interested in joining an accredited dietetic

internship program. Students applying for these programs strive to make their application

noticeable to those reviewing and making the final decisions for acceptance. Making

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applications “noticeable” is usually done by volunteering, conducting research, obtaining

leadership positions, and having work experience in the field of interest. Our study on

leadership should be considered for use by admission counselors and board members

alike when choosing applicants for graduate school or specifically, for dietetic

internships. Leadership is not considered a primary focus on current applications for most

institutions, but would benefit both students and universities. Future related research can

further the discussion on the importance of leadership and the acceptance of dietetic

students into dietetic internships. Using similar methods, extending the research to

dietetic students could potentially offer insight into which applicants offer higher success

rates in their future endeavors as registered dietitians.

In a pilot study conducted by Jessica Frein, titled, “Measuring the Impact of

Leadership and Professionalism Training on Dietetic Students at the University of

Wisconsin-Stout,” the effects of a leadership program on dietetic students were

examined. Many similarities regarding methodology and findings are seen between this

pilot study and our study. The students at the university were evaluated using the SLPI

adapted from the LPI. Frein’s study also used demographic data to determine any effects

it may have on leadership characteristics. The findings of this study coincide with our

findings regarding the leadership category “challenging the process.”Frein stated, “the

leadership practice challenging the process, is involved with searching out opportunities

to grow and improve, as well as taking risks and experimenting to learn” (34).

In a study conducted by Dugan and Komives, factors associated with leadership

development in college students utilizing a multi-institutional national study were

examined. Similarities regarding changes in leadership over time were seen between this

multi-institutional study and our study. Students' perceptions on leadership changed over

time as did pre-test to posttest SLPI scores based on the multi-institutional study and our

study, respectively. Based on the results of our study, the leadership training program did

have an effect on pre-test to posttest SLPI scores in the categories of model the way and

challenge the process. According to the findings of the study conducted by Dugan and

Komives, the students' perceptions of leadership positively increased for consciousness of

self and leadership efficacy after completion of the leadership training program (3). The

88

students’ perceptions of leadership also positively increased for congruence,

collaboration, common purpose, citizenship, and change, but to a lesser degree. In

general, it was determined that short, moderate, and long-term leadership training

experiences all had significant effects on leadership efficacy (in comparison with no

leadership training) (3). Although our study did find an increase from pre-test to post-test

SLPI scores (specifically in males), a larger sample size may have provided us with even

more significant results, making the results more generalizable.

Generalizability

The issue of limited generalizability is present in our current study. With a

limited generalizability, applying the results to other colleges and institutions would be

more difficult. Our sample is unique and our research site offers a smaller sample size

due to the size of the institution. The relatively small sample size amongst the

experimental group (pre-test, post-test) also makes our results difficult to apply to the

general population.

Our results from the SLPI are highly generalizable since the SLPI is used

throughout the United States. Therefore, other researchers utilizing the SLPI should be

able to draw conclusions and compare their results with those of our study.

Limitations

There are some limitations within our study that have an effect on future

implications. We gathered quantitative and qualitative data, with the majority of the data

being quantitative. Qualitative data was not able to be analyzed due to unobtainable

NVivo software. This software is used for qualitative and mixed methods research and is

used to collect, organize, and analyze content in order to uncover subtle connections and

justify findings. This software would have been beneficial for analyzing the information

provided from the paired interviews that were conducted during the study.

89

Recommendations

Recommendations for further research include the use of NVivo to further

connect and comprehend the quantitative data output obtained from the SPSS software.

Improvements can also be made on the sample population by ensuring that institutions

conducting future studies have larger student populations. Conducting a study similar to

ours, but on a larger scale, may provide more insight and possible significant findings

surrounding the themes and their impact on the development of university leaders. Also,

it may be beneficial to extend the sample size to individuals other than active leaders,

providing a broader scope of individuals that are included in studies. By doing so, further

connections may be seen existing between leaders and non-leaders. Extensive research

comparing two separate groups (non-leaders and current leaders) may also be beneficial

to examine differences seen in these two groups and how they relate to the leadership

themes researched.

90

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thesis manuscript

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