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Evaluation of early career exploration interventions in a medical school professional development program

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Evaluation of early career exploration interventions in a medical school professional development program

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Evaluation of Early Career Exploration Interventions in a Medical School
Professional Development Program
by
Thomas Hector Hurtado

Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education

May, 2021

© Copyright by Thomas Hector Hurtado 2021
All Rights Reserved

The Committee for Thomas Hector Hurtado certifies the approval of this Dissertation

Boyd Richards
Patricia Tobey
Bryant Adibe, Committee Chair

Rossier School of Education
University of Southern California
2021
iv
Abstract
This dissertation examines early interventions with medical students with the goal to improve
self-authorship including specialty exploration resources. The structure of the study utilized a
gap analysis framework (Clark & Estes, 2008). Specifically, the study examined knowledge,
motivation, and organization (KMO) influencers to evaluate the Wasatch Medical School
(WMS) sponsored Purpose in Medicine Program (PMP). The methodology employed a
quantitative survey sent to 127 first-year medical students who had the opportunity to complete a
one-year certificate in the PMP. Ninety-seven (76%) completed the survey. The data analysis
process highlights a student tendency to prioritize declarative knowledge within the learning
environment at the expense of engaging in helpful resources and opportunities. Evidence from
the study also indicates that the PMP has a positive influence on student perspectives toward the
value of having purpose, building a personal network, and seeking help from career counseling
resources. The included implementation plan outlines needed actions to build upon identified
needs and assets with the express purpose to improve PMP organizational resources to enhance
medical student specialty exploration and self-authorship activities.

v
Dedication
To my children, may you lead purpose-driven lives.
vi
Acknowledgements
There are so many people to thank; it truly takes a village of family, friends, faculty,
staff, and colleagues to pursue a doctoral degree. To Laura, thank you for investing and believing
in me through it all—I could not have done this without you. To our children, Sam, Stella, and
Ruby, thanks for being patient and supportive during the long hours, including when I was a
stressed-out dad. To my mother for showing me from an early age the immense value of
education and the pursuit of lifelong learning; your words of encouragement have given me
courage and determination. To my father for teaching me about self-awareness, growth mindset,
and perseverance. To Don for your steady and kind example of leadership throughout my life. To
my siblings, thank you for always being there. To the rest of my extended family and friends,
thank you for lifting me when I needed it.
To my colleagues, you became a phenomenal team of experts to guide and challenge me
throughout the process. To Tony Tsai, thanks for being my creative partner, for teaching me to
live a purpose-driven life and to amplify this message throughout academic medicine and
beyond. To the student leaders who helped create and grow the program: Eli, Jordan, Bridger,
Sam, Ellie, Hank, Sadie, Corey, Karlie, Savannah, and Brandon—I am lucky to work alongside
and learn from each of you. To Dr. Boyd Richards, thank you for taking me under your wing, for
being my mentor, on my committee, and for all the early morning meetings; you have been
instrumental in my education and development. To Marc Pritchard for being the first person I
talked to about the OCL program and for the countless tracked changes, spur of the moment
meetings, sage advice, APA chiding, quick responses, and for helping me from day one to the
end, thank you brother! To Dr. Adam Stevenson for supporting me on my journey, being an
amazing boss, and offering unwavering encouragement to build this program. To Dr. Wayne
vii
Samuelson for providing me dedicated time and resources to perform research and write—Thank
you so much for the show of support. To Christina Tushman and Shira Kaplan at the AAMC for
your expertise, partnership, and support of the program. To Dr. Sharon Aiken-Wisniewski for
your continued mentorship and investment in my graduate education. To my student affairs
team, thank you for all you have taught me about helping students and each other—you are the
best. To Dr. Richard Sudweeks, thank you for weighing in on my data analysis process and for
all your helpful advice. To Ema Valverde, thank you for your help with the coding process.
To my professors, you made the OCL program phenomenal; I will continue to learn from
and apply these lessons for the rest of my career. To Dr. Bryant Adibe, thank you for helping
shape my problem of practice and for taking me across the finish line; your knowledge of
academic medicine and medical student life has been invaluable. To Dr. Patricia Tobey, thank
you for being on my committee and providing your talents and energy. To the Student Affairs
staff at Rossier, thanks for all your efforts; you are unsung heroes who deserve more credit for
what you do. To my OCL Cohort 12, I have loved getting to know you and look forward to
collaborating in the future. Finally, to Jonathan Eldridge and Jessica Walter, thank you for being
in the trench with me and for all the support—you are wonderful colleagues who are doing
amazing work.

viii
Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ....................................................................................................................................... v
Acknowledgements ........................................................................................................................ vi
List of Tables ................................................................................................................................. xi
List of Figures ............................................................................................................................... xii
Chapter One: Overview of the Study .............................................................................................. 1
Context and Background of the Problem ....................................................................................1
Purpose of the Project and Research Questions .........................................................................4
Importance of the Study ................................................................................................................4
Overview of Theoretical Framework and Methodology ..........................................................5
Definition of Terms .......................................................................................................................6
Organization of the Dissertation ..................................................................................................7
Chapter Two: Literature Review .................................................................................................... 8
Self-Authorship ..............................................................................................................................8
Medical Student Knowledge ..................................................................................................... 10
Medical Student Motivation ...................................................................................................... 15
Medical Education Reform: Professional Development ....................................................... 19
Conceptual Framework .............................................................................................................. 28
Summary ...................................................................................................................................... 31
Chapter Three: Methodology ........................................................................................................ 33
Research Questions ..................................................................................................................... 33
Overview of Design .................................................................................................................... 33
ix
Research Setting .......................................................................................................................... 34
The Researcher ............................................................................................................................ 35
Data Sources ................................................................................................................................ 35
Validity and Reliability .............................................................................................................. 39
Ethics ............................................................................................................................................ 41
Chapter Four: Findings ................................................................................................................. 43
Participating Stakeholders ................................................................................................ 43
Quantitative Analysis Overview ....................................................................................... 46
Results for Knowledge Influencers ................................................................................... 49
Results for Motivation Influencers ................................................................................... 60
Results for Organizational Influencers ............................................................................. 66
Summary of Validated Influences .................................................................................... 74
Chapter Five: Recommendations and Discussion......................................................................... 78
Discussion of Findings and Results .................................................................................. 78
Recommendations for Practice ......................................................................................... 79
Integrated Knowledge, Motivation, and Organizational Recommendations .................... 90
Limitations and Delimitations........................................................................................... 93
Recommendations for Future Research ............................................................................ 94
Conclusion ........................................................................................................................ 95
References ..................................................................................................................................... 97
Appendix A: Survey Instrument ................................................................................................. 119
Appendix B: Declarative Knowledge, Self-Determination, and Training Items ........................ 125

x
Appendix C: Self-Efficacy Correlation and Reliability .............................................................. 129
Appendix D: Autonomous Functioning Index ............................................................................ 130

xi
List of Tables
Table 1 Data Sources 34
Table 2 Respondent Demographics 44
Table 3 Quantitative Subgroups for Analyses 46
Table 4 Pearson's Correlation Coefficients—Total Sample 48
Table 5 Descriptive Statistics and Means Comparisons—Declarative Knowledge 51
Table 6 Coded Theme Subgroup Comparison 54
Table 7 Descriptive Statistics and Means Comparisons—Help Seeking 58
Table 8 Descriptive Statistics and Means Comparisons—Self-Efficacy 62
Table 9 Descriptive Statistics and Means Comparisons—Self-Determination 65
Table 10 Descriptive Statistics and Means Comparisons—Organizational Training 68
Table 11 Knowledge Assets or Needs as Determined by the Data 75
Table 12 Motivation Assets or Needs as Determined by the Data 75
Table 13 Organization Assets or Needs as Determined by the Data 76
Table 14 Summary of Knowledge Influences and Recommendations 80
Table 15 Summary of Motivation Influences and Recommendations 84
Table 16 Summary of Organization Influences and Recommendations 87
Appendix C: Self-Efficacy Correlation and Reliability 129
Appendix D: Autonomous Functioning Index 130
xii
List of Figures
Figure 1: Medical Student Environment 3
Figure 2: Conceptual Framework 29
Figure 3: High and Low Attendance Subgroup Means by Help-Seeking Item 59
Figure 4: High and Low Attendance Subgroups Means Comparison for Self-Efficacy Items 63
Figure 5: High and low attendance Subgroup Means by Influence Factor 71
Figure 6: High and Low Attendance Sub-Groups Comparison to Purpose, External Resources,
and Help-Seeking Subgroups 73

1
Chapter One: Overview of the Study
Medical training in the United States is relatively unchanged since the turn of the 20
th

century. In 1910, Abraham Flexner standardized medical education in North America by
implementing an education model for pre-clinical and clinical training that has for the most part
stayed intact today (Cooke et al., 2010). While the basic structure of medical education is
unchanged, the amount of content that medical students need to master during the first four years
of training is reaching unsustainable proportions (Prober & Khan, 2013). As a result, much of the
curricular interaction with students focuses on content delivery and clinical skill development,
with little or no time set aside for processing career interests and defining an individual purpose
in medicine. Today, training students to become physicians must also include meaningful career
exploration. This study examines early interventions with medical students to improve the
specialty exploration process by applying a gap analysis to evaluate the Wasatch Medical School
(WMS) professional development program.
Context and Background of the Problem
Preparing future physicians to select a specialty is a daunting task made even more
challenging by the limited amount of dedicated space for such exploration within medical school
curriculum (Crites et al., 2008; Abbas et al., 2011). With increasing physician burnout, mental
illness on the rise, and lack of physician career satisfaction (Dyrbye et al., 2013; Goebert et al.,
2009; Golob et al., 2018), it is not surprising that after studying 14 major medical centers across
the nation, calls for reform in medical education include the need to improve professional
identity or the “development of professional values, actions, and aspirations” during training
(O’Brien & Irby, 2013, p.226).

2
Demonstrating this alarming issue at hand, a 2018 survey of 20,000 physicians spanning
29 specialties indicated that a staggering 38% would select a different specialty if given the
opportunity to go back and make the choice again (Medscape, 2018). Beyond the need for
reform, there are also institutional expectations for professional development. For example, the
American Association of Medical Colleges (AAMC) has charged academic medicine to equip
medical students with leadership skills that improve team dynamics in the educational and
healthcare space (American Association of Medical Colleges, 2014). In addition, a high
percentage of medical students (85%) have expressed a desire to have leadership training during
medical education (Varkey et al., 2009). Yet despite student interest and AAMC standards, a
lack of space in an already packed and rigorous (and outdated model of) medical school
curriculum creates potential implementation barriers for leadership and professional identity
development related programming, thus placing students at a severe disadvantage as they choose
specialties and train to become physician leaders (Papadakis et al., 2004). Improving
professional identity development activities during medical school serves as a potential way to
infuse the learning environment with meaning, overcome burnout, and enhance the specialty
selection process.
Figure 1 illustrates the internal and external environment medical students are placed in.
The medical student resides in the center of an unrelenting academic setting in which a constant
stream of didactic lectures, quizzes, tests, and board exams occur. In the little remaining time for
extracurricular involvement, students are tasked with participating in research, volunteer service,
leadership experiences, networking, and specialty exploration. Internal aspects of being a student
include exploration of values, interests, purpose, self-awareness, professional identity, and self-
authorship. Personal and professional support relationships are also represented. The challenges

3
students face in this setting are lack of time for activities, feelings of isolation, mental illness,
and burnout.
Figure 1
Medical Student Environment

Starting in fall semester of 2016, Wasatch Medical School (WMS) developed and
implemented a co-curricular, opt-in Purpose in Medicine Program (PMP) for medical students.
The program engages students during their first four years of training to increase professional
development opportunities and provides early interventions around career satisfaction, drawing
primarily on individual and group interactions. The aim of PMP is to help connect trainees and
physicians to their highest purpose in medicine, to promote a sense of professional fulfillment
and engagement, and to positively benefit patients and the community. Built upon self-
authorship theories, the program provides a holistic approach to the internal and iterative nature

4
of the professional identity development process (Baxter Magolda, 1998; 2001; 2007; Cruess et
al., 2015; Kegan, 1994). These developmental lenses provide additional insights about how
students explore values and beliefs related to becoming physicians during medical education.
The PMP leverages coaching, self-discovery workshops, networking activities, and a self-
reflection workbook to build a positive professional community oriented toward purpose and the
promotion of a healing culture.
Purpose of the Project and Research Questions
The purpose of this quantitative study is to perform an in-depth program evaluation using
a traditional Clark and Estes (2008) gap analysis. The gap analysis framework identifies factors
during undergraduate medical education that negatively and positively impact physician career
satisfaction. The survey includes student participants and non-participants in PMP at WMS. The
following research questions serve as a guide to create the survey protocol. Knowledge,
motivation, and organizational (KMO) factors of the gap analysis inform the problem of practice
and PMP evaluation.
The following research questions guide this study:
1. What are the knowledge, motivation, and organizational influences that drive
early medical student interventions to improve the career exploration process?
2. What are the recommendations for improving the medical student career
exploration processes?
Importance of the Study
In addition to making program improvements that benefit students on the WMS campus,
this study provides other academic medicine institutions with a program model and assessment
to apply on their campuses and potentially benefit medical students on a wider scale.

5
Stakeholders who will potentially benefit from the study are medical students, administrators,
student affairs programs, and co-curricular efforts. The challenge of improving professional
development and specialty exploration activities during medical school are important to study
due to the direct influence on quality of life during training and future job satisfaction—both of
which contribute positively to the healthcare system in general and the community it serves (Irby
et al., 2010). To illustrate, medical students experience higher rates of depression and anxiety
than the rest of the undergraduate and graduate student populations (Goebert et al., 2009). They
also have higher levels of burnout as students and entering residency (Dyrbye et al., 2014).
During residency, many residents continue to face challenges related to mental health as well as
increased burnout (Golob et al., 2018). Professional development and specialty satisfaction also
influence the physician community. For instance, a lack of professionalism can have a negative
effect on organizational health related to interactions with patients, medical teams, and
departmental cultures (Gude et al., 2009). Burnout behaviors can also contribute to interpersonal
conflict (Dyrbye et al., 2014). Failing to study this topic negatively impacts the training
environment, quality of patient care, quality of life for future physicians, and organizational
health of teams and cultures, both locally at WMS and the medical profession generally.
Overview of Theoretical Framework and Methodology
The theoretical framework employed in this study is a gap analysis (Clark & Estes 2008).
Using a gap analysis will allow WMS to explore the professional development program
outcomes through knowledge, motivation, and organizational lenses as well as make
recommendations for improvement. Specifically, this framework provides a structure to explore
factors that have contributed to the successes and challenges related to the growth of the
professional development program. The research methodology is quantitative, drawing from

6
previously validated instruments with additional specific questions to assess student perceptions
of the PMP. The survey will target second year WMS students—including those who have opted
in and those who have not.
Definition of Terms
Included below are terms and definitions used throughout the study. Definitions are
drawn from the applicable literature and articulate the specific meaning of the terms relevant to
this research study.
• Career Exploration is a process that includes increased understanding of self in
relation to the work environment, resulting in positive outcomes (Cheung, 2015).
• Declarative Knowledge is explicit or factual knowledge (Krathwohl, 2002; Rueda,
2011).
• Help-seeking is obtaining assistance from adults and peers as needed (Nelson-Le
Gall, 1987).
• Metacognitive Knowledge is the capacity to connect the inner self with unfolding
external experiences and adapt behavior to align them (Flavell, 1976; Metcalfe &
Shimamura, 1994).
• Professionalism is defined by Byyny (2017) as “ethical codes” that physicians
espouse, including “a commitment to competence, integrity, morality, altruism, and
support of the public good” (p. 1).
• Professional Development is a socialization process wherein the student transitions
through the education process from a novice to professional (Berger & Luckmann,
1966).

7
• Professional Identity Development is the process of thinking, acting, and feeling like
a professional (Merton, 1957).
• Purpose is a deep intention to construct life and identity in the professional and
personal realms (Leider et al., 2014).
• Role Modeling is a method of teaching knowledge, skills, values, and behaviors by
example (Cruess et al., 2008).
• Self-authorship is the ability to define individual beliefs, identity, and interpersonal
connections in a complex, ambiguous environment (Baxter Magolda, 2014).
• Self-determination is the ability for an individual to have autonomy or control over
themselves and their life (Ryan & Deci, 2000).
• Self-efficacy is an individual’s belief that they can perform a behavior to achieve
desired results (Bandura 1977).
• Self-reflection is an active internal consideration of any belief or form of knowledge
(Dewey, 1933).
Organization of the Dissertation
Chapter 1 includes an introduction and background related to undergraduate medical
education and the challenges associated with content delivery, as well as a discussion of the
research questions and methodology. Chapter 2 includes a literature review of physician
specialty satisfaction. Chapter 3 provides an overview of data collection methods and analysis of
the PMP evaluation process. Chapter 4 provides an analysis of the data related to each interview
question and presents findings. Finally, Chapter 5 summarizes the data and makes program
improvement recommendations, as well as suggestions for broader application of the model to
other medical schools and their student populations.

8
Chapter Two: Literature Review
This literature review provides the context for improving career exploration during
medical school, with the specific goal to improve the overall process for students. The chapter
begins with an overview of self-authorship and the benefits of supporting self-authorship within
medical education. Next, Chapter 2 includes a detailed discussion of issues and gaps related to
student knowledge, including traditional knowledge expectations and increasing metacognitive
knowledge. Following the knowledge section, the chapter provides an overview of the literature
related to self-efficacy and self-determination within the context of student motivation. A
detailed discussion of organizational factors related to professional development resources offers
more perspective on the institutional challenges to create programmatic efforts that meet
students’ career exploration needs. Finally, this chapter concludes by introducing a conceptual
framework based on Clark and Estes (2008) KMO gap analysis, which provides the foundation
for conducting a quantitative research study.
Self-Authorship
Self-authorship is a critical and generally unsupported process in medical education.
Originally articulated as an internal process and part of adult development (Kegan, 1982; 1994),
Baxter Magolda (2014) further clarified self-authorship as the ability to define “one’s beliefs,
identity, and social relations” in a complex, ambiguous environment (p. 25). Within the context
of graduate education, Baxter Magolda (2014) showed that incorporating self-authorship within
educational institutions needs further development to meet scholarly and professional
expectations. Baxter Magolda (2001) identified three dimensions of self-authorship in which the
individual explores: epistemological or the “nature, limits, and certainty of knowledge,”

9
intrapersonal or “sense of self,” and interpersonal or “interdependence” (Creamer et al., 2010, p.
550). These intertwined dimensions provide a foundation for the self-authorship process.
Bringing self-authorship into the medical education learning environment, Sandars and
Jackson (2015) viewed the focus on personal development, specifically “cognitive maturity, an
integrated identity, and mature relationships” as “essential attributes for future healthcare
professionals” (p. 521). Gruppen et al. (2018) established that personal, relational, and
interpersonal development are indispensable aspects of a healthy learning environment within
health professions. Fallar et al. (2019) advocated for educators to assess and identify student
needs related to self-authorship to provide individualized support for student development in
these areas. Professors, advisors, and mentors within the medical education space benefit from a
self-authorship framework to assist students as they transition from a reliance on the expertise of
others to using internal beliefs and knowledge to make educational and career-related decisions
(Baxter Magolda, 2014; Creamer et al., 2010; Gruppen et al., 2018; Pizzolato, 2007; Sandars &
Jackson, 2015). As the literature suggests, while the value of self-authorship is clear, supports
need to be in place to foster it during medical training.
Increasing support structures around self-authorship in medical education benefits
medical students’ career exploration and the specialty selection process (Baxter Magolda, 2014).
As medical students navigate the external pressures associated with medical school, providing
guidance related to self-authorship, including the internal meaning-making process, increases
professional identity development and aids students in early specialty exploration experiences
(Faller et al., 2019; Johnson & Chauvin, 2016; Barber et al., 2013; Perez, 2016; 2017). Perez
(2016) identified that individual and group interactions with students enhance an understanding
of the developmental stages of self-authorship such as engaging students in a meaning-making

10
process as they transition to graduate school. In addition to knowledge and skill attainment, it is
critical to foster a learning environment that supports the self-authorship development process
(Perez, 2017). Fallar et al. (2019) argued that support efforts are more effective when catered
toward student needs based on developmental level of self-authorship. Barber et al. (2013)
advocated for an emphasis on supporting the development of the inner voice throughout the
educational experience, as it helps guide students through difficult experiences and accelerates
the self-authorship process. Incorporating self-authorship reflection opportunities in the learning
environment fosters professional identity development, including increased understanding of the
professional role (Johnson & Chauvin, 2016). Support of self-authorship experiences in medical
education increases career exploration and, in turn, identity development (Cooke et al., 2010;
Johnson & Chouvin, 2016; Sternszus et al., 2012). Performing a gap analysis (Clark & Estes,
2008) allows for an in-depth examination of self-authorship support systems within the learning
environment and includes a literature review of issues and gaps that exist within KMO domains.
Medical Student Knowledge
Declarative and metacognitive knowledge are two areas within the medical education
learning environment that students engage in as part of their training (Schmidmaier et al., 2013).
As students adjust to a rigorous preclinical curriculum requiring large amounts of factual
knowledge recall, metacognitive knowledge in the form of learning how to learn, as well as
problem solving, also need development during medical school and contributes positively to the
self-authorship process (King & Siddiqui, 2011).
Declarative Knowledge
Declarative knowledge is explicit or factual knowledge (Krathwohl, 2002; Rueda, 2011).
Within medical school, declarative knowledge is a primary focus of preclinical medical

11
education (Mancini et al., 2015). Unfortunately, within a crowded curriculum, declarative
knowledge acquisition occurs at the expense of self-authorship experiences (Chen et al., 2015).
The consequences of prioritizing declarative knowledge in medical school are that students feel
they do not attain needed psychosocial (personal, social, and organizational) aspects of education
and professional knowledge skills, resulting in a general lack of desirable physician qualities
(Chen et al., 2015; Gruppen et al., 2019). Medical schools must provide more than declarative
knowledge because practical knowledge and employment-related skills are an integral part of
professional identity development (Mancini et al., 2015). Schmidmaier et al. (2013) identified
that within the clinical environment, factual knowledge is not enough for students to succeed.
Additionally, Schei et al. (2018) established that declarative knowledge alone does not instill
desirable physician qualities and as a result, there is dissonance between the curriculum content
and the ideal values and qualities of the profession. As medical students transition to residency,
Chen et al. (2015) asserted that while residents were satisfied with declarative knowledge
attainment, they lacked psychosocial and professional knowledge training during medical school
to become successful residents. Konkin and Suddards (2012) found that longitudinal efforts
hyper focus on declarative knowledge and foster deep relationships with patients and faculty.
Declarative knowledge, while a necessary aspect of medical education, has a negative
impact on knowledge acquisition, including psychosocial and self-authorship experiences (Chen
et al., 2015; Konkin & Suddards, 2012; Mancini et al., 2015; Schmidmaier et al., 2013; Schei et
al., 2018). In contrast, metacognitive knowledge attainment is a key aspect of medical training
that contributes positively to self-authorship and specialty exploration.

12
Metacognitive Knowledge
Metacognitive knowledge and self-authorship inform each other (King & Siddiqui,
2011). Metacognitive ability is the capacity to connect the inner self with unfolding external
experiences and adapt behavior to align them (Flavell, 1976; Metcalfe & Shimamura, 1994).
Metacognitive skills are essential for physicians, yet medical students show a decline in
metacognitive development. Early interventions that foster metacognitive strategies contribute
positively to identity development for students (Bransen et al., 2020; Hegazi & Wilson, 2013;
Hong et al., 2015; Lucieer et al., 2016; Stansfield et al., 2016). For example, Hong et al. (2015)
identified that metacognitive skills are crucial for physicians. Lucieer et al. (2016) showed that
medical students’ self-regulation, including metacognitive skills, decreases during pre-clinical
years. Furthermore, metacognitive effort of medical students severely declines during clinical
years (Stansfield et al., 2016).
Hegazi and Wilson (2013) identified that moral judgment competence also declines
during medical school. Panchu et al. (2016) posited that metacognitive awareness is a needed
skill that needs early encouragement during medical education. Bransen et al. (2020) noted that
self-regulated learning requires a supportive social environment within the clinical setting.
Metacognitive skill development is crucial during training and helps students explore identity as
well as specialty (Chen et al., 2015). To self-author, students need the self-regulation skills of
self-reflection and help-seeking.
Self-Reflection
Self-reflection is a metacognitive skill that is a necessary practice in the student’s self-
authorship process. Dewey (1933) defines reflective thought as “active, persistent, and careful
consideration of any belief or supposed form of knowledge in the light of the grounds that

13
support it” and that deep learning cannot occur without self-reflection (p.118). Schön (1983)
connected self-reflection with professional and identity development. Kolb (1984) incorporated
self-reflection into an experiential learning cycle. Boud (1985) included reflection on emotional
state as part of the process of self-authorship and learning from experiences. Finding ways to
support self-reflection in medical education benefits student development.
Supporting a self-reflection practice early and throughout medical education has a
positive impact on a student’s ability to make meaning, form an identity, and seek help (Barber
et al., 2013; Cope et al., 2017; Hays et al., 2011; Steinauer et al., 2019; Volpe et al., 2019).
Barber et al. (2013) discussed that supporting self-reflection as a practice throughout the
educational experience enhances the student’s individual meaning-making process. Within
medical school, self-refection activities during preclinical education help students process their
professional identity (Volpe et al., 2019). For example, Kohn et al. (2011) incorporated self-
reflection activities successfully to help students process foundational science courses. As
students transition to clerkships, self-reflection efforts during clinical training facilitate increased
processing of emotions, motivation, and identity (Steinauer et al., 2019). Throughout medical
training, career exploration consisting of an internal learning process to define personal values
and attitudes is fundamental to professional identity development (Cope et al., 2017).
Consequently, Hays et al. (2011) demonstrated that a lack of personal insight may impair
students from asking for help and contribute to negative academic consequences. Self-reflection
contributes to an increased ability to process and make meaning of experiences, including
identity development and specialty exploration (Barber et al., 2013; Cope et al., 2017; Hays et
al., 2011; Kohn et al., 2011; Steinauer et al., 2019; Volpe et al., 2019). Self-reflection also links
to positive help-seeking behaviors.

14
Help-Seeking
Help-seeking is a necessary metacognitive skill that encourages students to seek guidance
during the self-authorship process. Help-seeking or obtaining “help from adults and peers when
it is needed” (Nelson-Le Gall, 1987, p. 53) includes seeking responses that elicit positive,
constructive, and supportive interactions with others (Bandura & Walters, 1963; Butler, 1998).
Help-avoidance in the educational setting is a common issue (Butler, 1998, Pintrich et al.,
1991). Medical school is no exception and there are many reasons attributed to help-avoidance
behaviors. Student mistreatment and negative stigmas associated with mental health discourage
help-seeking behaviors and, as a result, limit utilization of wellness services, career advising, and
mentoring experiences (Artino et al., 2012; Castillo-Angeles et al., 2017; Dyrbye et al., 2015;
Fnais et al., 2014; Gold et al., 2015; Pereira et al., 2016; Trépanier et al., 2015; Winter et al.,
2017). For example, Trépanier et al. (2015) noted that workplace bullying, including humiliation,
continues to occur in clinical settings. Further, medical trainees continue to experience high
levels of harassment and discrimination (Fnais et al., 2014). Within this medical training
environment, Castillo-Angeles et al. (2017) showed that fear of mistreatment inhibits students
from seeking assistance. In addition to fear, Artino et al. (2012) concluded that medical students
avoid seeking help because they do not want to look bad in front of others. Furthermore, Dyrbye
et al. (2015) and Winter et al. (2017) identified a stigma with students seeking mental health
support during medical school. Similarly, Gold et al. (2015) noted that increased needs
associated with mental health resulted in decreased care-seeking. Students who struggle with
professionalism are also not inclined to seek help (Gold et al., 2015). In contrast, there are
several benefits to seeking help early during medical school.

15
Gathering insight from fourth year medical students, Pereira et al. (2016) identified that
an important skill in clinical training is knowing when to engage mentors for help, advice, and
expertise. Building upon this skill, Gold et al. (2015) confirmed that help-seeking behaviors
foster supportive faculty relationships and benefit career indecision. Perez and Gati (2017)
showed that career counseling programs can reduce students’ negative coping strategies and
improve career exploration. Help-seeking skills are critical to overcoming challenges during
medical school and contribute positively to self-authorship and the career exploration process
(Artino et al., 2012; Castillo-Angeles et al., 2017; Dyrbye et al., 2015; Fnais et al. 2014; Gold et
al., 2015; Pereira et al. 2016; Perez & Gati, 2017; Trépanier et al., 2015; Winter et al., 2017).
Building upon student knowledge, student motivation specifically links to the quality of the self-
authorship process.
Medical Student Motivation
Motivation within the learning environment is essential for student success (Bandura,
2012). Becoming a physician requires a high degree of motivation. Intrinsic and extrinsic
supports are “interwoven” in the form of personal as well as institutional factors
(Kunanitthaworn et al., 2018). This process includes emotional experiences that occur during
medical training that have the potential to increase motivation and resilience (Helmich et al.,
2012). Self-efficacy and self-determination inform efforts to support intrinsic motivation in
students, which in turn contribute positively to the self-authorship and career exploration
process.
Self-Efficacy
Bandura (1977) defined self-efficacy as an individual’s belief that they “can successfully
execute the behavior required to produce the outcomes” (p. 193). Gannouni and Ramboarison-

16
Lalao (2018) reviewed the impact of self-efficacy behaviors on students as determining the
decision-making process “to approach a task or activity,” as well as the performance of, and
persistence in, completing the task (p. 69). Within a medical education context, student
experiences improve when interventions support an increase in self-efficacy beliefs (Artino et al.,
2012). Self-efficacy beliefs in educational settings have a positive impact on coping,
perseverance, goal attainment, and self-regulation (Bandura, 2012). The absence of self-efficacy
during medical training adversely affects students.
Lack of self-efficacy in medical school negatively impacts student academic
achievement, intrinsic motivation, and career exploration (Artino et al., 2012; Kim et al., 2014).
First year medical students experience a sharp decline in self-efficacy and need early
interventions such as leadership experiences, soft-skill development, and adequate time for
career exploration in order to reduce burnout, improve academic achievement, and encourage
goal attainment, as well as generally increase student motivation (Artino et al., 2012; Babenko &
Oswald, 2019; Gannouni & Ramboarison-Lalao, 2018; Gharetepeh et al., 2015; Halstead & Lare,
2018; Kim et al., 2014; Yu et al., 2016). Artino et al. (2012) identified that first year students
experience lower levels of self-efficacy and need early interventions to improve and maintain
self-efficacy behaviors throughout medical school. Gannouni and Ramboarison-Lalao (2018)
demonstrated that early interventions that promote leadership experiences during medical school
promote intrinsic motivation and goal achievement. Further, emotional intelligence contributes
positively to self-efficacy of students (Gharetepeh et al., 2015).
In addition to emotional intelligence, staff and faculty efforts have a positive impact on
students. Staff and faculty efforts to assist students in finding a calling as part of the career
exploration process also improve the academic achievement of students (Park, 2018). In

17
addition, Halstead and Lare (2018) showed that having additional time to do career exploration
during pre-clinical years positively impacts student self-efficacy. Yu et al. (2016) identified that
interventions that promote academic self-efficacy reduce medical student burnout. Institutional
efforts that provide self-efficacy experiences for students also benefit goal mastery during
medical school (Babenko & Oswald, 2019). Goal attainment is also linked to increased academic
self-efficacy, learning strategies, and student motivation (Kim et al., 2014). Self-efficacy related
interventions improve intrinsic motivation, academic achievement, career exploration, and self-
authorship (Artino et al., 2012; Babenko & Oswald, 2019; Gannouni & Ramboarison-Lalao,
2018; Gharetepeh et al., 2015; Halstead & Lare, 2018; Kim et al., 2014; Yu et al., 2016).
Decreased levels of career exploration, intrinsic motivation, and academic achievement are
associated with a lack of self-efficacy in the learning environment (Artino et al., 2012; Kim et
al., 2014). In addition to self-efficacy, self-determination is a key aspect of self-authorship and
career exploration.
Self-Determination
Self-determination theory (SDT) provides key insights about intrinsic motivation within
medical education. Developed by Ryan and Deci (2000), SDT explores factors that contribute to
healthy self-motivation, self-regulation, and personality development by identifying three
psychological student needs: “competence, relatedness, and autonomy” (p. 68). Neufeld and
Malin (2020) unpacked each need, stating that competence is “the need to feel challenged and
master one’s environment;” relatedness is “the need to feel close with and have trusting
relationships with others;” and autonomy is “the need to feel in control of one’s own life,
behaviors, and goals” (p. 6). Connecting SDT to the learning environment informs educators
about student needs within the space (Kusurkar et al., 2011; Kusurkar & Croiset, 2015; Williams

18
& Deci, 1998). Elaborating further on the term autonomy support, Kusurkar et al. (2011) pointed
out that autonomy support as described by SDT is not pure independence, but guided discovery
in which the learner is making their own decision with the support of others. SDT and
particularly autonomy support are relatively new areas of discussion within academic medicine
and need further examination in medical education (Kusurkar & Croiset, 2015; Ten Cate et al.,
2011).
Medical students lack autonomy in the education environment, and it has a negative
impact on the self-authorship process. Lack of medical student autonomy is associated with
exhaustion, burnout, and job dissatisfaction, while efforts to support self-determination during
medical school increase academic achievement, promote goal mastery, and boost intrinsic
motivation as well as student engagement (Biondi et al., 2015; Feri et al., 2016; Keating et al.,
2013; Kim et al., 2016; Kusurkar et al., 2013; 2019; Neufeld & Malin, 2020; Trépanier et al.,
2015). Neufeld and Malin (2020) showed that medical students lack autonomy support, which
contributes to a decline in overall well-being. Along the education continuum, residents lack
autonomy and need more opportunities for independence during training (Biondi et al., 2015).
Within the medical profession, lack of autonomy contributes to job dissatisfaction (Trépanier et
al., 2015). In contrast, autonomous motivation in medical school resulted in less exhaustion
(Kusurkar et al., 2013) and improved medical student academic achievement (Feri et al., 2016).
In an example of a successful intervention, students who had the opportunity to create electives
increased participation and engagement in courses (Keating et al., 2013). Within a career
exploration context, Kim et al. (2016) indicated that students who are intrinsically motivated
about career exploration are more invested academically than students who are extrinsically
motivated. As part of the SDT framework, Kusurkar et al. (2019) showed that students who are

19
satisfied with competence and autonomy needs also experience motivation for work and learning
within their specialty throughout their career span. Promoting self-determination in medical
education contributes to academic achievement, career exploration, and self-authorship (Biondi
et al., 2015; Feri et al., 2016; Keating et al., 2013; Kusurkar et al., 2013; 2019; Kim et al., 2016;
Trépanier et al., 2015). Medical education reform must consist of increased support of the self-
authorship process through meaningful professional development activities.
Medical Education Reform: Professional Development
A healthy academic learning environment emphasizes professional development
(Gruppen et al., 2018; Irby et al., 2010). Professional development is also an expectation of
graduate education (Austin, 2002). Berger and Luckmann (1966) described professional
development as a socialization process wherein the student transitions through the education
process from a novice to professional. Wear (1997) connected the general process of professional
development as “transmitting the accepted wisdom, values, and overall orientation” to providing
a medical education that emphasizes “ongoing reflection on self and profession” while
incorporating compassion toward patients, addressing societies’ health needs, and “respecting
individual autonomy” (p. 1061). Clearly within the complex setting of medical education,
professional development is an indispensable time to explore the personal and professional skills
needed to thrive as a physician. Unfortunately, professional development is not a priority in
medical education (Barber et al., 2013; Irby et al., 2010).
Traditional medical curriculum has not been ineffective in providing meaningful
professional development activities for students (Barber et al, 2013; Fallar et al., 2019; Gruppen
et al., 2018; Heflinger & Doykos, 2016; Irby et al., 2010; Kjaer et al., 2011; Malone & Supri,
2012; Teunissen & Westerman, 2011; Touchie & Ten Cate, 2016). Yet, within the general

20
context of graduate education, Heflinger and Doykos (2016) showed that while graduate students
feel prepared to perform scholarly activities, they feel a lack of professional education, including
teaching skills and leadership training. Examining this issue in medical education, Irby et al.
(2010) attributed the lack of professional development to a medical curriculum that is not
student-centric and is reluctant to change. This is due to a hyper focus on knowledge and skill
attainment that has left out important professional building blocks (Touchie & Ten Cate, 2016).
Efforts to transform the education environment led to the creation of competency-based medical
education (CBME).
In addition, CBME is ineffective in providing effective professional development
activities for students (Kjaer et al., 2011; Malone & Supri, 2012; Teunissen & Westerman,
2011). CMBE is a self-paced education model focused on achieving competency in defined
educational domains with set outcomes (Holmboe & Batalden, 2015). Proponents of CBME
desired to create and maintain a baseline of competency to increase quality of patient care
(Touchie & Ten Cate, 2016). However, Kjaer et al. (2011) asserted that the shift toward CBME
resulted in a loss of broad-based knowledge and lack of student confidence in their own skills.
Additionally, Malone and Supri (2012) identified that CMBE lacks the capability to produce
well-rounded and highly qualified physicians. Teunissen and Westerman (2011) highlighted
another negative aspect of the current education environment—as students experience several
difficult transitions during medical school, they lack coping skills. In addition to the negative
reaction to CBME, there is evidence of attempts to improve upon it.
Counteracting the lack of space for professional development in CBME requires
increased student support. For example, Gruppen et al. (2018) recommended improvements in
the learning environment that include student support efforts of meaning-making, autonomy

21
support, and resilience training, particularly as students experience transitions and stressors.
Fallar et al. (2019) specifically advocated for efforts to engage students in professional identity
development, including self-authorship, as imperative aspects of medical education to
compensate for the professional development gaps within the CBME learning environment.
Barber et al. (2013), using a self-authorship lens, performed a comprehensive examination of
higher education, and as a result, advocated for educational reform that includes an emphasis on
supporting the development of the student’s inner voice throughout the educational experience.
Understandably, training physicians in a competency-based environment must include adequate
allocation of time and resources dedicated to meaningful professional development activities
(Barber et al, 2013; Fallar et al., 2019; Gruppen et al., 2018; Heflinger & Doykos, 2016; Irby et
al., 2010; Kjaer et al., 2011; Malone & Supri, 2012; Teunissen & Westerman, 2011; Touchie &
Ten Cate, 2016). Specific developmental activities within the learning environment must
incorporate activities that are conducive to a self-authorship process including professional
identity formation, professionalism training, positive role modeling, and career exploration.
Need for Professional Identity Formation
Professional identity development is a much-needed part of a well-rounded medical
education. After visiting major medical centers across the United States, Irby et al. (2010)
concluded that professional identity formation (PIF) is one of four primary areas needing reform
in medical education. PIF is “a holistic construct addressing physicians’ development of
professional values, actions, and aspirations” (O’Brien & Irby, 2013, p.226). Chow et al. (2018)
expanded the definition to include “a blend of one’s personal values and behaviors (which
include social identity) and the shared values and behaviors of the profession” (p. 1540). In his
seminal work on physician identity development, Merton (1957) summarized PIF as the process

22
that results in medical students thinking, acting, and feeling like a physician. Although PIF is a
key area needing reform within academic medicine, research around the topic struggles to adapt
to the needs of the learning environment to become less didactic and more developmental in
nature (Cruess et al., 2018; Shochet et al., 2015; Wald, 2015). Unfortunately, specific efforts to
implement PIF in medical education are lacking.
Transitioning from acknowledgment that PIF is important in medical education to
providing a learning environment that can teach it properly continues to be a challenge. Although
validated by scholarship, PIF reform efforts remain conceptual, lack implementation, and to be
successful, require progressive efforts that include interventions spanning the entire curriculum,
as well as longitudinal formative assessments (Ahmad et al., 2018; Bransen et al., 2020; Chow et
al., 2018; Holden et al., 2015; Irby et al., 2010; Johnson & Chauvin, 2016; Liddell et al., 2014;
O’Brien & Irby, 2013; White et al., 2011). Irby et al. (2010), after observing major areas of the
U.S. medical education sites, called for significant educational focus to be around the
professional identity development of future physicians. While there is general buy-in from the
educational community, O’Brien et al. (2013) identified that institutional efforts to engage
students in PIF activities remain conceptual and lack curricular innovation.
A significant area of innovation identified as promoting PIF includes increasing
interpersonal interaction throughout training as being highly impactful (White et al., 2011).
Particularly, Liddell et al. (2014) pointed out that extracurricular experiences have a higher
impact on professional identity development than the classroom. For example, Ahmad et al.
(2018) noted the benefits to PIF associated with student participation in co-curricular
community-based clinics. Within the curriculum, Bransen et al. (2020) recommended early
intervention in co-regulated learning, or shared learning between faculty and students in clinical

23
spaces, to foster identity. Although PIF efforts apply to all students, Chow et al. (2018) showed
that underrepresented populations experience professional practice curriculum differently than
privileged physician populations, and inclusive efforts to engage marginalized populations in PIF
interventions must be more intentional. Johnson and Chauvin (2016) made the connection that
self-authorship is an important part of the PIF process. As new programmatic efforts emerge,
Holden et al. (2015) advocated for long-term formative assessments of PIF experiences to be
effective with medical students. Implementing PIF activities must include specific and proactive
efforts throughout medical school (Ahmad et al., 2018; Bransen et al., 2020; Chow et al., 2018;
Holden et al., 2015; Irby et al., 2010; Johnson & Chauvin, 2016; Liddell et al., 2014; O’Brien &
Irby, 2013; White et al., 2011). Effective professionalism training is an integral part of PIF and
continues to be an area of struggle during training.
Need for Effective Professionalism Training
Professionalism training is significantly lacking in medical school and needs reform.
Byyny (2017) defines professionalism as “ethical codes” that physicians espouse and are “a
commitment to competence, integrity, morality, altruism, and support of the public good” (p. 1).
Regrettably, curricular efforts to teach professionalism are ineffective due to the educational
approach and negative role modeling (Frenk et al., 2010; Hendelman & Byszewski, 2014;
Klemenc-Ketis & Vrecko, 2014; Mak-Van Der Vossen et al., 2018; Monrouxe & Rees, 2012;
Rabow et al., 2013; Wong & Trollope‐Kumar, 2014). Professionalism education struggles with
formal and informal training efforts that undermine improvement and perpetuate negative
behaviors.
For example, Hendelman and Byszewski (2014) found that current methods of teaching
professionalism are generally ineffective. In describing current teaching methods further, Frenk

24
et al. (2010) contended that a learning environment focused on memorization is no longer
sustainable, and a needed shift in medical education is to increase professionalism education.
While it is obvious professionalism education is necessary, Klemenc-Ketis and Vrecko (2014)
pointed to a gap between desired outcomes and implementation. Monrouxe and Reese. (2012)
elaborated that the underlying issue is negative role modeling that contradicts any formal
teaching efforts. Unfortunately, the “hidden curriculum” or unspoken rules teach students
behaviors that undermine professionalism education (Hafferty, 1998, p. 404). Wong and
Trollope‐Kumar (2014) noted that students who cannot conform to the hidden rules of behavior
experience rejection by the medical community. As a result, Mak-Van Der Vossen (2018)
showed that students experience a decrease in professional behavior in the learning environment
when they do not know what to do or fear retribution. Rabow et al. (2013) explained further that
medical education needs to ensure that achievement of competence in professionalism does not
occur at the expense of the individual student’s personal values and attributes. Professionalism
training is noticeably lacking in medical education and therefore has a negative impact on
student training and professional development (Frenk et al., 2010; Klemenc-Ketis & Vrecko,
2014; Hendelman & Byszewski, 2014; Mak-Van Der Vossen et al., 2018; Monrouxe & Rees,
2012; Rabow et al., 2013; Wong & Trollope‐Kumar, 2014). Incorporating experienced role
models who can teach professionalism by engaging students appropriately during training
positively impacts self-authorship and career exploration.
Need for Positive Role Modeling
Cruess and Cruess (2008) define role modeling as a method of teaching knowledge,
skills, values, and behaviors by example. The lack of positive role modeling in medical
education places medical students at a disadvantage in terms of personal and professional

25
growth. Role modeling has a high impact on student identity development, knowledge of role,
specialty exploration, and selection process (Frei et al., 2010; Hendelman & Byszewski, 2014;
Parker et al., 2014, Stahn & Harendza, 2014; Sternszus et al., 2012). Role modeling experiences
are a significant contributor to PIF. Parker et al. (2014) showed that role models have a
substantial negative or positive impact on medical students’ career choice. Examining
institutional endeavors, Stahn & Harendza (2014) asserted that role modeling education needs to
include efforts that increase role awareness in the student’s professional development process.
Frei et al. (2010) highlighted that effective training of mentors contributes positively to career
exploration and advancement. Noting residents specifically and their direct influence on
students, Sternszus et al. (2012) recommended increasing awareness of their position as role
models and their impact on clinical teaching and specialty exploration. Stahn & Harendza (2014)
explained the significance of role models in this process as being the most important factor
during the specialty selection process. Role modeling has shown to be a key factor in a student’s
professional development and must occur constructively (Frei et al., 2010; Hendelman &
Byszewski, 2014; Parker et al., 2014; Stahn & Harendza, 2014; Sternszus et al., 2012). The
career exploration process connects directly to the self-authorship process and needs
encouragement as well as support throughout medical school.
Need for Career Exploration Support
Career exploration is a fundamental aspect of higher education. Gruppen (2018)
contended that the learning environment must contain this kind of exploratory learning. Career
exploration includes “gaining understanding about oneself and the world of work, as well as of
how self and environment interact to produce desirable outcomes” (Cheung, 2015, p.157).
Within medical education, Borges et al. (2005) advocated that the specialty exploration and

26
selection process need to culminate in congruence for long-term career satisfaction to occur.
Henry et al. (1992) pointed out the difficulty of the medical specialty selection process and the
long-term significance of this decision on an individual physician’s career. For career
exploration to have a high impact on student development, such exploration must occur within
the learning environment.
Career exploration is an underdeveloped aspect of medical education. Lack of
institutional support of the specialty exploration process leads to inadequate engagement in early
interventions, unproductive career planning courses, and ineffective developmental interactions
that contribute to student burnout and career indecision (Domene, 2015; Duffy et al., 2011; 2012;
Dyrbye et al., 2018; Fares et al., 2016; Halstead & Lare, 2018; Lent et al., 2016; Park, 2018;
Querido et al., 2018; Vo et al., 2017; Wang et al., 2018; White et al., 2011). Vo et al. (2017)
identified that medical students begin considering specialty during the first year of medical
school, earlier than originally thought. Halstead and Lare (2018) suggested that students benefit
from having additional time to explore career options early during school. Yet, McDow and
Zabrucky (2015) demonstrated that students view career development offerings as secondary to
more pressing curricular obligations. Querido et al. (2018) advised that institutional efforts to
promote and support early specialty exploration include student-driven initiatives such as
elective creation as an effective way to engage students in professional development. Expressing
concern about medical student well-being, Dyrbye et al. (2018) related physician burnout to lack
of specialty satisfaction. In addition to burnout, research points to connecting meaning to the
specialty exploration process.
Duffy et al. (2011) drew a positive connection between the specialty exploration process,
meaning-making, and increased ability to find a career calling. Referring to college students

27
generally, Park (2018) noted that they benefit academically from having a calling orientation as
they navigate career choice. Building on the idea of calling orientation further, Duffy et al.
(2012) showed that college students who view professional endeavors as a calling experience
higher satisfaction with career and life meaning. Unfortunately, Domene (2018) identified that
college students’ efforts to find a calling decrease over the course of their education. Speaking to
the benefits of counteracting the student decline in career exploration experiences, Wang et al.
(2018) associated increased institutional efforts with improving college student career
adaptability, boosting student confidence, and improving career decision-making. Returning the
focus to medical students specifically, White et al. (2011) attributed successful specialty
exploration to interpersonal experiences that promote soft skill development. In addition to
benefiting from interpersonal skill, Lent et al. (2016) posited self-efficacy related to career
decision-making provided an increased ability to deal with career decision related challenges and
disappointments. In response to the challenges of persisting in medical education, Fares et al.
(2016) connected career counseling and life-coaching efforts to reducing medical student stress
and burnout. Institutional commitment to support early career exploration experiences reduces
medical student burnout, improves specialty exploration and meaning-making, and fosters
calling orientation, leading to increased specialty satisfaction (Domene, 2015; Duffy et al., 2011;
Duffy et al., 2012; Dyrbye et al., 2018; Fares et al., 2016; Halstead & Lare, 2018; Lent et al.,
2016; McDow & Zabrucky, 2015; Park, 2018; Querido et al., 2018; Vo et al., 2017; Wang et al.,
2018; White et al., 2011). As students continue to develop, the learning environment must
identify areas of weakness to make improvements that ensure a meaningful career exploration
process.

28
Conceptual Framework
Improving upon early career exploration experiences for medical students requires an
examination of issues and gaps within the medical learning environment. Clark and Estes (2008)
provide an effective framework to perform a gap analysis geared toward improving the early
career exploration process. The gap analysis framework breaks down performance improvement
by investigating three specific influences: knowledge, motivation, and organization (KMO).
Clark and Estes (2008) further define each area as an individual’s “knowledge and skills,”
“motivation to achieve the goal,” and barriers within the organization such as “missing or
inadequate work processes” (p. 43). Within the context of medical education, the gap analysis
provides a framework to identify and examine gaps in student knowledge, student motivation,
and the organizational programs related to early career exploration. In addition, the framework
includes setting performance goals that narrow the gaps by assessing current processes related to
career exploration and self-authorship efforts. Using the conceptual framework below provides
an overview of a modified gap analysis that combines knowledge, motivation, and organizational
gaps within the context of the medical education learning environment that promotes meaningful
career exploration through psychosocial engagement and self-authorship experiences.
The conceptual framework (Figure 1) depicts the relationship between student
knowledge, student motivation, and the organizational goal to improve the career exploration
process for students. The column on the left highlights KMO influences articulated throughout
the literature review. Continuing from left to right, the next two columns build upon Fallar et
al.’s (2019) approach of measuring low and high self-authorship and updates the labels to
Emerging (low) Self-authorship and Maturing (high) Self-authorship stages. Of note, the
Emerging Self-Authorship stage summarizes overarching KMO gaps within medical education.

29
In addition, the Maturing Self-Authorship stage on the far right draws a specific tie to the
organizational goal to improve the early specialty exploration process for students. The sections
highlighted in green represent the positive impact of institutional efforts to promote psychosocial
engagement within the learning environment. An explanation of each section in the conceptual
framework follows.

Figure 2
Conceptual Framework

In the KMO Influences column, knowledge, both declarative and metacognitive,
(specifically self-reflection and help-seeking) are key concepts that draw influence from the
epistemological dimension or how one views the world in relation to the self within self-
authorship theory (Baxter Magolda, 2008; Kegan, 1982). Continuing from left to right, the

30
Emerging Self-Authorship first stage focuses on the student’s overemphasis on declarative
knowledge and lack of metacognitive knowledge, whereas the Maturing Self-Authorship stage
shows a balance between declarative and metacognitive knowledge, as well as increased self-
reflection and help-seeking behaviors as they apply to the career exploration process.
Within the framework, motivational influences interconnect with student knowledge and
include key concepts of self-efficacy and self-determination theories that align with the
intrapersonal self-authorship dimension of asserting self-knowledge (Baxter Magolda, 2008;
Kegan, 1982). During the Emerging Self-Authorship stage, students lack autonomy and are
extrinsically motivated within the learning environment. In contrast, the Maturing Self-
Authorship stage includes a balance between intrinsic and extrinsic motivation. With increased
self-efficacy and self-determination, the student asserts self-defined values and beliefs when
making career choices.
Reinforcing student knowledge and student motivation are organizational influences.
Organizational influences link to Baxter Magolda (2008) and Kegan’s (1982) interpersonal self-
authorship dimension or the relational aspects of identity development. Key concepts within the
category of professional development include professionalism training and supportive career
exploration in the form of role modeling, and career exploration. During the Emerging Self-
Authorship stage, the organization lacks programmatic training and resources related to
professional development. During the Maturing Self-Authorship stage, the learning environment
supports interventions with students that foster professional development and, in turn, promote
metacognitive knowledge acquisition, self-efficacy, and self-determination. As a result, the
Maturing Self-Authorship stage includes a meaningful exploration process in which the
institution effectively supports students in their career exploration process, and the students have

31
high engagement with professional development training and resources. The conceptual
framework (Figure 1) demonstrates the interconnected nature of KMO Influences and Emerging
and Mature Self-Authorship as well as the organizational goal to assess assets and needs to
enhance career exploration programs for students.
Summary
The literature review identifies and examines KMO gaps associated with providing
meaningful career exploration programs for medical students. Within the knowledge influences,
issues and gaps include an overemphasis on declarative knowledge, a lack of metacognitive
knowledge development, including student insufficiencies in self-reflection, and help-seeking
behaviors (Artino et al., 2012; Chen et al., 2015; Volpe et al., 2019). Both help-seeking and self-
reflection are critical to the self-authorship and career exploration process during medical school
(Gold et al., 2015; Volpe et al., 2019).
Issues and gaps related to motivation influences include a lack of student self-efficacy
(Artino et al., 2012; Kim et al., 2014) and self-determination (Neufeld & Malin, 2020) within the
learning environment. Self-efficacy gaps negatively impact academic achievement, intrinsic
motivation, and career exploration (Artino et al., 2012; Kim et al., 2014). Lack of self-
determination negatively impacts self-authorship and career exploration, resulting in increased
burnout, exhaustion, and low specialty satisfaction (Kusurkar et al., 2019; Neufeld & Malin,
2020; Trépanier et al., 2015). In contrast, faculty and staff efforts to support student self-efficacy
and self-determination have shown to have a positive impact on self-authorship and career
exploration (Artino et al., 2012; Kusurkar et al., 2013; 2019).
Organizational issues and gaps include a deficiency in being student-focused (Irby et al.,
2010) and a general institutional lack of support for professional development in traditional

32
(Touchie & Ten Cate, 2016) and CBME education (Malone & Supri, 2012) models. Specifically,
medical education lacks the ability to support PIF, provide effective professionalism training,
engage in positive role modeling, and implement adequate career exploration programming
(Barber et al, 2013; Fallar et al., 2019; Gruppen et al., 2018; Heflinger & Doykos, 2016; Irby et
al., 2010; Kjaer et al., 2011; Malone & Supri, 2012; Teunissen & Westerman, 2011; Touchie &
Ten Cate, 2016). The issues and gaps on medical student self-authorship and the career
exploration process during medical school demonstrate the overall negative impact within these
three domains (Cooke et al., 2010; Johnson & Chauvin, 2016; Sternszus et al, 2012). The review
of the literature and conceptual framework provide the background for the research methodology
discussed in the next chapter.

33
Chapter Three: Methodology
The purpose of this study is to identify factors during undergraduate medical education
that negatively and positively impact early career exploration. As the demand for emerging
physicians to enter the field with high levels of professional development continues to increase,
the outcome of this study has general appeal to academic medicine and the healthcare field.
However, research in this area also has direct benefit within each individual medical school. In
this case, the specific research focus is the PMP at the WMS and the organizational goal is to
improve the self-authorship process including career exploration for medical students. This study
employs a gap analysis as a framework to explore KMO influences in conjunction with a
quantitative assessment of the PMP. This chapter includes a discussion of the research design
and methodology, data collection and instrumentation, and data analysis.
Research Questions
The research questions used to guide this study are:
1. What are the knowledge, motivation, and organizational influences that drive
early medical student interventions to improve the specialty exploration process?
2. What are the recommendations for improving medical student specialty
exploration processes?
Overview of Design
This study utilizes a quantitative instrument for the primary data collection process. This
form of assessment allows for an in-depth examination of the KMO influences to improve the
medical student career exploration and self-authorship process. Table 1 provides a description of
the data collection methods used for this study.

34
Table 1
Data Sources
Research Questions Survey
RQ1: What are the knowledge, motivation, and organizational
influences that drive early medical student interventions to
improve the specialty exploration process?
X
RQ2: What are the recommendations for improving medical
student specialty exploration processes?
X

Research Setting
WMS is located within a large, state-funded Research I university in the western United
States. The school has a student population of 530 medical students and connects to a teaching
hospital that serves the Intermountain West region. The target sample population for this survey
was second year medical students (n = 126), second year medical students who completed the
PMP first-year certificate (n = 60), and second year medical students who did not complete the
PMP first-year certificate (n = 37). This sample population was appropriate because they are in
the preclinical years of the curriculum and the purpose was to study specialty exploration
interventions that occur during early undergraduate medical education. Portions of this
population participated in the PMP, which provides professional development activities and
resources, including a yearly certificate that students could opt in to complete. Data from the

35
survey assessed and improved the program as well as the quality of the specialty exploration
process in general at WMS.
The Researcher
The researcher holds a leadership position within the Student Affairs unit with direct and
frequent engagement with the student body. In addition, the researcher is the Co-Director of the
PMP and is highly visible to students in that role and works with student leaders who represent
the PMP as representatives for each of the four classes. The researcher does not employ any
students or relatives within the Student Affairs unit or PMP. To reduce potential confirmation
bias or improper influence due to the researcher’s positions, the Director of Education and
Scholarship who regularly conducts surveys as an independent researcher within the medical
school distributed the survey. Of note, the researcher does not have authority or direct oversight
related to the academic progression of students, including course grades, clinical evaluations, or
academic outcomes. No compensation of any kind is part of this study for the researcher or
participants.
Data Sources
The primary data source was a quantitative survey. The timing of the survey coincided
with fall semester of 2020 when the target population transitioned into second year. The first-
year curriculum and PMP certificate completion made this is an optimal time to distribute the
survey. Due to COVID-19 related modifications, including large gathering restrictions,
preparations were in place to continue preclinical curriculum online in the fall. Since the delivery
method was by email, the survey moved forward as planned.

36
Survey
The survey instrument combined previously validated instruments to identify assets and
needs to improve programmatic efforts by the PMP to support self-authorship including career
exploration. Following Robinson and Firth Leonard’s (2019) counsel to use preexisting surveys
with similar populations and subject matter, the preplanning efforts intentionally identified
instruments with adult learners, college students, and, specifically, medical students in a career
exploration and self-authorship context. The instrument contained 47 questions including general
demographics and items that link directly to the KMO influencers as well as one open-ended
question. In addition, the survey design process used Cresswell and Cresswell’s (2018) survey
design study plan as a guide. The pilot test indicated that the survey takes on average 20 minutes
to complete. Overall, the institutional goal was to use this study to improve career exploration
outcomes for students.
Participants
This study used cross-sectional, purposeful sampling, and the potential participants from
the target population had an equal opportunity to participate in the survey (Cresswell &
Cresswell, 2018). Recruitment of students occurred via email communication. Approximately
127 second-year medical students (50 female, 76 male) were eligible to participate in the online
survey. The survey compared students who participated in the PMP (n = 60) and with those who
did not (n = 37). For the students who participated in PMP, expectations for the study included
higher rates of metacognitive behaviors (self-reflection and help-seeking), motivation (self-
efficacy and self-determination), and engagement with professional development resources,
resulting in meaningful career exploration and self-authorship by students (Duffy et al., 2012;
Fares et al., 2016; Lent et al., 2016; Park, 2018, Wang et al., 2018; White et al., 2011). In

37
contrast, for the students who did not participate in PMP, expectations included lower rates of
metacognitive knowledge, motivation, self-authorship, involvement with professional
development resources, and struggle to explore career options (Duffy et al., 2012; Halstead &
Lare, 2018; McDow & Zabrucky, 2015; Querido et al., 2018; Vo et al., 2017).
Instrumentation
The survey drew from validated instruments to evaluate and understand the KMO
influencers within the conceptual framework. The researcher adapted a survey tool from existing
self-authorship (Fallar et al. 2019; Baxter Magolda & King, 2007), self-efficacy (Bandura,
2006), and help-seeking instruments (Pintrich, 2009; Wilson et al., 2005). Fallar et al. (2019)
granted permission to use their instrument. Balmer et al. (2013) granted permission to model
survey items after their approach. Baxter Magolda (2007), Bandura (2006), Pintrich (1991), and
Wilson’s (2005) instruments are part of the public domain and did not require permission. This
study surveyed second year medical students at WMS to specifically compare the students who
participated in the PMP and those who did not. The survey aligned with capturing student
engagement data related to career exploration and self-authorship support efforts that occurred
during the preclinical years.
The modified instrument in this study assessed KMO influences that prevent the
organization from reaching the goal to provide effective self-authorship and career exploration
resources to students. The survey examined knowledge influences: declarative and metacognitive
(help-seeking and self-reflection); motivation influences (self-efficacy and self-determination);
and finally, organization influences, i.e., professional development training and resources (see
Appendix A and Figure 1).

38
Specific adjustments to the instrument included updating questions to fit the medical
student context. As recommended by Fallar et al. (2019), adjustments to the self-authorship
instrument included removal of specific references to global warming in questions 39-40 to a
general scientific issue instead. In addition, open-ended question 19 replaced the open-ended
ethics question used in the original survey (Fallar et al., 2019). This updated question drew
influence from Baxter Magolda and King (2007) seeking to gather narrative around
“developmentally effective” experiences designated by the student (p. 111). However, the
analysis of the narrative used the same method from Fallar et al. (2019) since the overall intent of
the open-ended question remained the same, “to gather information regarding the student’s
thought process as a potential corroborating measure” (p. 3). Question 44 drew influence from
Balmer et al.’s (2013) efforts to encourage students to rank influential factors within the learning
environment by making judgements and assigning a fixed number of points to the list of factors.
Help-seeking question 20 incorporated the General Help-Seeking Questionnaire (GHSQ)
developed by Wilson et al. (2005) to assess student intention to engage specific individuals when
experiencing challenges. In this case, the researcher included career exploration sources of
support. Questions 21 through 27 based questions on best practices to construct self-efficacy
instruments (Bandura, 2006).
Data Collection Procedures
All current second year medical students who attend WMS received an introduction
email at the beginning of fall semester in July of 2020 followed by a Qualtrics survey link also
delivered electronically. The introduction for the survey included the purpose of the study,
encouragement of student participation, confidentiality, and privacy policies as well as general
instructions. The estimated amount of time to complete the survey was 15 minutes. Although

39
Fallar et al. (2019) used a paper survey and it worked well at the respective campus, electronic
surveys at the WMS have a history of being successful and achieving high response rates.
Data Analysis
Data analysis utilizing Qualtrics, Microsoft Excel 2016, and IBM® SPSS® Statistics
27.0.1.0 provided the appropriate tools for sense-making of the survey data. Statistical analysis
used Likert scales to allow for the numeric rendering of the data. Exploration of the data
examined the interconnected nature of the KMO influencers. Cronbach’s alpha comparisons
between previously validated instruments and the individual sections within this study’s
instrument provided an opportunity to demonstrate continuity between instruments. General data
analysis focused on understanding the responses in terms of descriptive statistics (e.g., means,
standard deviations, etc.). Additionally, following factor analysis of individual KMO question
groups, inferential statistics such as Pearson’s correlations allowed for an expanded
understanding of the relationship between variables. The focus of the study centered on the
results based on level of student participation and completion of the PMP.
Validity and Reliability
Validity measures whether the instrument accomplished what it intended to do, while
reliability measures if the instrument gathered consistent results over time Salkind (2014). Using
preexisting instruments that have shown both validity and reliability, this survey instrument was
an amalgamation of elements from previously validated studies, with slight modifications to suit
the needs of the medical education context. Sources that made up the combined instrument for
this study included established instruments from Fallar et al. (2019), Pintrich et al. (1991), Baxter
Magolda and King (2007), Wilson et al. (2005), and Bandura (2006). Pilot testing also
contributed to the internal validity of the combined instrument used in this study.

40
The quantitative instrument for this study included 47 questions to examine five KMO
influencers in relation to emerging and maturing self-authorship within a career exploration
context (Appendix A). Six questions addressed knowledge influences, including four questions
related to declarative knowledge and two related to metacognitive influence, specifically one
help-seeking and one self-reflection question. Motivation influences comprised seven questions
related to self-efficacy and 16 questions related to self-determination. Organization influencers
included four questions related to professional development resources and training. Finally, an
open-ended question gathered narrative response from students about organizational factors that
influenced developmental experiences during medical school.
The use of Pearson’s correlations and Cronbach’s alpha established concurrent validity
with a measure of .70 or higher within questions that employ a four-point Likert scale. As stated
by Tavakol and Dennick (2011), sections of the instrument that used alternate forms of
measurement were subscales. Psychometric data from each preexisting instrument contributed
positively to the overall potential validity and reliability of the survey. Fallar et al. (2019)
provided a validated instrument used with medical students in a similar setting. Bandura’s (2006)
self-efficacy scales have shown to measure self-regulation consistently over time and in multiple
settings. Pintrich et al. (1991) and Wilson et al. (2005) provided established instruments around
help-seeking and resource utilization.
In addition to the quantitative instruments, an open-ended field in the survey instrument
determined what has influenced student success during medical school. After the researcher’s
initial review to identify recurring themes, two raters coded open-ended responses based on
identified influential factor(s) highlighted in respondent’s narratives. After coding was
completed by each rater, a mediated discussion occurred to reconcile differences. Coding

41
analysis included a Kappa (McHugh, 2012) performed in SPSS® Statistics 27.0.1.0. to verify an
acceptable level or congruence between ratings (.75 or higher). Responses showed low and high
engagement with professional development success factors. Responses provided further
explanation as to why respondents placed high value on previously identified influence(s) from
survey item 44 (Appendix A).
Refinement efforts to improve the instrument and test internal reliability included a pilot
study with 15 current third- and fourth-year students. As discussed by Robinson and Firth
Leonard (2019) and Cresswell and Cresswell (2018), this process allowed for student
perspective, feedback regarding individual questions, and testing the overall flow of the survey.
Recruitment efforts sought to obtain an acceptable response rate of 75% of the second-year class
based on a 5% margin of error, 95% confidence level, second-year student population of 126,
and response distribution of 50% (Raosoft, 2019). As outlined by Pazzaglia et al. (2016) to
maximize response rates and reliability, recruitment efforts included clear communication
announcing the study over email beforehand and emailing the survey directly to second-year
students. The survey window was 4 weeks to boost a high response rate. Monitoring overall
survey response and sending out weekly reminders occured as needed. To incentivize response,
participants who completed the survey were entered in a random drawing for three Cotopaxi
backpacks valued at $75 each. The Director of Education and Scholarship monitored and
oversaw the survey process, including incentives.
Ethics
The researcher must maintain neutrality and protect human subjects from harm while
participating in a study (Cresswell & Cresswell, 2018; Robinson & Firth Leonard, 2019). Using
an anonymous survey ensured the confidentiality of participants. The survey was voluntary and

42
students were under no obligation to participate. The researcher stored deidentified data securely
in a locked file cabinet (as needed) and stored digital files on a password-protected computer and
secure encrypted server requiring dual authentication. Informed consent forms obtained from all
participants included communication of potential risks and benefits related to the study.
Participants did not receive any compensation, but were eligible for a random drawing for three
$75 Cotopaxi backpacks. The Director of Education and Scholarship serves as an independent
researcher conducting various research projects for WMS and does not report to the Dean of
Student Affairs or have direct involvement with the PMP. Within this role, he handled the
distribution of the survey to eliminate any power dynamic due to the researcher’s leadership role
within student affairs and the PMP. The data gathering protocols and analysis process adhered to
the IRB processes at both the University of Southern California and WMS. Any approvals
related to survey distribution protocols followed both schools’ IRB processes.

43
Chapter Four: Findings
The quantitative data collected in this study examines self-authorship and early career
exploration. Using a gap analysis identified in Chapter 3, sorted into knowledge, motivation, and
organization (KMO) influencers, these data help address the following research questions:
1. What are the knowledge, motivation, and organizational influences that drive
early medical student interventions to improve the specialty exploration process?
2. What are the recommendations for improving medical student specialty
exploration processes?
The quantitative analyses are organized into assets and needs related to first-year medical
students’ attitudes, perceptions, and/or behaviors, toward self-authorship as it relates to early
career exploration.
Participating Stakeholders
The stakeholders for this study were students from the Wasatch School of Medicine. The
students completed their first year of the program and had the opportunity to participate in the
PMP as well as potentially complete a one-year certificate in the program. With a population size
of 127, 76% of the students responded (n = 97). Table 2 highlights respondent demographics and
shows that most participants fell within the age range of 27-30 (58%). Of those who responded
to the survey, 38 (39%) identified as female and 56 (58%) identified as male. One student
identified as “non-binary” and two students (2%) preferred not to say. In addition to age and
gender, respondents primarily identified as White (81.4%), while 18 students (18.5%) identified
as people of color or multiple ethnicities within the sample.

44
Table 2
Respondent Demographics
Age n f
24-26 37 38.1%
27-30 50 51.5%
31 and over 10 10.3%
Gender

Female 38 39%
Male 56 58%
Non-binary 1 1%
Prefer not to say 2 2%
Cultural Background

American Indian or Alaskan Native 1 1.0%
Asian 11 11.3%
Black or African American 1 1.0%
Hispanic, Latinx, or of Spanish Origin 2 2.1%
Native Hawaiian or other Pacific
Islander 1 1.0%
Multiple ethnicity 2 2.1%
White 79 81.4%

45
Table 3 displays the subgroups used for the analysis process. The methodology in
Chapter 3 outlined examination of the PMP by comparing groups of students who completed and
did not complete a one-year certificate in the program. However, the analyses that follow
indicate this was insufficient and necessitate additional subgroup analyses. Respondent data
indicating level of participation in workshops facilitated better understanding of the impact of the
PMP on early career exploration interventions. As a result, the analysis uses subgroups based on
level of workshop attendance and certificate completion. The subgroups naturally narrowed the
focus of the analysis to the impact of participation in the PMP on KMO influencers in relation to
self-authorship dimensions. To optimize the ability to detect differences between groups,
analyses included only the low (0-1) and high (7 or more) attendance groups. Of the 97 students
who answered a multiple-choice question indicating how many PMP sessions they attended, 22
respondents (23%) attended one or fewer workshops, 58 (60%) attended two to six, and 17
(17%) attended seven or more.

46
Table 3
Quantitative Subgroups for Analyses
Subgroups Number (n) Comparisons
Total Sample 97
Certificate Completed (CC)
Incomplete Certificate (IC)
60
37
CC to IC
High Workshop Attendance (HA)
Mid Workshop Attendance (MA)
Low Workshop Attendance (LA)
22
58
17
HA to LA

As described in Chapter 3, Tables 5 and 6 include additional subgroupings of students.
Table 5 includes students who indicated a higher degree of purpose. Table 6 includes the same
purpose subgroup as well as students who indicated a higher degree of help-seeking and a higher
degree of reliance on external resources. Response comparisons between attendance, certificate
completion, and purpose subgroups for all survey items are discussed in the next section
overview.
Quantitative Analysis Overview
Chapter 3 provided a basic overview of the quantitative analysis process. The analysis
effort includes a Cronbach’s alpha where applicable to show the reliability of the various KMO
influencers assessed with the 47-items across dependent measures. Using Excel 2016 and IBM®

47
SPSS® Statistics 27.0.1.0, an in-depth analysis of response data includes means comparisons
with a 95% confidence level to show statistical significance.
Table 4 displays the Pearson’s correlation coefficients for identified KMO influencers
from the conceptual framework. Due to the nature of the survey items related to self-reflection
(metacognitive knowledge) and organization resources were not included in the table below.
Correlation coefficients ranged from .21 to .31. Correlation coefficients connected to help-
seeking are self-efficacy (r = .21) and self-determination (r = .31). Correlation coefficients
involving self-efficacy are self-determination (r = .22) and organizational training
(r = .23). These correlations demonstrate the significant interrelated relationship between these
items. However, the table also displays the challenge encountered with attempts to measure
declarative knowledge, as the related instrument items did not have a high correlation with the
other KMO influencers and pose challenges identifying conclusive evidence. Of note, declarative
knowledge items display an insignificant correlation with self-efficacy items. Further discussion
of survey item reliability follows in the next section.

48
Table 4
Pearson's Correlation Coefficients—Total Sample
Measure 1 2 3 4 5
1. Knowledge: Declarative –
2. Knowledge: Help-Seeking -.04 –
3. Motivation: Self-Efficacy -.11 .21* –
4. Motivation: Self-Determination .18 .31** .22* –
5. Organization: Training .09 .06 .23* .12 –
*p < .05. **p < .01.

The knowledge, motivation, and organization sections that follow discuss descriptive
statistics as well as identify assets and needs as part of the inferential analysis process.
Specifically, comparisons made between high and low attendance subgroups yielded statistically
significant responses to some of the KMO influencers.
A reliability analysis of dependent measures yielded mixed results. The dependent
measures included modified items from Fallar et al. (2019) to measure declarative knowledge,
self-determination, and organization training, Pintrich et al. (1991) to measure help-seeking, and
Bandura (2006) to measure self-efficacy, as well as a question modeled after Balmer et al. (2013)
to measure organization resources. Appendix B indicates the reliability analysis of the
declarative knowledge, motivation as self-determination, and organization training items (Fallar
et al., 2019). Appendix C shows the reliability of self-efficacy items analysis (Bandura, 2006).
Both appendices include individual survey questions, factor loading, corrected item correlations,

49
and Cronbach’s alpha for each set of items. Additional survey items related to help-seeking,
influential success factors, and open-ended questions are included in their respective KMO
sections and indicate reliability as well as statistical significance where applicable.
Due to low reliability (α < 0.7) of the survey items noted in Appendix B related to
declarative knowledge and organizational training, use of these items to measure the impact of
the PMP is limited, thus requiring further research. Regarding declarative knowledge, the low
Cronbach’s alpha is potentially reflective of survey items that fail to measure elements capturing
the role and influence of declarative knowledge on self-authorship including career exploration.
It could also mean that during the first year, respondents are incapable of exploring knowledge
types outside of the intense demand for factual knowledge attainment. However, frequencies and
means are discussed in their respective sections to demonstrate the data analysis process for these
items.
Appendix C displays the overall reliability of items that measure self-efficacy based on
Bandura (2006). The resulting reliability of the items (α = .80) demonstrates that the questions
consistently measure self-efficacy and function reliably together. Additional discussion regarding
the analysis of student response in relation to these items is provided in the self-efficacy section.
The sections that follow provide the results for each KMO influencer and include specific tables
and figures to further discuss the survey results and impact of the PMP on each influencer.
Results for Knowledge Influencers
Three knowledge influencers surfaced during the literature review process: declarative
knowledge and metacognitive knowledge (self-reflection and help-seeking). Declarative
knowledge survey items employed a Likert scale; the self-reflection item used an open-ended
question; and the help-seeking item provided a “select all that apply” question. As discussed in

50
Chapter 3, the conceptual framework outlines how these knowledge influencers, coupled with
low and high self-authorship behaviors, are potentially enhanced by program interventions. The
purpose of the quantitative research is to look at student knowledge related to early career
exploration and, specifically, if the PMP is having a positive impact on student knowledge
related to self-authorship. This study examines assets and needs related to first-year medical
students’ attitudes, perceptions, behaviors, and proclivities toward self-authorship as it relates to
career exploration. Each influencer is addressed sequentially in the sections that follow.
Influence 1 —Declarative Knowledge
As found in the literature review, declarative knowledge is generally overemphasized
during medical school and limits the effectiveness of the learning environment. Students need to
acquire metacognitive knowledge as they begin exploring specialty during the first two years
(Chen et al., 2015; Mancini et al., 2015). The barriers students face in making the transition from
memorization of facts to other forms of knowledge are lack of time and lack of much-needed
psychosocial and professional skills due to the immediate demands of ever-present exams
(Gruppen et al., 2019). This section of the study looks at students’ focus on declarative
knowledge and if the PMP is decreasing emphasis on this form of knowledge.
Declarative Knowledge Survey Results
The data gathered for this quantitative analysis was drawn from the self-authorship
instrument (Fallar et al., 2019) and contained four Likert scale questions related to declarative
knowledge in the form of assessing how students interpret information (Appendix B). A higher
mean indicates students tend to be more focused on factual knowledge above their own opinions.
Ninety-seven students responded to these four items (76%). Appendix B indicated these survey
items had low reliability (α = .53).

51
Table 5 displays a statistical breakdown and comparison of the total sample and subgroup
means, indicating the instrument overall did not detect a difference in student perceptions about
interpreting information based on the level of participation in the PMP. However, the high
purpose subgroup indicates less agreement on average than the low purpose group (M = 2.26
versus M = 2.50; p < 0.05) with a medium effect size (d = 0.61) regarding the importance of
relying on the expertise of authority figures (declarative knowledge) above their own opinions.

Table 5
Descriptive Statistics and Means Comparisons—Declarative Knowledge
Comparison
n M
SD df t F Cohen’s d p
TS 97 2.44 0.40
HA
LA
17
22
2.46
2.44
0.41
0.49
1 0.08 0.01 0.04 .932
CC
IC
60
37
2.46
2.39
0.39
0.42
1 -0.83 0.70 0.17 .410
HP
LP
25
72
2.26
2.50
0.28
0.42
1 -2.60 6.75 0.61 .011
Note. Total Sample (TS), High Attendance (HA), Low Attendance (LA), Completed Certificate
(CC), Incomplete Certificate (IC), High Purpose (HP), and Low Purpose (LP). 95% CI utilized
for calculating p values. Cohen’s d used for calculating effect size. Instrument uses a four-point
Likert scale. Higher mean indicates students tend to be more focused on factual knowledge
above own opinions.

52
Declarative Knowledge Survey Analysis
In line with previous studies (Mancini et al., 2015; Schmidmaier et al., 2013; Schei et al.,
2018) encouraging efforts to deemphasize declarative knowledge in medical education, there is
evidence related to the high and low purpose subgroups who participated in the PMP, indicating
a trend to assert their own opinions instead of relying solely on the expertise of authority figures
to interpret information. However, as noted in Appendix B, this section of the instrument lacked
sufficient reliability, as the Cronbach’s alpha fell below an acceptable level
(α =.53). Consequently, additional data is needed to detect the effectiveness of programmatic
efforts by the PMP to reduce student focus on declarative knowledge. As a result, this portion of
the study is identified as a need. The following section of the quantitative study examines
metacognitive knowledge attainment and if the PMP specifically increases self-reflection
behaviors and help-seeking perceptions among program participants.
Influence 2 —Metacognitive Knowledge: Self-Reflection
Metacognitive knowledge is an essential aspect of the career exploration process that is
lacking in academic medicine and which decreases during preclinical training (Chen et al., 2015;
Hong et al., 2015). Self-reflection is a necessity throughout medical education and is directly
linked to self-authorship as well as early career exploration (Barber et al., 2013; Volpe et al.,
2019). A lack of self-reflection has a negative impact on academic performance and
developmental experiences (Hays et al., 2011). Conversely, the benefits of self-reflection include
making meaning of experiences and increasing professional identity development (Cope et al.,
2017). This section of the study looks at efforts by the PMP to promote metacognitive
knowledge in the form of enhancing student self-reflection behaviors.

53
Metacognitive Knowledge: Self-Reflection Survey Results
Students responded to an open-ended field in the survey instrument to determine what
has influenced their success during medical school. Responses provided further explanation as to
why they placed high value on previously identified influence(s) from survey item 44 (Appendix
A). The initial review of student responses identified three themes in student comments that add
clarity to student perceptions of the relationship between having a sense purpose, seeking help
from PMP resources, and using external resources related to their perceptions of success in
medical school.
As described in Chapter 3, two raters coded open-ended responses based on these three
influential factor(s) respondents highlighted in their narratives. After initial coding was
completed by each rater, a mediated discussion was used to reconcile differences. The Kappa
confirmed an acceptable level of congruence for having a sense of purpose (k = .75), seeking
help from PMP resources (k = .86), and using external resources (k = .95) themes. The purpose
code indicates the students who in their comments tended to emphasize the influence of having a
purpose to their success in medical school. The help-seeking code indicates the students who in
their comments tended to emphasize the source of their success in medical school to a particular
WMS support program such as mentoring, Wellness, or Academic Success. The external
resources code signifies the students who in their comments tended to emphasize the influence of
outside study resources on their success in medical school. Table 6 displays a breakdown of the
student response according to the three emergent themes and serves as a basis for discussion that
follows.

54
Table 6
Coded Theme Subgroup Comparison
Subgroups Number (n) Comparisons
External Resource Group (EG)
Non-External Resource Group (NEG)
29
68
EG/NEG to HA/LA

Purpose Group (PG)
Non-Purpose Group (NPG)
26
71
PG/NPG to HA/LA

Help-Seeking Group (HG)
Non-Help-Seeking Group (NG)
31
66
HG/NG to HA/LA

External Resources Subgroup. Twenty-nine respondents (30%) placed significant value
on declarative knowledge as influential to their success during preclinical education. Notably,
these students prioritized and relied heavily on factual knowledge attainment above success
factors that contribute to metacognitive knowledge development, as illustrated by the following
student response: “I rely heavily on external resources to learn. . . . I think less about the other
factors…either because I don't have time or because I don't have the capacity to care about
them.”
The students who placed high value on factual knowledge attainment as most important
to their success in medical school felt they were unable to engage in other resources. In this
example, the student reflects about lacking the capacity to care about anything else and attributed
their success almost exclusively to using external resources. The above narrative illustrates the

55
negative impact on students who primarily focus on declarative knowledge because it limits their
access to much needed forms of knowledge attainment.
Purpose Subgroup. In contrast, 26 students (27%) provided narrative about why having
purpose has been the most important factor to their success. For example, one student stated:
No matter the quality of curriculum or the quantity of resources available, what
makes the most difference in my taking advantage of the opportunities available is my
personal commitment and work ethic, which are supported by and determined by my
sense of purpose and personal support system.
In another example, a student wrote, “I've had moments during which I questioned
whether or not I wanted to continue a career in medicine . . . having that sense of purpose
provided the base for me to continue forward. Without that, I would have chosen a different
career path.” As described by both students above, the perspective shared identifies having
purpose as helping them get through the challenges they face in medical education by keeping
perspective about what matters as well as future goals, a metacognitive approach that included a
deeper level of self-reflection. The students who identified purpose as a significant success factor
continued to use external resources a function of declarative knowledge, but prioritized self-
reflection about having purpose (metacognitive knowledge) as more influential to their career
exploration process, identity development, and success in the program than external resources
Help-Seeking Subgroup. Similarly, 33 students (32%) commented about the high value
they placed on help-seeking to overcome struggles during medical school. To illustrate the
overall sentiments shared, one student stated, “Support from the [W]ellness [P]rogram has
allowed me to work through a lot of concerns with my family and my past that may have
otherwise inhibited my success so far in medical school.”

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The students who reflected on help-seeking recognized the value of reaching out for
support with their personal life to improve mental health, which in turn contributed positively to
academic outcomes and overall identity development. Analysis of these results are discussed
below.
Metacognitive Knowledge: Self-Reflection Survey Analysis
This section of the study uses student narratives triggered by the open-ended survey item
and illustrates a relationship between subgroups with high participation in the PMP. Respondents
in the purpose and help-seeking subgroups display the benefits of in-depth self-reflection
behaviors in relation to self-authorship. Previous studies identified the negative consequences
students experience when prioritizing declarative knowledge (Chen et al., 2015; Mancini et al.,
2015; Schmidmaier et al., 2013; Schei et al., 2018). Similarly, the student who provided narrative
indicating a strong focus and dependence on declarative knowledge was negatively impacted by
their limited perspective and felt they lacked capacity to benefit from other forms of knowledge.
In contrast, the students in the purpose and help-seeking subgroups describe an internal process
of overcoming and making meaning when challenged as a function of increasing individual self-
authorship (Baxter Magolda et al., 2007). The evidence aligns with the research describing the
benefits of self-reflection (Barber et al., 2013; Cope et al., 2017; Hays et al., 2011; Steinauer et
al., 2019; Volpe et al., 2019), confirming that programmatic efforts by the PMP to encourage
self-reflection related to purpose and help-seeking are assets, have a positive impact on
overcoming challenges, and should be encouraged to help students process their future goals,
including career exploration. A discussion of the next knowledge influencer, help-seeking,
follows.

57
Influence 3 — Metacognitive Knowledge: Help-Seeking
Medical students generally lack necessary help-seeking skills and do not engage available
resources at the level needed for effective training and career exploration (Gold et al., 2015). The
barriers students face in seeking help include help avoidance due to a perceived stigma and fear
of mistreatment as well as appearing vulnerable to peers and faculty (Artino et al., 2012;
Castillo-Angeles et al., 2017). This section of the study examines respondent help-seeking
behaviors and if participation in the PMP is increasing this form of metacognitive knowledge
development.
Metacognitive Knowledge: Help-Seeking Survey Results
To better understand the impact of the PMP on student propensity to seek help, student
respondents were asked to select from a list of 13 types of individuals, ranging from personal to
professional, from whom they would seek help for career exploration. The question was
designed to assess students’ help-seeking tendencies in relation to PMP participation. Table 7
provides descriptive statistics of the total sample (n = 97) and calculates an average of the total
help-seeking types selected to explore differences as a measure in high and low attendance and
certificate completion subgroups. The descriptive statistics and means comparisons indicate the
high attendance and certificate completion subgroups (M = 6.65; p > 0.05 and M = 6.81; p <
0.05) are engaging in help-seeking for specialty exploration more than the low attendance and
incomplete certificate subgroups (M = 5.41 and M = 5.57). Of note, the high and low attendance
subgroups indicate a large effect size (d = 0.75). While the certificate completion subgroups
indicate a medium effect size (d = 0.50). Further analysis follows based on the specific items
selected in this section of the study to provide additional insight regarding the influence of the
PMP on student help-seeking perspectives.

58
Table 7
Descriptive Statistics and Means Comparisons—Help Seeking
Comparison n M SD df t F Cohen’s d p
TS 97 6.34 2.53
HA
LA
17
22
6.65
5.41
2.42
0.56
1 1.47 2.16 0.75 .150
CC
IC
60
37
6.81
5.57
2.31
2.70
1 -2.42 5.87 0.50 .017
Note. Total Sample (TS), High Attendance (HA), Low Attendance (LA), Completed Certificate
(CC), and Incomplete Certificate (IC). 95% CI utilized for calculating p values. Cohen’s d used
for calculating effect size. Instrument has 13 options to select from. Higher mean indicates
student tendency to seek-help from a wider variety of individuals.

Figure 3 shows the average responses by high and low attendance subgroups comparing
means using a one-way ANOVA for each item. Utilizing the high and low attendance subgroups
to examine help-seeking tendencies, 17 students (18%) in the high attendance group more
frequently indicated a willingness to seek help from PMP coaches (M = 94% versus M = 36%; p
< 0.05) and PMP Staff (M = 41% versus M = 14%; p = 0.05) in early career exploration than 22
respondents in the low attendance group (23%). Figure 3 also displays the overall trend for the
low attendance group to rely more on family, relatives, and friends for assistance with specialty
exploration, while the high attendance group shows a trend to engage school of medicine
professional development resources, including PMP coaches, staff, and mentors and faculty as

59
well as student affairs and academic success programs, to aid specialty exploration. These results
indicate that the high attendance group was more willing to seek help for career exploration from
WMS mentors and staff than the low attendance subgroup.

Figure 3
High and Low Attendance Subgroup Means by Help-Seeking Item

*p < .05.
5%
27%
14%
32%
14%
59%
36%
73%
5%
68%
27%
59%
82%
0%
24%
24%
42%
41%
82%
94%
88%
12%
65%
29%
41%
65%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Other
Curriculum Staff
Academic Success
Student Affairs Dean
PMP Staff*
Faculty/Other
PMP Coach*
Mentor
Minister
Friend
Other Relative
Parent
Intimate Partner
High Attendance Mean Low Attendance Mean

60
Metacognitive Knowledge: Help-Seeking Survey Analysis
The evidence found in this study and confirmed by other scholars (Artino et al., 2012;
Castillo-Angeles et al., 2017; Dyrbye et al., 2015; Fnais et al. 2014; Gold et al., 2015; Pereira et
al. 2016; Trépanier et al., 2015; Winter et al., 2017) suggests that efforts to improve student
perspectives regarding help-seeking from staff and faculty have a positive impact on self-
authorship including career exploration. Further, this study demonstrates students with high
participation in the PMP are more likely to seek help from school of medicine resources than the
low attendance subgroup. The results also confirm that efforts to improve student perceptions
about help-seeking by the PMP are an asset and should continue to be employed to optimize
early career exploration efforts.
Results for Motivation Influencers
Two motivation influencers emerged during the literature review process related to the
motivation: self-efficacy and self-determination. The conceptual framework outlines how these
motivation influencers, coupled with high and low self-authorship behaviors, are potentially
enhanced by program interventions. The purpose of the quantitative research is to look at student
motivation related to early specialty exploration and specifically if the PMP is having a positive
impact on student motivation related to this exploration. This study examines assets and needs
related to first-year medical students’ attitudes, perceptions, behaviors, and proclivities toward
self-authorship as it relates to career exploration. Each motivation influencer is addressed
sequentially in the sections that follow.
Influence 1 —Motivation: Self-Efficacy
The lack of self-efficacy in medical school has a detrimental effect on academic
performance and career exploration (Kim et al., 2014). Early interventions are needed during the

61
first year to boost and encourage students to maintain self-efficacy behaviors throughout their
training (Artino et al., 2012). This section of the study investigates students’ confidence levels
related to self-authorship and career exploration to determine if the PMP is increasing student
motivation in this area.
Motivation: Self-Efficacy Survey Results
The data gathered for this section of the quantitative analysis utilized a self-efficacy
instrument (Bandura, 2006). Appendix C displays that the survey items had high reliability (α =
.80), function together, and generally measure self-efficacy levels as intended. Table 8 displays a
statistical breakdown and comparison of the total sample and subgroup means across an average
of all items. Generally, the 97 respondents (76%) demonstrate having high confidence in each
item topic (M = 74). As discussed by Bandura (2006), this meets the threshold for high self-
efficacy. However, the instrument did not detect a difference in student perceptions regarding
self-efficacy level. Subgroup statistics below also indicate low variability for the certificate
complete/incomplete (MCC = 74.52 and MIC = 73.15; p > 0.05) and high/low attendance (MHA =
75.64 and MLA = 75.72; p > 0.05).

62
Table 8
Descriptive Statistics and Means Comparisons—Self-Efficacy
Comparison
n M SD df t F p
TS 97 74.00 13.12
HA
LA
17
22
75.64
75.72
12.63
12.01
1 1.47 2.16 .150
CC
IC
60
37
74.52
73.15
13.35
12.88
1 -0.50 0.25 .618

Note. Total Sample (TS), High Attendance (HA), Low Attendance (LA), Completed Certificate
(CC), and Incomplete Certificate (IC). 95% CI utilized for calculating p values. Instrument uses
a 100-point scale. Higher mean indicates students tend to be more confident in areas related to
self-authorship and career exploration.

Figure 4 displays a graphic representing the results for the high and low attendance
subgroups in relation to the seven self-efficacy items. A one-way ANOVA to compare means
across each item to determine if a connection exists between an increase in self-efficacy and the
PMP is occurring on a granular level. As visually indicated below, there is no detectable
connection to an increase in self-efficacy across the items and PMP attendance.

63
Figure 4
High and Low Attendance Subgroups Means Comparison for Self-Efficacy Items

Motivation: Self-Efficacy Survey Analysis
Previous studies state the positive benefits of fostering self-efficacy during the first year
of medical school as improving self-authorship intrinsic motivation, and career exploration
(Artino et al., 2012; Babenko & Oswald, 2019; Gannouni & Ramboarison-Lalao, 2018;
Gharetepeh et al., 2015; Halstead & Lare, 2018; Kim et al., 2014; Yu et al., 2016). While Table 6
and Figure 4 show respondents generally answered these questions similarly, it is important to
note the overall response is on the high end of the scale, indicating the respondent confidence
level in the identified self-efficacy areas. This is a notably positive result unrelated to the PMP.
Regarding participation in the PMP, there are minor upward and downward trends shown in
69
75
78
81
64
80
83
75
72
67
82
67
80
86
0 10 20 30 40 50 60 70 80 90 100
Reach Out Mentor
Define Strengths
Define Weaknesses
Define Values
Balance Life
Define Purpose
Teamwork
2 High Attendance Group Mean 1 Low Attendance Group Mean

64
Figure 4 for the high and low attendance subgroups in the areas of teamwork, balance life, reach
out to mentor, and define weaknesses items. However, the instrument items are unable to detect
if the participation in the PMP is influencing the apparent high levels of self-efficacy. The
evidence suggests additional efforts to examine the potential positive impact of the overall high
self-efficacy average in relation to the learning environment. In addition, reevaluating methods
used to detect self-efficacy related to PMP interventions around self-authorship and career
exploration are needed. A discussion of self-determination results and analysis follows.
Influence 2 —Motivation: Self-Determination
Lack of autonomy support has a negative impact on medical students and is associated
with a motivation loss and a decline in well-being (Neufeld & Malin, 2020). Successful
interventions include efforts to increase intrinsic motivation in the learning environment around
career exploration and self-authorship (Bondi et al., 2015; Kim et al., 2016; Kusurkar et al.,
2019). This section of the study investigates self-determination levels related to self-authorship
and career exploration to determine if the PMP is increasing student motivation in this area.
Motivation: Self-Determination Survey Results
The data gathered for this section of the quantitative analysis draws from the self-
authorship instrument (Fallar et al., 2019) and contained 16 Likert scale questions to explore
student perception of the importance of having autonomy and independence when making career
related decisions during medical school. However, as discussed previously, Appendix B shows
the outcome of the analysis for these items indicating that the 16 items reached an acceptable
level of reliability (α =.71). Table 9 displays a statistical breakdown of the total sample as well as
subgroups means, indicating the instrument did not detect a difference in student perceptions of
autonomy importance during career exploration. The overall response indicated general

65
agreement around the importance of autonomy related to career decisions (MTS = 3.30). Further
examination of subgroups indicates the certificate completion subgroup on average showed more
agreement around the importance of having independence and autonomy related to career
decisions than the certificate incomplete subgroup (MCC = 3.33 and MIC = 3.26; p = 0.15).
Similarly, the high attendance subgroup responded with more agreement around the importance
of having independence and autonomy related to career decisions than the low attendance
subgroup (MHA = 3.33 and MLA = 3.26; p = 0.37). Similarly, both the attendance (d = 0.29) and
certificate completion (d = 0.30) subgroups indicated a small effect size.

Table 9
Descriptive Statistics and Means Comparisons—Self-Determination
Comparison n M SD df t F Cohen’s d p
TS 97 3.30 0.23
HA
LA
17
22
3.35
3.28
0.22
0.26
1 0.92 0.84 0.29 .365
CC
IC
60
37
3.33
3.26
0.23
0.23
1 -1.46 2.14 0.30 .147
Note. Total Sample (TS), High Attendance (HA), Low Attendance (LA), Completed Certificate
(CC), and Incomplete Certificate (IC). 95% CI utilized for calculating p values. Cohen’s d
utilized for calculating effect size. The instrument uses a 4-point Likert scale. Higher mean
indicates students tend to consider their own opinions and views more when making career
related decisions.

66
Motivation: Self-Determination Survey Analysis
This study shows that this sample of students generally acknowledge the importance of
having autonomy and independence, which includes all three dimensions of self-authorship
regardless of level of participation in PMP. Although there is a trend noted above for the high
attendance and certificate completion subgroups showing a slightly higher response than their
counterparts, there is no detectable difference related to student responses and participation in the
PMP. Additional research is needed to look at effectiveness of programmatic efforts of the PMP
to increase student perceptions around self-determination (autonomy and independence) during
medical school. Organization influencers are discussed in the next section.
Results for Organizational Influencers
This section discusses two emergent organizational influencers: training and resources.
The conceptual framework outlines how these organization influencers, coupled with low and
high self-authorship behaviors, are potentially enhanced by program interventions. The purpose
of the quantitative research is to look at organizational influencers related to early career
exploration and specifically if the PMP is having a positive impact on organizational resources
and training related to this exploration. This study examines assets and needs related to first-year
medical students’ attitudes, perceptions, behaviors, and proclivities toward self-authorship as it
relates to career exploration. Each influencer is addressed sequentially in the sections that follow.
Influence 1 —Organization: Training
Professional development training is an essential and neglected aspect in the medical
school learning environment (Barber et al., 2013; Irby et al., 2010). Due to an intense focus on
knowledge and skill development, the curriculum has omitted important stages of professional
development training (Touchie & Ten Cate, 2016). This section of the study examines training

67
within the organization as experienced by the students and if the PMP is increasing positive
student outcomes.
Organization: Training Survey Results
The data gathered for this quantitative analysis was drawn from the self-authorship
instrument (Fallar et al., 2019) and contained three Likert scale questions related to training
students how to handle themselves in ethical situations (Appendix A). Appendix B indicates that
the Cronbach’s alpha fell below an acceptable level (α = .58). Table 10 provides an overview and
means comparison based on total and subgroup response to these items. Ninety-seven students
responded to these items (76%). Of note, the total sample indicated a lack of training in this area
(MTS = 2.64). In addition, a means comparison of subgroups shows very little difference between
the certificate complete/incomplete (MCC = 2.66 versus MIC = 2.60; p = 0.64) and the high/low
attendance (MHA = 2.78 versus MLA = 2.71; p = 0.63). In addition, both the attendance (d = 0.15
and certificate completion (d = 0.11) subgroups indicated a small effect size. As a result,
additional data is needed to detect the effectiveness of programmatic efforts to assess student
responses related to organization training influencers.

68
Table 10
Descriptive Statistics and Means Comparisons—Organizational Training
Comparison n M SD df t F Cohen’s d p
TS 97 2.64 0.52
HA
LA
17
22
2.78
2.71
0.46
0.45
1 0.49 0.24 0.15 .625
CC
IC
60
37
2.66
2.60
0.52
0.53
1 -0.48 0.27 0.11 .636
Note. Total Sample (TS), High Attendance (HA), Low Attendance (LA), Completed Certificate
(CC), and Incomplete Certificate (IC). 95% CI utilized for calculating p values. Cohen’s d
utilized to for calculating effect size. Instrument uses 4-point Likert scale. Higher mean indicates
students tend to be more aware of how to handle ethical dilemmas.

Organization: Training Survey Analysis
Current scholarship on this topic grapples with the lack of time and dedicated resources
for the professional development of future physicians (Barber et al, 2013; Fallar et al., 2019;
Gruppen et al., 2018; Heflinger & Doykos, 2016; Irby et al., 2010; Kjaer et al., 2011; Malone &
Supri, 2012; Teunissen & Westerman, 2011; Touchie & Ten Cate, 2016). While the need for
more time and resources is clear, the associated Cronbach’s alpha (α = .58) in this section of the
instrument lacks sufficient reliability and is therefore identified as a need. Further research must
occur to detect if PMP participation is having a positive impact on overcoming the challenges

69
providing sufficient time and resources for organizational training. The next section discusses
organizational resources.
Influence 2 —Organization: Resources
There is a lack of support for early career exploration that results in inconsistent student
engagement, high potential for career indecision, and increased physician burnout (Dyrbye et al.,
2018). The barriers students face are lack of exploration time (Halstead & Lare, 2018) and the
student perspective that career related resources are secondary to immediate academic demands
(Querido et al., 2018). To aid in overcoming the above-mentioned barriers, organization
resources, such as professional and personal networks, as well as having career purpose, aid
students in overcoming burnout and career indecision (Duffy et al., 2011; Fares et al., 2016). A
key success element within professional networking is having positive role-models from mentors
and faculty, which has shown to have significant influence on self-authorship and career
exploration (Frei et al., 2010; Parker et al., 2014; Sternzuz et al., 2012). This section of the study
examines resources within the organization as experienced by the students and whether the PMP
is increasing positive student outcomes related to career exploration and self-authorship.
Organization: Resources Survey Results
The data gathered for this quantitative analysis was modeled after the Balmer et al.
(2003) influence items found in question 44 (Appendix A). Students were asked to divide up 100
points among a list of 10 factors that potentially influence their success in medical school,
including career exploration. The response means were compared between low and high
attendance groups by using a one-way ANOVA.
Influence Factors. Figure 5 shows that the high attendance subgroup recognized the
value of purpose and maintaining a personal network as most influential to their success in

70
medical school. Respondents in the high attendance group assigned more points to the purpose
influence factor than the low attendance group (MHA = 14.12 versus MLA = 8.45; p < 0.01). The
high attendance group also assigned more points to maintaining a personal network, including
strong relationships with peers, than the low attendance group (MHA = 9.76 versus M = 6.18LA; p
< 0.05). In contrast, the low attendance subgroup assigned more points to the influence of
participating in research opportunities than the high attendance subgroup (MHA = 9.86 versus MLA
= 5.88, respectively; p < 0.05). The student inclination to build personal relationships also
indicates the high attendance group assigned more points to maintaining a professional network
than the low attendance group (MHA = 10 versus MLA = 7.32, respectively; p > 0.05). Finding
similarity in response, the high attendance and low attendance groups tended to assign similar
points to factors such as curriculum (MHA = 16.47 versus MLA = 17.27; p = 0.82) or service
learning (MHA = 8.35 versus MLA = 8.95; p = 0.73).
While not shown to be statistically significant, Figure 5 shows the average response from
the high attendance group was lower (MHA = 11.15 versus MLA = 15.14; p = 0.30) indicating a
trend in the difference of perspective about the value placed on the influence of external study
resources between the two attendance subgroups. While not possible to draw a direct connection
to PMP resources offerings, it is a notable trend worthy of further study.

71
Figure 5
High and Low Attendance Subgroup Means by Influence Factor

*p < .05. **p < .01.

17.27
15.14
8.41
8.41
8.45
6.18
7.32
10
8.95
9.86
16.47
11.65
6.88
8.65
14.12
9.76
10
8.24
8.35
5.88
0 2 4 6 8 10 12 14 16 18 20
Curriculum
External Resources
Wellness
Academic Succes
**Having Purpose
*Personal Network
Professional Network
Strong Relationships
Service Learning
*Research
High Attendance Group Mean Low Attendance Group Mean

72
Additional Subgroups. Examining the three additional subgroups mentioned in Table 6
is useful to further examine student tendencies based on participation in PMP related to purpose,
external resource, and help-seeking. As mentioned previously, these three subgroups consisted of
students who indicated in an open-ended survey item that purpose, external resources, and help-
seeking had a high influence on their success in medical school and were used to perform this
examination. Figure 6 employs a Chi-square test to compare the high and low attendance groups
with purpose, external resources, and help-seeking subgroups; the results confirm a strong
positive relationship with high/low attendance and the purpose groups (MHA = 75% versus MLA =
25%; p < 0.05). Continuing the trend, students in the high attendance group also lean more
toward help-seeking as a positive influence related to their success than the low attendance
group.
Supplementing the identified help-seeking trend, student narrative from the open-ended
item referenced previously includes commentary about the benefits of seeking help from role
models. One student stated, “Close relationships with mentors/faculty has been instrumental in
exploring specialties and making professional connections in my chosen field.” Efforts to
connect students with role models clearly aids the specialty exploration process. Figure 6 also
displays a tendency for the low attendance group to seek help through external resources more
than the high attendance group. Although challenging to capture, this analysis begins to show the
potential for the PMP to have influence on help-seeking from resources that decrease student
focus on declarative knowledge in favor of experiences that foster metacognitive knowledge
such as help-seeking and valuing purpose as a significant success factor.

73
Figure 6
High and Low Attendance Sub-Groups Comparison to Purpose, External Resources, and Help-
Seeking Subgroups

*p < .05.
Resources Survey Results
The institution must be committed to providing increased career exploration resources,
including the process of defining a purpose in medicine and cultivating meaningful relationships
to aid the process (Domene, 2015; Duffy et al., 2011; Duffy et al., 2012; Dyrbye et al., 2018;
Fares et al., 2016; Halstead & Lare, 2018; Lent et al., 2016; McDow & Zabrucky, 2015; Park,
2018; Querido et al., 2018; Vo et al., 2017; Wang et al., 2018; White et al., 2011). Meaningful
relationships include PMP coaches and mentors who can provide much needed positive role
modeling around self-authorship behaviors and career exploration experiences during the
preclinical years. This analysis demonstrates the ability for PMP to assist students in seeing the
25%
58%
42%
75%
42%
58%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Purpose* External Help-Seeking
Subgroups
1 Low Attendance Group Mean 2 High Attendance Group Mean

74
value in having a sense of purpose and the necessity of cultivating personal and professional
networks as part of the early career exploration process. The evidence in this section is viewed as
a strong asset. This study provides a basis for further research to examine the impact of early
interventions to alter student perceptions around the value of defining a purpose and building a
personal network in support of career exploration at WMS.
Summary of Validated Influences
The following is a summary of the assets and needs determined in the study. In terms of
knowledge causes, there is a general overemphasis on declarative knowledge in academic
medicine, but the survey item was deemed unreliable and, as a result, there is a need for
additional research to determine if the PMP is deemphasizing factual knowledge. However,
regarding metacognitive knowledge causes, evidence indicated that students with high
participation in the PMP are more likely to seek help from the school of medicine resources and
programs than low attendance groups. In addition, respondents who provided narrative about
having purpose during medical school indicated an ability to self-reflect more deeply about
overcoming challenges related to medical school by relying on their purpose. Next,
organizational training lacked reliability, which also resulted in the need for additional research
to determine the impact of the PMP in this area. However, around organizational resources,
evidence demonstrated the ability for the PMP to positively influence student perceptions of
having a sense of purpose and cultivating a personal network as part of the early career
exploration process. Tables 11, 12, and 13 show the knowledge, motivation, and organization
influences for this study and their determination as an asset or a need.

75
Table 11
Knowledge Assets or Needs as Determined by the Data
Knowledge Influence Asset or Need
Declarative Knowledge Need
Metacognitive: Help-Seeking Asset
Metacognitive: Self-Reflection Asset

Table 12
Motivation Assets or Needs as Determined by the Data
Motivation Influence Asset or Need
Self-Efficacy Need
Self-Determination Need

76
Table 13
Organization Assets or Needs as Determined by the Data
Organization Influence Asset or Need
Training Need
Resources Asset

77
Chapter 5 uses the evidence from the data analysis process to discuss recommendations
and solutions for improving self-authorship and early specialty exploration for medical students
through the PMP.

78
Chapter Five: Recommendations and Discussion
Chapter 5 includes recommendations based on the identified assets and needs related to
knowledge, motivation, and organization influencers as well as their impact on the early
specialty exploration and self-authorship process. The following discussion of findings and
results is framed in an overall identified need to reimagine the PMP. The KMO gap analysis
process provides a framework to explore program improvements throughout this chapter. A
discussion of how findings and results inform recommendations follows.
Discussion of Findings and Results
Knowledge, motivation, and organization findings follow the previously established
order found in Chapter 2. Throughout the analysis process, it became apparent that the survey
results yielded limited interactions between knowledge, motivation, and organization influencers.
Although identified assets include active participants in the PMP exhibiting increased self-
reflection behaviors, positive help-seeking perspectives, and improved identification of success
factors during medical school, the overall results demonstrated student indifference toward the
PMP. As a result, evidence to support the hypothesis that the PMP improves self-authorship and
early career exploration are mixed, with some areas of the program improving student
perspectives while other areas were inconclusive, leaving much to be desired. Future research
and exploration are needed to better understand the impact of the program. Given the nature of
the results, further need for examination also creates a space for reimagination of the PMP. The
recommendations in the sections that follow acknowledge the need to build upon the results,
apply best practices from other programs, and improve the program evaluation approach going
forward. The gap analysis framework provides a structure for future program recommendations.

79
Recommendations for Practice
The recommendations follow the KMO order used in Chapters 2, 3, and 4 and center on
how each influencer contributes to the redesign of the PMP. There are six identified
recommendations to address key findings. Tables 13, 14, and 15 summarize KMO
recommendations, results, and proposed changes. The respective recommendations provide next
steps to reimagine the PMP and are discussed for each KMO in the sections that follow.
Knowledge Recommendations
The analysis process identified declarative knowledge needs and metacognitive
knowledge assets. Due to the challenge of an intense student focus on declarative knowledge,
there is clear evidence of an overemphasis on declarative knowledge, resulting in a lack of self-
authorship and early specialty exploration activities. This need requires a realignment of
educational priorities to decrease the emphasis on declarative knowledge to allow space for
increased self-authorship and early specialty exploration during medical school. Metacognitive
influencers, including self-reflection and help-seeking, are confirmed assets in this realignment
process and, as such, efforts need to be made to reinforce student engagement in these crucial
metacognitive activities early in their training. Table 14 summarizes the following
recommendations to address interconnected knowledge assets and needs.

80
Table 14
Summary of Knowledge Influences and Recommendations
KMO Recommendation Summary of Results Proposed Changes
Declarative: The curriculum
needs to provide space for
first-year students to make
meaningful connections to
the profession
Evidence suggests that
students generally prioritize
declarative knowledge
above professional
development resources
within the learning
environment
Partnership between PMP and
Curriculum to explore
other means to deliver
factual knowledge and
enhance student
relationships with support
networks
Metacognitive: The PMP
needs to further develop
and promote self-reflection
activities
Evidence indicated that active
participants in the PMP
exhibited increased self-
reflection behaviors around
professional development
Integration of PMP self-
reflection content
throughout the learning
environment, further aiding
the self-authorship and
career exploration process
Metacognitive: The PMP
needs to increase student
engagement in career-
related help-seeking
Evidence demonstrates
improved student
perception of help-seeking
from PMP-provided
resources
Embed PMP coaches into
existing first-year learning
communities and
incorporate coaching
sessions in parallel with
curriculum

81
Curriculum Adjustments
The curriculum needs to provide space for first-year students to make meaningful
connections to the profession. Graduate level curricula struggle to incorporate meaning-making
in conjunction with factual content delivery, thus hindering the complex learning processes that
contribute to self-authorship, specialty exploration, and identity formation (Perez, 2017).
Preclinical instruction can no longer be based primarily on factual knowledge acquisition and
needs to provide longitudinal experiences that foster strong relationships with patients, mentors,
staff, and faculty (Cooke et al., 2010). The evidence from the study suggests that students appear
to prioritize declarative knowledge above professional development resources within the learning
environment. To enhance the specialty exploration process, students need to see the PMP
coaches, faculty mentors, and staff as significant resources for career exploration and start to
engage them early in their training. Programmatic efforts that build meaningful connections with
faculty include identifying support relationships as a central component to education and altering
the curriculum by using online learning platforms for factual knowledge delivery to maximize
in-person time for relationship building (O’Brien & Irby, 2013). Efforts by the PMP to partner
with curriculum would be stronger if relationship building is a core aspect of the learning
environment by introducing PMP resources as students matriculate. Interconnections among
students also need to promote early career exploration, interpersonal skills, and knowledge of
self. In addition to utilizing online platforms for teaching, longitudinal learning experiences that
introduce clinical training starting in the first year are another means of providing relationship
development and connection to the profession.
Efforts to modify curriculum supported by the PMP should be modeled after longitudinal
integrated clerkships where students spend additional time in one location to forge deeper

82
relationships with patients and faculty (Konkin & Suddards, 2012). Adjusting the curriculum
significantly to alter the historical separation between clinical and preclinical training is a
necessary evolution to emphasize relationship development and maximize the PMP’s ability to
provide early specialty exploration and self-authorship experiences. As important as the
adjustments to the curriculum are for improving student connections to the profession, a critical
goal of the PMP is to improve student self-reflection.
Increase Self-Reflection Activities
The PMP needs to further develop and promote self-reflection activities. Cope et al.
(2017) confirm the benefits of self-reflection activities in relation to specialty exploration.
Current programmatic efforts by other institutions demonstrate the value of providing self-
reflection in the form of writing (Steinauer et al., 2019) and small group reflection (Volpe et al.,
2019). Augmenting existing efforts include the use of the PMP workbook and content exploring
individual purpose, strengths, values, and career options. Enhancing workshop and individual
coaching sessions is also a necessary step to building upon the success of the current program.
The Cleveland Clinic Learner College of Medicine provides a strong example of a first-year
program that incorporates self-reflection during foundational science courses in which students
write about and make meaning of their experiences (Kohn et al., 2011). Evidence from the study
indicated that active participants in the PMP exhibited increased self-reflection behaviors around
professional development. Integrating PMP self-reflection content into curricular and co-
curricular settings offers multiple self-awareness touch points throughout the learning
environment, further aiding students in the self-authorship and career exploration process. In
conjunction with fostering self-reflections activities, a key effort of the PMP is to encourage
students to seek help from PMP-provided individuals.

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Increase Help-Seeking Engagement
The PMP needs to increase student engagement in career related help-seeking. Examples
of successful initiatives at other institutions include integrated efforts to assist students in
overcoming barriers and encourage utilization of provided resources (Winter et al., 2017). Early
integration of PMP resources includes disseminating explicit information that promotes help-
seeking specifically from faculty mentors, PMP coaches, and staff. Evidence from the study
demonstrates improved student perception of help-seeking from PMP resources. Improvements
to the program include introducing positive help-seeking practices during medical school
orientation, the first PMP workshops, and the first PMP coaching session. Early student
interactions such as these increase awareness and destigmatize help-seeking, thus encouraging
students to take ownership of the available resources and access support from available PMP
personnel (Winter et al., 2017). Counseling efforts by PMP coaches, faculty mentors, and staff
must also include efforts to reduce negative coping strategies related to career exploration (Perez
& Gati, 2017). In addition, programs that offer flexible participation structures encouraging
creativity and adaptive help-seeking have proven to be effective (Artino et al., 2012). Following
this guidance, programmatic recommendations also include embedding PMP coaches into
existing first year learning communities and incorporating coaching sessions into flexible
engagement activities in parallel with regular curricular instruction. Increasing personnel
resources are explored further in the organization resources section. While help-seeking is
central to forging meaningful relationships that aid career exploration, a crucial need for the
PMP is to understand the connection between the program and motivation.

84
Motivation Recommendations
Self-efficacy and self-determination are fundamental to self-authorship and career
exploration. Unfortunately, medical education has a history of low student self-efficacy and
autonomy (Artino et al., 2012; Neufeld & Malin, 2020). Efforts to explore the relationship
between the PMP and these motivational influencers proved challenging. The resulting data
analysis identified self-efficacy and self-determination as needs. Surprisingly, WMS students
exhibited high self-efficacy levels based on Bandura’s (2006) thresholds. Further, attempts to
measure self-determination yielded no detectable difference in response based upon participation
in the PMP. As a result, the relationship between the PMP, self-efficacy, and self-determination
need further examination. The challenging nature of assessing self-efficacy and self-
determination influencers is an important issue that the PMP needs to address in future
evaluations. Table 15 summarizes the following recommendation to self-efficacy and self-
determination needs.
Table 15
Summary of Motivation Influences and Recommendations
KMO Recommendation Summary of Results Proposed Changes
Motivation: Assessment
efforts need to be
redesigned to explore the
relationship to the PMP
Evidence found low
variability and inability to
detect a relationship to the
PMP
Incorporate new quantitative
instrument for self-
determination and utilize
qualitative instrument to
gather more insight into
student experience

85
Assessment efforts need to be redesigned to explore the relationship to the PMP. Previous
scholarship identified challenges associated with capturing self-efficacy and self-determination
data using only quantitative means (Bandura, 2012; Creamer et al., 2010). Within this study, the
student sample generally exhibited high self-efficacy and moderate self-determination levels.
However, the survey detected low variability around these motivation influencers and an
inability to detect a relationship to the PMP. Previous studies incorporated mixed methods to
explore programmatic efforts to improve motivation related to career exploration. Halstead and
Lare (2018) found that successful programs increase student self-efficacy around career
exploration when counselors provide targeted outreach, positive affirmations, and role modeling.
Similarly, Keating et al. (2013) assessed student-created specialty-specific electives and found an
increase in self-determination as well as engagement in the courses. The PMP incorporates
elements described in the studies above such as PMP staff proactively reaching out to students
and using coaching sessions to both affirm and provide career related role modeling. Students
also have opportunities in the program to shape workshop content and evaluate guest speakers,
resulting in increased participation. While similarities exist between the PMP and other
programs, effective evaluation will provide much-needed additional information.
Future efforts to capture programmatic contributions of the PMP that improve self-
efficacy and self-determination need to incorporate quantitative and qualitative data gathering.
Appendix D outlines a previously validated Index of Autonomous Functioning (Weinstein et al.,
2012). The instrument assesses internal perceptions of control, pursuing interests, and self-
awareness related to authorship experiences. Interviews based on the item questions will gather
additional details of individual student experiences with autonomy and career exploration during
medical school. Using this assessment tool will allow further examination of PMP and student

86
perception of self-determination. The evaluation method will aid the process of examining
elements that have proven effective in previous scholarship. Enhancing program evaluations
would potentially provide insights into perceptions and behaviors of students prior to starting the
PMP and after completion of a one-year certificate. While motivation influencers clearly need
additional examination, a crucial goal of the PMP is to enhance organization resources.
Organization Recommendations
Reimagining the PMP builds upon the early successes of the program and has the
potential to aid curricular reform and enhance the professional development landscape. As it
currently stands, medical schools lack effective professional development resources (Irby et al.,
2010; Touchie & Ten Cate, 2016). Under the existing WMS educational structure, most students
continue to follow traditional patterns, prioritizing declarative knowledge and lacking
engagement in professional development resources. The negative impact of this pattern is well
documented in other studies and results in lack of self-efficacy (Artino et al., 2012), autonomy
loss (Neufeld & Malin, 2020), and career indecision (McDow & Zabrucky, 2015). In contrast,
the evidence gathered in this study confirms the ability for the PMP to improve student
perspectives of identified career exploration success factors in medical school when there is high
participation in the program. Specifically, the PMP improved attitudes around having purpose
and developing a personal network as important contributors to success in medical school.
Improved networking must also include positive role modeling by PMP coaches during the
preclinical years. Clearly, future efforts to fund, develop, and expand PMP programming are
distinctly needed to improve student perceptions in these areas. In addition, the results of the
study indicate a need for increased evaluation of PMP to further explore, build upon, and

87
strengthen the impact of the program on the full range of success factors. Table 16 summarizes
the recommendations to address organization assets and needs.
Table 16
Summary of Organization Influences and Recommendations
KMO Recommendation Summary of Results Proposed Changes
Organization: The PMP needs
to increase student
engagement in career
exploration supports,
including professional
development, role
modeling, and mentoring
Evidence of interventions that
improve student
perspectives about having
purpose and help-seeking
Introduce career exploration
success factors during
medical school orientation
as well as highlight the
benefits of PMP resources.
Increase specialty mentor,
role modeling, and coach
training.
Organization: The PMP needs
to enhance the program
evaluation and
improvement process
Additional evidence of
impact of PMP
organizational resources
needed
Employ annual pre- and post-
survey using updated
instrument items and
qualitative interviews

88
Increase Student Engagement
The PMP needs to increase student engagement in career exploration support, including
professional development and mentoring. Promoting involvement in professional development
and career exploration programming is a gap area needing further research in large part due to a
lack of innovative and concrete interventions (Cruess et al., 2018; Shochet et al., 2015; Wald,
2015). This study provides initial evidence of interventions that improve student perspectives
about having purpose in medicine and help-seeking. However, more work is needed to increase
student engagement with PMP personnel. Drawing on other successful support areas within
academic medicine, health promotion programs have proven to increase engagement by
collaborating with students to co-create support offerings, resulting in better coping strategies for
students (Fares et al., 2016). Similarly, the PMP collaborated with students throughout the initial
program development process and continues to co-create program modifications. Future
promotion efforts coming out of this partnership include introducing career exploration success
factors during medical school orientation as well as highlighting the benefits of PMP workshops,
coaching sessions, and workbook early and often throughout the education continuum.
Increasing engagement in these program offerings has the potential to positively impact
professional development. Although student engagement with the PMP staff is important for
overall success, direct mentoring is essential for developing a greater sense of self.
The PMP needs to increase student engagement with mentors who serve as role models.
Role modeling has a significant impact— negative or positive—on student professional
behaviors and specialty exploration (Parker et al., 2016). Unfortunately, there is a lack of
effective mentoring programs to promote strong role models in medical schools (Frei et al.,
2010). Previous attempts within academic medicine to teach students professionalism behaviors

89
in the classroom were quickly undermined by negative role modeling in clinical settings
(Monrouxe &Rees, 2012). This study provides helpful evidence of interventions that improve
student perspectives about the value of building a personal network. The PMP has an opportunity
to improve the quality of the interaction that students have with mentors and in turn increase the
engagement level of the students. Successful programs rely on improving physician and resident
awareness of the significant influence a role model has on professional behaviors and career
exploration (Sternszus et al., 2012), providing effective training opportunities such as improving
career coaching skills (Frei et al., 2010), and helping physicians understand how to aid in the
professional identity formation process (Hendelman & Byszewski, 2014). The training efforts
above provide building blocks for professional development to counteract the overemphasis on
knowledge and skill attainment (Touchie & Ten Cate, 2016). Efforts to increase student
engagement with PMP coaches, specialty mentors, and staff require additional training. The
PMP also needs to invest in training and provide compensation for coaches who engage with
students. Building on the recommendation to partner with curriculum in learning communities,
the collaboration should include a shared expense to compensate PMP coaches for their
curricular and professional development roles. Training will also occur in this space. Going
forward, PMP coaches, specialty mentors, and staff will be provided with additional training and
compensation based on the above recommendations. Although increasing student engagement in
the PMP is much needed, improving the PMP resources also includes improving program
evaluation.
Program Evaluation and Improvement
The PMP needs to enhance the program evaluation and improvement process. Due to the
nature of career exploration data, previous studies advocated for long-term formative

90
assessments of professional development experiences to better understand student needs and
program impact (Holden et al., 2015). As noted in the discussion of self-efficacy and self-
determination, the related survey items failed to detect if the PMP was impacting students. Going
forward, a pre- and post-survey will be used annually to look at the effect completion of the one-
year certificate has on students as well as an evaluation of PMP organization training and
resources. In addition to improved quantitative instrumentation, Clark and Estes (2008) outlined
the importance of supplementing survey data by tuning in to employee and client needs through
interviews and focus groups. As a result, the process going forward includes qualitative student
interviews and a consistent data gathering and analysis process for continual improvement of the
program. While the above KMO recommendations outline areas needing change, the PMP will
also need to apply gap analysis principles to craft a more effective implementation process going
forward.
Integrated Knowledge, Motivation, and Organizational Recommendations
Integrating changes into the PMP requires a thoughtful and intentional process to
leverage the identified knowledge, motivation, and organization recommendations. The
following is an overview of the process, including the timeline and steps to implement the
proposed recommendations. They include improving the evaluation process, adjusting
curriculum, incorporating metacognitive knowledge activities earlier in medical school, and
improving integration of organizational resources to better engage students in early career
exploration and self-authorship.
Evaluation Process
The first step of the implementation process is to retool the evaluation process. As
advised by Clark and Estes (2008), a complete evaluation and analysis of the KMO influencers

91
should be performed prior to implementation of program changes. Due to the inconsistent results
of several sections of the instrument, including knowledge and motivation influencers used in
this study, this is the first consideration. The timing also naturally coincides with the upcoming
opportunity to gather data from the current first-year cohort as they complete one year of the
PMP. The process will include updating the questions as recommended. Going forward, a pre-
measure will be utilized as students matriculate in the summer, and a post-measure will occur at
the end of each academic year. Since motivation influencers were particularly challenging to
measure due to their internal psychological nature (Clark and Estes, 2008), qualitative interviews
will also be conducted at the end of each academic year. This effort will allow for a better
understanding of the PMP impact on student self-efficacy and self-determination as well as
knowledge and organization influencers. In addition to altering the PMP, adjustments will also
need to be made to the curriculum based on these evaluations.
Curricular Adjustments
The curriculum structure needs to include specialty exploration. To provide context for
this change, the WMS curriculum is currently going through a change process based on
recommended strategies for supporting program improvements (Clark and Estes, 2008). This has
already incorporated a visioning and goal setting process. Efforts also include the data analysis
from this study as well as the above improvement to the instrument for future use. Because goals
have been adjusted to improve early career exploration, curricular modifications need to follow
suit. The process will include the creation of a working group consisting of members of the
Curriculum and Student Affairs units. This group will be tasked with restructuring and
streamlining curricular time to better engage students in clinical and relational experiences that

92
aid the specialty exploration and self-authorship. In addition to the curriculum changes,
knowledge related activities will also need to be modified as part of this change.
Knowledge Activities
The PMP needs to train students to adopt help-seeking and self-reflection practices
during medical school. As part of the change process, Clark and Estes (2008) identify the need to
utilize training efforts to guide students in adopting new perspectives and behaviors. The
identified assets related to self-reflection and help-seeking require additional efforts to make
incoming students aware of best practices found in these two metacognitive areas. The work to
align these knowledge areas with the goal of improving early specialty exploration and self-
authorship includes better communicating the benefits self-reflection and help-seeking as
students matriculate. This aspect of process improvement includes adjusting orientation events to
include this content and training PMP coaches to provide this information to students during
early sessions. Clark and Estes (2008) also advocate for better outreach efforts to engage more
active participation in the program. As indicated in the small sample with high attendance,
efforts will need to be employed to increase participation in the PMP. Improving organization
resources is a key aspect of making program improvements.
Organization Resources
The PMP needs to incorporate the knowledge and motivation recommendations to
improve organization resources. Identified success factors break down into various personnel and
the services they provide. While student perceptions around having purpose and the value of
building a personal network are identified assets, there is much work to do building out
additional resources around success factors while being intentional about helping students
navigate access to various services within the organization. Clark and Estes (2008) point out that

93
the change effort requires helping team members understand the organizational goals around the
resources being provided as well as providing necessary training. This will include making sure
personnel have the knowledge and skills to provide early specialty exploration resources as well
as awareness across the team of how to connect students to other available resources. In addition
to training, there are increased personnel costs associated with introducing PMP coaches who
serve as role models within learning communities. The change effort will require that additional
funds be allocated to compensate faculty who serve in these roles. The proposed partnership with
curriculum includes hiring two faculty co-directors who oversee the training and implementation
of PMP coaches. Also, the portion of effort dedicated specifically to coaching for the PMP will
need to be built into faculty compensation. Building on the identified assets and further research
and evaluation will aid the process of improving organization resources. Research limitations are
discussed in the next section.
Limitations and Delimitations
Limitations as defined by Ross and Bibler Zaidi (2019) describe what is lacking in the
research design that could potentially impact research outcomes and conclusions. Limitations in
this study include a lack of generalizability since the population is located at a single institution.
In addition, the co-curricular nature of the PMP makes it difficult to identify who is a participant
as well as to control for all associated variables. Further, the PMP certificate has only been
available for one year and therefore limits the number of students who are eligible to participate
in the study. As mentioned by Robinson and Leonard (2019), of the students who participate in
the study, there is also no control over the truthfulness of their anonymous responses to the
survey. In addition, the lack of a control group and pre-measure pose challenges in detecting the
impact of the PMP. Another outside factor worthy of mention is that the timing of the study

94
coincided with the COVID-19 pandemic. It is difficult to determine the impact the pandemic had
on student responses about the PMP. Clearly, it caused a global disruption and potential
limitation to this study and the ability to capture student responses requiring depth of thought
during an extremely stressful time.
Delimitations of the study include the rationale for narrowing the research focus (Ross &
Bibler Zaidi, 2019). In this study, the specific population is second-year medical students at
WMS who participate in the survey. This is an intentional choice to explore specific factors that
influence career exploration for the target sample population at this institution. As such, the
survey’s focus on career exploration does not address other factors directly such as burnout,
mental illness, and academic issues that contribute to other problems within the learning
environment.
Recommendations for Future Research
The data analysis process identified assets and needs related to early specialty exploration
and self-authorship. However, the process also demonstrated several areas that require additional
research, including additional sample groups, pre-post measures, and qualitative interviews. As
discussed previously, the study focuses on a student sample who participated in one year of the
PMP. Additional participation groups need to be studied to increase understanding of program
impact. In addition to increasing the sample size, employing pre-post measures and a control
group would also provide increased understanding of the impact of various program elements.
Finally, due to the nature of self-authorship and the KMO influencers, qualitative interviews
would be helpful in unpacking individual student experiences with the PMP and generating
themes that provide insight regarding the internal processing that students experience while
engaging in program activities, including self-reflection.

95
Conclusion
This dissertation examined self-authorship and early career exploration by employing a
gap analysis of knowledge, motivation, and organization influencers. The purpose of the study
was to improve the ability for the PMP to provide enhanced early career exploration
opportunities and self-authorship experiences. The research questions providing a basis for each
step of the design, methodology, data analysis, and recommendations were:
1. What are the knowledge, motivation, and organizational influences that drive
early medical student interventions to improve the specialty exploration process?
2. What are the recommendations for improving medical student specialty
exploration processes?
The gap analysis provided the format for the literature review and includes six
influencers, including declarative and metacognitive knowledge, motivation influencers, self-
efficacy and self-determination, and organization training and resources (Clark and Estes, 2008).
The qualitative analysis of each influencer identified needs and assets in medical student
knowledge, motivation, and organization areas that impact the specialty exploration and self-
authorship process.
The strong emphasis that students place on declarative knowledge hinders critical
engagement in other important forms of knowledge. First-year student behaviors around self-
reflection and seeking help from PMP resources are crucial aspects of specialty exploration and
self-authorship. Self-efficacy and self-determination within the motivation influence require
additional research to better detect the impact of the PMP on students in these areas. Lastly,
efforts to provide resources to students that positively impact perceptions related to success

96
factors have proven effective. However, future refinements include organizational efforts to train
personnel in support roles and create more awareness of expertise across the team.
Using subgroups based on the participation level in the PMP indicated that students
varied in their engagement and perceptions related to help-seeking, having purpose, and external
resources. Self-reflection behaviors also varied by participation level in the program. This study
shows that students who had high attendance in the PMP experienced increased positive
perceptions of help-seeking from university resources, having purpose in medicine, and valuing
personal networks. This student group also experienced deeper levels of metacognitive thinking
related to self-reflection than students with little to no engagement with the program.
The recommendations developed out of the gap analysis process include building upon
identified assets as well as addressing needs. Program assets include enhancing resources that
increase help-seeking, self-reflection, and success factors related to medical student perspectives
and behaviors. Identified needs include further examination of the PMP through the creation of a
continual evaluation and improvement process. Programmatic efforts to improve early specialty
exploration and self-authorship provide resources that aid the long-term success and career
satisfaction of future physicians.

97
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119
Appendix A: Survey Instrument

General Questions
1. Did you complete the first-year certificate of the Purpose in Medicine Program (yes /
no)?
2. How many Purpose in Medicine workshop sessions did you attend during the 2019-2020
academic year? (0 / 1-3 / 4-6 / 7 or more)
3. During the 2019-2020 academic year, how many times did you meet individually with
your Purpose in Medicine coach? (0 / 1 / 2 / 3 / 4 or more)
4. How many Purpose in Medicine workshop sessions did you attend during the 2020-2021
academic year? (0 / 1 / 2 / 3)
5. During the 2020-2021 academic year, how many times did you meet individually with
your Purpose in Medicine coach? (0 / 1 / 2 / 3 / 4 or more)
6. What do you plan to pursue upon completion of medical training? (Check all that apply:
clinical practice / research – basic / research – clinical / administration / education /
industry/corporate / I do not know)
7. How certain are you of the medical specialty you will practice (4-point Likert scale)?
8. Has your choice of medical specialty changed in the last 12 months (yes / no / still no top
choice)?
9. What was your entry path into medical school (regular admissions track, MD/PhD, Idaho,
Montana, Wyoming resident)?

120
10. Which of the following best describes your primary college major (arts & humanities /
behavioral & social sciences / business / engineering (including math and computer
science, natural science)?
11. Did you complete undergraduate post-baccalaureate coursework prior to applying to
medical school (yes / no)?
12. What year were you born (open-ended)?
13. What is your gender (female / male / other / prefer not to say)?
14. How do you self-identify (American Indian or Alaska Native / Asian / Black or African
American / Hispanic, Latinx, or of Spanish Origin / Native Hawaiian or Other Pacific
Islander / Caucasian / multiple ethnicity/ other please specify)?
Declarative Knowledge (4-point Likert scale)
15. When people have different interpretations of a journal article, I think only one
interpretation can be right (modified from Creamer et al., 2010; Fallar et al., 2019).
16. When people have different interpretations of a journal article, only experts can say
which interpretation is really correct (modified from Creamer et al., 2010; Fallar et al.,
2019).
17. When experts are divided on some scientific issues, I rely on the experts to decide
(modified from Creamer et al., 2010; Fallar et al., 2019).
18. An extremely important role of an effective mentor or advisor is to be an expert on one or
more medical specialties (modified from Creamer et al., 2010; Fallar et al., 2019).

121
Metacognitive Knowledge – Self-Reflection (open-ended)
19. Thinking about the factor(s) to which you gave the most points, describe how the
factor(s) contributed to your growth so far during medical school? (modified from Baxter
Magolda et al., 2007).
Metacognitive Knowledge – Help-Seeking
20. In the past 12 months, from whom have you sought career advice. (select all that apply):
Intimate partner (e.g., significant other, spouse) / friend (not related to you) / parent /
other relative or family member / mental health professional / faculty / specialty mentor /
Purpose in Medicine Coach / Purpose in Medicine Staff / Dean of Student Affairs /
Director of Student Affairs / Academic Success Program staff / Curriculum staff /
minister or religious leader / I would seek help from another not listed above) (modified
from Pintrich et al., 1991; Wilson et al., 2005).
Motivation – Self-Efficacy (0-100 scale)
21. I am confident I can reach out to a physician to develop a mentor relationship (based on
Bandura, 2006).
22. I am confident I can define my strengths (based on Bandura, 2006).
23. I am confident I can define my weaknesses (based on Bandura, 2006).
24. I am confident I can define my values (based on Bandura, 2006).
25. I am confident I can define my purpose for pursuing a career in medicine (based on
Bandura, 2006).
26. I am confident I can articulate my primary purpose for pursuing a career in medicine
(Bandura, 2006).
27. How do you rate your ability to work on a team (based on Bandura, 2006)?

122
Motivation – Self-Determination (4-point Likert scale)
28. As I choose a medical specialty, I think advisors and mentors can provide helpful advice
that I should consider along with my own ideas (modified from Creamer et al., 2010;
Fallar et al., 2019).
29. An extremely important role of an effective mentor or advisor is to direct students to
information which will help them to make a decision on their own (modified from
Creamer et al., 2010; Fallar et al., 2019).
30. An extremely important role of an effective mentor or advisor is to challenge a student to
clarify expectations (e.g., training, lifestyle) of a medical specialty (modified from
Creamer et al., 2010; Fallar et al., 2019).
31. An extremely important role of an effective mentor or advisor is to provide guidance
about a choice of specialty that is aligned with how I view my skills, talents, and
personality (modified from Creamer et al., 2010; Fallar et al., 2019).
32. When choosing a medical specialty, it is extremely important to consider my own
opinions and views (modified from Creamer et al., 2010; Fallar et al., 2019).
33. When choosing a medical specialty, it is extremely important to consider the available
information along with my own views and experiences (modified from Creamer et al.,
2010; Fallar et al., 2019).
34. When choosing a medical specialty, it is extremely important to acquire as much
information as possible (modified from Creamer et al., 2010; Fallar et al., 2019).
35. When choosing a medical specialty, it is extremely important to seek direction from
informed experts (modified from Creamer et al., 2010; Fallar et al., 2019).

123
36. When I encounter difficulties exploring a specialty, I typically try to work through those
difficulties on my own (modified from Creamer et al., 2010; Fallar et al., 2019).
37. When people have different interpretations of a journal article, I think some articles are
just that way. It is possible for all interpretations to be correct (modified from Creamer et
al., 2010; Fallar et al., 2019).
38. When people have different interpretations of a journal article, I think their ideas should
be compared to determine which makes more sense to me (modified from Creamer et al.,
2010; Fallar et al., 2019).
39. When experts are divided on some scientific issues, I would have to look at the evidence
and come to my own conclusion (modified from Creamer et al., 2010; Fallar et al., 2019).
40. When experts are divided on some scientific issues, I think it is best to accept the
uncertainty and try to understand the principal arguments behind the different points of
view (modified from Creamer et al., 2010; Fallar et al., 2019).
41. If a teacher or advisor recommended a medical specialty I have never considered before,
I would share my opinion about it (modified from Creamer et al., 2010; Fallar et al.,
2019).
42. If a teacher or advisor recommended a medical specialty I have never considered before,
I would try to understand their point of view and how it would best fit my needs and
interests (modified from Creamer et al., 2010; Fallar et al., 2019).
43. Other students can look to me for mentorship on at least some matters (modified from
Creamer et al., 2010; Fallar et al., 2019).

124
Organization – Professional Development Resources (factor selection)
44. Below is a list of ten factors that may influence your success in medical school. You are
given 100 points; divide the points across the 10 factors based on the strength of the
factor in shaping your overall success in medical school. If all factors were of equal
importance, you would assign each 10 points. Giving a factor 50 points would mean that
it is a very strong influence, whereas giving a factor 5 points would mean that it is a weak
influence. Remember, the total of all the points you assign must sum 100 points. (quality
of curriculum / use and availability of external resources (i.e., video subscription services,
questions banks, etc.) / support from the Wellness Program / support from the Academic
Success Program / sense of purpose / maintaining a personal network / building and
maintaining a professional network / strong relationships with faculty, advisors, or
mentors / service learning opportunities (i.e., student-run clinics) / participation in
research) (modeled the approach after Balmer et al., 2013).
Organization – Professional Development Training (4-point Likert Scale)
45. When faced with an ethical concern in medical school, I am extremely comfortable
keeping my concern to myself (modified from Creamer et al., 2010; Fallar et al., 2019).
46. When faced with an ethical concern in medical school, I am extremely comfortable
voicing my concern to other students (modified from Creamer et al., 2010; Fallar et al.,
2019).
47. When faced with an ethical concern in medical school, I am extremely comfortable
voicing my concern to a superior (modified from Creamer et al., 2010; Fallar et al.,
2019).

125
Appendix B: Declarative Knowledge, Self-Determination, and Training Items
Correlation and Reliability

Factor and Item M SD Corrected
Item Total
Correlation
Cronbach’s
Alpha
Knowledge: Declarative
When people have different interpretations of a
journal article, I think only one interpretation can
be right.
2.08 .55 .32 .53
When people have different interpretations of a
journal article, only experts can say which
interpretation is really correct.
2.39 .61 .47
When experts are divided on some scientific issues,
I rely on the experts to decide.
2.77 .59 .28
An extremely important role of an effective mentor
or advisor is to be an expert on one or more
medical specialties.
2.49 .75 .23
Motivation: Self-Determination
As I choose a medical specialty, I think advisors
and mentors can provide helpful advice that I
should consider along with my own ideas.
3.55 .56 .20 .71
An extremely important role of an effective mentor
or advisor is to direct students to information
3.58 .50 .27

126
Factor and Item M SD Corrected
Item Total
Correlation
Cronbach’s
Alpha
which will help them to make a decision on their
own.
An extremely important role of an effective mentor
or advisor is to challenge a student to clarify
expectations (e.g., training, lifestyle) of a
medical specialty.
3.35 .58 .42
An extremely important role of an effective mentor
or advisor is to provide guidance about a choice
of specialty that is aligned with how I view my
skills, talents and personality.
3.42 .57 .44
When choosing a medical specialty, it is extremely
important to consider my own opinions and
views.
3.81 .44 .33
When choosing a medical specialty, it is extremely
important to consider the available information
along with my own views and experiences.
3.68 .49 .57
When choosing a medical specialty, it is extremely
important to acquire as much information as
possible.
3.66 .60 .36
When choosing a medical specialty, it is extremely
important to seek direction from informed
experts.
3.55 .58 .56

127
Factor and Item M SD Corrected
Item Total
Correlation
Cronbach’s
Alpha
When I encounter difficulties exploring a specialty,
I typically try to work through those difficulties
on my own.
2.86 .57 .06
When people have different interpretations of a
journal article, I think some articles are just that
way. It is possible for all interpretations to be
correct.
2.48 .62 .15
When people have different interpretations of a
journal article, I think their ideas should be
compared to determine which makes more sense
to me.
3.05 .60 .35
When experts are divided on some scientific issues,
I would have to look at the evidence and come to
my own conclusion.
3.04 .52 .18
When experts are divided on some scientific issues,
I think it is best to accept the uncertainty and try
to understand the principal arguments behind the
different points of view.
3.26 .51 .28
If a teacher or advisor recommended a medical
specialty I have never considered before, I would
share my opinion about it.
2.92 .57 .18

128
Factor and Item M SD Corrected
Item Total
Correlation
Cronbach’s
Alpha
If a teacher or advisor recommended a medical
specialty I have never considered before, I would
try to understand their point of view and how it
would best fit my needs and interests.
3.34 .50 .40
Other students can look to me for mentorship on at
least some matters.
3.21 .48 .09
Organization: Training
When faced with an ethical concern in medical
school, I am extremely comfortable keeping my
concern to myself.
2.63 .63 1.88 .58
When faced with an ethical concern in medical
school, I am extremely comfortable voicing my
concern to other students.
2.76 .69 .56
When faced with an ethical concern in medical
school, I am extremely comfortable voicing my
concern to a superior.
2.52 .80 .45

129
Appendix C: Self-Efficacy Correlation and Reliability
Motivation: Self-Efficacy M SD Corrected
Item Total
Correlation
Cronbach’s
Alpha
I am confident I can reach out to a physician
to develop a mentor relationship.
63.36 23.56 .45 .80
I am confident I can define my strengths. 69.92 19.41 .71
I am confident I can define my weaknesses. 71.84 18.77 .45
I am confident I can define my values. 80.58 17.68 .57
I am confident I can balance school
responsibilities with my personal
commitments
66.71 24.11 .56
I am confident I can define my purpose for
pursuing a career in medicine.
76.96 19.38 .65
How do you rate your ability to work on a
team?
83.67 11.28 .43

130
Appendix D: Autonomous Functioning Index
Instructions: Below is a collection of statements about your general experiences. Please
indicate how true each statement is of your experiences on the whole. Remember that there are
no right or wrong answers. Please answer according to what really reflects your experience
rather than what you think your experience should be.

Items are usually paired with a Likert-type scale with 1 = ‘‘not at all true’’, 2 = ‘‘a bit
true’’, 3 = ‘‘somewhat true’’, 4 = ‘‘mostly true’’, and 5 = ‘‘completely true.’’

1.My decisions represent my most important values and feelings.
2.I do things in order to avoid feeling badly about myself.
3.I often reflect on why I react the way I do.
4.I strongly identify with the things that I do.
5.I am deeply curious when I react with fear or anxiety to events in my life.
6.I do a lot of things to avoid feeling ashamed.
7. I try to manipulate myself into doing certain things.
8. My actions are congruent with who I really am.
9.I am interested in understanding the reasons for my actions.
10. My whole self stands behind the important decisions I make.
11. I believe certain things so that others will like me.
12. I am interested in why I act the way I do.
13. I like to investigate my feelings.
14. I often pressure myself.

131
15. My decisions are steadily informed by things I want or care about.

Scoring Information for the IAF. First, items 2, 6, 7, 11, and 14 need to be reverse-scored
so that higher scores on every item will indicate a higher level of autonomous functioning. To
reverse-score an item, subtract the item response from 6 and use that as the item score.
Calculate total IAF by averaging the item scores for the 15 items in the scale. If interested
in the subscales, calculate the scores for the Authorship/Self-Congruence subscale, Susceptibility
to control subscale, and the Interest-taking subscale by averaging the item scores for the 5 items
within each subscale.
The subscales are:
Authorship/Self-Congruence: 1, 4, 8, 10, 15
Susceptibility to control: 2, 6, 7, 11, 14
Interest-taking: 3, 5, 9, 12, 13

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Asset Metadata

Creator Hurtado, Thomas Hector (author)

Core Title Evaluation of early career exploration interventions in a medical school professional development program

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Publication Date 04/09/2021

Defense Date 03/17/2021

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag career exploration,help-seeking,medical school,medical students,OAI-PMH Harvest,professional development,professional identify formation,Purpose,self-authorship,undergraduate medical education

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Adibe, Bryant (committee chair), Richards, Boyd (committee member), Tobey, Patricia (committee member)

Creator Email thurtado@usc.edu,tom.hurtado@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-441684

Unique identifier UC11667601

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Legacy Identifier etd-HurtadoTho-9434.pdf

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Document Type Dissertation

Rights Hurtado, Thomas Hector

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Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

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