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Developing rates of psychological safety in Army Officer Candidates

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Developing rates of psychological safety in Army Officer Candidates

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Content 1
Developing Rates of Psychological Safety in Army Officer Candidates
by
Eric Jon Nielson
A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION
May 2024
Copyright 2024 Eric Jon Nielson
24-P-0754

Acknowledgements
This dissertation could not have been possible without the assistance of countless
individuals. To my chair, Dr. Hocevar, I thank you for your continued guidance and advice
through this long journey. It is incredible to look back to Immersion and think how far we’ve
come. To my committee members, Dr. Picus and Dr. Legault, I thank you for all your efforts to
critique this research and your feedback to improve both its final form but also my academic
writing for future papers. To my friends and family, I thank you for your continued
understanding as I spent my last three years declining social events and quality time to progress
in this journey to write this dissertation. To the staff of the Army Officer Candidate School, your
assistance in this research was insurmountable and your entire team was constantly bending over
backwards to make this possible. Lastly, to whomever may read this work, thank you taking the
time and I hope that you learn something. I certainly know I did.

Table of Contents
Acknowledgements 2
Table of Contents 3
List of Tables 5
List of Figures 7
Abstract 8
CHAPTER ONE: INTRODUCTION TO THE STUDY 9
Problem of Practice 9
Research Problem 9
Research Questions and Hypothesis 11
Theoretical and Conceptual Framework 11
Research Design 13
Organization of the Dissertation 13
CHAPTER TWO: LITERATURE REVIEW 15
A History of Psychological Safety Research 15
Organizational Level 20
Organizational Psychological Safety as a Consequent and Mediator 21
Organizational Psychological Safety as an Antecedent 22
Team Level 23
Team Psychological Safety as a Consequent and Mediator 24
Team Psychological Safety as an Antecedent 32
Individual Level 34
Individual Psychological Safety as a Consequent and Mediator 35
Individual Psychological Safety as an Antecedent 39
Psychological Safety in Military Teams 43
Conservation of Resources 47
Understanding the Barriers 50
Conceptual Framework 55
Summary 56
CHAPTER THREE: METHODOLOGY 57
Sample and Setting 57
Instrumentation 58
Quantitative Data Collection 59
Data Analysis 60
Ethics 60
The Researcher 61
CHAPTER FOUR: FINDINGS 62
RQ1: Do Stages of Psychological Safety Relate to Performance? 66
RQ2: Do Stages of Psychological Safety Change Over Time? 69
RQ3: Does Availability of Resources Correlate With Psychological Safety? 75
Summary 83
CHAPTER FIVE: RECOMMENDATIONS 84
Discussion of Findings 84
Recommendation 1: Temporal Tracking of Psychological Safety and Resources 87
Recommendation 2: Targeted Individual Interventions 89

Recommendation 3: Targeted Leadership Development 93
Recommendation 4: Survey Scale Revision 96
Recommendation 5: Reconceptualization of Psychological Safety Stages 99
Limitations and Delimitations 100
Recommendations for Future Research 102
Conclusion 102
References 104
Appendix A: Supplemental Tables 151
Appendix B: Survey Instrument for First Response 154
Appendix C: Post-Initial Survey Instrument 159
Appendix D: Informed Consent Form 163
Introduction 163
Key Information 163
Purpose 164
Procedures 164
Risk and Discomforts 164
Surveys/Questionnaires/Interviews 165
Breach of Confidentiality 165
Department of Defense 165
Benefits 165
Privacy/Confidentiality 165
Voluntary Participation 167
Contact Information 167
Statement of Consent 167

List of Tables
Table 1 Psychological Safety Stages Time 1 Correlations .......................................................... 63
Table 2 Inclusion Questions Time 1 Item-Total Statistics............................................................ 64
Table 3 Learner Questions Time 1 Item-Total Statistics ............................................................. 64
Table 4 Contributor Questions Time 1 Item-Total Statistics....................................................... 65
Table 5 Challenger Questions Time 1 Item-Total Statistics ........................................................ 65
Table 6 Mean and Standard Deviations of Time 1 Stages of Psychological Safety..................... 65
Table 7 Performance Metrics Inter-Correlation.......................................................................... 66
Table 8 Psychological Safety Scales and their Relationship to Performance at Time 1 ............. 67
Table 9 Psychological Safety Scales and their Relationship to Performance at Time 2 ............. 68
Table 10 Psychological Safety Scales and their Relationship to Performance at Time 3 ........... 68
Table 11 Inclusion Marginal Means Over Time .......................................................................... 69
Table 12 Learning Marginal Means Over Time .......................................................................... 71
Table 13 Contributor Marginal Means Over Time...................................................................... 72
Table 14 Challenger Marginal Means Over Time ....................................................................... 73
Table 15 Resource Correlation with Psychological Safety Stages at Time 1 .............................. 75
Table 16 Resource Correlation with Psychological Safety Stages at Time 2 .............................. 75
Table 17 Resource Correlation with Psychological Safety Stages at Time 3 .............................. 76
Table 18 Resource-Psychological Safety Stage Correlations at Time 1...................................... 77
Table 19 Resource-Psychological Safety Stage Correlations at Time 2...................................... 79
Table 20 Resource-Psychological Safety Stage Correlations at Time 3...................................... 81
Table 21 Mean and Standard Deviation of Time 2 Stages of Psychological Safety .................. 151
Table 22 Intra-Scale Correlation and Reliability at Time 2 ...................................................... 151

Table 23 Mean and Standard Deviation of Time 3 Stages of Psychological Safety .................. 152
Table 24 Intra-Scale Correlation and Reliability at Time 3 ...................................................... 152
Table 25 Demographics............................................................................................................. 153

List of Figures
Figure 1 Stages of Psychological Safety and Performance Conceptual Framework .................. 12
Figure 2 Organizational Themes, Consequents, and Antecedents of Psychological Safety ........ 18
Figure 3 Team Themes, Consequents, and Antecedents of Psychological Safety........................ 19
Figure 4 Individual Themes, Consequents, and Antecedents of Psychological Safety ................ 20
Figure 5 Psychological Safety-Accountability For Performance Framework............................. 33
Figure 6 Team and Individual Level Barriers to Psychological Safety ....................................... 54
Figure 7 Change of Marginal Mean of Inclusion Over Time ...................................................... 70
Figure 8 Change of Marginal Mean of Learning Over Time....................................................... 71
Figure 9 Change of Marginal Mean of Contributor Over Time .................................................. 72
Figure 10 Change of Marginal Mean of Challenger Over Time ................................................. 73
Figure 11 Change in Mean Psychological Safety Stage Over Time ............................................ 74
Figure 12 Temporal Tracking of Psychological Safety Logic Model .......................................... 89
Figure 13 Targeted Individual Training Interventions Logic Model........................................... 92
Figure 14 Conflict Management Model ....................................................................................... 95
Figure 15 Targeted Leadership Training Logic Model ............................................................... 96
Figure 16 Revised Psychological Safety Stages Conceptual Model .......................................... 100

Abstract
Psychological safety is “a shared belief that the team is safe for interpersonal risk taking”
(Edmondson, 1999, p. 354) that has been purported to be one of the most important variables to
team success (Duhigg, 2016). This research project aimed to examine if psychological safety
relates to performance and how it changes over time while at the U. S. Army’s Officer Candidate
School (OCS). Clark’s (2020) Four Stages of Psychological Safety conceptualized psychological
safety into Inclusion, Learner, Contributor and Challenger. Additionally, this research tested and
applied the Conservation of Resources theory to identify whether individual resources, such as
hope and confidence, relate to perceived psychological safety. The purpose of this study is to
then provide recommendations to improve psychological safety to Army OCS Staff based on the
findings. The data were collected in four waves through online surveys to 102 Officer
Candidates from October 2023 – February 2024. Psychological safety was found to be
statistically unrelated to performance and changed over time revealing a concave curvilinear
relationship. Lastly, most resources were found to be positively related to psychological safety.
These findings indicate the need to examine performance metrics and whether psychological
safety is required as well as the need to track psychological safety over time. Practitioners and
leaders can also measure and target specific resources when aiming to increase individual’s
psychological safety.

CHAPTER ONE: INTRODUCTION TO THE STUDY
Problem of Practice
This study seeks to understand how different levels of psychological safety drove
individual performance among United States Army Officer Training. U.S. Army Officers have
“played an integral role in the formulation and execution of its national security strategy”
(Wardynski et al., 2009, p. V). A lack of psychological safety leads teams to provide ideas and
contributions only at the levels they feel safe doing so (Sablan, 2022). However, this principle is
at odds with the U. S. Army’s People Strategy where they aim to “leverage the unique productive
capacities of each person” (U.S. Army, 2019, p. 4). Although psychological safety is a mature
topic (Edmondson & Bransby, 2023), no known research has been conducted on Officer
candidates. If various levels of psychological safety are not studied, with appropriate
prescriptions and strategies for improvement, the Army may see its ranks cut as its Soldiers
depart from the military resulting in shallower talent pools, loss of institutional and operational
knowledge, and capability reductions at a time when some predict that a large-scale war looms
(Campbell, 2023).
Research Problem
Psychological safety is a construct that has been shown to impact team effectiveness
(Edmondson, 1999). Defined as “a shared belief that the team is safe for interpersonal risk
taking” (Edmondson, 1999, p. 354), psychological safety shows that managers rated a nine on a
scale of 10 have an average psychological safety score of 84% while those rated a six have an
average score of 36% (PR Newswire, 2022). If teams, and organizations, want to continue to
grow and innovate, psychological safety needs be prioritized as it has been shown to moderate
the relationship between innovation and performance (Baer & Frese, 2003).

To date, only five studies were found that investigate psychological safety within the
military sector (Hedlund & Osterberg, 2012; Prykhodko, 2022; Sowden et al., 2020; Veestraeten
et al., 2014; Wermser et al., 2016). Of those five, only one was conducted in the United States
and it focused more on how sleep quality affected psychological safety rather than how
psychological safety affected performance (Sowden et al., 2020). Results of other studies found
that psychological safety was positively related to team learning in military teams (Veestraeten et
al., 2014), coping strategies and psychological welfare during combat (Prykhodko, 2022),
psychological safety during intra-nation integrations (Wersmer, 2016). Further, psychological
safety is essential in military exercises for soldiers and exercises to be successful (Hedlund &
Osterberg, 2012).
While studies around psychological safety within the military are limited, recent focus on
the subject after recent focus on the subject in the private sector has grown since Google
substantiated it as the primary moderator of team performance (Duhigg, 2016). In their metaanalyses, Edmondson and Lei (2014), Edmonson and Bransby (2023), Frazier et al. (2017), and
Newman et al. (2017) show that psychological safety has been positively related to organization
and team outcomes, work behaviors, work attitudes, learning, creativity, voice, commitment,
engagement, and a litany of other variables. Clark’s (2020) recent work, psychological safety
was purported to have four different levels: inclusion, learning, contributor, and challenger
safety. These levels have yet to be studied in practice, where identifying where an individual lies
may allow practitioners to apply more targeted intervention strategies to improve those rates
(Clark, 2020).

Research Questions and Hypothesis
The body of literature on team development research has largely focused on three
theories (Mathieu et al., 2019). Kozlowski et al. (1999) coined the ‘forming, storming, norming,
and performing’ team stages, Marks et al. (2001) showed development more as episodic arguing
that teams execute different processes at different times. In contrast, Morgeson et al. (2015)
proclaimed development was more events driven. This study aimed to identify how Army
Officer teams develop and how their varying levels of psychological safety equate to
performance. As such, three research questions were of focus:
RQ1: Do stages of psychological safety relate to performance?
RQ2: Do stages of psychological safety change over time?
RQ3: Does availability of resources correlate with psychological safety?
A large body of evidence has already shown how overall psychological safety correlates
to higher team performance (Edmondson & Lei, 2014). However, the levels of psychological
safety, as described by Clark (2020) have not been studied under the lens of performance.
Theoretical and Conceptual Framework
The progression of individual stages of psychological safety will be viewed through the
Conservation of Resources lens. The Conservation of Resources (COR) theory posits that
individuals strive to maintain, retain, build, and protect their resources (Hobfoll, 1989). When an
individual’s resources are threatened with loss, are lost, or when they fail to gain resources, the
individual experiences psychological stress (Hobfoll et al., 2018) regardless of the alignment
between perception and reality (Clarkson et al., 2010). The COR theory best frames this study as
individuals with more resources, perceived or real, are shown to invest those resources more
often, whether through voice, action, or thought (Ng & Feldman, 2012).

Resources, in the context of COR, are defined as “those objects, personal characteristics,
conditions, or energies that are valued by the individual or that serve as a means for attainment of
these objects, personal characteristics, conditions, or energies” (Hobfoll, 1989, p. 516). From this
theoretical perspective, those with higher levels of resources will be willing, if not motivated, to
take risks and expend those resources for goal achievement, and vice versa (Marx-Fleck et al.,
2021). Thus, as an individual’s ‘reservoir’ of resources accumulates, it can be implied that they
will then be more motivated to learn, contribute, and challenge – the three later stages of
psychological safety (Clark, 2020) and contribute to team performance. Figure 1 showcases this
relationship along the X and Y axis as an individual moves along these stages as psychological
safety and resources increase.
Figure 1
Stages of Psychological Safety and Performance Conceptual Framework
Note. This model was redesigned by Clark, T. (2020). The 4 Stages of Psychological Safety.
Berret-Koehler.

Research Design
A quantitative survey method was used in this study. This method was selected to test
whether a relationship exists between specific variables (Creswell & Creswell, 2018). The survey
used was a consolidation of the four stages of psychological safety measurement tool developed
by Zhang et al. (2022) and an adaptation of the Conservation of Resources-Evaluation (Hobfoll
& Lilly, 1993) survey. These surveys were chosen as Zhang et al.’s (2022) instrument was the
only survey published that measures the four stages of psychological safety. Hobfoll and Lilly’s
(1993) COR-E tool has been the most common questionnaire for measuring resources
(Halbesleben et al., 2014).
A survey method was selected to describe how variables are distributed across a
population and as an efficient way of gathering quantitative data (Merriam & Tisdell, 2016). The
survey was distributed to all consenting candidates at the Army Officer Candidate School (OCS)
at Fort Moore, Georgia from October 2023 until February 2024. The site was best situated to
give access to the ideal participants as it is a program that takes individuals from across the
United States and embeds them in high-stress environments to build leadership skills (United
States Army, n.d.) that allows levels of psychological safety to be observed over time relative to
performance. This site also allowed the opportunity to study teams at their formation and how
psychological safety develops over time.
Organization of the Dissertation
This dissertation is divided into five distinct chapters. The first chapter serves to
introduce the problem, purpose, and research questions for this study. Immediately following is a
substantial review of the body of literature on psychological safety, military teams, and an
overview of the Conservation of Resources theory. The third chapter describes the research

methods and the research design and hypothesis. The fourth chapter then provides the research
findings along with an analysis of the data. The fifth, and final chapter, describes
recommendations based on the findings.

CHAPTER TWO: LITERATURE REVIEW
A History of Psychological Safety Research
Psychological safety is defined as “a shared belief that the team is safe for interpersonal
risk taking” (Edmondson, 1999, p. 354). Psychological safety was initially introduced by
Massachusetts Institute of Technology (MIT) professors Edgar Schein and Warren Bennis
(1965) when they described it as an integral piece during the “unfreezing” portion of
organizational change. Specifically, they believed psychological safety reduces the barriers to
change and creates an environment that accepts failure without fearing guilt or retaliation
(Schein & Bennis, 1965). For the next two decades, psychological safety was largely unstudied
until William Kahn (1990) published his research on a qualitative study of summer camp
counselors. In his work, he suggested that psychological safety was necessary for employee
engagement and affected an employee’s ability to “employ or express themselves physically,
cognitively, and emotionally” (Kahn, 1990, p. 694).
Nine years later Amy Edmondson (1999) was investigating whether more effective
hospital medical teams made fewer mistakes in their work. Instead, she found that more effective
teams made more mistakes and reported them more frequently (Edmondson, 1999).
Edmondson’s hypothesis around this phenomenon was that these teams were not committing
more errors but instead able to disclose errors more frequency because of the team’s lower rates
of perceived fear of backlash or repercussions following these disclosures (Edmondson, 1999).
From these three pieces of work, psychological safety has become a mature and well-studied
concept (Edmondson & Bransby, 2023).
A consistent message over time across the body of research on psychological safety
suggests that psychological safety facilitates the contribution of ideas, voice, and action

(Edmondson & Lei, 2014). It has also been shown to create nonthreatening team environments,
encourage cultures of openness, and decrease perceptions of retaliation (Devaraj et al., 2021).
Newman et al. (2017) purport that psychological safety is so widespread that its importance has
roots in nearly every organization and industry. Google even went so far as to say it was the
number one predictor of high-performing teams (Bergmann & Schaeppi, 2016). However,
admitting error, voicing opinions, or challenging the status quo may go against the interests of
others in an organization (Detert & Burris, 2007) with those individuals viewed more negatively
(Van Dyne & LePine, 1998), which then leads to greater perceptions of fear (Edmondson, 1999).
These perceptions of fear increase the reluctance of individuals to speak up even when it
would benefit the team (Lee, 1997). Ray Dalio (2011) suggests this fear is driven by society’s
phobia of making mistakes and that we are taught from a young age to be correct instead of
learning from mistakes. As individuals eventually enter the workplace, this drive to be right and
not make mistakes encourages individuals to regulate and control information (Edmondson,
2018). A study found that 85% of respondents had felt, at least once, that they were not able to
raise a concern they had to their boss (Edmondson, 2019).
Edmondson (2012) writes in her book, Teaming: How Organizations Learn, that these
reactions are at least partly driven by how the modern organization is organized. For example,
she claims the workplace has created an overreliance on fear to manage employees to drive
performance. This fear drives individuals to repeat safe processes encouraging derivative, not
innovative, work and encourages silence given the belief that silence never causes employment
termination (Edmondson, 2019). Without the psychological safety to speak up, individuals,
teams, and organizations fail to learn and thus, fail to grow (Edmondson, 1999). This growth and

focus on performance have been a focal point of organizational efforts driving a parabolic
increase in research on psychological safety (Edmondson & Bransby, 2023).
In four of the more extensive meta-analyses to date, Edmondson and Lei (2014), Frazier
et al. (2017), Newman et al. (2017) and Edmondson and Bransby (2023) provide a
comprehensive overview of the research on psychological safety. Edmondson and Lei (2014)
were among the first to substantiate that psychological safety exists and differentiates at the
organizational, team, and individual levels. Additionally, they provided a review that
psychological safety acts as both a mediator and a moderator of several key variables such as
voice, learning and performance (Edmonson & Lei, 2014), something that Newman et al. (2017)
later supported. Frazier et al. (2017) followed suit and provided further evidence that
psychological safety exists at the organizational, team, and individual levels. Their work showed
that antecedents exist that predict psychological safety, such as emotional stability, work designs,
and learning orientation. They also found that psychological safety predicts outcomes, such as
engagement, performance, and knowledge sharing. Lastly, Edmondson and Bransby (2023) took
a different approach to their research and substantiated that the body of knowledge on
psychological safety can be organized into four clusters or themes. These themes are: 1) getting
things done, 2) fostering learning behaviors, 3) improving the work experience, and 4) leaders
and leadership (Edmondson & Bransby, 2023). Figures 2, 3, and 4 showcase these reviews and
variables that were consolidated and adapted from Edmondson and Lei (2014), Frazier et al.
(2017), Newman et al. (2017) and Edmondson and Bransby (2023). To fully understand the
power of psychological safety, a review of all three levels and how psychological acts as both a
consequent and antecedent is reviewed below.

Figure 2
Organizational Themes, Consequents, and Antecedents of Psychological Safety
Note. This figure was redesigned by Edmondson and Bransby (2023), Edmondson and Lei
(2014), Frazier et al. (2017) and Newman et al. (2017).

Figure 3
Team Themes, Consequents, and Antecedents of Psychological Safety
Note. This figure was redesigned by Edmondson and Bransby (2023), Edmondson and Lei
(2014), Frazier et al. (2017) and Newman et al. (2017).

Figure 4
Individual Themes, Consequents, and Antecedents of Psychological Safety
Note. This figure was redesigned by Edmondson and Bransby (2023), Edmondson and Lei
(2014), Frazier et al. (2017) and Newman et al. (2017).
Organizational Level
The body of research on psychological safety at the organizational level is limited as
many claim that an agreement of an entire organization on a collective perception of
psychological safety is unlikely given the scale and team members (Newman et al., 2017).
Carmeli et al. (2010) believed this as organizations are a makeup of many different teams that
may have different climates aimed at accomplishing a variety of different tasks. However, of the
research that does exist, consistent with the team and individual levels, psychological safety at
the organizational level is commonly positioned as both a consequent and an antecedent of other
variables (Edmondson & Lei, 2014).

Organizational Psychological Safety as a Consequent and Mediator
Organizational research has shown that psychological safety is vital to understanding and
identifying how individuals collaborate (Edmondson, 2004). A consolidation of meta-analyses
and individual studies shows that psychological safety can either be a mediator/consequent of
preceding variables or maybe a moderator of proceeding variables (Frazier et al., 2017). The
most common consequences of psychological safety at the organizational level include
leadership, structure, context, organizational and human-resource based practices, and process
innovations (Edmondson & Lei, 2014; Newman et al., 2017).
Leadership. Several studies have shown the importance of leadership in developing
psychological safety (Edmondson & Lei, 2014). One of the first was Carmeli’s (2007) research
in Israel which found social capital and leadership to be key factors in developing psychological
safety. From a top-down perspective, Miao et al. (2019) found that the relationship between a
Chief Executive Officer (CEO) and their levels of entrepreneurial leadership (which focuses on
driving opportunity-seeking behavior) that affect performance was partially mediated by
psychological safety. Additionally, Tang et al. (2021) studied the relationship between gender
diversity and performance and found that a gender-balanced top management team increases
psychological safety, showcasing the value of organizational and human resource practices.
Organizational and Human Resource (HR) Practices. Organizational climates have
been shown to increase failure-based learning (Carmeli, 2007). Carmeli et al. (2009) also found
that psychological safety mediates connectivity, positive regard, mutuality, and emotional
carrying capacity with organizational learning. These results were consistent with Collins and
Smith’s (2006) study that found climates of trust and cooperation positively related to
organizational performance. From a more mission-based perspective, climates that focus on

corporate social responsibility were shown to increase the feelings of safety and the ability of
employees to take risks to improve products and processes (Ahmad et al., 2022). These findings
suggest that, in addition to organizational and HR practices, the structure and context of an
organization also affect psychological safety (Bresman & Zellmer-Bruhn, 2013).
Structure and Context. Structure has also been central to organizational functioning
research (Shaw, 1976). Previous studies show that structure can promote learning and
psychological safety in self-managed teams with stable tasks (Bunderson & Boumgarden, 2010)
and that psychological safety positively mediates structure and learning (Bresman & ZellmerBruhn, 2013). In a review of power status differences, speaking up was found to be partially
mediated by psychological safety (Bienefeld & Grote, 2014). However, Bienefeld and Grote
(2014) also found that psychological safety did not mediate the relationship of speaking up
across teams. In their research, they suggested that the mechanisms that supporting speaking up
across teams, showing how organizational practices influence psychological safety.
Organizational Psychological Safety as an Antecedent
In Schein and Bennis’s (1965) seminal work, they introduced the idea that psychological
safety reduces perceived threats and barriers to change during the ‘unfreezing’ process of
organizational change based on Lewin’s theory of change. Since then, several studies have
shown how psychological safety increases various organizational characteristics, such as
learning (Carmeli & Gittell, 2009) and voice (Edmondson, 1999). Edmondson and Bransby
(2023) show that most of the research at the organizational level has shown that psychological
safety acts as an antecedent to enhance performance, knowledge exchange, and learning.
Knowledge Exchange and Learning. Delays and distortions in organizational
communication have been a well-documented finding in organizational communication (Fulk &

Mani, 1986). Upward communication often contains unfavorable information, such as the
admission of error (Edmondson, 1999), that often prohibits or discourages information sharing
(Tynan, 2005). In a study of Italian hospitals, Mura et al. (2016) purported that error exposing
communication had a direct relationship with a climate of psychological safety as psychological
safety increases so too does communication.
A climate of psychological safety was shown to increase overall learning in an
organization by enabling individuals to voice their ideas and provide opportunities to test, fail,
and learn (Tucker et al., 2007). In a German chemical plant study, Wilhelm et al. (2019) found
employees were more apt to learn from failure when psychological safety levels were higher.
This act of learning has long been shown to be a strong predictor of organizational performance
(Luo & Peng, 1999; VandeWalle et al., 1999).
Performance and Innovation. While some scholars have argued that psychological
safety at the organizational level is less likely to occur (Carmeli et al., 2010), Baer and Frese’s
(2003) study found a link between psychological safety’s impact and organizational
performance. Others have shown how psychological safety moderates the climate of trust and
support (Emery et al., 1996), diversity (Gerpott et al., 2021), entrepreneurial orientation (Yoon &
Solomon, 2017), and innovation (Andersson et al., 2020) to improve performance. Specifically,
Gibson and Gibbs (2006) found that a psychologically safe climate to be a facilitator of
innovation. However, this body of literature remains less established than team and individual
psychological safety research levels (Edmondson & Bransby, 2023).
Team Level
Individuals become more resilient and motivated when they feel safe (Delizonna, 2017).
Psychological safety, which induces this safe environment (Edmondson, 1999), was proven in

Google’s multi-year study on team effectiveness as one of, if not the leading, indicator of highly
successful teams (Duhigg, 2016). Divesting slightly from Schein and Bennis’s (1965) and
Kahn’s (1990) positions that psychological safety is largely individualistic, Edmondson (1999)
has provided two decades of evidence that shows how psychological safety is largely a team
construct and that it acts as both a consequent and an antecedent of several other team variables
(Edmondson & Lei, 2014).
Team Psychological Safety as a Consequent and Mediator
Newman et al.’s (2017) review of the psychological safety literature revealed that the
work at the team level has largely shown psychological safety as a mediator to other related
variables. As scholars have studied teamwork and its effects on performance for over a century
(Mathieu et al., 2019), understanding how psychological safety can improve team processes can
be paramount for future performance. These variables range from performance to leadership to
conflict and will be discussed below (Edmondson & Lei, 2014).
Conflict. While some may view conflict as a deterrent to team effectiveness, a line of
research has shown that it can increase innovation, quality, knowledge, and performance that is
moderated by psychological safety (Bradley et al., 2012; Mu & Gnyawali, 2003; Wilkens &
London, 2006). Amason and Sapienza (1997) break down the idea of conflict into two forms:
cognitive and affective. Cognitive conflict reflects a disagreement in tasks, ideas, opinions, and
viewpoints whereas affective conflict is related to personal incompatibilities evoked by a
spectrum of values and beliefs (Amason & Sapienza, 1997). Centering their research on both
types of conflict, Xie et al. (2022) found that, in addition to strengthening the advantages of
cognitive conflict, psychological safety also weakens the disadvantages of affective conflict.

Thus, understanding climate at the team level also illustrates the benefits of psychological safety
(Ning & Jin, 2009).
Climate. To encourage knowledge exchange, a climate of cooperation, willingness to
share, and trust must be established (Collins & Smith, 2006). These variables predict and foster
psychological safety, influencing performance and organizational learning by diminishing
anxiety and resistance (Ning & Jin, 2009). Additionally, humor (Potipiroon & Ford, 2021) and
having friends at work (Cao & Zhang, 2020) have been shown to increase psychological safety,
innovation, and decrease prohibitive voice behaviors. These variables were also tested in
disparaging and hostile climates (Janes & Olson, 2000). Results showed that participants who
were ridiculed or witnessed others being ridiculed by a leader, significantly increased their
perceptions of the negative consequences of speaking up (Janes & Olson, 2000).
Leadership. Supervisors and leaders have long been shown to have significant influence
on their subordinates’ psychological safety (Detert & Burris, 2007). In uncertain environments,
employees depend on their leaders for security and resources (Madjar et al., 2002). Data show
highly rated managers had teams with an average psychological safety score of 84% (PR
Newswire, 2022). Conversely, average rated managers had psychological safety scores of just
36% (2022). This is important as higher rated managers brought in an average of $4.3 million
more in revenue per year than lower rated managers (2022). This data is further supported by the
various studies showing that psychological safety is increased by ethical leadership (Hu et al.,
2018; Men et al., 2020; Tu et al., 2019; Walumbwa & Schaubroeck, 2009), leader inclusiveness
(Hirak et al., 2012; Javed et al., 2019; Kim, 2020), leader behavioral integrity (Palanski &
Vogelgesang, 2011), creativity (Tu et al., 2019), innovation (Cai et al., 2023), job satisfaction
(Moin et al., 2021), team learning (Ortega et al., 2014; Wong et al., 2010), problem-solving

abilities (Carmeli et al., 2013), engagement (Nembhard & Edmondson, 2006), knowledge
exchange (Men et al., 2020; Nemanich & Vera, 2009) and leader-expressed humility (Rego et
al., 2021).
Thyness et al. (2023) showed that coaching, modeling, articulation, and exploration could
be used to increase rates of psychological safety in teams. Another study showed that supervisors
psychological safety can increase employee psychological safety (Frazier & Tupper, 2018).
Meanwhile, abusive leadership has been postulated to decrease psychological safety and team
characteristics such as lower team creativity (Jiang & Gu, 2016; Liu et al., 2016), and
performance (Chan & McAllister, 2014).
Team Characteristics. The uniqueness of teams primarily revolves around individual
work interdependence and coordination, knowledge exchange in complex environments, and
they often have limited life spans (Salas et al., 2000). These life spans have been shown to
contain what researchers call ‘emergent states’ (Marks et al., 2001). Like conflict, these states are
divided into cognitive, affective and motivation (Marks et al., 2001). Cognitive emergent states
contain team trust, climate, and cognition (Rapp et al., 2021). Affective states include
psychological states relating to feelings and attitudes (Rapp et al., 2021). Motivational states
reflect a team’s belief regarding their direction and effort regulation toward a goal (Rapp et al.,
2021). Psychological safety is most often associated with the affective state and can change over
time as tenure increases (Rapp et al., 2021).
Traditional team literature suggests that shorter tenure teams experience lower
psychological safety rates whereas longer tenure teams were likely to experience higher rates
suggesting a linear association (Koopmann et al., 2016). In Koopmann et al.’s (2016) study of
tenure and psychological safety, they found a curvilinear relationship where shorter and longer

teams had higher ratings than medium tenure teams (Koopmann et al., 2016). These results may
imply further evidence of the ‘form, storm, norm, and perform’ team research (Mathieu et al.,
2019). Other studies have shown that other team characteristics, such as cohesion (Mathieu et al.,
2008), cooperative norms (De Jong & Elfring, 2010) and diversity (Gibson & Gibbs, 2006), also
play a role in psychological safety.
Relationship Networks. High-quality relationships contain shared goals, shared
knowledge, and mutual respect (Gittell, 2003; 2006). Having these positive and high-quality
relationships has been shown to be a key mechanism for increasing psychological safety and
learning in teams (Carmeli et al., 2009). A study involving hospital physicians showed that those
with higher rates of psychological safety were also more prone to receive corrective and positive
feedback from peers (Scheepers et al., 2018). This feedback implies others’ willingness to invest
in each other leading to higher rates of quality improvement (Scheepers et al., 2018). Other
studies have shown that individuals higher in psychological safety have more friendship ties to
grow their relationships (Schulte et al., 2012). Individuals are also shown to expect more respect
and acceptance from their peers in psychologically safe environments (Kozlowski & Ilgen,
2006). Google’s Project Aristotle affirms these findings as they found that all high performing
teams had members who spoke up in a roughly equal proportion and had high social sensitivity
ratings suggesting this peer acceptance across work designs and structures (Duhigg, 2016).
Structure and Work Design. Team contexts can cause wide variations in psychological
safety across teams (Edmondson, 1999). For example, Bunderson and Boumgarden (2010) claim
that decision-making autonomy enhances psychological safety. However, Chandrasekaran and
Mishra (2012) argued that team autonomy can decrease psychological safety when team
exploration (the choosing of our actions with an objective to learn) is already high. They also

found psychological safety increases when team goal and metric alignment was high, and
exploration was low (Bunderson & Boumgarden, 2010). Metric alignment and cooperative goals
were shown in another study to enable openness and increase psychological safety (Chen &
Tjosvold, 2012). Lastly, cooperation and a climate of psychological safety mitigated any
negative effective of geographic dispersion, dynamic structure, national diversity, and spanned
boundaries (Gibson & Gibbs, 2006).
Boundary Spanning. Work that forces individuals to work with others outside of their
immediate team is known as boundary spanning teaming (Edmondson & Harvey, 2018). These
cross-boundary teams often differ from other teams given their task duration or closed objective
to accomplish a project (Edmondson & Harvey, 2018). Cross-boundary initiatives have been
shown to increase team performance amid the uncertainty moderated by psychological safety
(Edmondson, 2003; Faraj & Yan, 2009).
Task Uncertainty, Adaptation, and Problem Solving. For teams that work on tasks
involving high complexity and uncertainty, psychological safety has been shown to stimulate
learning for teams to adapt and solve these problems (Sanner & Bunderson, 2015). Edmondson
(1999) first showed how psychological safety facilitates individuals to take appropriate actions to
accomplish their work in her study on error rates in hospital teams. Not only does psychological
safety enable higher reporting of errors, but it can also lead to identifying and improving
processes that likely lead to errors (Reason, 2000). Mistakes are highly likely in these uncertain
environments where psychological safety mediates error making and reflection (Hetzner et al.,
2011).
Knowledge Sharing. Psychological safety is shown to be a strong predictor of
knowledge sharing (Kessel et al., 2012). These psychologically safe environments are especially

vital with uncertain tasks where teams need encouragement to speak up where psychological
safety has shown to increase these behaviors (Liu & Keller, 2021). Creativity and performance
are hindered if teams hide knowledge due to fear (He et al., 2022). Thus, in psychologically safe
climates, individuals openly share cognitive based information that benefits their team
(Bunderson & Boumgarden, 2010; Edmondson, 1999). Knowledge sharing and voice is vital to a
team as it and has been shown to increase productivity and enhance team capacity (Carmeli et
al., 2013).
Confidence. Confidence has been shown to increase knowledge sharing through
psychological safety (Siemsen et al., 2009). The more confident an individual is in their
knowledge, the more they speak up, and a psychologically safe environment may help to
overcome any lack of confidence (Edmondson, 2019). Siemsen et al. (2009) provides evidence
that greater confidence level relates to both higher rates of psychological safety and a motivation
to share. Conversely, a negative and safe environment curtails confidence and may lower selfexpression and voice (Singh et al., 2013). One of the ways that Schaubroeck et al. (2011) found
to increase confidence was through the effects of affective and cognitive-based trust.
Trust. Both affect and cognitive-based trust can unleash team potential through
confidence building and through the creation of conditions that enable expression of opinions
(Schaubroeck et al., 2011). Psychological safety was shown to mediate the effects of affect-based
trust and increase cognitive-based trust (Schaubroeck et al., 2011). Mutual trust in teams has
been shown to be an important factor in influencing psychological safety (Cao & Zhang, 2020;
Edmondson, 2004). While psychological safety may share characteristics to trust, they are two
different concepts (Siemsen et al., 2009). Psychological safety focuses more on the belief holder,
has a short-term and fluid tenure, and can be viewed at the organizational, team, or individual

levels (Edmondson, 2004). Trust is viewed as the belief that others will view behavior faborably,
thus enabling the individual to add contributions (Edmondson & Mogelof, 2006).
Voice. There have been two main approaches to the idea of voice: one that aims to
predict speaking up and another that examines the concept of not speaking up (Detert &
Edmondson, 2011). Regarding speaking up, evidence has shown that leader openness (Detert &
Burris, 2007), the message type (negative or positive) (Milliken et al., 2003), and how well
thought out a message was (Edmondson & Besieux, 2021) were all moderated by psychological
safety. Conversely, Sherf et al. (2021) showed that behavioral inhibition systems promote
behaviors in individuals that avoid harm or punishment, and that psychological safety was more
strongly related to silence than to voice. This research that psychological safety was related more
to silence than voice was also found by Liang et al. (2012).
Play. Osborn’s (1953) work was among the first to propose that play increases team
innovation and collaboration. An analysis by Mukerjee and Metiu (2022) found play to foster
five elements that may increase psychological safety: safety to speak up, respect, feedback,
support and acceptance of mistakes, and helping behavior. They also found psychological safety
to be both an outcome and an antecedent of play working consistently to drive innovation
(Mukerjee & Metiu, 2022). Parker and du Plooy (2021) found similar results in that
psychological safety increased immediately following play and optimized knowledge exchange
and problem solving. This is consistent with results from Kim et al. (2020) in that psychological
safety will precede learning that enables teams to build effective and consistent mental models.
Mental Models. Mental models, or a team’s shared and organized understanding of
information about their environment (Mohammed & Dumville, 2001), have been suggested to
increase team members ability to anticipate and coordinate other’s actions (Lim & Klein, 2006).

While studying teams within nuclear power plants, Waller et al. (2004) found that shared mental
models to be the variable that differentiates high from low crews. To build these shared mental
models, structured briefings, debriefings (Smith-Jentsch et al., 2008), knowledge exchange and
conflict (Van den Bossche et al., 2011) (moderated by psychological safety) have all been shown
to be significant in this process. Klimoski and Mohammed (1994) showed in their research these
mental models are often higher in teams that communicate and listen to one another.
Listening. Listening has been argued to create an environment of safety for decades
(Rogers, 1951). Individuals who have honed listening skills are often viewed as leaders (Kluger
& Zaidel, 2013), with subordinates that report higher job satisfaction (Tangirala & Ramanujam,
2012), and higher rates of psychological safety (Fenniman, 2010). Castro et al. (2018) showed
similar results where listening consistently predicted psychological safety. One study reported
increases in psychological safety from listening on average but added that an avoidanceattachment style limited the positive effects of psychological safety (Castro et al., 2015). These
personal factors suggest that psychological safety may also play a role at the individual level
where ethical orientations may vary (Edmondson & Lei, 2014; Reynolds, 2006).
Ethics. One variable that has shown a negative relationship with psychological safety
was ethical behavior (Pearsall & Ellis, 2011). Psychological safety influences team behaviors
and attitudes where those that feel safe within their teams were less ethical than teams with lower
psychological safety (Pearsall & Ellis, 2011). Ferrere et al. (2022) substantiates that this may be
because employees that had observed unethical behaviors, but with less psychological safety, felt
less safe to voice those actions to their leaders. In addition, they also found that this relationship
is inversely related where increased occurrences of observed unethical behavior may also lower
psychological safety (Ferrere et al., 2022).

Team Psychological Safety as an Antecedent
In one of Edmondson and Harvey’s (2018) recent work, they describe that psychological
safety is the engine of performance, not the fuel. From this perspective, the argument on the
importance of psychological safety is viewed as a variable to enhance team processes to improve
teamwork (Kim et al., 2020). A substantial body of research exists at this level where the
variables discussed below are all improved through team psychological safety (Edmondson &
Lei, 2014).
Diversity. While some researchers have found that increased diversity rates increase
conflict rates, psychological safety was shown to moderate these variables to increase
performance and counteract any potential negative effects of diversity (Gibson & Gibbs, 2006;
Singh et al., 2013). In various studies, diversity was viewed through the lens of cognitive
diversity (Martins et al., 2013), national diversity (Gibson & Gibbs, 2006), and age diversity
(Gerpott et al., 2021) – all of which showed how psychological safety moderates these variables
with performance and creativity.
Performance and Creativity. Only 47% of employees worldwide say their workplaces
are psychologically safe (Ipsos, 2012). While the study of team effectiveness has an ocean of
research, new studies are recognizing the value of the psychological perspective (Donaldson et
al., 2011). Psychological safety has shown in several studies that it moderates a wide variety of
variables that then correlate to team performance (Edmondson & Bransby, 2023; Kim et al.,
2020; Xie et al., 2022). Edmondson (2012) believes that, while psychological safety likely
improves the odds of performance, that accountability is also necessary. From this idea the
psychological safety-accountability framework was created (as shown in Figure 5).

Figure 5
Psychological Safety-Accountability For Performance Framework
Edmondson, A. C. (2012). Teaming: How organizations learn, innovate, and compete in the
knowledge economy. Jossey-Bass.
As teams enter the high psychological safety zones, team members may feel more willing
to voice novel ideas that generate new solutions and improve performance (Han et al., 2019).
This idea is supported as other studies have shown high performing teams often produce more
creative ideas (Agarwal & Farndale, 2017). Psychologically safe environments support these
ideas by enhancing the positive and minimizing the negative effects of risk-taking and speaking
up (Andersson et al., 2020). This creativity then fosters learning behaviors across individuals in
teams to further build on those ideas (Edmondson & Bransby, 2023).
Learning. A team’s willingness to learn and their psychological safety have been
identified as two vital aspects in overall team learning (Blawath et al., 2012). Edmondson’s
(1999) seminal article on psychological safety showed that learning behavior is highly dependent
on team psychological safety. Studies have confirmed this idea that psychological safety has
been linked to higher tolerance of failure (Tjosvold et al., 2004) and higher learning orientation

of teams (Harvey et al., 2019). Psychological safety enables team learning by building a climate
of risk-free voice where errors are communicated more frequently (Edmondson, 1999),
individuals feel safe to make those errors and fail (Cannon & Edmondson, 2005), and innovative
ideas are free to prosper that builds that team knowledge base (Edmondson & Bransby, 2023).
Innovation and Decision Quality. To innovate, a work environment must encourage
interpersonal risk taking (Baer & Frese, 2003). A growing body of evidence determines that the
innovation process of experimenting, making mistakes, and pursuing the unknowns as dependent
on individuals’ risk-bearing activities (Mukerjee & Metiu, 2022). A psychologically safe
environment has been shown to do exactly that (Edmondson et al., 2001). The presence of
psychological safety promotes innovative actions (Kark & Carmeli, 2009) and constructively
manages cognitive conflict, leading to more creativity and innovation across teams and
individuals (Gu et al., 2013).
Individual Level
At the individual level, Kahn’s (1990) work-related-work engagement model contained
three psychological elements: meaningfulness, safety, and availability. He believed individuals
would “employ and express or withdraw and defend themselves during role performance”
(Kahn, 1990, p. 717). Specifically related to safety, Mathieu et al. (2019) found that social
surroundings and psychological safety were critical factors enabling engagement. A growing
body of research on psychological safety at the individual level continues to showcase that,
similar to the organizational and team levels, individual psychological safety acts as both a
consequent and an antecedent (Edmondson & Lei, 2014).

Individual Psychological Safety as a Consequent and Mediator
Edmondson and Bransby (2023) examined 185 articles on psychological safety in their
most recent meta-analysis. Of those 185 articles, 153 were quantitively measured at either the
individual, team, or organizational level, with 40 (~26%) of those studies conducted at the
individual level (Edmonson & Bransby, 2023). A review of Frazier et al. (2017), Newman et al.
(2017), Edmondson and Lei (2014) and Edmondson and Bransby’s (2023) substantial reviews on
the body of research on psychological safety indicates that psychological safety mediates several
other variables at the individual level. The review below delves into the most relevant to this
study.
Behavioral Integrity. Behavioral integrity, or the “perceived pattern of alignment
between an actor’s words and deeds” (Simons, 2002, p. 19), has been linked to authenticity and
consistency (Palanski & Yammarino, 2007). When applying the lens of psychological safety, this
concept shows that those leaders who ‘walk the walk’ and stay true to their word are shown to
increase the psychological safety in their employees as it reduces uncertainty about how they will
react (Leroy et al., 2012). Any sense of uncertainty has been shown to introduce fear of failure,
provoking anxiety and anticipation of repercussions – the types of thoughts contrary to the
enablement of psychological safety (Edmondson, 2003). While important at the horizontal level,
behavioral integrity is especially vital among persons in leadership positions (Leroy et al., 2012).
Leadership Relations. Leaders influence on an individual’s ability to ask for feedback
and their levels of openness has been studied for decades (Ashford & Tsui, 1991). While Sherf et
al. (2020) showed that while feedback and openness from a leader can lead to increased levels of
voice, a leader must always be aware that employees who feel heard by them have increased
levels of psychological safety at the individual level (Castro et al., 2018). Additionally,

Coutifaris and Grant (2022) found that leaders who showed vulnerability and sought feedback
from their employees increased employee openness, but only if they did not become defensive
and not act on that feedback. This type of vulnerability also goes both ways where psychological
safety has been shown to mediate the negative effects of admitting errors or asking for help that
an employee feels from asking their supervisor (Tynan, 2005). These variables and dynamics
between a leader and subordinate are also shown by Kahn (1990) as a primary driver of
psychological safety in interpersonal relationships with others.
Relations with Others. Psychological safety has been posited as a short-term perception
of interpersonal consequences during interaction with others (Edmondson, 2004). Several studies
have identified how psychological safety mediates interpersonal relationships and social bonds
with secondary variables such as learning from failures (Carmeli et al., 2009), self-disclosure
(Mikulincer & Nachshon, 1991) and voice (Burris et al., 2008). From an evolutionary
perspective, social bonds are often seen as vital to survival (Eisenberger et al., 2003). For
example, if psychological norms with others are breached, patterns of activations in the brain,
similar to physical pain, are activated leaving individuals to act to restore those social bonds and
impacting an individual’s emotional stability (Eisenberger et al., 2003). Neurologically, the brain
equates social needs with survival, such as when being ostracized, which activates similar
responses in the brain as hunger (Rock, 2019). As such, healthy personal relationships depend on
psychological safety and trust in each other (Rock, 2019).
Trust. Trust and psychological safety are often conflated as they share many similarities,
but the two concepts differ in several ways (Carmeli et al., 2009). The first difference is that trust
focuses on relation with others whereas psychological safety is focused on individual perceptions
(Edmondson, 2004). The other difference pertains to trust spanning across a wide range of time

while psychological safety is a relatively short-term interpersonal, dyadic, or organizational
construct (Edmondson, 2004).
Kahn (1990) found that psychological safety was promoted when environments and
relationships were supportive and trusting. Zhang et al. (2010) added to that notion and found
that psychological safety is beset by trust and when individuals feel high levels of both they are
more willing to speak up. Additionally, trust can be both/either affective or cognitive (May et al.,
2004), where cognitive trust opens the ability to discuss errors and affective trust enables
psychological attachment (Scheepers et al., 2018). Building cultures of both affective and
cognitive trust have been shown to build psychologically safe environments (Rakowsky et al.,
2020). To build trust, as it is largely an individual perception of reality, one must also examine
individual factors and differences (Edmondson, 2004).
Individual Differences. Individualization (both personal qualities and characteristics)
has been shown to have a significant relationship in driving an independent influence on the
perceived psychological safety an individual feels (Edmondson & Mogelof, 2006). Among the
studies on individualization and subsequent psychological safety, individual expertise (Lee et al.,
2011), profession-derived status (Newbhard & Edmondson, 2006), perceived age diversity
(Gerpott et al., 2021; Moake et al., 2019), gender (O’Donovan & McAuliffe, 2020) and stress
levels (Hölzel et al., 2010) all show how psychological safety moderates these effects.
Additionally, resilience is vital for individual psychological safety, especially in military settings,
to manage uncertainty and maintain emotional stability (Mjelde et al., 2016).
Emotional Pain and Stability. Once a psychological contract is breached between
persons, job satisfaction decreases, and burnout increases (Erkutlu & Chafra, 2016). This pain,
known as social pain, has been argued to share a similar neuroarchitecture to physical pain

(Eisenberger et al., 2004; Panksepp, 2003) where individuals can relive social pain long after it
has happened (Hansson et al., 1990). In fact, the same opioids used to treat physical pain has also
been shown to alleviate social pain (Panksepp, 2003). Social pain varies from physical pain
where, once the stimulus of physical pain is removed, the salience and memory of that pain will
decrease over time (Chen et al., 2008). Conversely, social pain can increase subsequent levels of
fear and be conditioned off these associative responses (Power & Dalgleish, 2008).
Once fear of any type is activated, an individual’s desire for risk-taking is turned off
(Berns, 2008). A 1998 study by Ryan and Osetrich found that approximately 70% of respondents
did not, or hesitated to, speak up because of a perceived fear of repercussion (Kish-Gephart et al.,
2009). This type of silence has been linked to lower levels of psychological safety (Edmondson,
2003) because psychological safety implies and induces a feeling of lower interpersonal fear
(Edmondson, 1999). While some individuals may respond to threats with fear, a separate
response to a negative stimulus is anger (Kish-Gephart et al., 2009).
Anger, the belief that the person has been offended or injured (Lerner & Tiedens, 2006),
can be triggered by a variety of psychological contract breaches (Kish-Gephart et al., 2009).
While both fear and anger can be detrimental to voice and speaking up, repeated successful
events of speaking up can stabilize these emotions (Kish-Gephart et al., 2009). These secondary
appraisals learned through experience can then identify a situation as more controllable, thus
lowering their threat levels and increasing their emotional control to speak up and be more
proactive (Kish-Gephart et al., 2009).
Proactive Behavior. Proactive behavior, also known as intrapreneurship behavior (IB),
is a voluntary activity (Valsania et al., 2016) measured by an individual’s propensity to take risk,
innovate, and be proactive (Stewart, 2009). In their study, Mahmoud et al. (2022) found

psychological safety to have a direct and significant relationship with IB. However, IB often
requires help seeking activities by individuals that can imply incompetence or dependence on
that individual (Lee, 1997). Supervisors and leaders are often a focal point for individuals to
drive questions (Xu et al., 2019). Similarity of levels of proactive behavior were shown to
increase subordinate levels of psychological safety (Xu et al., 2019). Furthermore, psychological
safety has also shown to mitigate these negative thoughts and encourages individuals to engage
in openness (Edmondson, 1999).
Openness. Withdrawal and openness in individuals have been studied across the social
sciences (Bion, 1961; Freud, 1922). In Kahn’s (1990) study, he found four dimensions to
openness and availability: depletion of physical energy, depletion of emotional energy,
individual insecurity, and outside lives. Through this lens, Kahn (1990) measured psychological
safety by how ready individuals are to engage in their social systems. Kark and Carmeli (2009)
relate this type of energy to the concept of vitality in the workplace, which is an individual’s
approach to life and work with energy, openness, and vigor. Kark and Carmeli (2009) found
thatvitality was positively related to psychological safety and enhances their creative work across
teams and individuals.
Individual Psychological Safety as an Antecedent
A 2017 Gallup study found that only 30% of employees believe their opinions matter
(Edmondson, 2019). Organizations of all sizes depend on individual employees to drive their
work and organization forward through their untapped knowledge (Edmondson, 2012). From a
neurological perspective, when an environment is appraised as safe, the defensive limbic systems
are inhibited, and social engagement prospers (Porges, 2022). As these systems of fear in the

body subside and psychological safety blossoms, several variables are affected (Edmondson &
Lei, 2014).
Organizational Identification and Obligation. An individual’s degree of organizational
commitment and identification has been shown to increase with a person’s participation,
position, and tenure in addition to their perceived level of psychological safety (De Clerq &
Rius, 2007; Guzley, 1992). Johnson et al. (2010) purport that individuals with high degrees of
organizational identification are more willing to invest their resources to support organizational
interests. Additionally, a study of U.S. and South Korean firms, (Kim, 2020) found that
psychological safety often mediated individualization and organizational identification. Kim
(2019) also found that perceptions of a safe environment increase self-expression often seen as
an underlying factor in individual engagement (Kahn, 1990).
Engagement, Commitment, and Job Satisfaction. A psychological safe work
environment can reduce depression and work exhaustion (Idris et al., 2014). Emotionally
exhausted employees are shown to contribute less effectively and lower the quality of
interpersonal teamwork (Welp et al., 2016). Emotional exhaustion is shown to most often occur
when there is either an actual loss of resources, a perceived loss, or a lack of return on invested
resources (Hobfoll, 1989). Additionally, exhaustion negatively impacts job satisfaction and
engagement (Rathi & Lee, 2016).
Meanwhile, psychological safety stimulates job involvement (Brown & Leigh, 1996; Li
& Peng, 2022) and increases levels of work engagement (May et al., 2004). In psychologically
safe environments, employees reported an increase in job resources they can use, leading to these
higher levels of engagement (Dollard & Bakker, 2010). Moreover, in these safe environments,

employees are more engaged (Kahn, 1990) and use their voice more frequently (Edmondson &
Bransby, 2023).
Voice. While voice can be risky because of its associated risk (Van Dyne & LePine,
1998), a growing body of evidence shows that psychological safety increases willingness to
speak up (Edmondson & Lei, 2014). Employees often feel the dilemma of speaking up to better
their organization or remain silent to avoid the risk of adverse consequences (Tangirala &
Ramanujam, 2012). Liang et al. (2012) claimed that there are two types of voice: promotive and
prohibitive. Promotive voice describes speaking up to improve the organization whereas
prohibitive voice expresses concern about practices or behaviors (Liang et al., 2012).
Psychological safety has also been shown to moderate several variables to increase voice, such
as ethical leadership (Walumbwa & Schaubroeck, 2009), change initiative and leadership (Detert
& Burris, 2007), and knowledge sharing (Newman et al., 2017).
Knowledge Sharing and Communication. When individuals fear the repercussions of
communicating and sharing their knowledge, their organization and team is hindered in its
capacity to learn and grow (Lu et al., 2006). A consistent stream of research has shown how
psychological safety leads to more knowledge sharing and communication between individuals
and teams (Edmondson, 2019; Liu & Keller, 2021; Siemsen et al., 2009). Environments of safety
break down many of the barriers incurred by interpersonal threat and fear such that individuals
who do not believe they will suffer consequences of sharing information or communication
information (including errors) will often be more motivated to do so, thereby increasing their
psychological safety and learning (Newman et al., 2017).
Learning. When an environment is nonthreatening and psychologically safe there is an
increased likelihood for learning (Devaraj et al., 2021). Learning has been substantiated through

a free flow of knowledge transfer, voice, creativity, and innovation (Edmondson & Bransby,
2023). In such an environment peers feel free to provide honest feedback that drives further
learning (Scheepers et al., 2018). One limitation in the relationship between learning and
psychological safety was shown in Sanner and Bunderson’s (2015) research in which they found
psychological safety only enabled learning in knowledge-extensive work and that standard,
repeatable, and low complexity work benefits little from psychological safety. These findings are
consistent with other psychological safety research positing job variety as a potential moderator
between learning and psychological safety (Liu et al., 2014). Job variety thus requires varying
skills and psychological safety to manage complexity and performance (Baer & Frese, 2003;
Sanner & Bunderson, 2015).
Performance. By creating the conditions for individuals to speak, share, and ask,
psychological safety enables individuals to drive performance (Edmondson & Bransby, 2023).
Through mediation, psychological safety has been shown to drive performance in diverse teams
(Singh et al., 2013), inclusive leadership (Li & Peng, 2022), error detection and admission
(Morrison & Milliken, 2003), and engagement (Kahn, 1990). Edmondson and Lei (2014) discuss
how the relationship between performance and psychological safety is logical given the amount
of uncertainty in today’s work and that psychological safety can overcome knowledge hiding and
silence that often comes with uncertainty. As individuals overcome this uncertainty, confidence
and motivation often follow suite (Siemsen et al., 2009).
Confidence and Motivation. An individual trait often driven by psychological safety is
confidence (Siemsen et al., 2009). In their research, Siemsen et al. (2009) found confidence acts
as a moderator between psychological safety and knowledge sharing wherein individuals high in
confidence also rated higher in psychological safety and the motivation to share their knowledge.

Lyman et al. (2020) also showed that safe environments enable others to feel supported and
thereby increasing confidence. Meanwhile, not only does psychological safety affect an
individual’s confidence, but it also increases their motivation (Lin et al., 2022).
Specifically, when individuals perceive a sense of safety and security, they have a strong
tendency to experience a positive emotional state and subsequent motivation (Lin et al., 2022). In
their a study of financial accountants, Lin et al. (2022) found that when individuals had a strong
sense of psychological safety that motivation paralleled in its strength. From this motivational
perspective, the Conservation of Resources theory aims to explain human behavior through the
lens of acquisition and conservation of resources (Hobfoll, 1989), which can help explain
behavior influenced by psychological safety.
Psychological Safety in Military Teams
The military has always been an arena of ample research where team effectiveness
(Shuffler et al., 2012), training (Salas et al., 2005), and learning (Mathieu et al., 2000) have all
been extensively studied. However, much of the research on psychological safety has centered
on the civil and public sectors (Prykhodko, 2022). While the review on psychological safety in
the previous section described the positives of psychological safety in the civilian sector, the
high-risk work environments inherent in the military encompasses may also benefit from
psychological safety (Boe, 2015; Chu et al., 2016; Nindl et al., 2018).
Military teams parallel non-military teams in many ways but the military’s stressful and
high-risk environments present several key differences, including risking others’, and their own,
lives (Essens et al., 2009; Okray & Lubnau, 2004). The risks and restrictions that teams within
these environments face can result in increased mission constraints and varying degrees of risk
that result in the actions these teams make having potentially significant repercussions

(Veestraeten et al., 2014). Hageman et al. (2012) defined military teams as high responsibility
teams (HRTs) given these complexities.
While military HRTs may operate in extreme environments, they must also persist in
non-combat and lower-risk conditions (Prykhodko, 2022). The uncertainty of these mismatches
in environments leads to further reliance on understanding the variables that enable effective
teamwork (Mathieu et al., 2008). These conditions are those in which drills, planning, and
training is conducted (Mjelde et al., 2016). To understand the state of military training today, it is
important to identify how military training has changed over time.
The History of Military Research. The team is at the center of the United States (U.S.)
military. Integrating individuals from across the U.S. leads to diverse perspectives and
backgrounds that can allow teams to accomplish tasks more complex and at a larger scale than
individuals acting alone (Goodwin et al., 2018). However, because of the high-risk nature of the
military, maximizing team performance has continued to elude researchers and practitioners
(Goodwin et al., 2018). Researchers began investigating and applying psychological research in
1917 as World War I was raging as psychologists attempted to develop tests for job selection and
placement (Goodwin et al., 2018). As time progressed and World War II showcased how the
German Army expanded its footprint so rapidly, Shils and Janowitz (1948) concluded that these
soldiers could do so in part because of loyalty and cohesion amongst their teams. This research
continued until the end of the Vietnam War as the U.S. military shifted from mandatory service
to a smaller all-volunteer force (Rostker, 2006). Team effectiveness was now at the forefront of
research to balance personnel reduction and overall military effectiveness (Dyer et al., 1980).
A second tactical shift was occurring at the same time after the U.S. Navy, Army and Air
Force conducted one of the first joint service missions in history as they attempted to rescue 66

hostages from Iran that resulted in two crashed aircraft and eight service members dead (Ball,
n.d.). This event led to a parabolic rise in joint warfare planning and the integration of teams
across the services (Goodwin et al., 2018). During this time, research focused on the actions and
behaviors of individuals and teams to discover variables leading to more effective performance
and teamwork (Salas et al., 1995). Nearly 40 years later, the events of September 11, 2001,
prompted the military to adopt new approaches to training teams (Goodwin et al., 2018). These
approaches included using advanced tools and technologies and where research emphasized
organizational and environmental contexts that may influence team performance (Chapman &
Colegrove, 2013).
Military Training. Military training is designed for systematic socialization to forge a
cohesive military identity (Arkin & Dobrofsky, 1978). The intensity surrounding this training is
designed to instill specific values and discipline necessary for military team effectiveness
(Gonzalez et al., 2020). This type of training faces unique challenges not experienced by those in
non-military sectors as individuals must become uniform and adhere to high standards under
extreme conditions in austere environments (McCarthy, 2008). The consolidation of Service
Members from all walks of life during this training brings both high levels of diversity but also
varying levels of skill, leadership experience, and self-confidence that suggests one standard way
of training may be ineffective at training all individuals to the same standards (Spain et al.,
2012).
Learning in Military Teams. A significant body of research showcases the positive
effects on military team learning and team performance (Goodwin et al., 2018; Shuffler et al.,
2012). However, sustaining team learning in military teams (Shuffler et al., 2012), where strict
hierarchy exists (Gordon, 2002), has been difficult as learning in environments of high-power

disparity has been shown to act as a barrier to learning (Bunderson & Reagans, 2011; Schilling
& Kluge, 2009). While members experience this power disparity in nearly every interaction
given the rank worn on their uniforms, each team varies in these power disparities (Stothard &
Drobnjak, 2020). The learning-oriented leadership style has been shown to improve levels of
team learning – even in hierarchical military teams (Popper & Lipshitz, 2000). This style of
leaderships involves leaders of all ranks encouraging and rewarding individual and team learning
(Halevy et al., 2011). As Edmondson (1999) showed in her seminal article, encouraging this type
of learning requires psychological safety.
Psychological Safety in the Military. To date, only a handful of studies exist on the
relationship between psychological safety and the military (Hedlund & Osterberg, 2012;
Prykhodko, 2022; Sowden et al., 2020; Veestraeten et al., 2014; Wermser et al., 2016). With the
exception of Sowden et al (2020) who studied the relationship between sleep quality and
psychological safety in U.S. Army tank crews and Prykhodko (2022) who examined
psychological states of Soldier’s in Ukraine, the other studies focused primarily on team learning
and performance in the military.
Hedlund and Osterberg (2012) studied psychological safety and team learning during a
joint military exercise involving forces from Sweden, Finland, and Norway. They found
psychological safety imperative in creating an environment for team learning and overall team
and organizational performance (Hedlund & Osterberg, 2012). The study identified the
challenges presented in joint operations with individuals from multiple countries and
backgrounds integrating together to try to complete various tasks together (Hedlund &
Osterberg, 2012).

Wermser et al. (2016) observed a similar challenge as all individuals identified as
military members, but specific norms and values inserted themselves to impact behavior. These
differences can be problematic and reduce psychological safety if individuals identify only with
their originating nation and not as a collective force, particularly when individuals expect others
to behave similarly because of the expectation of similarity based on this membership identity
(Wermser et al., 2016). These expectations can violate social cohesion and group potency – both
variables that Veestraeten et al. (2013) found to be positively related to team learning behavior
(in addition to psychological safety) in their study of the Belgian military engaged in
peacekeeping operations in the Middle East and Africa between 2008 and 2010.
Conservation of Resources
The Conservation of Resources (COR) theory, first described by Hobfoll (1989), posits
that individuals strive to maintain, retain, build, and protect their resources. When an individual’s
resources are threatened with loss, are lost, or fail to gain resources, they experience
psychological stress (Hobfoll et al., 2018) regardless of the alignment between perception and
reality (Clarkson et al., 2010). This stress derives from an evolutionary disposition to overweight
resource loss while underweighting resource gain (Hobfoll et al. 2018). While there are several
models attempting to understand human behavior when confronted with stress, COR goes
beyond that and seeks to explain behavior based on the need to mitigate resource loss, but also
the desire for resource acquisition from a motivational perspective (Hobfoll et al., 2018).
Hobfoll (1989) also suggests that the theory was derived from Wicklund and Gollwitzer’s
(1982) work where they suggested that individuals will build and maintain both personal and
social characteristics. However, when resources are lost, and direct replacement is not possible,
symbolic, superficial and indirect replacement of resources occurs to re-regulate these resource

levels (Hobfoll, 1989). For use in the COR theory, these resources are defined as “those objects,
personal characteristics, conditions, or energies that are valued by the individual or that serve as
a means for attainment of these objects, personal characteristics, conditions, or energies”
(Hobfoll, 1989, p. 516).
The individualization component suggests that the value of resources may vary between
individuals based on individual experiences and environments (Halbesleben et al., 2014). These
resources may be provided by the organization or stem directly at the individual level in which
their perceived levels of adequacy of resources may direct behavior regardless of the accuracy of
those perceptions (Hobfoll et al., 2018). As these resources ebb and flow, Marx-Fleck et al.
(2021) operationalized the defensiveness of behavior in that individuals will respond with threats
to resources by prioritizing resource conservation over acquisition. This notion was supported by
previous research that found that individuals’ defensiveness levels grow stronger as their
resource loss continues (Halbesleben & Bowler, 2007; Halbesleben & Wheeler, 2015).
Principles. COR rests on four principles: primacy of loss, resource investment, gain
paradox, and desperation (Hobfoll, 1989). Primary of loss suggests that loss of resources is felt
unequivocally more than resource gain (Hobfoll, 1989). As individuals experience psychological
stress it is suggested that they will withdraw or engage in defensive measures to protect those
resources (Carnevale et al., 2018). When resources are lost, evidence has suggested that these
individuals are more likely to experience depression (Kessler et al., 1988), burnout (Shirom,
1989), and other physiological outcomes (DeVente et al., 2003; Melamed et al., 2006). The
second, resource investment, suggests that individuals will invest their resource to protect,
recover, and gain resources (Hobfoll et al., 2018). The third, gain paradox, suggests that resource
gains increase in value as circumstances for resource loss grow. The last principle, desperation,

suggests that defensiveness and irrationality grow when resources are lost or exhausted (Hobfoll
et al., 2018).
Corollaries and Caravans. In addition to the four principles, COR also encompasses the
constructs of corollaries and caravans. Caravans suggest that resources do not exist in isolation
or individually and will travel in groups (Hobfoll et al., 2018). The crux of this concept is that
resources are a consequence of individual adaptation, nurturance, and learning (Hobfoll, 2011).
Caravans have even been posited as being consequential at the group level rather than merely at
an individual one (Hobfoll, 2011). For example, the stress experienced by one person may then
affect their behavior influencing another person in the same or nearby environment (Bolger et al.,
1989).
Three corollaries exist within COR. The first corollary suggests that greater resource
levels result in less vulnerability to resource loss and an increase in the capability to gain
resources (Hobfoll, 1989). The second corollary suggests that because the loss of resources is
more powerful than the gaining of resources, the stress that occurs when resources are lost gains
in momentum and magnitude as individuals have fewer and fewer resources to offset those losses
(Hobfoll, 1989). The last corollary suggests that resource gains are weaker, slower, and are less
salient than resource loss (Hobfoll, 1989).
In addition to caravans, these corollaries can be transferred across individuals via
crossovers (Hobfoll et al., 2018). Previous research shows that resources such as performance
self-esteem and self-efficacy (Neff et al., 2012), supervisor-supervisee relationship and the
subsequent supervisee performance (Breevaart et al., 2014) and engagement (Gutermann et al.,
2017) can all metastasize from one person to another. One resource, social support, is among
those resources found most assumed to mitigate the stressors and demands of work (Halbesleben,

2006; Kurtessis et al., 2017). While evidence shows that social support can be neutral or even
negatively affect a situation (Beehr et al., 2003; 2010), social support is a driving factor for
psychological safety.
Resource Investment. From a COR perspective, those with higher levels of resources
will be willing, if not motivated, to take risks and expend those resources for goal achievement
(Marx-Fleck et al., 2021). Greater resources also shield individuals from loss and make resource
gain more achievable (Marx-Fleck et al., 2021). Additionally, a large body of research shows
that individuals react differently to resource threats by either driving individuals to avoid failure
and at the same time encouraging others to invest those resources for potential gains (Artinger et
al., 2015; Corr, 2013). As such, those with fewer resources may feel less safe and secure to
expend those resources as they seek to conserve them leading to reluctance to engage in their
environments (Hobfoll, 2011; Marx-Fleck et al., 2021). Conversely, Bolino and Turnley (2005)
found that when employees took initiative they also experienced higher psychological stress
while needing to invest more resources to deal with ensuing conflicts. One resource, that of
voice, appears to deplete resources when activated suggesting that only those with these
reservoirs of resources will actively use it but can lead to increased team and individual
performance (Ng & Feldman, 2012). Additionally, individuals showed a stronger affinity to use
voice when conserving resources versus when gaining resources (Ng & Feldman, 2012).
Understanding the Barriers
Recent research has discovered several variables ranging from individualistic to team
level constructs in psychological safety (Konings et al., 2020). Evidence shows that team level
psychological safety is influenced both from the combination of individual safety rates and by

team level variables (Edmondson & Lei, 2014). A separation of factors between individual and
team level barriers will be provided.
Team level barriers. The four major themes for team level barriers, as shown in Figure
2, include hierarchy, leadership, work environment, and relationship conflict (Lackie et al., 2023;
Konings et al., 2020; Remtulla et al., 2021). Hierarchy has been cited in roughly one-third of
studies on its effects to predict lower rates of psychological safety (Lackie et al., 2023). Remtulla
et al. (2021) found that hierarchy fostered perceptions of inferiority and that members believed
their leaders valued their opinions less. Konings et al. (2020) found that students often withheld
thoughts and ideas on the fear of punishment that was compounded when their teacher was
involved in assessment.
Leadership types have also been shown to directly impact subordinates’ psychological
safety (Detert & Burris, 2007). Positive leadership traits, such as ethicality (Hu et al., 2018) and
inclusiveness (Hirak et al., 2012), have been repeatedly shown to increase psychological safety
(Edmondson & Lei, 2014). Conversely, abusiveness (Jiang & Gu, 2016) and toxicity decrease
these rates (Williams, 2019). These results prove that the relationship between the subordinate
and leader can positively or negatively impact psychological safety (Edmondson & Lei, 2014).
A team’s work environment also significantly affects team psychological safety
(Remtulla et al., 2021). Arnetz et al. (2019) found that workplace bullying had a significant
effect on psychological safety. Intolerance to failure (Smeets et al., 2021), task overload
(Cartwright & Pappas, 2008) and uncertainty (Grote, 2015) all link to decreased psychological
safety. Relationship conflict (separate from task conflict) has also been shown to be a fourth
impediment to psychological safety (Johnson & Avolio, 2019; Stalmeijer et al., 2007; Tang et
al., 2021; Xie et al., 2022). In the above scenarios, Kish-Gephart et al. (2009) posit that these

team conflicts can elicit both anger and fear, ultimately leading to future silence and low
psychological safety.
On the individual level, the four major barriers include lack of knowledge or expertise,
perceptions, self-preservation, and voice fatigue (Lackie et al., 2023; Konings et al., 2020;
Wawersik et al., 2023). A lack of knowledge has been shown to block psychological safety
largely due to a fear of judgment (Brown, 2019; Konings et al., 2020). Kang and Min (2019)
found similar results in a nursing simulation experiment and found a lack of readiness for the
task decreased psychological safety. Conversely, possessing that knowledge has been shown to
increase confidence, assertiveness, voice, and psychological safety (Wawersik et al., 2023).
The second individual barrier to psychological safety is perception (Kang & Min, 2019;
Wawersik et al., 2023). Past experiences can predict future actions and events that decrease
psychological safety can impact the perception of future harm (Vrbnjak et al., 2016). These
perceptions range from expecting error (Landgren et al., 2016; Rich et al., 2019) to future shame
and embarrassment (Kang & Min, 2019). These perceptions were compounded when individuals
believe they are being surveilled or evaluated at work that can expose errors (Ganley & LinnardPalmer, 2010; Lackie et al., 2023). This surveillance often results in a heightened sense of
vulnerability (Calhoun et al., 2014).
The third individual barrier to psychological safety is self-preservation (Wawersik et al.,
2023). Kahn’s (1990) preliminary work on psychological safety provided the initial definition of
the concept. He defined it as the ability to “show and employ one’s self without fear of negative
consequences to self-image, status, or career” (Kahn, 1990, p. 708). This fear can range from
punishment or retaliation (White & Delacroix, 2020; Hemon et al., 2020; Landgren et al., 2016),
blame (Lee et al., 2018; Sahay et al., 2015; Chegini et al., 2020), labeling (Sahay et al., 2015), or

termination of a job (White & Delacrois, 2020; Hemon et al., 2020; Landgren et al., 2016).
Wawersik et al. (2023) assert that self-preservation is a determinant of psychological safety
conserving that fear.
The last barrier to individual psychological safety is voice fatigue. Voice fatigue occurs
when input is repeatedly provided but rarely acted on (Konings et al., 2020). This fatigue is
driven by previous events of non-resolution and often backs individuals into passivity (Carey,
2013; Martens et al., 2020). This barrier requires identifying team tenure and longitudinal studies
(Konings et al., 2020).

Figure 6
Team and Individual Level Barriers to Psychological Safety
Note. Barriers examined in team and individual level research on psychological safety.

Conceptual Framework
This study will combine the four stages of psychological safety set forth by Clark (2020)
with the Conservation of Resources theory. In the book, The 4 Stages of Psychological Safety:
Defining the Path to Inclusion and Innovation, Clark (2020) argues that psychological safety can
be divided into four stages: inclusion safety, learner safety, contributor safety, and challenger
safety. The idea follows that as an individual grows in levels of psychological safety, they will
follow along this path in their journey to higher levels of inclusion and innovation (Clark, 2020).
Clark (2020) posits that inclusion safety is based on merely labeling an individual as
being associated with a team. For example, once an individual signs an oath of enlistment or oath
of commission in the Army, they can be seen as having inclusion safety based on that status.
Learner safety follows immediately after and is when an individual feels safe to engage in
discovery, ask questions, experiment, and to make mistakes (Clark, 2020). This level implies
both activity and participation within defined boundaries and typically entails onboarding
activities, training, or other knowledge exchange (Clark, 2020). Contributor safety then offers
more psychological safety where the individual is seen as an active participant and fully engaged
member of the team and organization (Clark, 2020). Doing the job an individual was hired to do
is an example of contributor safety. Lastly, challenger safety affords an individual the ability to
challenge the status quo without consequence or repercussion to their status or reputation (Clark,
2020). At this level, individuals can perform more creatively and to higher standards (Clark,
2020).
The four stages of psychological safety, through the lens of the Conservation of
Resources theory, can be viewed as increasing and decreasing levels of resources within the four
stages. As an individual progresses through these stages, they then accumulate more resources,

such as status, voice, or autonomy, they can then use and invest in their work. As an individual
then accumulates resources they can expend then and progress in the linear track upwards.
Conversely, if resources are lost, individuals will digress in these stages, which will then alter
their behavior to become more conservative in their resources and to secure those remaining.
While the stepwise conceptual framework of Clark’s (2020) Four Stages of Psychological Safety
shows these stages and resource reservoirs as a linear scale, individuals can, and will, rise and
fall based on experiences and events in their workplace.
Summary
The history, depth, and breadth of research over the previous six decades has shown the
expansive benefits of building psychological safety within organizations (Edmondson &
Bransby, 2023). Most of the evidence has shown how the organizational, team, and individual
levels of the modern-day workforce are moderated and mediated differently via this construct
(Newman et al., 2017). Relating specifically to the military sphere, limited research has studied
these effects on this unique environment and how to build psychologically safe environments.
Using the theory of Conservation of Resources in tandem with the four stages of psychological
safety (Clark, 2020), psychological safety can be argued to act as an investment/divestment
strategy for individuals as they expend/secure their resource reservoir in various settings.

CHAPTER THREE: METHODOLOGY
This study aims to identify how the reservoir of resources an individual has relates to
perceived psychological safety stages and subsequent performance. To collect this information, a
longitudinal and correlational quantitative survey was distributed to 102 Army Officer
Candidates (OCs) from October 2023 to February 2024. Measurement of psychological safety
ratings were taken at the beginning and after each of the three phases of training. These phases
are: Basic, Intermediate, and Senior phases of training (United States Army, n.d.). The survey
instrument will be centered on the three research questions:
RQ1: Do stages of psychological safety relate to performance?
RQ2: Do stages of psychological safety change over time?
RQ3: Does availability of resources correlate with psychological safety?
This chapter will describe additional information on the sample and setting,
instrumentation, data collection, ethics, and the researcher.
Sample and Setting
Army Officer Candidates are comprised of college graduates from across the United
States and range from 19 to 32 years old (United States Army, n.d.). Each OCS class contains up
to 160 candidates divided into four Platoons of 40 (Boot Camp & Military Fitness Institute, n.d.).
The location of OCS is at Fort Moore, Georgia (United States Army, n.d.). Due to limited access
to OCs, availability sampling was used. The recruitment approach was to capture and survey all
consenting candidates.
While no official demographics are provided for each graduating class, in 2022, there
were 79,204 Active-Duty Army Officers (U.S. Army, 2022). Of those, nearly 80% were men and
20% women while 69% were white, 11% Black, not Hispanic, 9% Hispanic, 8% Asian or Pacific

Islander, and 1% American Indian or Alaskan Native (U.S. Army, 2022). Officer candidates
have a wide variety of backgrounds, experiences, education, and upbringings as they are a
collection of individuals from thousands of communities that make them ideal candidates for this
study.
Demographics of this class were 62% were male (n = 68), 13% female (n = 28) with the
other 25% not reporting gender. The class was primarily White (46%, n = 51) with
Undergraduate degrees (57%, n = 63). Of the non-White participants, 11% reported Other (n =
12), 9% Asian (n = 10), 6% Black or African American (n = 6), 2% Native Hawaiian or Pacific
Islander (n = 2), 2% Prefer Not to Say (n = 2), and 25% (n = 27) not reporting. Of those who
reported, 20% (n = 22) were prior service meaning they were enlisted before receiving their
commission and entering OCS while 56% (n = 61) were not and 25% (n = 27) not reporting. The
range for the number of years of service if prior service was from 1 – 15 with 6 (4%, n = 4) and 7
(4%, n = 4) as the most reported with rank ranging from E-4 (4%, n = 4) to E-7 (4%, n = 4) with
E-5 being most reported (8%, n = 9). A table of these demographics can be found in Table 25 in
the Appendix.
This sample and setting were appropriate to address the research questions as the
environment offers the opportunity to capture individuals that have never met before. This starts
team tenure at zero where psychological safety changes can be observed over time. Additionally,
the sample of this setting is from nearly every environment and culture from around the United
States.
Instrumentation
A quantitative survey was used to collect responses. The survey (found in Appendix B)
was a consolidation of the four stages of psychological safety measurement tool developed by

Zhang et al. (2022) and the Conservation of Resources-Evaluation (COR-E) (Hobfoll & Lilly,
1993). Zhang et al.’s (2022) instrument was chosen because it was the only survey published that
measures the four stages of psychological safety. Cronbach’s α was not provided (Zhang et al.,
2022). Zhang et al.’s (2022) instrument was used to correlate stages of psychological safety with
performance at OCS. Performance at OCS is measured through academic, fitness, leadership,
and military evaluations. All four categories were aggregated and compared to perceived
psychological safety stages to capture any potential patterns or correlations. To ensure the
individual data of these events are not widely disseminated, this study used only the final scores
for each category.
While most of the psychological safety research to date has used Edmondson’s (1999)
seven-item scale (Frazier et al., 2017), that scale only views psychological safety has a whole.
This limits its efficacy in this study as this research aims to test hypotheses drawn from Clark’s
(2020) theory on how psychological safety is divided in four stages. To measure perceived
resources, an adapted version of the COR-E survey was used. The COR-E is a 74-item
questionnaire developed by Hobfoll and Lilly (1993) to measure resources. While the entirety of
74-item questionnaire has been limited in use, a common approach researchers have taken is to
reduce the items to the one relevant to their research questions (Halbesleben et al., 2014). For
this study, 36 questions relating to psychological or social resources were used. Responses and
analysis were examined to investigate the evolving rates and stages of safety over time and its
relation to performance.
Quantitative Data Collection
Data were collected at the beginning and after each phase of training over the course of
the twelve-week OCS class. Data were collected to capture how rates of psychological safety

develop and affect individual performance around graded events during those weeks. The fiveminute survey was taken online and distributed to each candidate via Qualtrics. Results were
then downloaded to the researcher’s local hard drive for storage. Data will be maintained for
three years after completion of the study.
Data Analysis
Data analysis was conducted using the IBM SPSS statistical package. The first part of the
analysis examined survey reliability and validity. A correlation of psychological safety stages
against performance over time were then performed. Third, a comparison of each psychological
safety stage was plotted over time to identify changes over time. Last, a correlation examine was
conducted between resources and psychological safety stages at each time. All analyses were
done at the individual rather than team level.
Ethics
In addition to sample and method in relation to research design, ethical considerations
must be considered before researching human populations. I also declared my role as an Officer
in the Air Force having gone through the Air Force’s version of Officer Training. I showcased
how I had no legal or punitive authority over the candidates and that my military affiliation is
merely a factor that drew me to this sample. Additionally, I did not observe behavior directly and
solidified my role as researcher-only.
Regarding the population, the interests this research serves allows both military and
civilian leadership to gain a clearer understanding of how psychological safety develops over
time and how different levels of psychological safety may impact performance. In addition,
employees will benefit as they understand where they are within the psychological safety
spectrum to identify how to become more included in their organizations.

The design of the study anonymized all participants by removing identifying information.
The University of Southern California and the Army’s Institutional Review Boards reviewed this
study prior to collecting data. Additionally, all participation was voluntary including informed
consent forms that were provided at the beginning of the study along with the option to opt-out
of the study at any point in time. Results of this study will then be published in this doctoral
dissertation and offered to the OCS after those participants have graduated. No funding was
provided for this study to limit conflict and interest.
The Researcher
Recognizing that a researcher’s background may influence a study, ranging from the
design, execution, and analysis, I sought to acknowledge my own biases and relationships to the
setting and participants that may mitigate any potential biases as much as possible (Secules et al.,
2021). In addition to the benefits of the chosen population on advancing the research on
psychological safety, this sample was also chosen through the insights I have as I have gone
through OCS as well. As a current Air National Guard Officer, I recognized the challenges of
training and believe this offers a lens of insight into the direction the sample will move in with
respect to their levels of psychological safety.
This experience confers an empathic viewpoint as the sample undergoes many training
days reaching physical, mental, and emotional fatigue. However, it may also introduce
assumptions and bias as my experience will not be the same as the candidates in the sample. To
combat this, utilized a tested instrument designed by separate researchers (Zhang et al., 2023) to
minimize the impact of this bias.

CHAPTER FOUR: FINDINGS
The results provided below outline the findings from the longitudinal surveys
administered to the Army Officer Candidate School (OCS) class from October 2023 – February
2024. The analyses are framed and presented specific to each of the three research questions
beginning with a review of scale reliability. Data and information are also presented in several
tables and figures in the discussion. A summary of findings is also provided. Of note, the fourth
round of survey responses was eliminated from these findings due to the low sample size (n =
10).
Scale Reliability
At Time 1, as shown in Table 1 below, all four stages were statistically significant and
correlated with each of the other stages. The lowest Pearson Correlation (rxy = 0.561) was
between Contributor and Inclusion suggesting participants did not always need to feel included
to contribute. The highest Pearson Correlation (rxy = 0.778) was between Contributor and
Learning suggesting that participants often learned before contributing and/or learned after
contributing. Results of these findings do not suggest a stepwise pattern between stages but
rather dynamic and interrelated constructs. A high correlation also suggests that respondents may
have had difficulty differentiating between stages resulting in shared characteristics.

Table 1
Psychological Safety Stages Time 1 Correlations
Inclusion Learning Contributor Challenger
Inclusion Pearson Correlation --
N 82
Learning Pearson Correlation .60* --
Observed Probability .00
N 82 82
Contributor Pearson Correlation .57* .78* --
Observed Probability .00 .00
N 82 82 82
Challenger Pearson Correlation .59* .67* .77* --
Observed Probability .00 .00 .00
N 82 82 82 82
*p < 0.05 level, 2-tailed.
Pearson’s r ranged across the stages with Learning and Inclusion (⍺ = .60), Contributor
and Learning (⍺ = .78), and Challenger and Contributor (⍺ = .77). The removal of reverse
ordered questions was found to increase reliability of the instrument across all stages as shown in
Tables 2 – 5 below. Findings suggest removing negatively worded questions (labeled with [R] in
Tables 2 – 5) from the survey scale for increased reliability or rephrasing to ensure all questions
are positively worded. The Learning stage had the highest mean (M = 4.12) followed by
Contributor, Inclusion, then Challenger, as seen in Table 6. The pattern of means does not
suggest a sequential stepwise pattern for the four stages because the means did not increase from
lower stages to upper stages. Results also suggest interdependency among stages. Standard
deviations increased with each stage, suggesting a wider range of perceptions of psychological
safety at those stages, as shown in Table 6. Time 2 and 3 stage descriptive statistics can be found
in Tables 21 and 23 in the Appendix.

Table 2
Inclusion Questions Time 1 Item-Total Statistics
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Cronbach's
Alpha if Item
Deleted
Feeling Included 24.85 14.52 .47 .50
Feeling Listened To 24.93 14.64 .46 .51
Safe To Take Risks 25.39 15.35 .26 .56
Mistakes Held Against Me (R) 25.96 15.44 .22 .58
Undermine Efforts 25.46 15.21 .29 .55
Reject Other’s Differences (R) 26.37 16.26 .10 .62
Difficulty Asking For Help (R) 25.65 15.61 .17 .60
Teamwork 24.90 14.98 .53 .50
Table 3
Learner Questions Time 1 Item-Total Statistics
Scale Mean if Item
Deleted
Scale
Variance if
Item Deleted
Corrected ItemTotal Correlation
Cronbach's
Alpha if Item
Deleted
Depend On Leader 20.32 8.15 .64 .72
Value New Ideas 20.57 7.90 .61 .72
Encourage Growth 20.27 7.90 .70 .70
Resistance (R) 21.45 8.70 .26 .83
Support In New Tasks 20.67 7.58 .59 .73
Sharing Info 20.26 8.83 .48 .75

Table 4
Contributor Questions Time 1 Item-Total Statistics
Scale Mean if
Item Deleted
Scale Variance if
Item Deleted
Corrected ItemTotal Correlation
Cronbach's
Alpha if Item
Deleted
Skills Utilized 15.49 8.94 .68 .81
Safe To Speak 15.56 8.35 .75 .79
Voice Problems 15.56 9.24 .61 .83
New Ideas 15.39 8.56 .82 .78
Idea Length (R) 15.71 9.30 .48 .87
Table 5
Challenger Questions Time 1 Item-Total Statistics
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Cronbach's
Alpha if Item
Deleted
Comfort Speaking Up 14.26 9.01 .61 .76
Comfort Suggesting Ideas 14.17 9.25 .67 .75
Express Opinions Offline (R) 15.63 9.35 .45 .82
Differences In Opinions Welcome 14.23 9.07 .67 .75
Alternate Ways To Work 14.20 9.99 .62 .77
Table 6
Mean and Standard Deviations of Time 1 Stages of Psychological Safety
Mean Std. Deviation N
Inclusion 3.63 .54 82
Learning 4.12 .56 82
Contributor 3.89 .73 82
Challenger 3.62 .75 82

RQ1: Do Stages of Psychological Safety Relate to Performance?
Research question 1 was answered through a correlation analysis between the average
scores of each psychological safety stage during each wave and an OC’s total physical,
academic, technical and leadership points they earned.
Time 1
The observations and correlations within the performance metrics itself show significance and
direct correlations between all but two metrics. Table 7 shows the relationships between the four
performance metrics and their strength and direction of correlation. The only two non-significant
correlation coefficients were between Physical and Academic (rxy = 0.08). The strongest
relationship existed between Physical and Technical points (rxy = 0.35).
Table 7
Performance Metrics Inter-Correlation
Leadership
Points
Physical
Points
Academic
Points
Technical
Points
Leadership Points Pearson Correlation --
N 109
Physical Points Pearson Correlation .29* --
Observed Probability .00
N 109 109
Academic Points Pearson Correlation .27* .08 --
Observed Probability .00 .40
N 109 109 109
Technical Points Pearson Correlation .20* .35* .25* --
Observed Probability .04 .00 .01
N 109 109 109 109
*p < 0.05 level, 2-tailed.
As shown in Table 8 below, no statistical significance was found between any
psychological safety stage at time 1 and any of the performance measures apart from both

Inclusion and Learning stages with Technical Points. Inclusion and Learner were significant at
the .05 level (ρ = .05) and (ρ = .03), respectively. The relationship between these stages and
Technical points were both negative (ρ = -.22) and (ρ = -.23), respectively, suggesting an inverse
relationship. The correlations suggest lower safety is associated with high performance is
contrary to expectations. Results suggest either psychological safety stages have no relation to
performance at OCS or scale limitations in measuring said relationship.
Table 8
Psychological Safety Scales and their Relationship to Performance at Time 1
Leadership
Points
Physical
Points
Academic
Points
Technical
Points
Inclusion Pearson Correlation -.07 -.01 .00 -.22*
Observed Probability .51 .92 .97 .05
N 82 82 82 82
Learning Pearson Correlation -.06 -.01 .11 -.23*
Observed Probability .60 .94 .35 .03
N 82 82 82 82
Contributor Pearson Correlation -.11 .00 -.14 -.17
Observed Probability .34 .98 .22 .12
N 82 82 82 82
Challenger Pearson Correlation .06 .00 -.17 -.16
Observed Probability .59 .97 .12 .14
N 82 82 82 82
*p < 0.05 level, 2-tailed.
Times 2 and 3
No significance was found between any psychological safety stage at Times 2 or 3 and
the performance metrics. Results reaffirm the findings in time 1 as to psychological safety stages
having no relation to performance at OCS or scale limitations in measurement. See Tables 9 and
10 below for time 2 and 3 psychological safety stage and performance correlations.

Table 9
Psychological Safety Scales and their Relationship to Performance at Time 2
Leadership
Points
Physical
Points
Academic
Points
Technical
Points
Inclusion Pearson Correlation -.10 .04 .08 -.09
Observed Probability .56 .81 .64 .59
N 39 39 39 39
Learning Pearson Correlation -.29 -.08 .15 -.16
Observed Probability .07 .62 .36 .34
N 39 39 39 39
Contributor Pearson Correlation -.20 -.01 .12 -.12
Observed Probability .23 .94 .46 .46
N 39 39 39 39
Challenger Pearson Correlation -.04 -.11 .23 .05
Observed Probability .80 .52 .17 .78
N 39 39 39 39
Table 10
Psychological Safety Scales and their Relationship to Performance at Time 3
Leadership
Points
Physical
Points
Academic
Points
Technical
Points
Inclusion Pearson Correlation .09 -.16 .00 .01
Observed Probability .65 .39 1.00 .97
N 30 30 30 30
Learning Pearson Correlation .02 -.05 .18 .04
Observed Probability .94 .79 .33 .84
N 30 30 30 30
Contributor Pearson Correlation -.02 -.10 .06 .14
Observed Probability .93 .60 .74 .45
N 30 30 30 30
Challenger Pearson Correlation .05 -.08 -.05 .17
Observed Probability .79 .69 .80 .38
N 30 30 30 30

RQ2: Do Stages of Psychological Safety Change Over Time?
Research question 2 was answered by analyzing significance using Pillai’s Trace. Each
stage was isolated to view change from Time 1 to Time 2 to Time 3. A consolidated view of all
four stages using a box-and-whisker plot is also provided in Figure 11.
Inclusion
Pillai’s trace indicated that 29% of the variation was explained by the differences
between times, F (2, 20) = 4.11, p < .05. When plotting the Inclusion results over time, results
show an increase in the estimated marginal mean from Time 1 to Time 2 with a subsequent
decrease from Time 2 to Time 3 as reflected in both Table 11 and Figure 7. These findings
suggest that participants experienced changing levels of the Inclusion stage over time.
Table 11
Inclusion Marginal Means Over Time
Mean Std. Deviation N
Inclusion Time 1 3.55 .45 22
Inclusion Time 2 3.80 .53 22
Inclusion Time 3 3.37 .70 22

Figure 7
Change of Marginal Mean of Inclusion Over Time
Learning
Pillai’s trace indicated that 4% of the variation was explained by the differences between
times, F (2, 20) = 0.36, p = 0.7. Results also indicate non-significance of the Learning stage.
When plotting results over time, results show an increase in the estimated marginal mean from
Time 1 to Time 2 with a subsequent decrease from Time 2 to Time 3 as reflected in both Table
12 and Figure 8. These findings suggest that participants experienced changing levels of the
Learning stage over time. While not significant due to small sample size, these results parallel
those reported previously for Inclusion.

Table 12
Learning Marginal Means Over Time
Mean Std. Deviation N
Learning Time 1 4.08 .52 22
Learning Time 2 4.14 .64 22
Learning Time 3 4.01 .73 22
Figure 8
Change of Marginal Mean of Learning Over Time
Contributor
Pillai’s trace indicated that 24% of the variation was explained by the differences
between times, F (2, 20) = 0.24, p = 0.07. Results indicate borderline significance of the
Contributor stage. When plotting results over time, results show an increase in the estimated
marginal mean from Time 1 to Time 2 with a subsequent decrease from Time 2 to Time 3,

similar to both Inclusion and Learning, as reflected in both Table 13 and Figure 9. These findings
suggest that participants experienced changing levels of the Contributor stage over time.
Table 13
Contributor Marginal Means Over Time
Mean Std. Deviation N
Contributor Time 1 3.76 .68 22
Contributor Time 2 4.06 .67 22
Contributor Time 3 3.76 .92 22
Figure 9
Change of Marginal Mean of Contributor Over Time
Challenger
Pillai’s trace indicated that 1% of the variation was explained by the differences between
times, F (2, 20) = 0.08, p = 0.92. Results indicate non-significance of the Challenger stage. When

plotting results over time, results show an increase in the estimated marginal mean from Time 1
to Time 2 with a subsequent decrease from Time 2 to Time 3, similar to the other stages, as
reflected in both Table 14 and Figure 10. These findings suggest that participants experienced
changing levels of the Challenger stage over time.
Table 14
Challenger Marginal Means Over Time
Mean Std. Deviation N
Challenger Time 1 3.54 .59 22
Challenger Time 2 3.57 .64 22
Challenger Time 3 3.51 .66 22
Figure 10
Change of Marginal Mean of Challenger Over Time

Figure 11 below showcases the means and standard deviations of all four stages. Time 1
responses were more tightly coupled with standard deviations expanding over time with Time 3
resulting in the widest range of responses. Results show Learning continued to have higher
ratings in each stage followed by Contributor, Inclusion, and Challenger.
Figure 11
Change in Mean Psychological Safety Stage Over Time
The results of these findings contradict the theory that the four stages of psychological
safety are represented in a hierarchical and stepwise structure. Instead, each stage may rise and
fall at different rates over time and may overlap with common areas of other stages. A revised
conceptual model will be proposed in Chapter 5.

RQ3: Does Availability of Resources Correlate With Psychological Safety?
All three waves of surveys found a strong and positive relationship between resources and
psychological safety at the p = .05 level, apart from resources at time 2 with Challenger (r = .14).
Of note, time 1 measured the baseline of resources for each OC whereas times 2 and 3 measured
the change of those resources. Times 2 and 3 thus show that the changing of resource levels over
time also indicates a relationship with psychological safety stages. Tables 15 – 17 show these
observed probabilities and correlation strengths at each time.
Table 15
Resource Correlation with Psychological Safety Stages at Time 1
Inclusion Learning Contributor Challenger
Resources Time 1 Pearson Correlation .51* .58* .67* .66*
Observed Probability .00 .00 .00 .00
N 82 82 82 82
*p < 0.05 level, 2-tailed.
Table 16
Resource Correlation with Psychological Safety Stages at Time 2
Inclusion Learning Contributor Challenger
Resources Time 2 Pearson Correlation .52* .49* .59* .24
Observed Probability .00 .00 .00 .14
N 39 39 39 39
*p < 0.05 level, 2-tailed.

Table 17
Resource Correlation with Psychological Safety Stages at Time 3
Inclusion Learning Contributor Challenger
Resources Time 3 Pearson Correlation .43* .74* .68* .66*
Observed Probability .02 .00 .00 .00
N 30 30 30 30
*p < 0.05 level, 2-tailed.
Inter-resource variability existed with some variables proving stronger and others proving
non-significant. The resources with the highest correlations with psychological safety were
‘Sense of Accomplishment’, ‘Recognition’, and ‘Having an Understanding from Leaders’. The
resources with the lowest correlations were ‘Humor’, ‘Self-Discipline’ and ‘Knowing Who I
Am’.
Certain resources increased correlations when moving from Inclusion to Challenger while
others decreased. This likely suggests an increased/decreased importance to psychological safety
per resource as an individual progresses from Inclusion to Challenger. Additionally, some
resources maintained a consistent correlation across all stages, such as ‘Help With Tasks’,
suggesting an importance in each stage. See Tables 18 – 20 below for resource item-total
statistics for a breakdown at each time.

Table 18
Resource-Psychological Safety Stage Correlations at Time 1
Inclusion Learner Contributor Challenger
Feeling Successful Pearson Correlation .32* .42* .52* .46*
Observed Probability .00 .00 .00 .00
Adequate Sleep Pearson Correlation .24* .21 .15 .28*
Observed Probability .03 .06 .17 .01
Feeling Valuable Pearson Correlation .40* .46* .56* .52*
Observed Probability .00 .00 .00 .00
Sense Of Pride Pearson Correlation .40* .43* .54* .52*
Observed Probability .00 .00 .00 .00
Sense Of
Accomplishment
Pearson Correlation .43* .51* .62* .59*
Observed Probability .00 .00 .00 .00
Tools For Work Pearson Correlation .39* .49* .52* .53*
Observed Probability .00 .00 .00 .00
Hope Pearson Correlation .37* .49* .54* .58*
Observed Probability .00 .00 .00 .00
Stamina Pearson Correlation .33* .36* .33* .30*
Observed Probability .00 .00 .00 .01
Future Success Pearson Correlation .35* .46* .44* .43*
Observed Probability .00 .00 .00 .00
Challenging Routine Pearson Correlation .38* .38* .44* .45*
Observed Probability .00 .00 .00 .00
Health Pearson Correlation .34* .36* .39* .39*
Observed Probability .00 .00 .00 .00
Optimism Pearson Correlation .37* .40* .47* .46*
Observed Probability .00 .00 .00 .00
Status Pearson Correlation .35* .31* .39* .48*
Observed Probability .00 .00 .00 .00
Humor Pearson Correlation .18 .29* .33* .28*
Observed Probability .10 .01 .00 .01
Control Of Life Pearson Correlation .29* .29* .31* .38*
Observed Probability .01 .01 .00 .00
Leader Role Pearson Correlation .44* .47* .59* .66*
Observed Probability .00 .00 .00 .00
Communication Pearson Correlation .37* .34* .46* .53*

Inclusion Learner Contributor Challenger
Observed Probability .00 .00 .00 .00
Recognition Pearson Correlation .46* .54* .66* .66*
Observed Probability .00 .00 .00 .00
Organization Pearson Correlation .28* .40* .45* .42*
Observed Probability .01 .00 .00 .00
Commitment Pearson Correlation .32* .43* .44* .41*
Observed Probability .00 .00 .00 .00
Self-Discipline Pearson Correlation .20 .36* .35* .28*
Observed Probability .07 .00 .00 .01
Understanding From
Leaders
Pearson Correlation .42* .53* .61* .66*
Observed Probability .00 .00 .00 .00
Motivation Pearson Correlation .40* .51* .61* .47*
Observed Probability .00 .00 .00 .00
Support Pearson Correlation .49* .55* .64* .59*
Observed Probability .00 .00 .00 .00
Know Who I Am Pearson Correlation .21 .30* .43* .36*
Observed Probability .06 .01 .00 .00
Job Advancement Pearson Correlation .48* .47* .59* .56*
Observed Probability .00 .00 .00 .00
Companionship Pearson Correlation .52* .49* .52* .54*
Observed Probability .00 .00 .00 .00
Direction Pearson Correlation .29* .31* .44* .51*
Observed Probability .01 .00 .00 .00
Purpose Pearson Correlation .40* .44* .55* .47*
Observed Probability .00 .00 .00 .00
Positive Sense of
Self
Pearson Correlation .43* .45* .57* .46*
Observed Probability .00 .00 .00 .00
People To Learn
From
Pearson Correlation .41* .43* .48* .39*
Observed Probability .00 .00 .00 .00
Help With Tasks Pearson Correlation .60* .61* .62* .61*
Observed Probability .00 .00 .00 .00
*p < 0.05 level, 2-tailed.

Table 19
Resource-Psychological Safety Stage Correlations at Time 2
Inclusion Learner Contributor Challenger
Feeling Successful Pearson Correlation .61* .52* .63* .16
Observed Probability .00 .00 .00 .33
Adequate Sleep Pearson Correlation .16 .31 .25 .25
Observed Probability .32 .06 .13 .13
Feeling Valuable Pearson Correlation .53* .50* .56* .45*
Observed Probability .00 .00 .00 .00
Sense Of Pride Pearson Correlation .56* .46* .53* .08
Observed Probability .00 .00 .00 .63
Sense Of
Accomplishment
Pearson Correlation .44* .35* .58* .28
Observed Probability .00 .03 .00 .09
Tools For Work Pearson Correlation .08 .31 .29 .05
Observed Probability .64 .05 .07 .78
Hope Pearson Correlation .33* .31 .39* .04
Observed Probability .04 .05 .01 .83
Stamina Pearson Correlation .33* .21 .24 .08
Observed Probability .04 .19 .15 .63
Future Success Pearson Correlation .36* .38* .51* .09
Observed Probability .03 .02 .00 .57
Challenging Routine Pearson Correlation .39* .42* .49* .16
Observed Probability .01 .01 .00 .33
Health Pearson Correlation .01 -.01 .10 -.10
Observed Probability .94 .95 .53 .53
Optimism Pearson Correlation .27 .27 .40* .25
Observed Probability .10 .09 .01 .12
Status Pearson Correlation .41* .19 .18 .02
Observed Probability .01 .24 .27 .93
Humor Pearson Correlation .36* .36* .32 .16
Observed Probability .03 .02 .05 .32
Control Of Life Pearson Correlation .35* .13 .26 .18
Observed Probability .03 .44 .10 .27
Leader Role Pearson Correlation .42* .49* .51* .14
Observed Probability .01 .00 .00 .40
Communication Pearson Correlation .45* .52* .64* .34*

Inclusion Learner Contributor Challenger
Observed Probability .00 .00 .00 .04
Recognition Pearson Correlation .43* .46* .48* .47*
Observed Probability .01 .00 .00 .00
Organization Pearson Correlation .54* .39* .51* .22
Observed Probability .00 .02 .00 .17
Commitment Pearson Correlation .38* .39* .44* .23
Observed Probability .02 .02 .01 .16
Self-Discipline Pearson Correlation .50* .40* .52* .09
Observed Probability .00 .01 .00 .59
Understanding From
Leaders
Pearson Correlation .06 .16 .24 .07
Observed Probability .72 .32 .14 .68
Motivation Pearson Correlation .40* .28 .43* .22
Observed Probability .01 .08 .01 .18
Support Pearson Correlation .48* .59* .62* .42*
Observed Probability .00 .00 .00 .01
Know Who I Am Pearson Correlation .36* .31 .48* .28
Observed Probability .03 .05 .00 .08
Job Advancement Pearson Correlation .16 .29 .33* .30
Observed Probability .32 .08 .04 .06
Companionship Pearson Correlation .46* .37* .34* .19
Observed Probability .00 .02 .03 .24
Direction Pearson Correlation .29 .23 .30 .08
Observed Probability .08 .17 .06 .62
Purpose Pearson Correlation .39* .41* .41* .12
Observed Probability .01 .01 .01 .46
Positive Sense Of
Self
Pearson Correlation .49* .44* .52* .09
Observed Probability .00 .00 .00 .59
People To Learn
From
Pearson Correlation .45* .47* .52* .17
Observed Probability .00 .00 .00 .30
Help With Tasks Pearson Correlation .51* .51* .57* .11
Observed Probability .00 .00 .00 .50
*p < 0.05 level, 2-tailed.

Table 20
Resource-Psychological Safety Stage Correlations at Time 3
Inclusion Learner Contributor Challenger
Feeling Successful Pearson Correlation .37* .65* .52* .46*
Observed Probability .04 .00 .00 .01
Adequate Sleep Pearson Correlation .30 .57* .52* .42*
Observed Probability .10 .00 .00 .02
Feeling Valuable Pearson Correlation .38* .62* .57* .53*
Observed Probability .04 .00 .00 .00
Sense Of Pride Pearson Correlation .47* .62* .57* .47*
Observed Probability .01 .00 .00 .01
Sense Of
Accomplishment
Pearson Correlation .46* .59* .57* .50*
Observed Probability .01 .00 .00 .01
Tools For Work Pearson Correlation .50* .55* .53* .54*
Observed Probability .00 .00 .00 .00
Hope Pearson Correlation .30 .63* .57* .55*
Observed Probability .10 .00 .00 .00
Stamina Pearson Correlation -.14 .17 .07 .17
Observed Probability .45 .36 .70 .37
Future Success Pearson Correlation .10 .41* .29 .23
Observed Probability .59 .03 .12 .22
Challenging Routine Pearson Correlation .22 .54* .54* .64*
Observed Probability .24 .00 .00 .00
Health Pearson Correlation .08 .49* .42* .50*
Observed Probability .69 .01 .02 .00
Optimism Pearson Correlation .27 .43* .47* .39*
Observed Probability .16 .02 .01 .03
Status Pearson Correlation .37* .57* .51* .46*
Observed Probability .04 .00 .00 .01
Humor Pearson Correlation .21 .51* .46* .48*
Observed Probability .26 .00 .01 .01
Control Of Life Pearson Correlation .36 .39* .35 .35
Observed Probability .05 .03 .06 .06
Leader Role Pearson Correlation .48* .58* .62* .63*
Observed Probability .01 .00 .00 .00
Communication Pearson Correlation .41* .45* .36 .25

Inclusion Learner Contributor Challenger
Observed Probability .03 .01 .05 .19
Recognition Pearson Correlation .59* .67* .55* .51*
Observed Probability .00 .00 .00 .00
Organization Pearson Correlation .26 .59* .56* .55*
Observed Probability .17 .00 .00 .00
Commitment Pearson Correlation .19 .38* .40* .43*
Observed Probability .32 .04 .03 .02
Self-Discipline Pearson Correlation .06 .45* .36 .30
Observed Probability .76 .01 .05 .11
Understanding From
Leaders
Pearson Correlation .60* .62* .69* .68*
Observed Probability .00 .00 .00 .00
Motivation Pearson Correlation .08 .44* .38* .41*
Observed Probability .67 .01 .04 .03
Support Pearson Correlation .58* .60* .65* .68*
Observed Probability .00 .00 .00 .00
Know Who I Am Pearson Correlation .17 .40* .35 .38*
Observed Probability .36 .03 .06 .04
Job Advancement Pearson Correlation .11 .64* .52* .57*
Observed Probability .57 .00 .00 .00
Companionship Pearson Correlation .45* .60* .61* .58*
Observed Probability .01 .00 .00 .00
Direction Pearson Correlation .23 .50* .54* .53*
Observed Probability .23 .00 .00 .00
Purpose Pearson Correlation .24 .47* .41* .39*
Observed Probability .20 .01 .02 .03
Positive Sense Of Self Pearson Correlation .38* .65* .55* .56*
Observed Probability .04 .00 .00 .00
People To Learn From Pearson Correlation .30 .48* .27 .28
Observed Probability .10 .01 .15 .14
Help With Tasks Pearson Correlation .42* .67* .64* .58*
Observed Probability .02 .00 .00 .00
*p < 0.05 level, 2-tailed.

Summary
The findings above showcase the results specific to the three research questions of this
study. The first research question ‘Do changes in stages of psychological safety relate to
performance?’ was found to be statistically non-significant for each wave of surveys. However,
findings from this question validate the reliability of the survey instrument developed to measure
stages of psychological safety by Zhang et al. (2022). The second research question ‘Do stages
of psychological safety change over time?’ was significant with evidence to support a non-linear
trajectory. In this study, from Time 1 to Time 2 the average score of each stage increased
whereas from Time 2 to Time 3 that average score of each stage decreased. The third research
‘Does availability of resources correlate with psychological safety?’ was significant and
directionally correlated. However, within resource variability existed with some resources with
statistical non-significance.

CHAPTER FIVE: RECOMMENDATIONS
In Clark’s (2020) recent work, psychological safety was purported to have four different
levels: inclusion, learning, contributor, and challenger safety. The present study attempted to
analyze whether these stages have a relationship with Officer Candidate’s (OC) performance at
Army Officer Candidate School (OCS). Additionally, the present study examined if and how
psychological safety ratings change over time in this 12-week course and if an individual’s
perceptions of resources correlate with psychological safety. This chapter will summarize the
findings and provide evidence-based and evidence-tested recommendations for practice.
Discussion of Findings
The longitudinal survey completed by OCs revealed that psychological safety, as
measured through Zhang et al.’s (2022) survey instrument, was not significantly related to
individual performance at OCS. These results differ from the main body of literature that has
found that psychological safety to be directly related to performance (Edmonson & Bransby,
2023). Performance was evaluated in four categories: academic, leadership, physical and
technical skills. These metrics were individual metrics and not measures of team performance
that may have influenced the type of significance and correlation between psychological safety
and type of performance.
The body of literature on the relationship between individual performance and
psychological safety has focused on individuals in teams with no specific termination point
(Edmondson & Bransby, 2023). Additionally, performance has been reported to terms such as
creativity (Kessel et al., 2012), innovation (Lee et al., 2011) or firm performance (Baer & Frese,
2003) with little or no explanation as to those specific metrics or goals. The gap in the literature
may present inconsistencies in reporting illuminated by this study. For example, the performance

of OCs was related to individual performance that had no significance to psychological safety.
However, individual performance in other studies may directly relate to metrics where
psychological safety is necessary, such as creating new ideas for increased sales or decreasing
errors in medical teams for patient safety (Edmondson, 1999). Thus, the differences in how
teams and researchers attempt to correlate performance and psychological safety may directly
influence the findings before the study begins. For Army OCS, psychological safety was not
significantly related to performance. Staff should thus identify alternatives to increase
performance.
The second finding of this study added to the body of literature on how psychological
safety changes over time. Longitudinal data collected revealed a non-linear timeline of
psychological safety over time, which matched existing literature (Cole et al., 2022; Koopmann
et al., 2016). Psychological safety ratings went up from Time 1 to Time 2 but had a subsequent
drop at Time 3. Time 3 also had the largest standard deviation in psychological safety suggesting
that individual differences were larger at this time than at Time 1 or Time 2.
The concave shape of the longitudinal results contrasted Koopmann et al.’s (2016)
findings while mirroring Cole et al.’s (2022). Of note, Cole et al.’s (2022) study focused on
temporary teams of students in a university semester group project. Koopmann et al.’s (2016)
research focused instead on longer tenured teams, whose findings were based on yearly data. The
differences in findings, in addition to this study’s non-linear results, suggest that project and
time-based teams may result in lower or varying rates of psychological safety as teams aim to
deliver final deliverables (Cole et al., 2022). Meanwhile, teams with no natural stopping points
may dictate the need for increased psychological safety as a requirement for team building
(Koopmann et al. 2016).

Finally, survey data from the present study showed both a significant and directional
relationship between most resources, resource change and psychological safety. Results at Time
1 suggested that the baseline level of resources revealed a higher baseline of psychological
safety. Psychological safety may then be dependent on individual resources. These findings
parallel other evidence indicating individual differences influence psychological safety
(Edmondson & Mogelof, 2006). Thus, to delve more deeply into an individual’s formation of
psychological safety, leaders may need to identify the perceived level of resources that individual
reports.
Time 2 and Time 3 studied whether resource changes reflected psychological safety
levels. Results found a significant and positive relationship between resource change and
psychological safety. This suggests that as the perceived reservoir of resources are increased or
decreased that psychological safety follows. Leaders should note that the perceived level of
resources is likely context and environmentally driven where OCS may provide or eliminate
specific resources, such as sleep, that other organizations may not. These findings suggest that
organizations and leaders identify resource baselines and subsequent changes to find
environmentally specific information. ‘
Recommendations for Practice
The main findings of this study revealed the need for practitioners and leaders to 1)
identify if psychological safety is necessary for performance goals; 2) track psychological safety
over time; 3) target individual interventions; and 4) promote leadership development to build
psychological safety when necessary. A revision of Zhang et al.’s (2022) survey instrument is
recommended given the increased validity through the removal of negatively worded questions.

Lastly, a reconceptualization of Clark’s four stages of psychological safety is also necessary
given the discrepant findings against the original stepwise construct.
Recommendation 1: Temporal Tracking of Psychological Safety and Resources
Longitudinal studies have shown that psychological safety is a dynamic construct that
requires time to manifest (Blawath et al., 2012). Jamal et al. (2022) purport that one must assess
the status quo to build a safety culture. Cole et al. (2022) discussed a similar concept where to
effectively gauge psychological safety one must identify when it first exists. Longitudinal
research has shown that teams can develop or degrade their psychological safety over time
(Koopmann et al., 2016). Analyses that study psychological safety at only a single moment in
time may skew representations of safety ratings (Cole et al., 2022). Instead, psychological safety
must be maintained, studied and nurtured consistently over time for growth (Jamal et al., 2022).
In one longitudinal study, Koopmann et al. (2016) found that psychological safety had a
convex curvilinear relationship with team tenure. Their research found an initial drop in safety
ratings and a subsequent increase over time from team inception (Koopmann et al., 2016). Their
research also found that individual teams exhibited different starting points in how much initial
psychological safety the teams possessed (Koopmann et al., 2016). Cole et al. (2022) found that
psychological safety decreased over time in a study of engineering students during a semesterlong project. Cole et al.’s (2022) finding is consistent with other literature finding that temporary
teams experience similar drops (Denison et al., 1996; Levesque et al., 2001).
These dynamic trajectories of psychological safety show that while “the “what” and the
“who” are indeed critical to team functioning, a failure to understand the “when” can jeopardize
final team outcomes” (Mohammed et al., 2010, p. 905). Thus, teams need to first establish a
baseline and subsequently determine when teams need interventions (Cole et al., 2022). An

additional element of examining and tracking resource baseline and changes may also increase
insights to psychological safety changes. The combination of studies listed above with this
study’s findings supports that teams start, progress, and end at different psychological safety
levels (O’Leary, 2016).
Working in a healthy and psychologically safe environment has been repeatedly reported
as vital to a positive employee experience (Huddleston & Gray, 2016). However, the passage of
time alone cannot build psychological safety in and of itself (Lyman et al., 2020). The logic
model shown in Figure 2 below provides inputs, activities, outputs, and outcomes to build
psychological safety based on continuous activities of building and measuring psychological
safety and resources in teams.

Figure 12
Temporal Tracking of Psychological Safety Logic Model
Note. Logic model created from research on benefits of team psychological safety.
Recommendation 2: Targeted Individual Interventions
A one-size-fits-all approach to psychological safety interventions may not be effective for
diverse teams with individuals of varying backgrounds and barriers to psychological safety
(Spain et al., 2012). Targeted individual interventions focus on decreasing those individual
barriers (Hunt et al., 2021). These training activities have been shown to improve individual and
team performance (Aguinis & Kraiger, 2009). Training activities include a personalized
knowledge program (Clark & Estes, 2008), increasing and improving feedback (Edmondson &
Woolley, 2003), suppressing punishments (Edmondson, 1999), and an emphasis on followthrough (Dusenberry & Robinson, 2020).

As knowledge and skills increase, confidence and psychological safety correspond with
similar increases (Wawersik et al., 2022). To build both knowledge and confidence, researchinformed and targeted individual interventions will be based on the Knowledge, Motivation, and
Organization (KMO) framework from Clark and Estes (2008) and validated using the New
World Kirkpatrick Model of Evaluation (Kirkpatrick, 2015). The KMO framework states that
performance gaps are caused by knowledge, motivation, or organizational barriers (Clark &
Estes, 2008).
A needs assessment should be first conducted to identify gaps in knowledge (Aguinis &
Kraiger, 2009). For skill enhancement, four types of knowledge impact an individual:
information, self-help, training, and conceptual/theoretical (Clark & Estes, 2008). Familiar tasks
do not typically require assistance in applying that knowledge (Clark & Estes, 2008). Self-help
tasks are routine that can be in checklist form on how to execute (Clark & Estes, 2008). Training
is dictated when individuals require ‘how to’ including both guided practice and corrective
feedback (Clark & Estes, 2008). Lastly, conceptual and theoretical knowledge dictates an
educational approach for individuals to handle novel and unexpected challenges (Clark & Estes,
2008).
The Kirkpatrick Model of Evaluation can be used to assess, test, and analyze results of
training and outcomes (Kirkpatrick, 2015). Kirkpatrick’s model encompasses four levels of
learning: reaction (level 1), learning (level 2), behavior (level 3), and results (level 4)
(Kirkpatrick, 2015). The model provides leaders with measurable and identifiable outcomes and
to create both tangible and intangible training benefits (Yardley & Dornan, 2012). The original
Kirkpatrick model substantiated that organizations and individuals progress from level 1 to level
4 in a linear fashion (Kirkpatrick, 2015). However, the new Kirkpatrick model has evolved to

start at level 4 (results) to focus on end outcomes and create training and evaluation to achieve
those objectives (Kirkpatrick & Kirkpatrick, 2016). An example evaluation guide can be found
in Appendix A.
The second area of focus is to provide frequent feedback. Feedback can be provided to
dispel anxiety and reduce negative perceptions that degrade psychological safety (Edmondson &
Woolley, 2003). Providing specific goals, expectations, and predictability in this feedback will
encourage communication and increase psychological safety (Devaraj et al., 2021; Edmondson
& Woolley, 2003; Epstein & Krasner, 2013).
Third, suppressing punishments for error or voicing feedback is a major driver of
psychological safety research (Edmondson, 1999). Error is often viewed as incompetence,
leading some to deny, hide, or seek to cover up mistakes (Edmonson, 1996). However, evidence
shows that failure can lead to more salient learning and increased skill (Carmeli & Sheaffer,
2008; Carmeli et al., 2012; Young et al., 2016). This focus should also include resource specific
interventions, such as increasing recognition or understanding from leaders as needed. As
individuals create mistakes, the responses from peers and leaders result in emotional
conditioning through reinforcement (Schein, 1993).
Just as with Pavlov’s dog, individual behavior corresponds to the response to an event
and expects that same response in the future (Schein, 1993). This phenomenon corresponds to
different activity within the brain, as neurons can differentiate and respond differently to
different types of rewards and punishments (Yang et al., 2023). To create environments
conducive to failure-based learning behaviors, leaders need to suppress punishments, encourage
learning from mistakes, and model open discussion (Carmeli, 2007; Schein, 1993; Tucker &

Edmondson, 2003). By doing so, leaders reduce the flight or fight response and facilitate
restoration to encourage these learning events (Kirby et al., 2017).
The last focus of targeted individual interventions is voice fatigue. Martens et al. (2020)
shows that individuals desire involvement and to have their voices heard. If individuals perceive
non-resolution of feedback those individuals become passive and reluctant to participate (Carey,
2013). Therefore, specific time should be allocated to following through on feedback provided
by peers or subordinates. The logic model shown in Figure 3 below provides these inputs,
activities, outputs, and outcomes.
Figure 13
Targeted Individual Training Interventions Logic Model
Note. Logic model created from research on benefits of individual psychological safety.

Recommendation 3: Targeted Leadership Development
Leadership style has a significant effect on psychological safety (Shahid & Din, 2021).
Of the list of leadership styles, supportive and inclusive are most cited in increases in
psychological safety (De Smet et al., 2021; O’Donovan & McAuliffe, 2020). Supportive and
inclusive leadership styles are often associated with accessibility, listening, facilitation of
questions, and encouragement – all necessary components to cultivate psychological safety
(Brown & McCormack, 2016; Edmondson, 2012). Showing that a leader cares can create higher
psychological safety rates (Javed et al., 2019; Simpkin et al., 2019).
Targeted leadership development should be built into leaders’ everyday work, created
with immersive and engaging prompts, and deployed at scale (De Smet et al., 2021). Human
behavior can be sticky and is created through a lifelong process (Bronfenbrenner, 1979). To
change human behavior requires a clear strategy of leadership development tied to daily nudges
or learning tools to move from working memory to retention (De Smet et al., 2021). These
nudges are vital as each team’s psychological safety begins and progresses differently (Rider et
al., 2023). Immersive and engaging prompts will encourage long-lasting memory as leaders may
need to shift assumptions and emotions for sustained development (De Smet et al., 2021).
To create psychological safety, teams must first create a positive environment conducive
to supportive behaviors (De Smet et al., 2021). Two proven ways to do this are through humor
and games (Bolman & Deal, 2021; Helbig & Norman, 2023; Mukerjee & Metiu, 2022; Parker &
du Plooy, 2021; Potipiroon & Ford, 2021). A study of search and rescue teams found that high
performing teams often over-communicated and used humor, empathy, and praise whereas low
performing teams were more defensive (Fischer et al., 2007). Evidence has been found that

humor reduces tension, encourages creativity, increases psychological safety, and promotes
increased engagement (Bolman & Deal, 2021; Potipiroon & Ford, 2021).
Similar positive responses to humor are also found in games (Parker & du Plooy, 2021).
Osborn (1953) showed that games are a powerful way to increase collaboration and teamwork.
Later work correlated voluntary, non-task related games to create and foster psychological safety
(Mukerjee & Metiu, 2022). These activities increase both vulnerability and comradeship that are
crucial in the development of an effective work environment (Edmondson & Mogelof, 2006).
Engaging in these non-work and non-task related games can further create both teamwork and
psychological safety (Bolman & Deal, 2021; Potipiroon & Ford, 2021).
Conflict. Any team is susceptible to conflict (De Dreu & Weingart, 2003). Conflict
literature has narrowed types of conflict into either relationship or task issues (De Dreu &
Weingart, 2003). Both types typically evolve episodically with the stages of latency, feeling,
perception, manifestation, and aftermath (Pondy, 1967; Thomas, 1992). In a survey of over 5,000
employees in nine countries, researchers found that 85% of employees deal with conflict at work,
29% deal with it frequently or continuously, and the average worker spends 2.8 hours managing
conflict (Overton & Lowry, 2013). Through training, group skills in managing conflict rose by
10% (Overton & Lowry, 2013). Leaders must be skilled in managing conflict, including being
able to identify when conflict is relational or task driven (De Dreu & Weingart, 2003).
Task conflicts center on problem solving and differing points of view, while relationship
conflicts harm the psychological nature of teams (Edmondson & Bransby, 2023). The most
common responses to managing conflict are avoiding, accommodating, competing,
compromising, and collaborating (Overton & Lowry, 2013). However, avoidance most often
worsens a situation rather than improving it (Wang & Wu, 2020). Wang and Wu (2020) posited

that conflict is almost always preventable and summarized effective conflict management into
the four categories shown in Figure 4.
Figure 14
Conflict Management Model
Note. Reprinted from “A Systematic Approach to Effective Conflict Management for Program,”
by N. Wang and G. Wu, 2020, SAGE Open, 10(1), p. 12. Copyright 2020 by the Authors.
In addition to conflict management, peer coaching has been shown to be an effective tool
for learning and psychological safety development (Caporale-Berkowitz & Friedman, 2018). A
study of 150 military Admirals and Generals found that peer coaching developed both openness,
vulnerability, and trust (Cavallaro & Johnson, 2023). Peer coaching involves education through

reciprocal feedback and communication (Bialek & Hagen, 2022). These exercises have been
shown to increase job satisfaction that also extends to increases in psychological safety
(Itzchakov et al., 2023). The logic model shown in Figure 5 below provides these inputs,
activities, outputs, and outcomes.
Figure 15
Targeted Leadership Training Logic Model
Note. Logic model created from research on the benefits of leadership on psychological safety.
Recommendation 4: Survey Scale Revision
Negatively worded survey questions have been used for decades to combat acquiescence
bias (Chyung et al., 2018). Acquiescence bias is the belief that respondents will have the
tendency to agree with each question, regardless of the content (Roszkowski & Soven, 2010).
Rensis Likert was one of the first to suggest that half of the survey items be negatively worded

aimed at increasing respondents’ attention to their answers (Likert, 1932). However, there is no
consensus of this strategy in practice with many researchers arguing it mostly confuses
respondents (Johnson et al., 2011), introduces error (Colosi, 2005) and threatens instrument
validity and reliability (Chyung et al., 2018).
Evidence of negatively worded questions yields conflicting results (Roszkowski &
Soven, 2010). For example, Bergstrom and Lunz (1998) found no statistical difference in a
mixed survey question strategy. However, results that do show reduced validity through the
mixed strategy suggest that much of the bias can instead be contributed to respondent
carelessness (Roszkowski & Soven, 2010), survey fatigue (Robinson & Leonard, 2019), or
individual differences in response styles such as neuroticism and avoidance motivation (Lindwall
et al., 2012). Drolet and Morrison (2001) purported that respondents often answer the first
question and then answer subsequent questions assuming the same directionality of response.
Kamoen et al. (2011) took their research further and examined eye movement and response time
to answer mixed questionnaires. Their results showed no difference in time to read a question,
but negatively worded questions resulted in higher reread times suggesting respondents difficulty
mapping their opinion to a response (Kamoen et al., 2011). Given the lack of consensus and
conflicting strategies, it is suggested to keep Zhang et al.’s (2022) instrument with all positively
worded questions while focusing on when and whom to distribute it to reduce carelessness.
Zhang et al.’s (2022) survey instrument to measure psychological safety stages is divided
into five dimensions: Inclusion, Supportive Learning, Contributor, Challenger, and Behaviors
Safety. The present study used only the first four to align with Clark’s (2020) Four Stages of
Psychological Safety (excluding Behaviors). A revised instrument that is likely to increase
reliability is provided below. Four sections are maintained to measure responses across Clark’s

(2020) Four Stages. It is recommended that this new instrument be used in future research to
validate and continue to refine its application.
1. Inclusion Safety (8):
a. I feel valued, belonged and included as part of the team.
b. I feel appreciated and listened to at work in the team.
c. It is safe to take risks in my team at work.
d. It is safety to make mistakes that won’t be held again me.
e. No one would deliberately act in a way that undermines my effort.
f. People are not rejected for being different.
g. I feel safe to ask others for help.
2. Learning Safety (6):
a. If I have a problem, I can depend on my team leader to be my advocate.
b. People in my team value new ideas.
c. People in my team encourage continuation of learning, development and growth.
d. People in my team do not resist untried approaches.
e. My team encourages and supports me to take on new tasks or to learn how to do
things that have not been done before.
f. People in my team are eager to share information about what does and/or does not
work.
3. Contributor Safety (5):
a. My unique skills and talents are valued and utilized.
b. It is easy to speak up about what is in my mind regarding new
ideas/recommendations/suggestions.

c. I am able to bring up problems and tough issues freely.
d. My team values new ideas and are interested in better ways of doing things.
e. My team is open to alternative ideas or suggestions.
4. Challenger Safety (5):
a. I am comfortable speaking up (e.g. disagreements, personal issues, varying point
of views etc.).
b. I am comfortable to suggest new ideas to change certain things or ways of
working.
c. I am comfortable expressing my opinion directly with the team.
d. Differences in opinions are welcome.
e. People are open to alternative ways of getting work done.
Recommendation 5: Reconceptualization of Psychological Safety Stages
Inter-scale correlation results of Zhang et al.’s (2022) survey instrument revealed close
relationships between stages of psychological safety. The higher the correlation the more stages
are suggested to share similarities. For example, the highest correlation (p = .78) was observed
between Learner and Contributor. Even the lowest correlate scores (p = .57) and (p = .59)
between Contributor and Inclusion and Challenger and Inclusion suggest some overlap. Thus, the
stepwise conceptual model of the Four Stages of Psychological Safety (Clark, 2020) should be
revised to reflect these results.
A revised model of the Four Stages of Psychological Safety is provided below. Each of
the four stages has at least some correlation with the other with those relationships stronger
between pairing stages. For example, Contributor and Learner and Contributor and Challenger
exhibited the correlations (p = .78, p = .77) whereas the further separated the stage the lower the

correlation. These findings suggest more of an onion style or layered model where Inclusion is
the starting point for psychological safety. Then, as individuals express higher psychological
safety, they move into Learner, Contributor and Challenger stages. As the results above explain,
individuals will likely also move between stages over time. Thus, leaders and practitioners must
be cognizant and aware of where their team’s psychological safety and level of resources are if
they wish to increase those.
Figure 16
Revised Psychological Safety Stages Conceptual Model
Limitations and Delimitations
The main limitation to this study was the limited sample size in addition to the drop-off
from Time 1 to Time 4. Time 1 began with 82 valid responses which decreased over each wave

as Time 2 had 39, Time 3 had 30 and Time 4 had 10. Thus, the most valid data to represent and
answer this study’s questions lay at Time 1. While significant statistical correlation was still
found at Times 2 and 3, future studies should aim at increasing those responses for validity.
A second limitation of this study was the variance of survey instruments from the widely
used survey built by Edmondson (1999). The main body of literature on psychological safety has
used Edmondson’s (1999) seven-question scale to measure the construct whereas this study used
Zhang et al.’s (2022) instrument that only been used in Zhang et al.’s (2022) study. While the
survey instrument was found to have inter-scale reliability, as discussed above, additional
research should be done to continue to validate or revise for accuracy.
A third limitation of this study was around the characteristics and demographics of the
sample. This study examined Army OCS candidates during their 12-week journey to become
Army Officers. The school is demanding and challenging where the completion of a survey
during their course may have resulted in some responses to be skewed. Additionally, this class
was representative of only the OCs in this particle cohort due to time constraints whereas
additional studies should be done to increase external validity.
Data collection was also a limitation of this study, in instrumentation but also clarity on
tasks completed during OCS. Just one study (Zhang et al., 2022) has been developed and studied
as a measurement tool for Clark’s (2020) four stages of psychological safety. This introduces
potential variability in results as other researchers have not further validated this survey. The
lack of an agreed upon measurement of the Conservation of Resources (COR) also adds to the
survey limitations. A limited scope of the COR was chosen in alignment with other researchers
to focus the survey on the specific research questions and setting.

Recommendations for Future Research
Future research should focus on refining which performance metrics are correlated to
psychological safety and additional examination of the validity of the four-stage psychological
safety survey instrument. Leaders will then be able to identify both when and how to increase
psychological safety by defining which specific performance goals can be aided through it.
Leaders will then be able to build performance goals that do correlate with psychological safety
if their teams and organization desire a culture of openness, error tolerance, and inclusion.
Additionally, leaders will be able to use the four-stage survey to elicit more detailed information
if additional research is done to either confirm its validity or to present changes to increase it.
Conclusion
Psychological safety is a prominent and well-studied concept (Edmondson & Bransby,
2023). Numerous studies have shown its impact on financial success (Baer & Frese, 2003), job
satisfaction (Moin et al., 2021) and employee withdrawal (Kahn, 1990). The body of literature on
psychological safety has shown both its moderating and mediating powers in influencing
different variables such as creativity, job satisfaction, and performance. Clark’s (2020) Four
Stages of Psychological Safety concept and the Conservation of Resource theory were the main
topics and constructs behind the present research. The present study examined whether a
relationship between psychological safety stages and performance at OCS existed, how
psychological safety changed over time, and whether resources were related to levels of
psychological safety.
This study provided evidence that leaders must properly examine their team and
individual goals to ensure fit if improvements or increases in psychological safety are needed.
Results of the present study found that, based on stated performance metrics, psychological

safety is not significantly correlated at Army OCS. Staff can instead refocus their efforts on
interventions that address the need for performance. Additionally, this study found the
interrelationships between the Inclusion, Learning, Contributor, and Challenger stages to
showcase the need to track psychological safety over time but also recognize resources and the
different stages of psychological safety of those individuals. Only then can targeted interventions
be deployed for maximum effectiveness.

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APPENDICES
Appendix A: Supplemental Tables
Table 21
Mean and Standard Deviation of Time 2 Stages of Psychological Safety
Mean Std. Deviation N
Inclusion 3.73 .56 39
Learning 4.08 .58 39
Contributor 3.99 .69 39
Challenger 3.62 .67 39
Table 22
Intra-Scale Correlation and Reliability at Time 2
Inclusion
Time 2
Learning
Time 2
Contributor
Time 2
Challenger
Time 2
Inclusion Pearson Correlation --
N 39
Learning Pearson Correlation .61* --
Observed Probability .00
N 39 39
Contributor Pearson Correlation .60* .82* --
Observed Probability .00 .00
N 39 39 39
Challenger Pearson Correlation .24 .44* .53* --
Observed Probability .13 .00 .0
N 39 39 39 39
*p < 0.05 level, 2-tailed.

Table 23
Mean and Standard Deviation of Time 3 Stages of Psychological Safety
Mean Std. Deviation N
Inclusion 3.38 .64 30
Learning 4.04 .72 30
Contributor 3.75 .89 30
Challenger 3.45 .71 30
Table 24
Intra-Scale Correlation and Reliability at Time 3
Inclusion
Time 3
Learning
Time 3
Contributor
Time 3
Challenger
Time 3
Inclusion Pearson Correlation --
N 30
Learning Pearson Correlation .63* --
Observed Probability .00
N 30 30
Contributor Pearson Correlation .72* .89* --
Observed Probability .00 .00
N 30 30 30
Challenger Pearson Correlation .59* .78* .90* --
Observed Probability .00 .00 .00
N 30 30 30 30
*p < 0.05 level, 2-tailed.

Table 25
Demographics
Demographic Characteristic Percentage (%) n
Gender
Male 62 68
Female 13 28
Not reporting gender 25 27
Race/Ethnicity
White 46 51
Other 11 12
Asian 9 10
Black or African American 6 6
Native Hawaiian or Pacific Islander 2 2
Prefer Not to Say 2 2
Not reporting 25 27
Educational Background
Undergraduate degrees 57 63
Prior Service Status
Prior service 20 22
Not prior service 56 61
Not reporting 25 27
Years of Service (if Prior Service)
1 year - -
2 years - -
3 years - -
4 years 4 4
5 years - -
6 years 4 4
7 years 4 4
8+ years - -
Rank (if Prior Service)
E-4 4 4

Demographic Characteristic Percentage (%) n
E-5 8 9
E-6 - -
E-7 4 4
Appendix B: Survey Instrument for First Response
Demographic Information
1. What is your first name?
2. What is your last name?
3. What is your age?
4. What is your gender?
a. Male
b. Female
c. Other
5. What ethnicity do you identify as?
a. White / Caucasian
b. Black / African-American
c. Hispanic / Latino
d. Asian / Pacific Islander
e. Multiracial
f. Other
6. What is your highest level of education attained?
7. Were you prior military?
8. [If yes from #7] How many years of previous military service do you have?
9. [If yes from #7] What was your rank before OCS?

Please rate on a scale of 1-5 (Strongly Disagree, Disagree, Undecided, Agree, Strongly Agree)
1. I feel valued, belonged, and included as part of the team.
2. I feel appreciated and listened to at work in the team.
3. It is safe to take risk in my team at work.
4. If you make a mistake in the department, it is often held against you.
5. No one would deliberately act in a way that undermines my effort.
6. People sometimes reject others for being different.
7. I have difficulty asking others for help in the department.
8. We often work as a team to find the systemic cause when something goes wrong.
9. If I have a problem, I could depend on my team leader to be my advocate.
10. People in your team value new ideas.
11. People in my team encourage continuation of learning, developing and growing.
12. People in my team resist untried approaches.
13. The team encourages and supports me to take on new tasks or to learn how to do
things that have never been done before.
14. People in my team are eager to share information about what does and/or does not
work.
15. Working with the members of the team, my unique skills and talents are valued and
utilized.
16. It is easy to speak up about what is in my mind regarding new
ideas/recommendations/ or suggestions.
17. People are able to bring up problems and tough issues freely.
18. People value new ideas and are interested in better ways of doing things.

19. Unless an idea has been around for a long time no one in this team wants to hear it.
20. I am very comfortable in speaking up (e.g. disagreements, personal issues, varying
point of views etc.)
21. I feel very comfortable to suggest new ideas to change certain things or ways of
working.
22. I prefer expressing my opinion privately or off-line rather than addressing them
directly with the group.
23. Differences in opinions are welcome.
24. People are open to alternative ways of getting work done.
Please indicate how much of the following resources you feel you have on a scale of 1-5 (None,
Low, Moderate, High, Very High):
1. Feeling that I am successful
2. Time for adequate sleep
3. Feeling valuable to others
4. Free time
5. Sense of pride in myself
6. Feeling that I am accomplishing my goals
7. Necessary tools for work
8. Hope
9. Stamina/endurance
10. Feeling that my future success depends on me
11. Positively challenging routine
12. Personal health

13. Sense of optimism
14. Status/seniority at work
15. Sense of humor
16. Feeling that I have control over my life
17. Role as a leader
18. Ability to communicate well
19. Feeling that my life is peaceful
20. Acknowledgement of my accomplishments
21. Ability to organize tasks
22. Sense of commitment
23. Self-discipline
24. Understanding from my employer/boss
25. Motivation to get things done
26. Support from co-workers
27. Feeling that I know who I am
28. Advancement in education or job training
29. Feeling independent
30. Companionship
31. Knowing where I am going with my life
32. Affection from others
33. Feeling that my life has meaning/purpose
34. Positive feelings about myself
35. People I can learn from

36. Help with tasks at work

Appendix C: Post-Initial Survey Instrument
Demographic Information
1. What is your first name?
2. What is your last name?
Please rate on a scale of 1-5 (Strongly Disagree, Disagree, Undecided, Agree, Strongly Agree)
1. I feel valued, belonged, and included as part of the team.
2. I feel appreciated and listened to at work in the team.
3. It is safe to take risk in my team at work.
4. If you make a mistake in the department, it is often held against you.
5. No one would deliberately act in a way that undermines my effort.
6. People sometimes reject others for being different.
7. I have difficulty asking others for help in the department.
8. We often work as a team to find the systemic cause when something goes wrong.
9. If I have a problem, I could depend on my team leader to be my advocate.
10. People in your team value new ideas.
11. People in my team encourage continuation of learning, developing and growing.
12. People in my team resist untried approaches.
13. The team encourages and supports me to take on new tasks or to learn how to do
things that have never been done before.
14. People in my team are eager to share information about what does and/or does not
work.
15. Working with the members of the team, my unique skills and talents are valued and
utilized.

16. It is easy to speak up about what is in my mind regarding new
ideas/recommendations/ or suggestions.
17. People are able to bring up problems and tough issues freely.
18. People value new ideas and are interested in better ways of doing things.
19. Unless an idea has been around for a long time no one in this team wants to hear it.
20. I am very comfortable in speaking up (e.g. disagreements, personal issues, varying
point of views etc.)
21. I feel very comfortable to suggest new ideas to change certain things or ways of
working.
22. I prefer expressing my opinion privately or off-line rather than addressing them
directly with the group.
23. Differences in opinions are welcome.
24. People are open to alternative ways of getting work done.
Please indicate how much you have lost or gained of these resources since the last survey on a
scale of 1-5 (Great Loss, Little Loss, No Loss or Gain, A Little Gain, Great Gain):
1. Feeling that I am successful
2. Time for adequate sleep
3. Feeling valuable to others
4. Free time
5. Sense of pride in myself
6. Feeling that I am accomplishing my goals
7. Necessary tools for work
8. Hope

9. Stamina/endurance
10. Feeling that my future success depends on me
11. Positively challenging routine
12. Personal health
13. Sense of optimism
14. Status/seniority at work
15. Sense of humor
16. Feeling that I have control over my life
17. Role as a leader
18. Ability to communicate well
19. Feeling that my life is peaceful
20. Acknowledgement of my accomplishments
21. Ability to organize tasks
22. Sense of commitment
23. Self-discipline
24. Understanding from my employer/boss
25. Motivation to get things done
26. Support from co-workers
27. Feeling that I know who I am
28. Advancement in education or job training
29. Feeling independent
30. Companionship
31. Knowing where I am going with my life

32. Affection from others
33. Feeling that my life has meaning/purpose
34. Positive feelings about myself
35. People I can learn from
36. Help with tasks at work

Appendix D: Informed Consent Form
Informed Consent for Research
Study Title: Developing Rates of Psychological Safety in Army Officer Candidates
Principal Investigator: Eric Nielson
Department: USC Rossier School of Education
Survey Control Number: ISES-RMZ-23-206
Introduction
We invite you to take part in a research study. Please take as much time as you need to read the
consent form. If you find any of the language difficult to understand, please ask questions. If you
decide to participate, you will be asked to sign this form. A copy of the signed form will be
provided to you for your records.
Key Information
The following is a short summary of this study to help you decide whether you should
participate. More detailed information is listed later in this form.
1. Being in this research study is voluntary–it is your choice.
2. You are being asked to take part in this study because of your unique status as an Army
Officer Candidate. The purpose of this study is to extend our knowledge how of safe
individuals feel to take interpersonal risks in their jobs (psychological safety) develops
over time for OCS students. Your participation in this study will last the entirety of your
time at OCS. Procedures will include a <5-minute survey administered at the beginning
and after each phase of your training.

3. There are risks from participating in this study. The most common risks are breach of
confidentiality and breach of survey responses. More detailed information about the
risks of this study can be found under the “Risk and Discomfort” section.
4. The possible benefits to you for taking part in this study may include providing vital
information to progress our knowledge of how to encourage inclusion and team building
in the Army that will be aimed at improving team performance.
5. If you decide not to participate in this research, your other choices may include
excluding yourself and abstaining from completing the survey.
Purpose
The purpose of this study is to extend our knowledge how of safe individuals feel to take
interpersonal risks in their jobs (psychological safety) develops over time for OCS students. We
hope to learn if psychological safety directly impacts performance at OCS.
You are invited as a possible participant because of your status as an OCS student. About 160
participants will take part in the study.
Procedures
If you decide to take part, this is what will happen:
• A <5-minute survey will be administered at the beginning of training.
• That same survey will be administered again 3 more times after each phase of training.
Risk and Discomforts
Possible risks and discomforts you could experience during this study include:
1. Breach of confidentiality
2. Breach of survey responses

Surveys/Questionnaires/Interviews
Some of the questions may make you feel uneasy or embarrassed. You can choose to skip or stop
answering any questions you don’t want to.
Breach of Confidentiality
There is a small risk that people who are not connected with this study will learn your identity or
your personal information.
Department of Defense
Your first and last name will be collected on the sole basis of matching survey responses to
performance metrics. These identifiers will then be removed from the identifiable private
information and will not be used or distributed for future research studies.
There is no consequence if you choose to withdraw from the research.
Benefits
There are no direct benefits to you from taking part in this study. However, your participation in
this study may help us learn how to improve OCS Candidate performance by targeting
psychological safety.
Privacy/Confidentiality
We will keep your records for this study confidential as far as permitted by law. However, if we
are required to do so by law, we will disclose confidential information about you. Efforts will be
made to limit the use and disclosure of your personal information, including research study and
medical records, to people who are required to review this information. We may publish the
information from this study in journals or present it at meetings. If we do, we will not use your
name.

The University of Southern California’s Institutional Review Board (IRB) and Human Subject’s
Protections Program (HSPP) may review your records. Organizations that may also inspect and
copy your information include the Army Research Laboratory’s Human Research Protection
Program.
The Department of Defense (DOD) or Federal representatives may also access research records
for the purpose of protecting human subjects.
Officials of the U.S. Army Research Protections Office and the Army Research Laboratory’s
Human Research Protection Program are permitted by law to inspect the records obtained in this
study to ensure compliance with laws and regulations covering experiments using human
subjects.
This study will use Qualtrics. To understand the privacy and confidentiality limitations
associated with using Qualtrics, we strongly advise you to familiarize yourself with Qualtrics,
https://www.qualtrics.com/privacy-statement/ privacy policy. USC has no jurisdiction or
oversight of how data are used or shared on third party applications.
Alternatives
An alternative would be to not participate in this study.
Payments/Compensation
You will not be compensated for your participation in this research.

Voluntary Participation
It is your choice whether to participate. If you choose to participate, you may change your mind
and leave the study at any time. If you decide not to participate, or choose to end your
participation in this study, you will not be penalized or lose any benefits that you are otherwise
entitled to.
Contact Information
If you have questions, concerns, complaints, or think the research has hurt you, talk to the
investigator, Eric Nielson, at enielson@usc.edu or 3073711672.
This research has been reviewed by the USC Institutional Review Board (IRB). The IRB is a
research review board that reviews and monitors research studies to protect the rights and
welfare of research participants. Contact the IRB if you have questions about your rights as a
research participant or you have complaints about the research. You may contact the IRB at
(323) 442-0114 or by email at hrpp@usc.edu.
Statement of Consent
I have read (or someone has read to me) the information provided above. I have been given a
chance to ask questions. All my questions have been answered. By signing this form, I am
agreeing to take part in this study.

Name of Research Participant Signature Date Signed
(and Time*)

Abstract (if available)

Abstract Psychological safety is “a shared belief that the team is safe for interpersonal risk taking” (Edmondson, 1999, p. 354) that has been purported to be one of the most important variables to team success (Duhigg, 2016). This research project aimed to examine if psychological safety relates to performance and how it changes over time while at the U. S. Army’s Officer Candidate School (OCS). Clark’s (2020) Four Stages of Psychological Safety conceptualized psychological safety into Inclusion, Learner, Contributor and Challenger. Additionally, this research tested and applied the Conservation of Resources theory to identify whether individual resources, such as hope and confidence, relate to perceived psychological safety. The purpose of this study is to then provide recommendations to improve psychological safety to Army OCS Staff based on the findings. The data were collected in four waves through online surveys to 102 Officer Candidates from October 2023 – February 2024. Psychological safety was found to be statistically unrelated to performance and changed over time revealing a concave curvilinear relationship. Lastly, most resources were found to be positively related to psychological safety. These findings indicate the need to examine performance metrics and whether psychological safety is required as well as the need to track psychological safety over time. Practitioners and leaders can also measure and target specific resources when aiming to increase individual’s psychological safety.

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Asset Metadata

Creator Nielson, Eric (author)

Core Title Developing rates of psychological safety in Army Officer Candidates

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Degree Conferral Date 2024-08

Publication Date 08/19/2024

Defense Date 05/03/2024

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

Tag conversation of resources,Military,performance,psychological safety,stages of psychological safety,teams

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Hocevar, Dennis (committee chair), Legault, Richard (committee member), Picus, Lawrence (committee member)

Creator Email enielson@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC1139991ZI

Unique identifier UC1139991ZI

Identifier etd-NielsonEri-13068.pdf (filename)

Legacy Identifier etd-NielsonEri-13068

Document Type Dissertation

Format theses (aat)

Rights Nielson, Eric

Internet Media Type application/pdf

Type texts

Source 20240819-usctheses-batch-1199 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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 author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright.

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA

Repository Email cisadmin@lib.usc.edu