University of Southern California Dissertations and Theses

Leadership, accountability, and decision-making: An examination of first-responder experience and self-efficacy in real-time decision-making to improve community outcomes

(USC Thesis Other)

Leadership, accountability, and decision-making: An examination of first-responder experience and self-efficacy in real-time decision-making to improve community outcomes

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content

Leadership, Accountability, and Decision-Making: An Examination of First-Responder
Experience and Self-Efficacy in Real-Time Decision-Making to Improve Community
Outcomes

Jason Guidos

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

December 2022

© Copyright by Jason Guidos 2022
All Rights Reserved

The Committee for Jason Guidos certifies the approval of this Dissertation

Jennifer Phillips
Alan Green, Committee Co-Chair
Melanie Brady, Committee Co-Chair

Rossier School of Education
University of Southern California
2022

iv

Abstract
The purpose of this study was a preliminary examination of the relationship between first
responder self-efficacy and the dimensions of first responder training experience, which include
decision-making, situational awareness training, procedural training, and leadership
accountability. This is the first study of its kind to examine whether there is an indication of a
relationship between these variables and whether these variables are experienced differentially
across groups. The following three goals are thought to inform the links: (a) to investigate the
perceived organizational support that first responders are receiving toward positive decision-
making, (b) to observe what components of decision-making are being, or are not being,
developed, and (c) to examine how accountability, or lack of accountability, might be
contributing to a first responder’s self-efficacy in decision-making. Hypothesis 1: There is a
positive relationship between a first responder’s sense of self-efficacy and the frequency of
decision-making training received. Hypothesis 2: There is a significant difference (greater)
between self-efficacy for information action versus either information placement or information
gathering.
Hypothesis 3: There is a positive correlation between the perception of leadership accountability
and (a) training opportunities, (b) frequency of training for problem-solving, and (c) frequency of
training for tactics or procedures. This study used a quantitative approach to examine self-
efficacy and perception of leadership accountability from 93 first responders across fire, law
enforcement, and emergency medical services. The results suggest that there is a relationship
between a first responders’ self-efficacy in information action and frequency of training for
information gathering. The results also indicate that self-efficacy of information action
dominates both self-efficacy in information placement and self-efficacy in information

v

gathering. Lastly, the perception of leadership accountability improved as opportunities for
training and frequency of training were made more available. The key implications include the
need to question the emphasis on procedural/tactical training shifting to a more balanced
decision-making training process and the need to rethink a first responder’s work/training
balance. A new conceptual model is proposed to integrate the multiple components of decision-
making and to provide structure to the disparate fields of study in high-stakes, time-sensitive
environments. Finally, recommendations for training and future research are presented.

vi

Dedication
To my mother, who was taken by God before I could finish. I hope you have been able to read
this over my shoulder as I worked.

To my family. Thank you for understanding what the phrases “need to read” and “need to write”
meant and thank you for your patience through the process.

vii

Acknowledgments
Thank you to God for providing the patience and perseverance to stay the course. Thank
you to my wife and family for your support through the long days and class nights when you had
to disappear for a few hours. It would not have been possible without the time when I could be
alone to work or without the time when I could abandon my schoolwork and just “hang” with
you all. Thank you to my brother, whose conversation helped me focus on some important
concepts. Thank you to Dr. Hocevar who helped with understanding the intricacies and beauty of
SPSS and how to read what the data was telling me. Finally, thank you to Dr. Brady and Dr.
Green. Dr. Brady helped push me to say what I mean and mean what I say in a clear, concise
manner. Dr. Green guided me in the development of my conceptual model by asking me the
questions I required to build the structure for my literature review and research.

viii

Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ...................................................................................................................................... vi
Acknowledgments ......................................................................................................................... vii
List of Tables .................................................................................................................................. xi
List of Figures ............................................................................................................................... xii
Chapter One: Introduction to the Study .......................................................................................... 1
Context and Background of the Problem ............................................................................ 1
Importance of Addressing the Problem ............................................................................... 4
Stakeholder Group of Focus ............................................................................................... 5
Purpose of the Dissertation and Research Questions .......................................................... 5
Overview of the Conceptual Framework and Methodology ............................................... 6
Organization of the Study ................................................................................................... 7
Operational Definitions ....................................................................................................... 7
Chapter Two: Review of the Literature ......................................................................................... 10
Accountability ................................................................................................................... 11
Leadership Accountability for Information Gathering (How-to-Know-When) ................ 16
Leadership Accountability for Information Placement (When-to-Know-What) .............. 25
Leadership Accountability for Information Action (What-to-Know-How) ...................... 31
Conceptual Framework ..................................................................................................... 40
How Accountability Assumes a Central Role ................................................................... 42
Conceptual Framework Applied ....................................................................................... 43
Summary ........................................................................................................................... 47
Chapter Three: Research Methodology ........................................................................................ 48
Research Population and Sample ...................................................................................... 51

ix

Instrumentation ................................................................................................................. 53
Analysis............................................................................................................................. 54
Chapter Four: Results ................................................................................................................... 61
Research Question 1 ......................................................................................................... 62
Research Question 2 ......................................................................................................... 63
Hypothesis 1...................................................................................................................... 64
Hypothesis 2...................................................................................................................... 65
Hypothesis 3...................................................................................................................... 66
Discussion ......................................................................................................................... 67
Research Question 1 ......................................................................................................... 68
Research Question 2 ......................................................................................................... 69
Hypothesis 1...................................................................................................................... 72
Hypothesis 2...................................................................................................................... 73
Hypothesis 3...................................................................................................................... 74
Chapter Five: Implications and Future Recommendations ........................................................... 75
Implications for First Responder Environments and Communities .................................. 76
Unexpected Connection (Hypothesis 1) ........................................................................... 76
Information Action Domination (Hypothesis 2) ............................................................... 77
The Need to Rethink Training (Hypothesis 3) .................................................................. 78
Possible Solutions for First Responders ........................................................................... 80
Community Implications .................................................................................................. 85
Implications for Future Research ...................................................................................... 86
Conclusion ........................................................................................................................ 88
References ..................................................................................................................................... 89
Appendix A: Adaptive Toolbox .................................................................................................. 110

x

Appendix B: Detailed Situational Assessment Levels ................................................................ 112
Appendix C: Self-Efficacy Questionnaire Instructions .............................................................. 114
Appendix D: Self-Efficacy Questionnaire (Demographics) ....................................................... 115
Appendix E: Self-Efficacy Questionnaire (Demographics/Screening) ...................................... 116
Appendix F: Self-Efficacy Questionnaire: Information Gathering ............................................ 119
Appendix G: Self-Efficacy Questionnaire: Information Placement ........................................... 120
Appendix H: Self-Efficacy Questionnaire: Information Action ................................................. 121
Appendix I: Perception of Organizational Support Questionnaire ............................................. 122

xi

List of Tables
Table 1: Description of Heuristic Rules 22

Table 2: First Responder Demographics and General Characteristics 52

Table 3: Self-Efficacy of First Responders in Critical Situations and Perception 56
of Leadership Accountability in the Development of Self-Efficacy

Table 4: Coefficient Alpha of Self-Efficacy and Leadership Accountability 59

Table 5: Kruskal-Wallis Test Comparing Self-Efficacy with First Responder 63
Environment

Table 6: Kendall’s tau_b Correlation of Self-Efficacy and Frequency of Training 65

Table 7: Descriptive Statistics for Each Self-Efficacy Construct 67

Table 8: Mean Rank Trends Comparing Self-Efficacy and Ethnicity 70

Table 9: Mean Rank Trends Comparing Self-Efficacy and First Responder 72
Environment

Table 10: Example of Current Work Cycle for a Law Enforcement Department 83

Table 11: Example of Possible Work/Training Cycle for a Law Enforcement 84
Department

Appendix A: Adaptive Toolbox 110

xii

List of Figures
Figure 1. Measure of Working Memory as a Function of Set Size 33
Figure 2. Diagram of the Difference Between Efficacy and Outcome Expectations 41
Figure 3. Conceptual Model of Accountability and Decision-Making 45

1

Chapter One: Introduction to the Study
Research reveals that many attempts have been made to improve first responder training
related to decision-making. The focus has varied widely and has included areas such as
community policing (Tobon, 2021), crisis intervention (Rogers et al., 2019), less-than-lethal
(Ariel et al., 2019; O’Neill et al., 2018), bias prevention (Merino et al., 2018; Zeidan et al.,
2019), mental health (DeGue et al., 2016), de-escalation tactics (O’Neill et al., 2018), and
psychological skills development (Blumberg et al., 2019). However, these efforts fail to address
two issues at the core of decision errors. The first is that training volume, performance
expectation, and stress lead to cognitive overload resulting in increased susceptibility to
mistakes, decreased competence, and diminished communication skills (Iskander, 2019).
Cognitive overload may directly affect first responder’s self-efficacy further inundating their
mental capacity to affect positive community outcomes. The second is that much of the research
ignores training the root subject matter of making positive decisions: how decisions are made
and how they are trained. It is important to gain insight into how first responders measure their
self-efficacy, how first responders are supported by their organization, and what an organization
can do to better support first responders.
Context and Background of the Problem
Improper training and lack of organizational accountability contribute to poor decision-
making by first responders resulting in an organization’s negative reputation, adverse public
perception, and poor performance. This can be observed in the various first responder training
requirements. For example, in 37 states, a person can begin working in law enforcement before
attending basic training, basic training averages 936 hours (6 months), and in-service training
averages just 21 hours yearly (Council on Criminal Justice Task Force on Policing, 2021). For
2

emergency medical technicians (EMT), the average training is 6 to 16 weeks and for paramedics,
it is about 9 to 14 months (EMS1, May 27, 2021; National University, December 12). Fire
academy training lasts about 12 to 14 weeks (Engel, 2020). Due to the short duration of initial
training and lack of continuing education, much of which is optional, there have been calls for
increased training requirements (Preston, 2020; Task Force on 21
st
Century Policing, 2015).
However, these calls for increased training do not result in much, if any, change.
First responders operate in an environment in which they perform their tasks outside a
confined observable space, so leaders are unable to lead by direct oversight, and instead, must
rely on the judgments made by those workers “in the field.” Leaders are asked to train, instill
knowledge, set expectations, trust, and follow up without observing or having observed an event.
First-responder leaders must begin by understanding the objective and work backward to create
an environment in which the workers can give reasons for decisions. Heidelberg (2017) calls this
the reason-giving space, and it is the space where dialogue forces learning by analyzing the
critical points in the decision-making process. Another crucial responsibility that first responder
leaders must account for is projecting forward a fictional situation to create a reason-planning
space. This includes various forms of scenario-based training that simulate situations and
provides opportunities to combine theory and practice and provides space to make and learn
from mistakes (Haugland & Reime, 2018).
However, there are limitations that leaders should be aware of that contribute to what can
be trained and what can be expected from first responders. The first limitation is that time-
sensitive decision-making largely depends on either familiarity (Klein, 2017) or heuristics
(Gigerenzer et al., 2011). While some of this can be trained, most of it must be experienced
(Serfaty et al., 2014). The second limitation shows decision-making as being contingent upon
3

cognitive abilities (Yelon & Ford, 1999), environmental factors (Lockton, 2012; Simon, 1990),
and context (Raab & Gigerenzer, 2015). The third limitation is biological and includes working
memory (Oberauer et al., 2016), working memory capacity (DeCaro et al., 2016), and
automaticity (Anderson, 2017; Kahneman & Treisman, 1984; Sailing & Phillips, 2007), which
may hinder a first responder’s ability to process the multitude of incoming data.
The short duration of the training, the isolated and unsupervised nature of the work, and
the inherent limitations on human evolution all contribute to a sense of self-efficacy in first
responders. Because self-efficacy is representative of a person’s belief in their ability to
successfully perform an action (Bandura, 1997), it may influence “perceptions of a situation and
the quality of their analytic thinking” (Hepler & Feltz, 2012, p. 155). Bandura (1997)
distinguishes between high efficacy and low efficacy as follows: (a) people with high efficacy
perceive problems as challenges, envision success, and analyze efficiently, whereas (b) people
with low efficacy perceive problems as risks, envision failure, and analyze inefficiently.
Moreover, Hepler and Feltz (2012) add that individuals with low self-efficacy take longer and
consider more options because of doubt. In an environment in which time is limited, the negative
aspects of low self-efficacy may be a contributing factor to poor decision-making. The proposed
research will examine the self-efficacy of first responders in three components of decision-
making. The first component of decision-making is information gathering, which is how first
responders collect the necessary elements of an environment. The second component of decision-
making is information placement which is how the first responder situates information in the
context of their environment and their goals. Finally, the third component of decision-making is
information action, which is how the first responder physically interacts with their environment
to bring about a resolution.
4

Importance of Addressing the Problem
The evidence highlights that even calls for high-quantity training fall short if
implementation and quality are not substantive enough to yield positive outcomes. Training
autonomous workers is not the same as training non-autonomous workers and requires a vastly
different approach (Grossman & Burke-Smalley, 2018; Yelon & Ford, 1999). Autonomous
workers, specifically first responders, must make decisions independently and are not often
afforded the opportunity of consultation or careful consideration before making life-changing
decisions (Mosier and Orasanu, 1995; Zsambok, 2014). Training first responders requires an
understanding of how decisions are made (Gigerenzer et al., 2011; Klein, 2017), an
understanding of how decisions are situated in the context of an environment (Endsley, 2014;
Simon, 1990), and an understanding of how the information creates proper action (Fridland,
2014). Thus, calls for more training must be supported with opportunities for training, and it
must incorporate important concepts such as exploration (Grossman & Burke-Smalley, 2018;
Yelon & Ford, 1999; Yelon et al., 2004), risk-taking (Grossman & Burke-Smalley, 2018),
reflection (Lanza et al., 2018), and recovery (Boothroyd et al., 2019; Herman, 1998). The need
for attention on urbanized first responder efforts is essential in the increasingly diverse
communities in which they work (Walsh & Conway, 2011). Decision-making and leadership
accountability for training decision-makers is important to address because, in the United States,
our communities depend on first responders to make positive decisions in each of the estimated
240 million 9-1-1 calls for service each year (National Emergency Number Association, 2021).

5

Stakeholder Group of Focus
The stakeholders of focus are the members of first responder organizations and would
include law enforcement, fire, emergency medical services, and emergency medical technicians.
The respondents can be new or experienced to provide a range of data that might prove insightful
as differences in generations may yield differing perceptions. Although the members of the
responding personnel will be the primary focus of effort, alternative stakeholders will include the
leadership members. By including leadership, it might be possible to gather relevant information
concerning organizational accountability mechanisms and available training that is not perceived
or known by the responding personnel.
Purpose of the Dissertation and Research Questions
Failure to account for and properly train decision-makers contributes to poor decision-
making by first responders resulting in an organization’s negative reputation, adverse public
perception, and poor performance. The purpose of this study was a preliminary examination of
the relationship between first responder self-efficacy and the dimensions of first responder
training experience, which include decision-making, situational awareness training, procedural
training, and leadership accountability. The following three goals are thought to inform the links:
(a) to investigate the perceived organizational support that first responders are receiving toward
positive decision-making, (b) to observe what components of decision-making are being, or are
not being, developed, and (c) to examine how accountability, or lack of accountability, might be
contributing to a first responder’s self-efficacy in decision-making. To focus the purpose and
goals of the research, the following research questions are proposed to help guide the study.
1. Do specific first responder environments differentially affect self-efficacy in the
development of one or more phases of the decision-making process?
6

a. information gathering
b. information placement
c. information action
2. Is type of employment, gender, race/ethnicity, educational level, age, experience, or
rank/position related to first responder self-efficacy?
The following hypotheses will be examined:
1. There is a positive relationship between a first responder’s sense of self-efficacy and
the frequency of decision-making training received.
2. There is a significant difference (greater) between self-efficacy for information action
versus either information placement or information gathering.
3. There is a positive correlation between the perception of leadership accountability
and
a. training opportunities.
b. frequency of training for problem-solving.
c. frequency of training for tactics or procedures.
Overview of the Conceptual Framework and Methodology
The theoretical framework that guides this research and helped to create the conceptual
framework (Figure 3) is self-efficacy theory (Bandura, 1977), and will address the influencing
factors that link leadership accountability, training (procedural and situational), and decision-
making. First responders have individual needs, which can vary depending on the specific role
being filled, (i.e., fire, law enforcement, emergency medical services, or emergency medical
technicians), but common in all roles is self-efficacy. Self-efficacy theory is the cognitive
element of social cognitive theory and is defined as an individual’s perception of their ability to
7

exercise control over life events and the belief in their capabilities to act as needed for specific
task demands (Bandura, 1977, 1989). Self-efficacy assessments are not concerned with a
person’s judgment of a person’s abilities, but instead, with the judgment of what a person can do
with the abilities they possess (Bandura, 1986). This is appropriate for this problem because first
responders who have high self-efficacy in decision-making may be more apt to affect positive
situational outcomes. The methodology that will be employed for this study is a quantitative
analysis of first responder self-efficacy of information gathering, information placement, and
information action (conceptual model, p. 57) and an analysis of the perception of leadership that
might be contributing factors to those beliefs.
Organization of the Study
This chapter introduced the purpose of this research and explained the key concepts
motivating this study. This section also explored the importance of the problem, key
stakeholders, and a brief overview of the methodological framework guiding the exploration.
Five chapters will shape this study. Chapter 2 will address relevant literature regarding
accountability, decision-making, situational awareness, and procedural knowledge. Chapter 3
will explain the methodology in more detail including the stakeholders, method of data
collection, method of analysis, and respective support for each. The results and outcomes of the
collected data will be analyzed in Chapter 4. Finally, in Chapter 5, proposed solutions and
recommendations will be presented supported by empirical evidence and relevant literature.
Operational Definitions
Constitutive accountability arises out of the roles filled due to the identity of the
individual (Dubnick, 2020, February 18). Each role within the organization serves its specific
purpose and any deviation from the assigned role creates confusion and chaos when responding
8

to an event. An example might be a large brush fire that occurs near a main road. The fire
department, law enforcement, and medical transport each have a specific role. If medical
transport attempts to assist law enforcement with traffic control, it can confuse other law
enforcement personnel, it will confuse the public, and it may potentially prevent or delay their
ability to perform their intended function.
Epistemological accountability is a reference to the method of accountability and for first
responders, the method that most closely aligns with the community is responsibility. First
responders have an obligation to provide service for their community and the command element
requires that the service be accomplished with the highest standards of precision and
professionalism. The standard for each event, as stated before, is to leave the incident having
made the situation better. First responders are a highly decentralized structure, with decision-
making capabilities going all the way down to the most junior member, so responsibility begins
at the bottom of the hierarchy and works its way to the top.
Ethicality or ethical accountability is the established norms and values of a relationship
(Dubnick, 2020, February 18). When interacting with the public, law enforcement is expected to
be professional and to uphold the laws, rules, and regulations within their community. The
expectation is that any encounter with law enforcement is handled in such a manner that when
the event concludes, the situation was made better. If it is not made better, then the norms and
values of the expected relationship were violated, and post-factum accountability ensues.
Ontological accountability refers to the word accountability as a cultural keyword and
examines the idea and concept of the historical development of the word and how it has emerged
to today’s understanding Dubnick (2014). However, even today’s insight yields only marginal
9

understanding. Dubnick (2020, February 18) examines accountability through temporality,
ethicality, and constitutiveness, so understanding accountability requires context.
Satisficing is defined as obtaining the first option that works, rather than evaluating all
options and choosing the best (Simon, 1955). This was developed as a counter to rational choice
theory (Smith, 1776), which required too much time and too many alternatives to be useful in
time-limited environments. Simon (1955, 1979) describes satisficing as isolating the mental
model that most closely matches the perceived environment and choosing the best available
course of action. In other words, evaluate the perceived environment and evaluate the available
options and choose the first option that works even if a better option could be found if more time
was available.
Temporality refers to timing and event duration. Events happen in communities every
minute of every day. Emergency responses to many events cannot wait and the consequences,
whether positive or negative, occur in real-time and become events themselves. That interaction
results in temporal accountability being scrutinized during nearly every event. An example is a
law enforcement organization assisting a medical organization with the transport of an individual
who might be suffering from mental health distress to the hospital for care and evaluation. How
law enforcement personnel handle the transport is monitored directly by peers, leadership, the
hospital, and the public.
10

Chapter Two: Review of the Literature
Public services (i.e., fire departments, law enforcement, and medical services) are
intended to provide quality care for communities. However, the community’s support for first
responder institutions is not always consistent with the level of services demanded. The influence
of leadership is important within these organizations to positively affect outcomes in the areas
they serve. Decision-making is at the forefront of interactions with individuals in need of support
and thus, the most recognizable consequence of the services provided. Chapter 2 provides a
review of the literature regarding accountability and the culture of accountability within
autonomous work. It will then examine how the literature understands decision-making in the
context of information gathering (naturalistic decision-making and heuristics), information
placement (situational awareness), and information action (procedures). Afterward, this chapter
will explain the social cognitive theory, specifically, self-efficacy theory (Bandura, 1977) that
influenced this study. Finally, the chapter ends with a presentation of the conceptual framework.
Accountability will be discussed first as it is the central argument affecting change in the
context of decision-making. There are three components that leaders can use to facilitate
improved self-efficacy in decision-making in critical situations. The first component is
information gathering which is how first responders use experience and heuristics and requires
an environment that promotes risk-taking (Grossman & Burke-Smalley, 2018). The second
component is information placement which demands the information be given relevance
(Endsley, 2014). The final component is information action, which is the procedural portion and
the most recognized. The procedural portion requires knowledge and context to be acted upon
appropriately (Anderson, 2017). Leaders of first responders are accountable for and should be
continuously developing all three components to maximize positive outcomes.
11

Accountability
Decision-making is often closely linked to forms of accountability, but how the decisions
are linked to accountability has been debated throughout different periods of research and often
remains unanswered for ontological reasons (Wayne et al., 2016). In other words, because
accountability exists in various environments and is considered in many contexts (Dubnick,
2020, February 18), the practice of attributing decisions and outcomes fails to yield an accepted
standard. The definition of accountability is not universally accepted, which can cause confusion
within the director, provider, and observer relationship (Hentschke & Wohlstetter, 2004).
Accountability has been termed a cultural keyword and Dubnick (2014) examines the historical
development of the word and how it has emerged to today’s understanding. But even current
insight yields only marginal understanding. This, however, does not mean it is misunderstood, on
the contrary, it can be understood but requires context. As Dubnick (2020, February 18)
discusses, accountability can be known in terms of relationality, spatiality, temporality, ethicality,
and constitutiveness.
Because accountability can be thought of in terms of associations, space, time, moral
principles, and identity, the idea that one definition can cover all meanings is futile (Dubnick &
Yang, 2011). At its core, however, Frink and Klimoski (1998) define accountability as the desire
to justify an event to an entity that has the authority to reward or sanction. If this definition and
other similar definitions are considered fundamental in understanding accountability and its
various paradigms, then how has it been applied or how does it apply to an environment
inhabited by first responders? Attempting to answer how leadership structures an environment
that balances the needs of an organization, the needs of a decision-maker, and the needs of a
community in which they serve are in constant temporal conflict. Inevitably, it begs to question,
12

when is accountability considered? Much of the research would suggest that the conflict is
resolved through post factum accountability (Dubnick & Frederickson, 2011); that is to say,
understanding the links between action-consequence, cause-effect, decisions-outcomes, or
inputs-outputs (Millenson, 1997; Singleton, 2004; Walsh & Conway, 2011).
Within the medical environment (non-paramedic), medical mishaps are the third-leading
cause of death in the United States (Zadeh et al., 2019). Within law enforcement, deaths resulting
from police interactions amounted to 1055 in 2021 (Washington Post, April 1, 2022). Within the
firefighting community, vehicle accidents are the second leading cause of death for on-the-job
casualties (Emergency Vehicle Response, June 11, 2020). For emergency medical services,
vehicle accidents occur, on average, 6500 times each year of which 35% result in death for at
least one occupant of the involved vehicles (Emergency Vehicle Response, June 11, 2020). Each
of these examples demonstrates a community’s desire to seek an answer for a specified impact.
Dubnick and Frederickson (2011) termed this style of accountability as post factum
accountability in which after an event has occurred, either a person or group must be attributed to
it. They further explain that the ascription of the event is logically assumed to be because of
nonfeasance, misfeasance, or malfeasance in which the person or group must be held to account.
However, most of the negative outcomes are due to errors of omission rather than commission
(Hayward et al., 2005; Kalisch & Xie, 2014). More specifically, errors due to lack of proper
training, lack of proper supervision, or both (Walker, 2005). If post-factum accountability
pursues answers for events already having occurred, then pre-factum accountability strives to
preclude the need to do so.
Negative consequences for actions already having occurred often result in measures
being taken to create ways to mitigate future negative outcomes (Dubnick, 2011). He highlights
13

that space for accountability can be considered temporally as either occurring before or after an
action. Assuming the action is completed, the relationship in which accountability occurs results
in either reward or sanction as determined by proximity to the event. Accountability can take the
form of legal responsibility (Dubnick & Justice, 2006) or blameworthiness (Dubnick, 2003). In
either case, the first goal is to determine fault or responsibility. The second goal quickly follows
and that is to determine ways to create controls to prevent another occurrence. In a sense, post-
factum accountability is merely a conduit for pre-factum accountability (Heidelberg, 2017).
Heidelberg (2017) argues that the dichotomous definitions proposed by Dubnick and
Frederickson (2011), pre-factum accountability and post-factum accountability, are not, in fact,
dichotomous at all, but intertwined. For example, rules currently in place to encourage or prevent
certain actions are analyzed after an event and new rules are added or removed to create more
rules to either encourage or prevent similar events. Heidelberg (2017) reframes the concept of
pre-factum accountability as rule creation and post-factum accountability as consequences and
strips both as forms of accountability altogether.
Heidelberg (2017) convincingly argues that accountability does not occur before or after
an event but takes place during an event and terms it per factum accountability. His view is that
the relational aspect of accountability is most evident during an event and that only considering
accountability before or after misses the reason-giving space. The reason-giving space is defined
as the space where the decision process, not the outcome, is accounted for and contested in an
open forum (Heidelberg, 2017). And it is precisely this space in which contested decisions are
argued and ideas exchanged that facilitate growth and development. Bovins (2010) refers to
passive accountability which, instead of accounting for what could happen (rules) or what did
happen (consequences), demands that a forum exist to exchange dialogue between the director
14

and provider to understand the process. If, however, the accountability relationship was simply
built on rules, it would seek to eliminate conflict by standardizing situations, negating the need
for accountability. Still, Heidelberg (2017) argues that it is because conflict exists, resulting in
the debate of decision-making, that accountability becomes relevant.
Culture of Accountability
Both first responders and military personnel operate largely independently and in
uncertain environments. The nature of independent work is what Yelon and Ford (1999) consider
low supervision and open skill. Training for autonomous work implies that once the training is
completed, monitoring is either nonexistent or severely limited. The workers decide how and
what to apply to their daily tasks (Yelon et al., 2004) This situation requires leadership to use a
specific method of rewarding and sanctioning that best fits the environment to effectively ensure
that training is transferred, and the most effective way might be rewarding objective measures of
experimentation (Grossman & Burke-Smalley, 2018).
Grossman and Burke-Smalley (2018) provide a context-driven transfer model framed in
accountability which supports the development of future empirical studies. They offer several
propositions that, given the context of autonomous work, could yield the most effective results.
• proposition 1 and 2: reward objective measures of experimentation (p. 238).
• proposition 3: implement post-training interventions (p. 239).
• proposition 4: supervisors should manage workloads during training (p. 240).
• proposition 5: training and trainee selection should be strategic and be guided by
cognitive ability, learning orientation, and zest (p. 240).
• proposition 6: promote creativity, risk-taking, and adaptability (p. 241).
15

• proposition 7: promote positivity about independent work and self-determination (p.
241).
• proposition 8 and 9: select trainees high on generalized self-efficacy and perceived
ability to learn and solve problems (p. 242).
• proposition 10 and 11: moderate post-training support and accountability by
encouraging relevant goal setting (p. 242).
The objective of Grossman and Burke-Smalley (2018) was to synthesize transfer theory research
while looking at how accountability could be integrated and to provide specific testable
propositions for potential research. By including accountability as part of this study, rather than
simply adding to the myriad of research which includes additional training for first responder
reform, it might be possible to gain knowledge into the contributing factors at the source of
decision-making.
Key Accountability Concepts
The key concepts that were discovered during the research on accountability and
decision-making are as follows:
• supervision level: The degree of supervision that ranges from autonomous, or low
supervision, to dependent, or heavy supervision (Yelon & Ford, 1999).
• open skill: The combination of the degree of skill required, cognitive ability required,
and method for task completion. Again, like supervision, there is a range. Closed
skills require little skill, limited cognitive ability, and a single method for completion
whereas open skills require advanced skills, high cognitive ability, and multiple
methods for task completion (Yelon & Ford, 1999).
16

• objective measures of experimentation: Outcome measurements that are determined
by the successful implementation of open skills (Grossman and Burke-Smalley,
2018). They also emphasize that the measurement is refined over time as skills
evolve.
• generalized self-efficacy: The belief in one’s capability regardless of the challenges
(Grossman & Burke-Smalley, 2018).
• perceived ability to learn and solve problems: The ability to solve problems through
the acquisition of new knowledge (Grossman & Burke-Smalley, 2018).
Leadership Accountability for Information Gathering (How-to-Know-When)
How-to-know-when refers to the information gathering stage in the decision-making
process. Leaders are accountable for fostering an environment in which decision-makers can
recognize how to know when a decision is imminent, and they do this through training and post-
training interventions (Grossman & Burke-Smalley, 2018; Yelon & Ford, 1999). But decision-
making is not a simple task of choice-making in the classical sense, in which alternatives are
weighed and measured and the best option is chosen (Witztum, 2005). Decision-making involves
much more than simply weighing possible outcomes (Simon, 1979; Wittek et al., 2013),
especially in the complex environment of first responders (Klein & Mosier, 1995).
History of Decision-Making in Critical Environments
Decision-making is an often-studied topic that experiences resurgence decade after
decade. Rational choice theory is frequently considered the original formal decision-making
model and is credited to the philosopher and economist Adam Smith. In his classical work, Smith
(1776) captures both the economic and social dilemma of decision-making in which a problem is
evaluated by considering alternatives and finding the best possible path forward (Witztum,
17

2005). But it was not until the middle of the twentieth century that the social sciences took up the
mantel of pursuing decision-making as a valid model to be studied. Authors in the 1950s and
1960s began to look at social behavior as an exchange, like the economic model, but differed in
that costs and rewards are bound not by goods and wealth, but by behavior and relationships
(Homans, 1958; Simon, 1955). By the end of the 1970s, rational decision-making had begun to
be used interchangeably with rational choice theory, but rational decision-making added the
important concept of bounded rationality (Simon, 1979). In his work, Simon (1979) yields to the
reality that alternatives can still accomplish the task at hand, even if it is not optimal. Over the
last four decades, decision-making has been guided by topics such as experience, also known as
naturalistic decision-making (NDM), and temporal limitations (heuristics). It is in these two
areas that this study will explore in more detail.
Naturalistic Decision-Making
The term naturalistic decision-making was first used in 1989 at a conference where
researchers wanted to challenge the traditional paradigm of decision-making to pursue a more
rigorous study of how decisions were made in real-world settings (Klein, 2008; Orasanu, 1995;
Orasanu & Connally, 1993; Zsambok, 2014). Because of the nature of specific factors that
influence suboptimal decision-making, according to previous algorithmic models, there exist
subjective error analyses that are nearly impossible to assess (Huebner & Cummings, 1986;
Lipshitz, 2014). These factors include dynamic situations, temporal limitations, uncertainty,
inadequate assessment of cause and effect, and high risk (Mosier and Orasanu, 1995). A more
complete list of the contextual factors can be found in Zsambok’s (2014, p. 5) summary and
includes the following:
• ill-structured problems (not artificial, well-structured problems)
18

• uncertain, dynamic environments (not static, simulated situations)
• shifting, ill-defined, or competing goals (not clear and stable goals)
• action/feedback loops (not one-shot decisions)
• time stress (as opposed to ample time for tasks)
• high stakes (not situations devoid of true consequences for the decision maker)
• multiple players (as opposed to individual decision-making)
• organization goals and norms (as opposed to decision-making in a vacuum)
The decisions under consideration have real consequences for both the decision-maker
and the recipient(s) of the decision made. In the environment of first responders, all eight of
Zsambok’s (2014) criteria are met. In addition to the tasks and settings listed previously, three
other key focus areas for NDM research contribute to how NDM is defined. Again, Zsambok
(2014) contributed to the understanding of NDM by focusing the research on the elements that
define what “real world” decisions consist of and include the who (decision makers), the purpose
(how decisions are made, not how they should be made), and the situation (the options process
and the environment). In consideration of the who, the purpose, and the situation, a definition
was created that, instead of comparing it to previous decision models which would result in
defining it by what it is not, alternatively, defines it in positive terms and stands on its own
(Zsambok, 2014).
The study of NDM asks how experienced people, working as individuals or
groups in dynamic, uncertain, and often fast-paced environments, identify and
assess their situation, make decisions, and take actions whose consequences are
meaningful to them and to the larger organization in which they operate. (p. 5)
19

Note that the definition includes consequences that are meaningful, not that the decisions were
necessarily correct or good. Error analysis is subjective, and as Lipshitz (2014) assesses, the
what being observed is inextricably linked to the how it is observed. This means that the
situation and interpretation of events determine the action(s) taken (Kaempf et al., 1997).
Furthermore, the outcomes cannot always be traced to a cause, and sometimes understanding
how inaccurate decisions are made is as important as understanding how accurate decisions are
made (Huebner & Cummings, 1986).
How Decisions Are Made in the Natural Environment
Since the advent of NDM, several models/theories have developed that emphasize key
features of decision-making concentrating on issues associated with the previously mentioned
contextual factors. One such model is the recognition/metacognition (R/M) model in which
individuals absorb information and match it with previously constructed situations (either
experienced or trained) and resolve conflicting information by generating alternative situational
constructs (Cohen et al., 2014). Cohen et al. (2014) discovered that trained personnel were able
to grasp the situation faster and more clearly than untrained personnel by matching a greater
amount of information and discarding irrelevant information resulting in a higher awareness of
relevant factors. Other models/theories that have been developed are the situational awareness
model (Endsley, 2014), expertise (Duncker, 1945; Serfaty et al., 2014), and schemata/mental
model (Lipshitz and Ben Shaul, 1997). Other than the R/M model, the remaining models are
derivatives of one additional model, the recognition-primed decision (RPD) model (Klein &
Peio, 1989).

20

Recognition-Primed Decision Model
RPD combines two processes: how decision-makers assess a situation, and how decision-
makers visualize a proper course of action (Klein, 2017). In trying to discover how fire
commanders evaluated choices to decide the best course of action, Klein (2017) discovered that
they rarely, if ever, did. What was found, instead, was that commanders did not have to compare
options because as events unfolded, they could analyze novel situations as similar to previous
situations and thus, could eliminate options based on experience and training resulting in a more
fluid situational analysis process. By eliminating the need for deliberation, decisions took less
time and were considered more positive. Consequently, this method of decision-making employs
a strategy known as the singular evaluation approach and differs from a comparative approach in
that instead of considering two viable options, it analyzes each option on its own (Klein, 2017,
Simon, 1955). In time-sensitive environments, efficiency is the objective, so Simon (1955, 1979)
envisages satisficing rather than optimizing. Satisficing is defined as obtaining the first option
that works, rather than evaluating all options and choosing the best (Simon, 1955).
Fast and Frugal Heuristics (FFH)
The study of NDM overlaps with FFH in the research period and objectives. Both were
formalized in the 1990s and were born out of a desire to challenge the classical model of
decision-making in environments where circumstances prevent careful comparisons of two or
more criteria. And, although the similarities go further concerning decision-makers proficiency,
empirical-based treatments, process orientation, and situation-action matching (Lipshitz et al.,
2001), they differ tremendously in methods for modeling the decision-making process (Shan &
Yang, 2017). Lipshitz et al. (2001) prescribe that NDM seeks to qualitatively understand how
decision-makers can improve methods of making decisions, whereas FFH attempts to quantify
21

the synergy between decision strategies relative to their environment (Gigerenzer & Sturm,
2012).
In seeking to quantify the process of decision-making, much of the research organically
developed mathematically (Canellas & Feigh, 2016; Gigerenzer, 2008a; Gigerenzer et al., 2011;
Hoffrage et al., 2000). FFH was developed to combat logical and probabilistic analysis. Simply
put, while both serve a valuable function, logic cannot be tested, and probabilities take too long
(Gigerenzer, 2008b). Instead, FFH takes advantage of our desire to limit cognitive exertion.
Some say it is due to limited cognitive ability, but the data show otherwise (Gigerenzer et al.,
2011). FFH is fast and frugal because only a portion of the available information is considered.
The three components of FFH are searching for information, stopping the search, and decision-
making (Gigerenzer, 2008a). The first two are part of the search-stop rules and will be discussed
in greater detail later. But first, it is important to understand what heuristics are available. The
table in APPENDIX A (Gigerenzer, 2008b), also known as the Adaptive Toolbox, describes nine
different heuristics and is by no means complete, but it demonstrates the various ways a person
can quickly decide with limited information. The Adaptive Toolbox also represents how a person
might enter the decision process given their cognitive abilities and situation.
Each heuristic is associated with a particular environment and a person’s cognitive
ability. An advantage of FFH is that no person is limited to a single heuristic because all
individuals possess strengths and weaknesses in differing environments, so a person might
employ the recognition heuristic when information about a subject is low but use take-the-best
when enough knowledge is present to perform a cue analysis, or order ranking (Gigerenzer &
Goldstein, 1996; Goldstein & Gigerenzer, 2002). To use heuristics, much of which is instinctive
(Artinger, et al., 2015), people employ search criteria and stop criteria.
22

Search criteria involve searching one’s mind and the environment for relevant
information. Relevant information is relative to the individual creating a multitude of
possibilities for decision-making (Aringer et al., 2014). Stop criteria are determined by the
individual upon depletion of available cues that can be analyzed. The search-stop rules have
varying criteria and are more easily understood through a few examples (Table 1) depending on
the heuristic (Artinger et al., 2015).

Table 1
Description of Heuristic Rules
Heuristic Search rule Stopping rule Decision rule
Satisficing Set an aspiration
level and search
through objects.
Stop search when the
first object meets
the set aspiration
level.
Choose this object.
Tallying Search through cues
in any order, add
positive cues to the
tally, and deduct
negative cues from
the tally.
Stop after n cues
(where n can be
any number up to
the complete set of
cues).
Decide on the
alternative with the
higher tally. If after
searching through
all cues there is a
draw, guess.
Recognition Search for an object
that you recognize.
Stop as soon as one
object is
recognized.
Infer that the
recognized object
has the higher
value with respect
to the criterion.
Select that object.

Note. Adapted from “Heuristics as Adaptive Decision Strategies in Management”, by .F.
Artinger, M. Petersen, G. Gigerenzer, and J. Weibler, 2015, Journal of Organizational Behavior,
36(S1), S33–S52 (https://doi.org/10.1007/s11409-020-09231-x). Copyright 2014 by John Wiley
& Sons, Ltd.
23

There are other heuristics, but these examples show how FFH uses limited information to
quickly perform in time-sensitive situations. An obvious question now remains: to what extent
does this decision process, based on limited information, introduce bias (Artinger, et al., 2015;
Gigerenzer et al., 2011)?
The biases being referred to are not cultural biases, but instead, cognitive biases. Tversky
and Kahneman (1974) viewed human biases as problems that, if overcome, would yield better
decision-making. They perceived biases negatively and defined them as the difference between
human judgment and a rational norm. Heuristics, however, view it as part of pattern recognition
and machine learning where a biased algorithm makes fewer errors than an unbiased algorithm
(Hastie et al., 2001). It may be easier to understand by first looking at the equation (Gigerenzer et
al., 2011):
Total Error = (bias)
2
+ variance + noise
Mathematical reasoning is important to include because it explains the distinction between
choice theory (Smith, 1776) and temporally limited decision-making (Zsambok, 2014). The
former can eliminate many of the biases by determining what is and what is not noise whereas
the latter is not afforded the opportunity to carefully evaluate each piece of information. The
seminal article that discusses this equation is by Geman et al. (1992). The equation is
summarized as follows:
1. Begin with a true underlying function that needs to be learned.
2. From only a potentially noisy data sample, attempt to learn the function.
3. Bias is defined as the difference between the true function and the learned function
(averaged across all data samples).
4. If zero biases are present, then the true function and learned functions are the same.
24

5. Variance captures the difference between the learned function to the individual data
samples.
6. Noise refers to the unsystematic variation of the data.
Because the learned function cannot match both the data and the true function, it creates a
paradox known as the bias-variance dilemma. The dilemma occurs due to the tension between
bias and variance. By decreasing the bias, and matching more of the data sample, variance is
increased. This means that although the learned function represents more of the data, seemingly
creating a better model, the learned function fails to represent the true function. Conversely, if
the variance is decreased, the learned function will fail to match a high number of data but will
more closely match the true function. This means that fewer data are considered in creating the
learned function, thus introducing bias. Geman et al. (1992) are aware that some data not
considered might be meaningful, but it creates noise, that if considered, alter the alignment
between what is learned and what is true. For first responders, all data is not available, and
attempting to collect all data in a temporally limited environment might create more negative
outcomes. Addressing the problem of first responder decision-making, leaders should be acutely
aware of the limitation of gathering information and provide ample opportunity to learn
strategies for future decisions and review past strategies for future application (Grossman &
Burke-Smalley, 2018).
How-to-know-when captures the first need and situates the leader’s responsibility in
providing space for information gathering. Decisions begin with knowledge collection which can
be learned through naturalistic methods (Zsambok, 2014), developed with the recognition-
primed decision model (Klein, 2017), and gained through experience to build a set of matching
models (Cohen et al., 2014). Collecting knowledge can also be done through fast and frugal
25

heuristics (Gigerenzer, 2008a) which matches cognition and the environment to eliminate noise
in the analysis of a given situation. The more information that first responders can filter, the more
relevant the information can make. Leaders are accountable for facilitating growth in this
component, which may allow the first responder to be more capable during the next component:
information placement.
Leadership Accountability for Information Placement (When-to-Know-What)
After it is determined that an operator knows that they are in a decision-making situation,
it now must be determined how the individual situates the current circumstances with the need
for action. When-to-know-what is the stage in which the decision-maker must quickly progress
towards interpreting their environment and their goals to understand when to know what to do. It
is at this juncture that two possibilities can occur and Endsley (2014) summarizes it as the
inaccurate attribution of decision-making to choice-of-action rather than to situational awareness
(SA). The first possibility is that the decision-maker makes the correct decision, but the
perception of the situation is in error and the second possibility is that the perception of the
situation is correct, but the decision is in error. The leader is uniquely positioned to take
corrective action depending on which error is noted to assist the operator in recognizing it
themselves as they develop expertise (Klein, 1988).
Situational Awareness
SA invariably links the mind and the environment, and two theories attempt to bridge
NDM, FFH, and SA: Simon’s Scissors (Lockton, 2012; Simon, 1990) and ecological rationality
(Gigerenzer, 2008a; Lockton, 2012). Human behavior was thought to originate from internal
processes like intention, preference, risk aversion, egoism, and altruism among many others,
however, Simon (1990) suggested human behavior includes the environment, analogizing it to a
26

pair of scissors. He proposed a theory known as Simon’s scissors which described how “human
rational behavior is shaped by a scissors whose two blades are the structure of task and
environments and the computational capabilities of the actor” (Simon, 1990, p. 7). The
proposition is that it is impossible to understand how scissors work by considering only one
blade, just as it is impossible to understand human behavior by considering cognition sans
context (Gigerenzer, 2008a, 2011; Simon, 1990). The concept of describing behavior as part of
two systems (mind, environment) was not new and was described by Lewin (1936) with his
equation: B = f (P, E). He believed that behavior (B) is a function of the person (P); internal, and
the environment (E); external. But Ross and Nisbett (1991) and Winter and Koger (2004) warn
against the fundamental attribution error. The fundamental attribution error implies that when
considering one’s own behavior, the tendency is to emphasize the environmental (contextual)
influence over the personal (cognition) contribution. Conversely, when considering others, the
tendency is to emphasize personal contribution over environmental influence.
Ecological rationality, like Simon’s scissors, considers the environment as a crucial factor
in a person’s behavior, but unlike Simon’s scissors, ecological rationality seeks to answer two
specific questions. The first question asks in which environments specific heuristic succeeds
(Gigerenzer, 2008b). The answer relies on the search stop rules and cue analysis (Table 1) but
contextualizes it based on a specific environment (Raab and Gigerenzer, 2015). That means that
a cue analysis will only work in that specific environment. For instance, an EMS responder
might know how to stop a bleeding victim when the victim is lying on the ground, but if the
victim happens to be trapped in a vehicle, a different cue analysis is required. The second
question addresses why a heuristic is successful (Gigerenzer et al., 2011). The answer to this
question is much more complex and depends on the type of heuristic that is necessary. In FFH,
27

many heuristics could apply (Appendix A), for example, the recognition heuristic (Thorsten &
Gigerenzer, 2002), take-the-best (Goldstein & Gigerenzer, 2002), take-the-first (Johnson & Raab,
2003), and hot-hand (Csapo et al., 2015). Each heuristic is simple, but why they work is less
about understanding the underlying causes and more about understanding that they work (Raab
& Gigerenzer, 2015). Ecological rationality focuses on understanding the relationship between
the environment and cognitive abilities and since each person’s abilities differ, the heuristic they
choose to apply can vary as much as the environment.
SA is also closely associated with the previously discussed pattern matching model
(RPD) and incorporates memory structures to quickly make decisions (Klein, 1989; Dreyfus,
2007). But how those memory structures are internally conceptualized becomes the force behind
the decision-making process (Endsley, 2014). But SA is much more than simply understanding
the environment and in Endsley’s (1995) seminal work, it is framed in three parts. The first is
perceiving the information in the environment (Level 1 SA), the second is comprehending the
meaning of that information and how it fits with one’s goals (Level 2 SA), and the third,
projecting future environments (Level 3 SA). She argues that many people stop at Level 1 SA,
but that the higher levels are critical for decision-making in temporally limited environments. SA
is formally defined as “the perception of the elements in the environment within a volume of
time and space, the comprehension of their meaning, and the projection of their status in the near
future” (Endsley, 1988, p. 97). The following discussion explains each level and includes Level
1, observation, Level 2, making meaning, and Level 3, future projection.
Level 1, 2, and 3 SA
The first level in SA is to simply observe the environment and the elements that may
pertain to the affected environment (Endsley, 2014; Gasaway, 2008, 2010). By using primarily
28

sight and sound, Gasaway (2010) encourages the absorption of as much information as possible.
When a paramedic arrives on a scene, there could be 25 to 50 pieces of information, but the
information contains no meaning. The information is just a glimpse of the environment as
perceived by a decision-maker (Endsley, 2014). The second level in SA interprets the glimpse
and begins to make meaning of the data in the environment. In rapidly sifting through the
assortment of data, decision-makers begin to make connections that formulate the basis of the
third step (Endsley, 2014; Klein, 1993; Renaud, 2010). When a law enforcement officer observes
a vehicle repeatedly crossing in and out of a lane of travel, the data suggests an unsafe situation.
But to make meaning of that information implies that the law enforcement officer instinctively
considers relevant information to determine possible reasons (i.e., intoxication, under the
influence, tiredness, domestic violence, or vehicle malfunction)
Finally, the third step is to apply the information and meaning to a future environment
(Endsley, 1995). This step is the riskiest step and most open to external judgment. Gasaway
(2010) refers to it as a “gut feeling,” but it is far from random decision-making. It is based
heavily on situation matching (Cohen et al., 2014) and the recognition primed decision model
(Klein, 2017). Only the decision-maker is positioned to view the situation from their perspective,
so it is likened to a fire chief making the call to evacuate a building that they determine is likely
to collapse. There might be potential victims yet to save, but the future projection of all relevant
and meaningful data suggests that the costs do not outweigh the benefits. Simply put, the future
is unknown. See “Appendix B” for a more detailed explanation of the three levels of SA. The
question now becomes one of training decision-makers to recognize decision points and instilling
in them a high enough quantity of mental models to create ease of perception, meaning-making,
and efficient future projection.
29

Situational Awareness Training
Acquiring the ability to situate information in an event has only one common point of
agreement: the acquisition of applicable cognitive skills that foster SA development (Saus et al.,
2006; Stout & Salas, 1998). Beyond that, the debate includes impossibility (Stout & Salas,
1998), possible through work on pattern recognition training (Cohen, 1993; Kass et al., 1991),
possible through shared mental models, or team SA (Salas et al., 1995; Stout & Salas, 1998),
possible through cognitive development training (Endsley & Robertson, 2000; Frederickson &
White, 1989; Gopher, 1993; Gopher et al., 1989; O’Brien & O’Hare, 2007), and finally
conditionally possible only if the cognitive psychology community and training community can
discover the underlying SA competencies (Salas, 1998). In the meantime, some strategies have
emerged that attempt to capture (and measure) SA as a trainable and transferable construct. It
begins with the consensus that the three primary contributors to enhancing SA are effective
selection (of personnel), contextual system design, and training strategies (Stout & Salas, 1998).
The effective training strategies will be highlighted next.
A review of situational awareness training approaches was conducted by Nguyen et al.
(2019) specifically within the aviation environment, but it also has applicability in a first
responder’s environment. In their review, they describe six main categories that measure and
assess SA and detail their advantages and disadvantages. The six categories include the freeze-
probe technique, real-time probe technique, post-trial self-rating technique, observer rating
technique, performance measurements, and process indices. Before describing the first five,
(process indices can only be done in a lab setting and requires complex equipment), it is
important to understand that although situational awareness is trainable in specific contexts, there
is ample research that shows a significant decoupling of cognitive abilities and cognitive
30

activities (O’Brien & O’Hare, 2007). What this means is that although a person has high
cognitive abilities, they may not transfer to real-world environments (Roscoe et al., 2001) unless
accompanied by the ability to coordinate and integrate cognitive activities within a complex,
temporally limited, and fluid environment (Klein, 1993; O’Brien & O’Hare, 2007).
Each technique will be summarized according to the review conducted by Nguyen et al.
(2019). The first two techniques, freeze probe and real-time probe, are intrusive in that they
interrupt the agent while training or conducting field operations. The freeze probe technique
stops all action to seek input from each agent and provide input in accordance with the goals and
objectives. The real-time probe, however, does not stop the action, but instead, communicates
with the agents during the conduct of training or operation. The next two techniques, post-trial
self-rating and observer-rating, remove the intrusive nature of the first two, but they introduce
questions of validity. In post-trial self-rating, the agent subjectively analyzes their awareness
after the event which presents time for integration of awareness with performance outcome,
possibly weakening actual recall of SA at critical times. In observer-rating, a third party is tasked
with assessing SA, and can also be applied during live operations. However, the observer cannot
always be with the agent being assessed, decreasing the likelihood that an accurate assessment of
the agent’s SA can be made. The final technique requires very little effort, little investment, and
no intrusion on the agent. But the drawback is that it relies solely on the performance outcomes
in that a successful response is attributed to high SA and an unsuccessful response is attributed to
low SA. Due to the nature and complexity of first responder environments, ascribing satisfactory
performance with superior SA or unsatisfactory performance with inferior SA does not properly
account for the interacting variables necessary to understand the “picture” observed by the agent
(Nguyen et al., 2019).
31

Leadership Accountability for Information Action (What-to-Know-How)
After a decision-maker has entered the decision-making process and has perceived their
situation (environment and goals), they must now act. This is referred to as what-to-know-how to
do and is the final and only visible part of the process. At this point, procedures are engaged that
show purposeful action (Barrouillet et al., 2014, Souza et al., 2012) or automatic action
(Anderson, 2017). Because information action is the final component in the decision-making
process, the evidence of what information has been collected and how that information has been
situated becomes apparent. Errors in decision-making can occur at any stage, but what transpires
in the final stage is what is known to leadership and others who are external to the process. The
information action stage also suffers the limitations imposed on the human brain, especially in
high-stress and rapidly fluid environments (Cowan, 2016; Ruchkin et al., 2003).
First responders are now tasked with managing their working memory (WM) to interact
with their environment consciously or unconsciously. WM is defined as the “system that holds
mental representations available for processing” (Oberauer et al., 2016, p. 758). Working
memory capacity (WMC) expands this definition to “the ability to hold and manipulate
information in a temporary active state” (DeCaro et al., 2016, p. 39). In simpler terms, WM is
like a container and WMC is like the size of a container. Thus, the limits of WMC are regulated
by the system or by the size of the system (Constantinidis & Klingberg, 2016; Oberauer et al.,
2016), but a higher WMC might also be part of the problem (Cowan, 2016; DeCaro et al., 2016).
Limits of Working Memory Capacity
WMC is limited to approximately four items at any given time (Cowan, 2010, 2016;
Oberauer et al., 2016). The items are not limited to single objects like balls, numbers, or letters,
but “chunks” of information (Cowan, 2010; Oberauer et al., 2016). For example, one item might
32

be the digits of Pi. This means that someone who can access the numbers of pi to 25 decimal
places is not holding the numerical value of 3.1415926535897932384626433 as 27 items, but
instead as one item. In the same manner, first responders arriving at an emergency event are not
having to manage the vehicle operations before searching the scene for obstacles and dangers,
because vehicle operations are one item, obstacles are another item, and dangers are another item.
But the number of items upon arrival to a scene may exceed several dozen. Thus, the limitations
on what a first responder can store in working memory limit the actions they can take. But why
the limitations exist and whether the research agrees that it is a benefit or a hindrance is
contentious.
Cowan (2010, 2016) supports several reasons why working memory capacity might be
limited that include biological, evolutionary, psychological, and environmental. In his research,
he suggests that there are four distinct categories of limiting factors. The first limiting factor is
efficiency. The efficiency of WMC determines how much can be held. The quantity held may be
a result of ability, domain, or attention and is described as the number of items necessary for
temporary storage (Cowan, 2016). The human mind determines what information is relevant and
when relevancy wanes, it is inefficient to hold that information (Oberauer et al., 2016). The
question then becomes how much information can the human mind hold before it determines
relevancy. Figure 1 (right image), Cowan (2010) graphically represents Halford’s et al. (1988)
examination of the number of probe items versus recall of their presence. Subjects were given
sets of items (sequentially) and were asked to recall whether the items were part of the set while
measuring accuracy and reaction time. On the left side of Figure 1, the experiment was repeated
by Cowan (2010), but this time, all the items were presented concurrently instead of sequentially.
33

How the items were presented had little effect, but both show significant decay of working
memory in the accuracy and reaction time beyond the presentation of four items.

Figure 1
Measure of Working Memory as a Function of Set Size

Note. Representation of concurrent and sequential presentation of items and the mean of median
reaction time (of recognition) plotted by set size. From “Working Memory Capacity: Classic
Edition,” (1st ed.) by Cowan, 2016, Routledge, Taylor & Francis Group, p. 144. Copyright 2016
by the American Psychological Association.

Concurrent Presentation Sequential Presentation
Mean of Median Reaction Time (ms)
Set Size
2 3 4 5 6 7 8 9
2 3 4 5 6 7 8 9
1050
950
850
750
Set Size
34

The second limiting factor is referred to as formal and is based on mental models
(Cowan, 2016). The models represent the concept of competing neurobiological systems. Usher
et al. (2001) describe how long-term memory (LTM) and short-term memory (STM) are
designed in such a way that limits the functionality of the brain by structurally changing in the
case of LTM, but mediating neuroelectric reverberations in the case of STM. Because STM is
associated with awareness, the limits imposed by electrical impulses result in about 3-5 items
being available for immediate use. Oberauer et al. (2016) describe this conflict as information
decay (of STM), information resource sharing (STM and LTM), and information interference
(STM and LTM).
The third limiting factor is material (mechanisms) which is also a component of biology,
specifically the frontal regions and parietal regions of the human brain (Constantinidis &
Klingberg, 2016). Both Ruchkin et al. (2003) and Cowan (2016) find that the frontal lobe of the
human brain carries pointers to the conscience information of the posterior portion of the brain
(where attention is controlled). However, the researchers disagree on the underlying causes of the
WMC limitation. Ruchkin et al. (2003) suggest that it is limited by the number of pointers that
can be carried at once: from the posterior portion to the parietal portion (where attention is
focused). However, Cowan (2016) views the limitation not in how many pointers can be held,
but in how many sets of information can be pointed to. In either case, the biological limits of the
human brain seemingly restrict the capacity of WM.
The fourth factor is teleological and may be considered religiously, evolutionarily,
philosophically, or some combination of all three (Cowan, 2016). Cowan (2010) suggests two
views of WMC limits, one as weaknesses and one as strengths. If the limitation is a weakness,
perhaps the human brain is still in the evolutionary process of developing the ability to capture a
35

greater number of items. The limitation is only a current snapshot of human ability in WMC
(Jonides et al., 2008; Klingberg, 2009). Another reason for the weakness could be that it is as
God intended and that no creature would have the same ability to process information as God
(Cowan, 2016). Finally, the weakness could be due to the structural (environmental) factors that
might potentially overwhelm the human brain resulting in overprocessing, thus slowing down
reaction time in survival situations (Cowan, 2010).
If, however, the limitation of WM is a strength, the strength allows for a greater depth of
understanding of a situation as opposed to a breadth of understanding, resulting in a purposeful
failure to consider certain items. Cowan (2016) proposed that human evolution may have made
a trade-off between energy consumption for either processing capacity and/or physical prowess.
More energy was diverted toward activity instead of information processing. The advantages of
having more energy available for physical exertion and not mental exertion might have been
required for early human survival. But there are two current lines of research taking place that
warrant further discussion concerning WM: the differentiation between declarative working
memory and procedural working memory.
Declarative Working Memory Versus Procedural Working Memory
Several research paths have recently developed that suggest declarative working memory
and procedural working memory are separate and distinct (Barrouillet et al., 2014; Oberauer,
2009, 2010; Souza et al., 2012). Declarative WM is the stored objects of thought (STM or LTM)
that are available for future cognitive operations whereas procedural WM is a reactionary
(consciously or unconsciously) representation of what action to take with those objects
(Barrouillet et al., 2014; Oberauer, 2009; Souza et al., 2012). Oberauer (2009) proposed that the
two systems are independent and have their own capacity. In his framework, he suggests that
36

because each system has its own capacity, increasing the load on procedural WM would not
affect declarative WM and vice versa. This theory was supported by research conducted by
Souza et al. (2012). In their research, Souza et al. (2012) showed how task-switching and load
management had little to no effect on direct access to information held within declarative WM.
However, both Oberauer (2010) and Souza et al., (2012) conclude that procedural WM is limited
to one task item while declarative WM can hold several. Both researchers also concede that a
flaw existed in their experiments because the directions given to participants changed the tasks
from novel to known, thus potentially becoming part of declarative WM.
Barrouillet et al. (2014) confirmed what Oberauer (2010) and Souza et al. (2012) thought
might happen when novel stimuli were introduced. It was shown that when participants were
forced to consider more information, (i.e., increasing the load on declarative WM), it had a
detrimental effect on procedural WM by reducing accuracy and increasing time. This also
reinforces a phenomenon known as the law of Hick and Hyman (Hick, 1952; Hyman, 1953), in
which demand for executive control and attention increases as the difficulty of a task increases
(Szmalec et al., 2005). However, an exception to the inverse relationship exists and occurs when
a response is fostered that seems to bypass WM altogether and is referred to as prepared reflexes
(Hommel, 1998) or automaticity (Anderson, 2017). Decisions that are seemingly made through
automatic response do not allow for decision points and are not intentional (Sailing & Phillips,
2007). Therefore, training for stimuli that induce automatic action should be handled delicately
and purposefully.
Automaticity
There are times when a physiological action appears to be unconscious in that there was
little to no time to act, yet action occurred. Although WM can respond quickly, the
37

communication that yields a procedural response requires conscious thought. Automatic
behaviors, however, are defined as “fast, stimulus-driven, and characterized by a lack of
intention, attention, and awareness” (Saling & Phillips, 2007, p. 2). Two components of
automaticity that are not evident in the definition that further help to understand it include the
inability to stop the process once initiated and the immunity of the process to task/goal
interference (Anderson, 2017; Kahneman & Treisman, 1984). There are two theories for how
automatic processes occur. The first is that automaticity acts without resources: without cognitive
intervention (Logan, 1988; Peterson, 2018). Since the action is not being controlled, no resources
are used, and no information is processed. Logan (1988) also adds that this theory does not
account for how the behavior is learned but offers a possibility that practice, through repetition,
might account for the gradual elimination of the need for resources.
The second theory is that resources are used and that the cognitive process uses LTM to
bypass attention: the working memory (Anderson, 2017; Logan, 1988). As memories are stored,
then recognized in novel situations, the response is immediate and does not require WM to
facilitate action. In this theory, the task is also learned through repetition, but not to eliminate the
need for resources, but to eliminate the need for WM by creating a bridge from LTM to action
when a stimulus is introduced (Anderson, 2017; Logan, 1988; Toner et al., 2015). Both theories
recognize repetition as influencing the creation of an automatic response. However, the
principles underlying procedural training result in trade-offs between performance and outcomes
(Anderson, 2017; Fridland, 2014; Logan, 1988; Moors, 2016; Toner et al., 2015).
Procedural Training
First responders operate in high-stakes, temporally limited environments in which events
can occur that change the course of lives. Traffic accidents, fires, medical emergencies, and
38

criminal activity are among many other activities that are a result of circumstances created by the
individuals themselves or become part of the environment due to happenstance. When
emergency personnel are acting in response to emergency events, either through physical
interaction or through the communication of action, it is observed externally to be deliberate.
However, it could also be that the actions have entered a state of automaticity (Anderson, 2017;
Logan, 1988). In training decision-makers, skill is often referred to as an individual who is
skillful (or competent) at integrating their action appropriately in the context of their
environment (Anderson, 2017; Dreyfus, 2007; Stanley & Krakauer, 2013). Dreyfus (2007)
focuses mainly on the attainment of skill through practice and improvement of neural
connections, whereas Stanley & Krakauer (2013) emphasize intertwining strategic control and
motor acuity. However, Fridland (2014) argues that both researchers miss the mark in failing to
account for what she describes as the “three levels of control” (p. 2744).
The three levels of control are strategic, selective (top-down) automatic attention, and
motor skill (Fridland, 2014). She makes the case for skill to be developed through practice but
emphasizes that control does not necessarily mean the retainment of cognitive function. On the
contrary, it has been argued that one must understand that control can be both conscious and
unconscious (Fridland, 2014; Hassin, 2013; Kiefer, 2012; Kunde et al. 2012; Moors, 2016).
Unconscious behavior is involuntary, and Anderson (2017) implores researchers to proceed with
care about the assumptions of human cognitive control and to establish a putative measure of a
voluntary process.
The first level of control is strategic control, which simultaneously marries motor skills
with goals while divorcing motor skills from cognition (Fridland, 2014). She differentiates each
relationship by which one involves conscious control, and which does not. The conscious
39

relationship is the marriage of motor skills with goals. She uses the example of riding a bicycle
in the rain slower than when not in the rain. The technical aspects of riding the bicycle do not
change, but the goal of safety requires a conscious effort to employ the strategy of slower riding
to remain upright while turning on a wet surface. Conversely, the unconscious relationship is the
divorce of motor skills from cognition. In the same example, the individual might deviate from
their regular riding style while relying on the expert mechanical operation of the bicycle. They
can divert more attention toward their strategy of safety while eliminating resources dedicated to
bicycle operations. Fridland (2014) also adds that as circumstances become more complex, the
amount of focus on strategy increases, and motor skills decrease.
Because strategic control depends so heavily on the environment, it is the least able to be
trained. However, selective (top-down) automatic attention control and motor control can be
facilitated through training and exposure (Fridland, 2014). The second level, selective (top-
down) automatic attention control is closely related to situational awareness in that it primarily
involves information selection: what is and what is not important (Wu, 2014). Although still
unconsciously deployed (Fridland, 2014), selective attention can be developed through
perceptual improvements (Pylyshyn, 2003) and is rooted in the development of strategy (Wu,
2014). It is referred to as top-down because it begins with an intention, a goal, which ascribes a
specific cognitive function that upon determination of an objective, the automatic components
required for achievement facilitate progress toward the desired end state.
The third level is motor control, which is the “exact, nuanced ways in which a skilled
performer modifies, adjusts and guides her skill instantiation” (Fridland, 2014, p. 2748).
Examples of skills might include a firefighter deploying a ladder or unwinding a firehose, a
soldier disassembling and reassembling a combat weapon, or a medic inserting a breathing tube.
40

The repetitive practice automizes motor routines. With most of her cognitive function being
deployed on strategy and highly focused because of selective attention, the correct motor skill is
involuntarily initiated (Fridland, 2014). However, automatic motor skills are not simply faster
versions of nonautomatic motor skills, instead, they consist of a process conversion (Saling &
Phillips, 2007). The process algorithm changes from one of individual steps to one of goal
achievement. When learning to type on a standard keyboard, typing individual letters becomes
typing words, becomes typing sentences, becomes typing thoughts and the typist no longer
thinks about the location of letters. The algorithm, through practice and repetition, becomes
automatic yet, counterintuitively, allows for interjection at various junctures through skill
improvement because of the diversion of attention from motor skill toward selective attention
and strategy (Ericsson & Charness, 1994; Fridland, 2014; Saling & Phillips, 2007).
Conceptual Framework
The conceptual framework takes advantage of self-efficacy theory (Bandura, 1977).
Bandura states that,
The self-efficacy portion of social cognitive theory addresses the origin of self-efficacy
beliefs, their structure and function properties, their diverse effects, the processes through
which they work, and how to develop and enlist such beliefs for personal and social
change. (p. 14)
Self-Efficacy is carefully understood to be the link between the person and their behavior rather
than the behavior and the outcomes (Bandura, 1977; Stajkovic& Luthans, 1998). Figure 2 shows
where efficacy fits within the social cognitive theory and where it integrates the person with the
outcomes. Social cognitive theory includes three components: environmental factors, cognitive
factors, and behavioral factors. Self-efficacy directly connects the person with the behavior.
41

Figure 2
Diagram of the Difference Between Efficacy and Outcome Expectations
Person Behavior Outcome

Note. From Self-Efficacy: Toward a Unifying Theory of Behavioral Change (p. 193), by Bandura,
Psychological Review 84(2), (1977).

The sources of efficacy and the modes of induction include the following:
• Performance accomplishments – through participant modeling, performance
desensitization, performance exposure, and self-instructed performance.
• Vicarious experience – through live modeling and symbolic modeling.
• Verbal persuasion – through suggestion, exhortation, self-instruction, and interpretive
treatments.
• Emotional arousal – through attribution, relaxation, biofeedback, symbolic
desensitization, and symbolic exposure. (Bandura, 1977, p. 195)
Although each task or goal-oriented activity has a primary source/induction mode, it is common
that multiple sources are simultaneously engaged in the development of self-efficacy (Bandura,
1977; Bandura, 2012; Stajkovic & Luthans, 1998).
The importance of self-efficacy in a first responder environment is twofold. First, a
higher self-efficacy implies that the first responder believes they can successfully perform a
Efficacy
Expectations
Outcome
Expectations
42

given task. Second, given where self-efficacy fits in modifying behavior, the performance of that
task will yield the desired outcome (Chiaburu & Lindsay, 2008; Iqbal & Dastgeer, 2017;
Quratulain et al., 2021). Although the desired outcome is important, the focus of this study is on
the development of self-efficacy. Thus, the emphasis is on how leadership can influence growth
in what first responders believe they can do.
How Accountability Assumes a Central Role
As societies, organizations, and individuals progress, the desire for improved decision-
making and accountability has gained importance. However, training has not improved in quality
to match those expectations. To create this change, a closer examination of an organization’s
training mission, training strategy, leadership, culture, and individual needs may create
awareness as to why the change is not taking place. To further address this problem, the theory of
change to explore is a challenge to the belief that more procedural/response training always leads
to better individual performance. Theory of change is defined as a pragmatic theory that seeks to
understand how and why an initiative works by evaluating the cause and effect at each link in the
change process (De Silva et al., 2014).
Challenging the procedural/response component of training might prove unpopular, but
the previous literature review should help to convey the context that situates the need for that
challenge. If applied correctly, in creating a more complete training regimen and space for
productive contestation of decision-making, the result will be an improvement in organizational
and societal outcomes. To examine this problem further, there are several assumptions to
consider. The first is that training plays a large role in the decision-making process. The second is
that leadership accountability can and should directly affect the development of individuals,
specifically in situational decision-making. Third, that automated responses (due to overtraining
43

procedural knowledge) limit the heuristics of crisis operators. Finally, situational awareness has
more bearing on positive organizational outcomes than formal procedural knowledge.
Conceptual Framework Applied
Influenced by self-efficacy theory (Bandura, 1977; Maddux, 2013), this study will look at
the interaction between leadership accountability and the corresponding links between how-to-
know-when, when-to-know-what, and what-to-know-how. Figure 3 shows how each component
is linked and the direction of development. How-to-know-when is the information gathering link
in which information is collected by the crisis operator. It is the bridge in which knowledge is
learned through experience that develops an operator’s decision-making toolkit and may consist
of the NDM model and/or heuristics to create a picture of an event. Leadership is accountable for
fostering an environment of risk-taking, allowing for trial and error, and developing trust in the
developmental process and leadership.
When-to-know-what is the information placement link and the place where the operator
can take the gathered information and place it within a current context. It is at this stage that the
operator builds context through ecological rationality (Raab and Gigerenzer, 2015) and the
relationship between cognition and environment (Simon, 1955). Remember, the environment
dictates when a decision must be made, or not made, but the meaning of information from the
perspective of the decision-maker dictates what decision is made (Endsley, 2014). Leadership is
accountable for developing time and space for relevant situational awareness training so that
operators can build an effective decision strategy when confronted with unique environments.
What-to-know-how is the information action link where decisions and goals align to
develop a strategy resulting in action. In this stage, the operator performs the more commonly
understood, and more visible, procedures and tactics. It is also where the communication occurs
44

and where the decisions manifest and become the “items” which progress toward the contested
space for accountability (Heidelberg, 2017).
Leadership accountability is placed strategically in the middle of this model as it is
central to the continued development of each component. Also note that between the how, the
when, and the what is a one-directional arrow. Each component leads to the next, so although the
model begins with how, as experience is collected and more is learned, the cycle can restart at a
higher level of competence. This allows for continued development regardless of the level of
expertise.

Figure 3
Conceptual Model of Accountability and Decision-making

How
When
What
Collecting (Information Gathering)
Doing (Information Action)
Situating (Information Placement)
To Know
To Know
To Know
Leadership Accountability
Physiological
Feedback
(Bandura,
1977)
Situational
Awareness
(SA) Training
Foster Environment of Risk Taking
Vicarious Experiences (Bandura, 1977) &
Verbal Persuasion (Redmond, 2010)
Performance Outcomes
(Bandura, 1977)
Procedural Training
45
46

The blue arrows around the perimeter point from how, to when, to what, with to-know
bridging the gap. The goal is to increase competency and efficacy at each stage and then to
continue advancing as the first responder gains more knowledge and experience. The cycle
points in only one direction because upon demonstrating proficiency and gaining confidence in
certain skills, new tasks and challenges are presented to build upon the new knowledge. It is
intended for this to be a continuing cycle. External to the model are the items that leaders need to
be striving for in the development of first responders. How-to-know-when involves
understanding NDM and FFH and their subcomponents which assist the first responder in
gathering information in a time-limited, stressful, and fluid environment. When-to-know-what
bridges information and meaning, providing the first responder with as much understanding as
possible within the given environment. Situating information in the context of the environment
involves situational awareness, ecological rationality, and Simon’s scissors all of which
emphasize cognition and environment as inseparable components of decision-making. Finally,
what-to-know-how takes advantage of knowing how working memory, working memory
capacity, declarative working memory, procedural working memory, and automaticity limit a
first responder’s ability to collect, situate, and act upon information in high-stakes environments.
Leadership accountability is central to the model since leaders are accountable for
providing the necessary tools for first responders that enable them to develop knowledge and
self-efficacy. The red arrows point directly to the how, the when, and the what because leaders
should be intentional in what they do to provide the foundation for the first responders to move
along the blue arrow. The arrow that connects leadership accountability to how requires the
leader to foster an environment of risk-taking. By creating a conducive environment for learning
and development, the leader hopes to be guiding first responders toward when. The red arrow
47

that connects leadership accountability directly to when now requires the leader to develop
situational awareness. Finally, the red arrow that connects leadership accountability to what
demonstrates the leader’s responsibility in training procedures. Leaders are accountable for
processes that develop a first responder’s knowledge and efficacy for actionable procedures.
Summary
Chapter 2 addressed relevant literature related to the research of temporally limited
decision-making for first responders including accountability for training, naturalistic decision-
making, fast and frugal heuristics, situational awareness, working memory capacity, and
automaticity. While limited in its amalgamation, the literature demonstrates a strong foundation
with which to consolidate several key aspects of decision-making to explore further. Chapter two
also provided the conceptual framework which leveraged self-efficacy theory (Bandura, 1977) to
examine decision-making and accountability within the first responder community. The next
chapter will provide the methodological approach of this study and include the participant
stakeholders, methods, tools, and respective rationale in support of each.

48

Chapter Three: Research Methodology
Chapter 3 presents the research design and methods used to identify, collect, and analyze
data relevant to first responder self-efficacy and accountability to improve decision-making and
community outcomes. If the decision-makers are not being trained properly in the art of
decision-making, then perhaps their self-efficacy to perform in high-stress, time-sensitive and
critical environments wanes or fails to develop. The purpose of this study was a preliminary
examination of the relationship between first responder self-efficacy and the dimensions of first
responder training experience, which include decision-making, situational awareness training,
procedural training, and leadership accountability. The following three goals are thought to
inform the links: (a) to investigate the perceived organizational support that first responders are
receiving toward positive decision-making, (b) to observe what components of decision-making
are being, or are not being, developed, and (c) to examine how accountability, or lack of
accountability, might be contributing to a first responder’s self-efficacy in decision-making.
Based on the above goals, it is important to gather information concerning first
responders’ belief in what they can do in the context of their formal and informal development.
The purpose of Chapter 3 is to introduce the research methodology for a quantitative self-
efficacy study looking at the process first responders use to engage in decision-making in real-
time crisis situations. Using a quantitative approach, it will be possible to examine the
relationships between accountability and perceived ability in information gathering, information
placement, and information action. I will also investigate the correlation between training
opportunities and perceived accountability. Perceived self-efficacy is the sum of a person’s
beliefs in their capabilities to generate outcomes (Bandura, 1997). This chapter will begin with a
49

reminder of the research questions and describe the research design. After that, the chapter will
explain the sample, the population, the instrumentation, and the process of data collection.
Research Questions
To begin the study of decision-making pragmatically, it must first be determined how first
responders currently view their ability to perform in critical situations. Throughout Chapter 2, the
distinction between rational choice theory (Smith, 1776) and decision-making (Klein, 2008;
Simon, 1979; Zsambok, 2014) was explored. However, it became clear how disjointed the
research was and how it has failed to coalesce into an application-based theory that could
improve decision-making at the foundational level. Making decisions in high-stress,
informationally limited, and temporally limited environments are challenging and can result in
life-altering consequences (Gasaway, 2010). The result of this investigation has yielded the
following research questions.
1. Do specific first responder environments differentially affect self-efficacy in the
development of one or more phases of the decision-making process?
a. information gathering
b. information placement
c. information action
2. Is type of employment, gender, race/ethnicity, educational level, age, experience, or
rank/position related to first responder self-efficacy?
The following hypotheses will be examined:
1. There is a positive relationship between a first responder’s sense of self-efficacy and
the frequency of decision-making training received.
50

2. There is a significant difference (greater) between self-efficacy for information action
versus either information placement or information gathering.
3. There is a positive correlation between the perception of leadership accountability
and
a. training opportunities.
b. frequency of training for problem-solving.
c. frequency of training for tactics or procedures.
Research Design
Because the research has yet to coalesce into a more streamlined approach to decision-
making for first responders, the research questions first focused on the organizational support
and accountability that influences first responders, then how first responders’ self-efficacy is
influenced. The independent variables include:
• frequency of training received in information gathering
• frequency of training received in information placement
• frequency of training received in information action
• years of experience
• rank/leadership status
• training opportunities
• frequency of training for problem-solving
• frequency of training for tactics or procedures
The dependent variables will include self-efficacy for information gathering, self-efficacy for
information placement, self-efficacy for information action, and perception of leadership
accountability.
51

Research Population and Sample
There are over two million active first responders in the United States. Because access to
the full population was not possible, another method of gaining access was employed. The
participants were gathered anonymously using the snowball method. Initially, 20 known
participants were contacted and asked to either participate in the survey and/or forward the
survey to other potential participants within the first responder community. They were asked to
only forward the survey to members of fire, law enforcement, and emergency medical services.
Although a nonprobability sample is less desirable, the convenience, simplicity, and low cost
maximized access to these communities (Lavrakas, 2008). The specific benefits of this method
included anonymity and variety of participants.
As part of the data collection, specific demographic and general characteristic
information was gathered. Table 2 shows the number of respondents and the percentage of the
gathered information. Of the respondents, 87.1% were male (n = 81), 68.8% were White/Non-
Hispanic (n = 64), 40.9% (n = 38) have served for 25 years or longer, 84.9% (n = 79) are
currently employed full-time, and 57% (n = 53) have leadership experience at the senior level or
higher.
52

Table 2
First Responder Demographics and General Characteristics
General characteristic Respondents
n %
Gender

Female 12 12.9
Male 81 87.1
Education level*

Some college 38 44.2
Bachelor’s degree 33 38.4
Master’s degree 15 17.4
Service length

0–4 years 11 11.8
5–14 years 14 15.1
15–19 years 10 10.8
20–24 years 20 21.5
More than 25 years 38 40.9
Current employment status*

Employed full-time 79 84.9
Retired 13 14.1
Leadership Experience

Moderate/some leadership responsibility

40 43.0
Senior/positional leadership responsibility

20 21.5
Management/significant leadership responsibility

33 35.5
Ethnicity

Other 13 14.0
Hispanic 14 15.1
White/Non-Hispanic

64 68.8
Declined to answer 2 2.2

Note. N = 93. Represents the demographics of the respondents after the data was cleaned.
*N < 93 because several respondents opted to not answer this demographic question.

53

Instrumentation
An adapted self-efficacy survey was used to gather information for this study. The survey
was cross-sectional to capture as much data as possible over the short duration of the research
project (Creswell & Creswell, 2018). The survey design was guided by samples of related
efficacy surveys discovered (Bandura, 2006; Love et al., 2020; O’Connor, 1995; Tschannen-
Moran & Gareis, 2004). Currently, there are no first-responder surveys specifically addressing
decision-making, situational awareness, procedural response, and accountability. Some surveys
were found that investigated self-efficacy in first responders working in mental health situations
that were used to help format (Love et al., 2020). Sample questions include the following:
• In your current role as a first responder, to what extent can you…recognize a
significant decision situation (information gathering).
• In your current role as a first responder, to what extent can you…make meaning of a
current situation in the context of your goals (information placement).
• In your current role as a first responder, to what extent can you…produce the
appropriate response in a given situation (information action).
The first instrument was an adaptation of Norman’s (2010) self-efficacy tool for first
responders in mental health environments. Each of these questions was presented with a 10-point
Likert scale (Bandura, 2006) using Norman’s (2010) options specific to first responders. The
answers ranged as follows: (0) I cannot do that, (3) I doubt I can do that, (7) I am fairly certain I
can do that, and (10) I can do that (Norman, 2010). The phrasing for the self-efficacy instructions
included Bandura’s (2006) reference to “degree of confidence” in which he structures his surveys
by asking participants if they can do a specific task and to what degree of confidence they self-
assess: scaled from 0 to 10. In addition to the self-efficacy analysis, the second instrument will
54

include items influenced by the motivated strategies for learning questionnaire (Pintrich et al.,
1991), which was used to gain a further understanding of first responder development in
decision-making. Finally, a free response section was provided to the respondents that asked
them to provide any relevant information of their choosing. This option allowed the respondents
to qualitatively offer input that they deemed valid to their own experience.
Care was taken to design the survey so that each construct (information gathering,
information placement, and information action) was independent of one another, or as close to it
as possible. However, Cronbach and Shavelson (2004) emphasize the impossibility of true
independence, as it is unlikely that a response in one part of the survey does not affect another
part of the survey. Considering the topic of decision-making and the discussion of the
recognition heuristic (p. 20), it is reasonable to assume that some correlation between items may
have occurred. It is also reasonable to assume that one item may have been confusing and if
asked a different way, it remained confusing, or that survey fatigue can affect a later response
(Cronbach & Shavelson, 2004). This was mitigated as much as possible through pilot testing to
improve questions, improve formatting, and improve instructions (Creswell & Creswell, 2018).
Analysis
Statistical Package of the Social Sciences (SPSS) version 28 was used to analyze the
data. Upon conclusion of the survey, there were 121 total respondents. Of those 121 who
participated, 28 of them were deemed unusable. The first reason for not considering some of the
28 responses was that when submitted by the participant, less than 95% of the questions were
answered. The second reason for not including a portion of them was that time for completion (as
determined by the researcher) was not conducive to question consideration. After the elimination
55

of the 28 surveys, it was determined that 93 surveys could be used to analyze the hypothesis and
answer the research questions.
The data received and analyzed resulted in a non-normal distribution for all four
measures: self-efficacy of information gathering, self-efficacy of information placement, self-
efficacy of information action, and perception of leadership accountability. Due to the non-
normal distribution of data, it was determined that using non-parametric tests would be best for
further analysis. Kendall’s tau-b was used to evaluate correlation, the Kruskal-Wallis test was
used to compare each first responder group with a specific dependent variable, and the Friedman
test was used to compare each efficacy construct (see Table 3).

56

Table 3
Self-Efficacy of First Responders in Critical Situations and Perception of Leadership
Accountability in Development of Self-Efficacy
Independent
variables
Dependent
variables
Quantitative
research questions
Quantitative
hypothesis
Statistics/
test
First responder
environments
Self-efficacy for
information
gathering,
information
placement, and
information
action
Do specific first
responder
environments
differentially
affect self-
efficacy in the
development of
one or more
phases of the
decision-making
process?
Kruskal-
Wallis H
test
Demographic Self-efficacy for
information
gathering,
information
placement, and
information
action
Is type of
employment,
gender,
race/ethnicity,
educational
level, age,
experience, or
rank/position
related to self-
efficacy?
Kruskal-
Wallis H
test
Frequency of
decision-
making
training
Self-efficacy for
information
action,
information
placement, and
information
gathering
There is a positive
relationship between
a first responder’s
sense of self-efficacy
and frequency of
decision-making
training received.
Kendall’s
tau_b
57

Independent
variables
Dependent
variables
Quantitative
research questions
Quantitative
hypothesis
Statistics/
test
First responders Self-efficacy for
information
action,
information
placement, and
information
gathering
There is a significant
difference (greater)
between self-efficacy
for information
action versus either
information
placement or
information
gathering.
Friedman
test
a. Training
opportunities
b. Frequency of
training for
problem-
solving
c. Frequency of
training for
tactics/
procedures
Perception of
leadership
accountability
There is a positive
correlation between
the perception of
leadership
accountability and
a. training
opportunities.
b. frequency of training
for problem-solving.
c. frequency of training
for
tactics/procedures.
Kendall’s
tau_b

Content Reliability
The reliability of the survey was determined by the internal consistency of measurements
between items observed (Mueller & Knapp, 2019). The most accepted measure for the social
sciences is the coefficient alpha (Cronbach, 1951). Various measurements of strength have been
provided in the research, however, disagreements for appropriate lower-level cutoffs have also
been present. Nunnally and Bernstein (1994) advise that a value of 0.70 is acceptable, whereas
Hair et al. (2010) specify that a value of 0.60 would be suitable for exploratory research.
However, George and Mallery (2008) recommend a tiered approach as follows:
• α ≥ 0.90) is excellent
58

• 0.90 > α ≥ 0.80 is good
• 0.80 > α ≥ 0.70 is acceptable
• 0.70 > α ≥ 0.60 is questionable
• 0.60 > α ≥ 0.50 is poor
• α < 0.50 is unacceptable
Cho and Kim (2015) warn against creating an automatic cutoff because a minimum value should
be determined individually based on the research purpose, the importance of the decision, and/or
the research stage (i.e., exploratory, basic, or applied).
For this research, the recommendation of George and Mallery (2010) was used as the
initial starting metric. Reliability for this study was measured by calculating the coefficient alpha
(Cronbach, 1951). The efficacy measures and the leadership accountability measure were
evaluated, and Table 4 shows the results for each. The coefficient alpha returned excellent results
for self-efficacy of information placement (⍺ = .92), good results for self-efficacy of information
action (⍺ = .89) and perception of leadership accountability (⍺ = .86), and acceptable results for
self-efficacy of information gathering (⍺ = .75). Based on George and Mallery’s (2008)
recommendation, each of the construct’s coefficient alpha is within the acceptable value or
higher, so each construct is considered valid, and further analysis was conducted.

59

Table 4
Coefficient Alpha of Self-Efficacy and Leadership Accountability
Self-efficacy construct Coefficient alpha (⍺) Number of items (N)
Self-efficacy information
gathering
.75 12
Self-efficacy information
placement
.92 14
Self-efficacy information
action
.89 11
Perception of leadership
accountability
.86 13

Content Validity
Validity is defined as the extent to which the survey measures what it is designed to
measure (Mueller & Knapp, 2019). Care was taken to isolate the construct of efficacy. The items
in the survey were phrased as “can do” instead of “will do.” Bandura (2006) differentiates the
two by defining “can do” as a judgment of capability and “will do” as a statement of intent. He
also warns to be careful of other constructs such as self-esteem, a judgment of self-worth, locus
of control, a belief about outcome contingencies, and outcome expectancies, a judgment of likely
outcomes based on performance. Additionally, it should be noted that validity is a property of
inferences, not designs or methods (Shadish et al., 2002). This means that the same design might
yield greater or less validity in a different situation. For this research, the situations being
considered are those faced by first responders in critical situations or critical training.
Understanding that the results do not transfer to contexts outside of those parameters is important
as the respondents were asked to only considers critical or stressful situations. Because this study
60

is nonexperimental and was conducted through convenience sampling, external validity will not
be discussed (Danells, 2019).
Ethical Concerns
The field of first responders is sensitive to external examination. First responder self-
examination provided to external sources has a limited cognitive engagement (known due to
personal experience). The survey was designed with this in mind, so length, repetition, and
clarity were carefully considered to get the best results. Anonymity is also vital within the first
responder community, so names were not collected. Informed consent was included to ensure
participant safety and security. All information collected was stored on a password-protected
device and only those essential to the study were granted access. Before seeking participants,
approval from the institutional review board was granted.

61

Chapter Four: Results
The purpose of this study was a preliminary examination of the relationship between first
responder self-efficacy and the dimensions of first responder training experience, which include
decision-making, situational awareness training, procedural training, and leadership
accountability. The following three goals were thought to inform the links: (a) to investigate the
perceived organizational support that first responders are receiving toward positive decision-
making, (b) to observe what components of decision-making are being, or are not being,
developed, and (c) to examine how accountability, or lack of accountability, might be
contributing to a first responder’s self-efficacy in decision-making.
The following research questions and hypothesis guided the inquiry and the data
collected. Each of the following research questions and hypotheses will be discussed in its own
section but are included here for reference.
1. Do specific first responder environments differentially affect self-efficacy in the
development of one or more phases of the decision-making process?
a. information gathering
b. information placement
c. information action
2. Is type of employment, gender, race/ethnicity, educational level, age, experience, or
rank/position related to first responder self-efficacy?
The following hypotheses will be examined:
1. There is a positive relationship between a first responder’s sense of self-efficacy and
the frequency of decision-making training received.
62

2. There is a significant difference (greater) between self-efficacy for information action
versus either information placement or information gathering.
3. There is a positive correlation between the perception of leadership accountability
and
a. training opportunities.
b. frequency of training for problem-solving.
c. frequency of training for tactics or procedures.
The remainder of this chapter reveals the results of the data collected from first
responders. First, this chapter will discuss the reliability measures obtained with the study. After
that, the data for both research questions will be shown. Next, each of the hypotheses will be
analyzed. Finally, the results will be summarized.
Research Question 1
Research Question 1 asked the following: Do specific first responder environments
differentially affect self-efficacy in the development of one or more phases of the decision-
making process? The sub-items of the Research Question sought to learn more about the
development of information gathering, information placement, and information action.
The analysis was conducted using a Kruskal-Wallis H test to compare each decision-making
construct with each first responder environment (fire, law enforcement, emergency medical
services). As observed in Table 5, the test did not yield statistically significant results.

63

Table 5
Kruskal-Wallis Test Comparing Self-Efficacy with First Responder Environment
Kruskal-Wallis Test Self-efficacy for
information
gathering
Self-efficacy for
information
placement
Self-efficacy for
information
action
Kruskal-Wallis H 2.999 1.384 .289
df 2 2 2
Asymp. Sig .223 .501 .865

Research Question 2
Research Question 2 asked the following: Is type of employment, gender, race/ethnicity,
educational level, age, experience, or rank/position related to first responder self-efficacy? A
Kruskal-Wallis H test was conducted for each measure to assess the difference between each
group and each respective self-efficacy construct (information gathering, information placement,
and information action).
The analysis revealed significance in only one of the demographics/self-efficacy
comparisons: ethnicity. All other comparisons did not show significance. In comparing ethnicity
with self-efficacy, the Kruskal-Wallis H test showed that there was a statistically significant
difference in self-efficacy (information gathering) between the different ethnicity groups, χ
2
(2) =
7.737, p = 0.021, with a mean rank self-reported ethnicity of 39.50 for Other, 63.75 for Hispanic,
and 43.44 for White/Non-Hispanic. The Hispanic respondents had a significantly higher sense of
self-efficacy for information gathering as compared to White/Non-Hispanic and Other. Other
consists of Asian/Pacific Islander, Black/African American, Native American, and Other. The
responses in each of those categories did not contain enough respondents to perform an
independent analysis for each group.
64

Hypothesis 1
Hypothesis 1 stated that there is a positive relationship between a first responder’s sense
of self-efficacy and the frequency of decision-making training received. A Kendall’s tau_b
correlation test was used to test for significance. The first two items, self-efficacy for information
gathering and self-efficacy for information placement did not yield a statistically significant
correlation with any of the three elements of decision-making, thus, the null hypothesis is unable
to be rejected. However, there is a significant correlation (N = 88) between self-efficacy in
information action and training received in information gathering (τb = .172, p < .05), so the null
hypothesis is rejected (see Table 6). As the frequency of information gathering training
increased, the self-efficacy in information action increased.

65

Table 6
Kendall’s tau_b Correlation of Self-Efficacy and Frequency of Training
Frequency of training
Self-efficacy
information
gathering
Self-efficacy
information
placement
Self-efficacy
information
action
Information gathering

Correlation Coefficient .046 .112 .172*
Sig. (2-tailed) .580 .175 .041
N 88 88 88
Information placement

Correlation Coefficient .022 .156 .092
Sig. (2-tailed) .798 .073 .300
N 80 80 80
Information action
Correlation Coefficient .084 .061 .076
Sig. (2-tailed) .316 .468 .372
N 89 89 89

Note. N = 88. *p < .05.

Hypothesis 2
Hypothesis 2 stated that there is a significant difference (greater) between self-efficacy
for information action versus either information placement or information gathering. A Friedman
test was conducted to determine if self-efficacy of information action was greater than self-
efficacy of information gathering and information placement. The results show a significant
difference, χ
2
(2) = 27.440, N = 93, p < .001. The mean rank for self-efficacy in information
gathering is 1.60, self-efficacy for information placement is 2.12, and self-efficacy for
66

information action is 2.28. The null hypothesis is rejected indicating that self-efficacy for
information action is indeed greater than both information gathering and information placement.
Hypothesis 3
Finally, Hypothesis stated that there is a positive correlation between the perception of
leadership accountability and training opportunities, frequency of training for problem-solving,
and frequency of training for tactics or procedures. Training opportunity data was gathered using
a self-reported slider estimating the percentage of time spent training versus time spent working.
The median reported percentage of time spent training for fire was 20%, for law enforcement
was 15.5%, and for emergency medical services was 22%. Frequency of training was separated
into two categories: the first asked how often the respondents were trained for problem-solving
and the second asked how often the respondents were trained in tactics and procedures. A
Kendall’s tau_b correlation test was used to determine the significance of the relationship
between the perception of leadership accountability and the three variables of training
opportunities, frequency of training in problem-solving, and frequency of training in tactics or
procedures.
Each relationship was found to be statistically significant. First, there is a significant
correlation (N = 91) between training opportunities and perception of leadership accountability
(τb = .163, p < .05). Second, there is a significant correlation (N = 93) between the frequency of
training for problem-solving and perception of leadership accountability (τb = .2113, p < .01).
Lastly, there is a significant correlation (N = 93) between frequency of training for tactics or
procedures and perception of leadership accountability (τb = .184, p < .05). In each case, the null
hypothesis is rejected. The perception of leadership accountability improved as opportunities for
training and frequency of training were made more available.
67

Discussion
The analysis revealed that the general self-efficacy of all respondents skewed toward the
higher end. Table 7 shows the mean and standard deviation of the self-efficacy ratings for each
component of decision-making. The self-efficacy data was observed to be compressed at the
upper end of the scale, which was not unexpected. The negatively skewed distribution resulted in
the need to conduct a non-normal analysis of the data. While not all hypotheses were statistically
substantiated in the analysis, several important relationships were observed. First, the results of
the analysis revealed that the connections between efficacy and training may not be as direct as
expected. Next, the results showed that the current emphasis on the observable component of
decision-making, information action, might be directly related to the greater self-efficacy in that
construct. Finally, training opportunities and training frequency are strongly correlated with the
perception of leadership accountability. The remainder of the chapter will address the research
questions and discuss the results of each hypothesis.

Table 7
Descriptive Statistics for Each Self-Efficacy Construct
Self-efficacy construct N Mean Standard deviation
Information gathering 93 9.18 .61
Information placement 93 9.34 .57
Information action 93 9.44 .53

Note. Scale for self-efficacy was 0–10. See surveys in Appendices F, G, and H.

68

While not all hypotheses were statistically substantiated in the analysis, several important
relationships were observed. First, the results of the analysis revealed that the connections
between efficacy and training may not be as direct as expected. Next, the results showed that the
current emphasis on the observable component of decision-making, information action, might be
directly related to the greater self-efficacy in that construct. Finally, training opportunities and
training frequency are strongly correlated with the perception of leadership accountability. The
remainder of the chapter will address the research questions and discuss the results of each
hypothesis.
Research Question 1
The first research question asked if specific first responder environments differentially
affect self-efficacy in the development of one or more phases of the decision-making process.
The phases of the decision-making process include information gathering, information
placement, and information action. No significance was found to indicate that one community of
first responders had a higher self-efficacy in any of the three self-efficacy constructs. The results
from the research conducted suggest that the responder environments do not differentially affect
self-efficacy. However, the significance may lie in the fact that none of the three communities
distinguished themselves from the others as having a unique way of imbuing efficacy. The data
might be signaling that although each responder community has its way of developing its
decision-makers, not one of them has learned to set itself apart from the others. Conversely, the
participants representing each of the first responder communities may be demonstrating their
ability to manage self-efficacy within their unique first responder environment.
69

Research Question 2
The second research question asked if type of employment, gender, race/ethnicity,
educational level, age, experience, or rank/position is related to first responder self-efficacy. The
results did not find anything of significance that might be demographically meaningful based on
type of employment, gender, education level, age, experience, or rank/position. However,
significance was found for first responders who identified as Hispanic in self-efficacy related to
information gathering. But nothing was found in the research to suggest why the Hispanic first
responder population would have a higher self-efficacy for information gathering. It is difficult
to posit the reason for this in the context of time-sensitive decision-making. However, some
research has been conducted regarding decision-making in the business setting that might begin
to reveal some understanding.
Personal decisions, in the context of financial planning and cultural influence within the
Hispanic community, have been examined. Research results in this context demonstrate
understanding decision-making through cultural value (familism) and the integration of affect
and cognition. Weisfeld-Spolter et al. (2018) demonstrate how cultural values are embedded
antecedents to behavior and that cultural values influence attitude. However, decision-making
and culture are the intersection of many demographic identities and include ethnicity, but also
includes being a part of the first responder community. It is biased to assume that the respondents
who identified as Hispanic were answering the surveys in the context of one identity over
another (Yates & de Oliveira, 2016). The respondents are an amalgamation of identities,
therefore, act as individuals whose experiences and development of self-efficacy may be unique
to them (Leung & Cohen, 2011).
70

Although no significance was found between information placement and information
action, a noteworthy trend was observed among participants who identified Hispanic as their
ethnicity indicating potential differences in self-efficacy related to these two constructs (see
Table 8). First responders who identified their ethnicity as Hispanic rated their self-efficacy as
higher in all three components of decision-making.

Table 8
Mean Rank Trends Comparing Self-Efficacy and Ethnicity
Efficacy measure and ethnicity Respondents
n Mean Rank
Self-efficacy for information gathering

Other 13 39.50
Hispanic 14 63.75
White/Non-Hispanic 64 43.44
Self-efficacy for information placement

Other 13 40.62
Hispanic 14 58.00
White/Non-Hispanic 64 44.47
Self-efficacy for information action

Other 13 37.88
Hispanic 14 56.54
White/Non-Hispanic 64 45.34

71

In addition, possible differences between first-responder environments were found in the
self-efficacy of law enforcement, fire, and emergency medical services. The mean rank for fire is
greater than law enforcement and emergency medical services in both information gathering and
information placement, however, law enforcement is greater than fire in information action.
Emergency medical services trail both fire and law enforcement in all three measures (see Table
9). Whether this difference is actual and meaningful, a larger study might be able to discern.
However, it is worth noting that the nature of each first-responder environment requires a
response to a specific type of emergency. Although some overlap is to be expected, the relative
proximity that each environment observes within their domain differs. For example, fire is
typically working with structures, law enforcement is typically working with individuals but at a
distance, and emergency medical personnel are typically working directly with individuals. The
unknowns are present in each case, however, training for general situations may challenge the
self-efficacy of those in closer proximity to the event because the narrower the focus, the more
the unknowns impact information gathering, information placement, and information action
(Constantinidis & Klingberg, 2016).

72

Table 9
Mean Rank Trends Comparing Self-Efficacy and First-Responder Environment
Self-efficacy measure and first responder environment Respondents
n Mean rank
Self-efficacy for information gathering

Law enforcement 27 45.74
Fire 54 50.19
Emergency medical services 12 35.50
Self-efficacy for information placement

Law enforcement 27 47.94
Fire 54 48.42
Emergency medical services 12 38.50
Self-efficacy for information action

Law enforcement 27 48.57
Fire 54 46.97
Emergency medical services 12 43.58

Hypothesis 1
The more frequent the training received in information gathering, the higher the self-
efficacy of information action reported by first responders. In contrast to isolating each self-
efficacy construct with each construct of training received (i.e., self-efficacy of information
gathering versus training received in information gathering), the research intended to look for
any connection between any of the three self-efficacy constructs and training received. Because
the analysis resulted in a statistically meaningful result that linked training in information
gathering and self-efficacy in information action, it may mean that first responders are creating
links across constructs. The data suggest that training specifically to improve self-efficacy in
73

information gathering, information placement, or information action might not result in
improvement in self-efficacy in the corresponding construct.
Training research shows that learners make connections with new material based on
items already learned or through experience (Clark et al., 2012). The learner, then, in a first-
responder context, may be forming information gathering skills while connecting prior
experiences to create a new schema for future events requiring information gathering. Based on
the short durations of training received in the first responder communities (Council on Criminal
Justice Task Force on Policing, 2021; EMS1, May 27, 2021; Engel, 2020; National University,
December 12) it is possible that first responders are maximizing the minimal time spent
developing information gathering skills. By moving straight from information gathering to
information action, the first responder might use the development of information gathering to
create a greater belief in their ability to act.
Hypothesis 2
The second hypothesis stated that there would be a significant difference (greater)
between self-efficacy for information action versus either information placement or information
gathering. The results suggest that the organizational emphasis being placed on the observable
component of decision-making (information action) for each of the first responder communities
will result in greater self-efficacy in that specific construct as compared to the others. As
discussed in the introduction to the study in Chapter 1, the emphasis for much of the recent
research has been on areas such as community policing (Tobon, 2021), crisis intervention
(Rogers et al., 2019), less-than-lethal (Ariel et al., 2019; O’Neill et al., 2018), bias prevention
(Merino et al., 2018; Zeidan et al., 2019), mental health (DeGue et al., 2016), de-escalation
tactics (O’Neill et al., 2018), and psychological skills development (Blumberg et al., 2019). This
74

research is largely behavioral in nature which demonstrates the emphasis on the observable. This
means that there is little to no focus on the inputs or metacognition involved in the thought
process. The result is an overemphasis on outcomes tied to behaviors that disregard the thought
processes that are foundational to first-responder decision-making (information gathering,
information placement, and information action). The lower efficacies observed in information
gathering and information placement could mean that there is room for improvement and that the
overemphasis on behavioral outcomes might create an overreliance on action.
Hypothesis 3
The third hypothesis stated that there is a positive correlation between the perception of
leadership accountability and training opportunities, frequency of training for problem-solving,
and frequency of training for tactics or procedures. The results were statistically significant as
expected and as training opportunities and training frequencies increased, so did the perception
of leadership accountability. The perception of leadership accountability by first responders
demonstrates a direct positive relationship to leadership’s ability to provide training that
identifies areas in need of training. Within the first responder fields, training is work. Training is
directly applicable to the job of fighting fires, conducting rescues, responding to criminal
behavior, de-escalating situations, and saving lives (Wild et al., 2020). The applicability can be
observed in the research through intentional experiential development (Klein, 2008, Zsambok,
2014) and the development of automatic responses through repetition training (Fridland, 2014).
75

Chapter Five: Implications and Future Recommendations
The purpose of this study was a preliminary examination of the relationship between first
responder self-efficacy and the dimensions of first responder training experience, which include
decision-making, situational awareness training, procedural training, and leadership
accountability. The results indicate that there are significant relationships between first responder
self-efficacy and training. The relationship between training and perception of leadership
accountability is, perhaps, even more substantial. The following sections discuss the implications
of the results on the first responder environments and the communities they serve. Chapter 5 will
conclude with a discussion of possible research inquiries moving forward and provide a brief
conclusion of the research and data.
The analysis in Chapter 4 accepts:
• Hypothesis 1; there is a positive relationship between training for information
gathering and self-efficacy of information action. However, the relationships between
other factors of decision-making and self-efficacy were rejected.
• Hypothesis 2; there is a statistically significant difference (greater) between self-
efficacy for information action as compared to information gathering and information
placement.
• Hypothesis 3; there is a statistically significant correlation between the perception of
leadership accountability and each of opportunity for training, the frequency of
training for problem-solving, and the frequency of training for tactics or procedures.

76

Implications for First Responder Environments and Communities
This study resulted in several implications for first responders and the communities in
which they serve. The implications include: the contribution of training for information
gathering and self-efficacy for information action, the overemphasis on training information
action, and the need to rethink first responder training.
Unexpected Connection (Hypothesis 1)
At first glance, the relationship between training for information gathering and self-
efficacy for information action is not apparent. Information gathering is the first component of
decision-making and information action is the final component. However, the connection
between the two seemingly unrelated components may demonstrate the level of automaticity that
may influence the first responder’s evaluation of their self-efficacy. Information gathering and
information placement require conscience effort within the biological limitations of working
memory and working memory capacity (Constantinidis & Klingberg, 2016; Oberauer et al.,
2016). The belief in one’s ability to perform a task without thinking may increase the self-
efficacy of information action since many of those actions become involuntary (Fridland, 2014).
Therefore, with automaticity, either through repetitive practice or repetitive experience, the first
responder becomes somewhat immune to distraction in the performance of that task.
Training for information gathering may contribute to the self-efficacy of information
action, thus, demonstrating the challenge associated with working memory capacity and
automaticity (Cowan, 2016; DeCaro et al., 2016). At the moment of action, the information
gathered is stored as working memory. In a training environment, the next phase of the
discussion often involves a question about what is to be done. The first responder links the
hypothetical gathered information to the hypothetical action. Because the action is emphasized,
77

self-efficacy of action may increase, leaving behind self-efficacy in both information gathering
and information placement. The first responder then physically practices or mentally rehearses
the action, contributing to a higher likelihood of building that knowledge into automatic action.
Once an action becomes automatic, self-efficacy is maximized for that task/scenario. The cycle
then repeats with modifications in presented information resulting in more items becoming
automatic. Thus, the result is training for information gathering becomes directly linked with
self-efficacy of information action.
Information Action Domination (Hypothesis 2)
As hypothesized, self-efficacy in information action would outperform self-efficacy in
information gathering and self-efficacy in information placement. The results showed that self-
efficacy for information action did dominate self-efficacy for information action and information
placement. In the United States, the emphasis continues to be placed on the observable. Even in
studies that purport to examine decision-making as a process, the importance of the discussion
emphasized the critical decision point (Scott et al., 2022) or the point of interjection (Suss &
Ward, 2018). Therefore, it is essential to consider metacognition as part of decision-making
development for first responders. However, it will not be simple because several challenges in
the field of metacognition include definitional issues, how to distinguish metacognitive
knowledge from skills, the complex interaction between cognition and metacognition, the role of
conscious versus automatic metacognitive processes, and how to distinguish between domain-
generality and domain-specificity of metacognition (Azevedo, 2020). The challenges can be
overcome with specific applications within the temporally limited environments of first
responders and, perhaps, with isolated studies of each first responder environment.
78

First responder units have limited time and personnel, which means that they must
maximize their work schedules. The result of the limited time and personnel means there is little
time remaining for training, and when there is time, the focus is on the observable. The
work/training cycle becomes an exercise in efficiency with little regard for missed opportunities.
It is challenging because the expectation is that the unit or organization be held accountable for
ensuring adequate training, but what if the cycle is broken beyond their ability to influence?
External influences can affect organizations and organizational influences can affect units, but
the smaller units are limited by resource availability or response parameters. The limitations
require reliance on organizations and external entities to supply time, personnel, and funding so
that first responders can be properly trained in all aspects of decision-making.
Information action may dominate information gathering and information placement
because the emphasis has been on first responder training for outcomes (Ariel et al., 2019;
Rogers et al., 2019). The research conducted here might indicate that the emphasis should be
placed on external entities, like governments and legislation, and organizations. The literature up
until now has focused on how first responders can change to better community outcomes (Tobon,
2021). However, the education of governments, legislatures, and organizational leadership may
be needed to influence training, training focus, training standards, and the structures that
facilitate the implementation of a new way to train.
The Need to Rethink Training (Hypothesis 3)
The emphasis on training only the visible component of decision-making (information
action) must change. The reasons are twofold:
79

• First, the data shows there may be too much reliability on the visible aspect of
decision-making within the first responder community, leaving room for growth in
the other constructs (Suss & Ward, 2018).
• Second, the data also indicates that first responders want to be trained, providing
valuable knowledge directly from the first responders.
Relying on only the visible aspect of decision-making (Ariel et al., 2019; Merino et al.,
2018; O’Neill et al., 2018; Zeidan et al., 2019) means that nothing will change at the
macrolevels: the organizational level and first responder field. Some individual first responders
will continue to make positive decisions despite the lack of training (Lin et al., 2021) and some
individual first responders will continue to make negative decisions despite the training offered
(Hardy et al., 2014). Both can be true at the same time. That means that some first responder’s
cognitive abilities allow them to develop self-efficacy in information gathering and information
placement through experience, imagery, and mental toughness (Hardy et al., 2014; Jiang, 2022;
Lin et al., 2021) while those with limited cognitive abilities take what little training is offered
and become hyper-focused on developing self-efficacy in information action through fear of
failure or punishment (Hardy et al., 2014).
The results of Hypothesis 3 may be the most useful finding in the research conducted.
Training and leadership are inextricably linked within the first responder fields of law
enforcement, fire, and emergency medical services. Individual first responders rely on that
training, whether it comes in the form of formal training, informal training, maintenance training,
experiential training, or advancement training. The first responder’s perception of leadership
accountability and how that might be influenced by opportunities for training and the frequency
of training received in problem-solving and tactics or procedures is impossible to ignore.
80

Leadership must listen to their first responders and meet the needs of those workers in the field
and if done correctly, not only will the perception of leadership accountability likely improve,
but the enhanced training may develop the needed self-efficacy in decision-making.
Possible Solutions for First Responders
First responders engaged in a critical situation requiring decisions to be made are
essential for their organization and within their community. Fire personnel, emergency medical
personnel, and law enforcement make life-altering decisions every day and each circumstance is
unique and nearly impossible to standardize. However, there is a progression to decision-making
that can harness the skills of these unique working environments to improve the process and
outcomes of decision-making. The conceptual model (p. 57) shows how the process of decision-
making begins with information gathering, then moves to information placement, and finally
ends with information action. The process is cyclical and continues as events continue to
develop. Additionally, the model can be used for training and development as well as during an
actual event. The more it is practiced, the more comfortable a first responder will be with how to
work through the process. It is the responsibility of leadership to facilitate training opportunities
and promote a higher frequency of training for first responders.
Leadership accountability is central to the model (p. 57) because first responders need the
knowledge so they can work to transition from novice learners to expert practitioners. Without
the opportunity to practice, the change that is sought will continue to be singularly focused on
information action at best and remain hopeful at worst (Yelon & Ford, 1999). The leadership of
each first-responder group is aware that training is unique to the different environments and
roles. However, there are two commonalities in training needs across groups:
81

• First, the analysis of the data revealed that the respondents linked opportunities for
training and time for training with the perception of leadership accountability, which
must be addressed (Heidelberg, 2017).
• Second, to facilitate the training recommendations, organizations will need additional
personnel to offset an updated work/training cycle (Bovins, 2010).
Time to Train
Time to train should be the highest priority. As indicated by the data, frequency and
opportunity for training were positively correlated with the perception of leadership
accountability. Leadership should use that information to provide a better work/training balance
for its first responders. Perhaps looking at improving on the median reported percentage of time
spent training. For fire, training consisted of 20% of their work schedule, for law enforcement, it
was 15.5%, and for emergency medical services, it was 22%. In an environment where mistakes
can be costly, in terms of lives and property, these percentages may not be enough. Especially
considering that much of the training consists only of procedures and tactics, with little emphasis
placed on information gathering and information placement.
A recommendation for adjusting the work/training balance would be to get each of the
first responder communities at or near 40% of the time spent training (Grossman & Burke-
Smalley, 2018). This may seem disproportionate, but organizations and communities expect
positive outcomes. Industry best practices and first responder knowledge are not always aligned,
possibly due to high turnover or lack of time available to train. The community’s expectations
often outpace the ability to meet them and certainly outpace the self-efficacy to perform. The lag
in the ability to serve according to expectations requires time to close the gap. By increasing the
time to train, first responder organizations may be able to close two gaps at the same time.
82

First, the gap between self-efficacy for information gathering/information placement and
information action might become less severe resulting in a more balanced decision-making
cycle. Second, the perception of leadership accountability might increase. In many fields,
training is thought of as an interference or a distraction, but in the first responder community, it
is a need. If the perception of leadership accountability is low, it could be due to the need for
training not being met. By meeting this need, the organization could begin a positive sequence
where their increased commitment to proper training increases the perception of leadership
accountability, which could then increase the desire to offer more time for training.
Personnel to Facilitate Training
The next item to address is personnel. With the modifications recommended to the
training schedule, more personnel are needed to ensure that services are not interrupted. Shift
work versus training “work” balance requires more first responders covering shifts while others
train (Grossman & Burke-Smalley, 2018). Table 10 shows a current example of how a law
enforcement schedule might look. Note that each section works 84 hours over 2 weeks. For
example, Sections 1 and 3 work 60 hours during Week 1 and 24 hours during Week 2, then the
schedule flips for Sections 2 and 4. If training is conducted using the current schedule, it is done
during off time, and that is if there are no special events requiring additional shifts for personnel,
causing the off-sections to work additional hours. This work cycle requires 80 personnel in total.

83

Table 10
Example of Current Work Cycle for a Law Enforcement Department
Work sections Day of the week
Number of personnel
each shift
Number of hours
worked each shift
Week 1
1/3 Monday 20 12
1/3 Tuesday 20 12
2/4 Wednesday 20 12
2/4 Thursday 20 12
1/3 Friday 20 12
1/3 Saturday 20 12
1/3 Sunday 20 12
Week 2
2/4 Monday 20 12
2/4 Tuesday 20 12
1/3 Wednesday 20 12
1/3 Thursday 20 12
2/4 Friday 20 12
2/4 Saturday 20 12
2/4 Sunday 20 12

A modification to the example presented in Table 10 would require an additional 60
personnel, an increase of 75%. That would allow for certain workdays to be used as training days
and the work schedule would approach the recommended 40% of work time spent training. A
possible solution might look like Table 11.

84

Table 11
Example of Possible Work/Training Cycle for a Law Enforcement Department
Work sections Training sections Day of the week
Number of
personnel each
shift
Hours
worked/hours
trained
Week 1
1/3 7/5 Monday 20 12/10
1/3 7/5 Tuesday 20 12/10
5/6 2/4 Wednesday 20 12/10
5/6 2/4 Thursday 20 12/10
6/7 2/4 Friday 20 12/10
1/3 None Saturday 20 12/10
1/3 None Sunday 20 12/10
Week 2
2/4 5/6 Monday 20 12/10
2/4 5/6 Tuesday 20 12/10
6/7 1/3 Wednesday 20 12/10
6/7 1/3 Thursday 20 12/10
7/5 1/3 Friday 20 12/10
2/4 None Saturday 20 12/10
2/4 None Sunday 20 12/10
Week 3
1/3 6/7 Monday 20 12/10
1/3 6/7 Tuesday 20 12/10
7/5 2/4 Wednesday 20 12/10
7/5 2/4 Thursday 20 12/10
5/6 2/4 Friday 20 12/10
1/3 None Saturday 20 12/10
1/3 None Sunday 20 12/10

An additional recommendation associated with the adjusted schedule in Table 11 would
be to place newer employees in Sections 5, 6, and 7 and work on a three-week rotation schedule
in which they would receive 40 hours of training and 72 hours of work every three weeks.
Sections 1, 2, 3, and 4 would be the more experienced employees and would work on a two-
85

week rotation in which they would receive 30 hours of training and 48 hours of work every two
weeks. This schedule would meet the recommendation for work/training balance while providing
enough personnel to meet the community service needs without interruption or degradation.
Community Implications
Communities benefit from first responders who believe they can perform their duties to
the best of their ability. Overworked and undertrained first responders do not always meet the
expectations of their community (Walker, 2005). The generally high self-efficacy scores that first
responders have are a great starting point, but as the analysis revealed, self-efficacy is skewed
toward one part of the decision-making model (information action). It is beneficial to the
community that first responders can use the skills, tactics, and tools of their respective trades;
however, the research demonstrates that the communities might additionally benefit from a more
balanced model. A more balanced self-efficacy might improve community relations and further
efforts to build trust in emergency medical service responders, law enforcement responders, and
fire responders.
Additionally, by providing the necessary training and reducing the on-duty workload
(Grossman & Burke-Smalley, 2018), communities may also receive better-trained and less
overworked responders. Although the stress and grind of the daily workload were not a focus of
this research, it is difficult to ignore in the context of adjusting the training cycle and personnel
required to properly train and work. Most communities know that the first responder field is
struggling with the challenges of day-to-day tasks and expectations with limited resources.
However, the crucial nature of the work requires high outcome expectations and does not change
what the community demands, nor should it. The first responder field can change lives,
sometimes for the better, sometimes not. The expectation of each community should be that
86

emergency services are reliable with highly efficacious operational performance when engaged
in all first responder situations.
Implications for Future Research
This is the first study of its kind to examine whether there is an indication of a
relationship between the variables of self-efficacy and the dimensions of first responder training
experience, which include decision-making, situational awareness training, procedural training,
and leadership accountability, and whether these variables are experienced differentially across
groups. This study added to the research in decision-making by merging the separate fields of
study (information gathering, information placement, and information action) into a working
model that can be used for training and during real-time critical situations. Additionally, this
study explored the current state of first-responder self-efficacy and their perception of leadership
accountability. With this knowledge, future research can take what was started here and continue
to advance our understanding of the first-responder fields and the communities in which they
operate.
Further research can look at how the workload, stress, or traumatic events affect self-
efficacy in one or more phases of the decision-making model. Research suggests that all three
affect first responders resulting in a higher-than-necessary turnover rate (Hilal & Litsey, 2020).
The high turnover rate contributes to less experience fire personnel, emergency medical
responders, and law enforcement. By using self-efficacy as the basis for analysis, it might be
possible to understand how workload, stress, or traumatic events impact a first responders’ belief
in what they can do.
Additionally, it would be beneficial to repeat this study with 300 or more respondents
which would provide strength to the results of the current study. This would provide the
87

opportunity to examine demographics related to statistics with an adequate number of cases. A
limitation of this study was the number of respondents and the demographic breakdown
hindering the ability to divest more knowledge from specific categories. Receiving more
respondents with varying education levels and varying service times may add to the study.
Additionally, receiving more female respondents might further differentiate their experience and
self-efficacy rating. Although the percentage of female respondents coincides with the
percentage of those serving in the examined first responder fields, more knowledge can be
attained to further the study. Correspondingly, receiving more diverse ethnicities could also
provide valuable information about their experience with self-efficacy development and
perception of leadership accountability. Because of the limited number of respondents in certain
ethnic categories, the ‘other’ category was created to account for their responses, which does
little to provide usable information.
Finally, a qualitative examination could explore the self-efficacy ratings observed by
those who identified as Hispanic. The significance was meaningful, and it could be that there are
cultural aspects that contribute to Hispanic first responders’ sense of self-efficacy in information
gathering. A quantitative examination of this phenomenon may not be enough to fully realize the
intersection of culture, ethnicity, and self-efficacy.
88

Conclusion
With an estimated 240 million 9-1-1 calls for service each year (National Emergency
Number Association, 2021), decision-making in critical situations is vital for communities that
depend on members of fire, law enforcement, and emergency medical services for safety,
security, and life-saving needs. The number of calls has not been projected to decrease justifying
why self-efficacy in decision-making should become a focus of effort for researchers and
organizational leadership. Although the self-efficacy ratings were high, the imbalance was
noteworthy and could be a contributing factor in negative decision outcomes. Leadership must
take an active role in rethinking training and must create an environment that facilitates first-
responder development. Decision-making consists of three components, information gathering,
information placement, and information action. Each component is a vital part of how decisions
are made and should be emphasized in a training regimen. Now that it is understood that first
responders are training for information gathering and improving their self-efficacy in
information action, leadership can interject and promote training for information placement to
put information into context before requiring action to be taken. Moreover, the generally low
ratings in leadership accountability, specifically linked to training opportunities, provide clear
visibility of a gap in first responder needs that may potentially impact first responder self-
efficacy.

89

References
Anderson, B. A. (2017). Controlled information processing, automaticity, and the burden of
proof. Psychonomic Bulletin & Review, 25(5), 1814–1823.
https://doi.org/10.3758/s13423-017-1412-7
Ariel, B., Lawes, D., Weinborn, C., Henry, R., Chen, K., & Brants Sabo, H. (2019). The “less-
than-lethal weapons effect” - Introducing TASERs to routine police operations in
England and Wales: A randomized controlled trial. Criminal Justice and Behavior, 46(2),
280–300. https://doi.org/10.1177/0093854818812918
Artinger, F., Petersen, M., Gigerenzer, G., & Weibler, J. (2015). Heuristics as adaptive decision
strategies in management: Heuristics in management. Journal of Organizational
Behavior, 36(S1), S33–S52. https://doi.org/10.1002/job.1950
Azevedo, R. (2020). Reflections on the field of metacognition: issues, challenges, and
opportunities. Metacognition and Learning, 15(2), 91–98.
https://doi.org/10.1007/s11409-020-09231-x
Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological
Review, 84, 191-215.
Bandura, A. (1989). Human agency in social cognitive theory. American Psychologist, 44, 1175-
1184.
Bandura, A. (1997). Self-efficacy: The exercise of control. Feeman.
Bandura, A. (2006). Guide for constructing self-efficacy scales. In Pajares & T.C. Urdan (Eds.),
Self-efficacy beliefs of adolescents. (pp. 307-337). Information Age Pub., Inc.
Bandura, A. (2012). On the functional properties of perceived self-efficacy revisited. Journal of
Management, 38(1), 9–44. https://doi.org/10.1177/0149206311410606
90

Barrouillet, P., Corbin, L., Dagry, I., & Camos, V . (2014). An empirical test of the independence
between declarative and procedural working memory in Oberauer’s (2009)
theory. Psychonomic Bulletin & Review, 22(4), 1035–1040.
https://doi.org/10.3758/s13423-014-0787-y
Blumberg, D. M., Schlosser, M. D., Papazoglou, K., Creighton, S., & Kaye, C. C. (2019). New
directions in police academy training: A call to action. International Journal of
Environmental Research and Public Health, 16(24), 4941–.
https://doi.org/10.3390/ijerph16244941
Boothroyd, R. A., Green, S., & Dougherty, A. (2019). Evaluation of operation restore: A brief
intervention for first responders exposed to traumatic events. Traumatology, 25(3), 162–
171. https://doi.org/10.1037/trm0000168
Broadbent, D. (1958). Perception and Communication. Pergamon Press.
Council on Criminal Justice Task Force on Policing. (2021, March). Effectiveness of police
training. https://counciloncj.foleon.com/policing/assessing-the-evidence/iv-
effectiveness-of-police-training/
Chiaburu, D. S., & Lindsay, D. R. (2008). Can do or will do?: The importance of self-efficacy
and instrumentality for training transfer. Human Resource Development
International, 11(2), 199–206. https://doi.org/10.1080/13678860801933004
Cho, E., & Kim, S. (2015). Cronbach’s coefficient alpha: Well-known but poorly
understood. Organizational Research Methods, 18(2), 207–230.
https://doi.org/10.1177/1094428114555994
Clark, R. E., Kirschner, P. A., & Sweller, J. (2012). Putting students on the path to learning: the
case for fully guided instruction. American Educator, 36(1), 6–.
91

Constantinidis, C., & Klingberg, T. (2016). The neuroscience of working memory capacity and
training. Nature Reviews. Neuroscience, 17(7), 438–449.
https://doi.org/10.1038/nrn.2016.43
Cohen, M. S. (1993). Metacognitive strategies in support of recognition. Proceedings of the
Human Factors and Ergonomics Society Annual Meeting, 37(16), 1102–1106.
https://doi.org/10.1177/154193129303701614
Cohen M. S., Freeman, J. T., & Thompson, B. B. (2014). Training the naturalistic decision
maker. In C. E. Zsambok & G. Klein (Eds.), Naturalistic Decision-making, (pp. 257-
268). Taylor and Francis. https://doi.org/10.4324/9781315806129
Cowan, N. (2010). The magical mystery four: How is working memory capacity limited, and
why? Current Directions in Psychological Science: A Journal of the American
Psychological Society, 19(1), 51–57. https://doi.org/10.1177/0963721409359277
Cowan, N. (2016). Working Memory Capacity: Classic Edition (1st ed.). Routledge, Taylor &
Francis Group.
Creswell, J. W. & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed
methods approaches. Sage Publications.
Cronbach, L. J. (1951). Coefficient alpha and the internal structures of tests. Psychometrika,
16(3), 297-334.
Cronbach, L. J. & Shavelson, R. J. (2004). My current thoughts on coefficient alpha and
successor procedures. Educational and Psychological Measurement, 64(3), 391–418.
https://doi.org/10.1177/0013164404266386
Csapo, Avugos, S., Raab, M., & Bar-Eli, M. (2015). How should “hot” players in basketball be
defended? The use of fast-and-frugal heuristics by basketball coaches and players in
92

response to streakiness. Journal of Sports Sciences, 33(15), 1580–1588.
https://doi.org/10.1080/02640414.2014.999251
Danells, S. A. (2019) Research design. In G. R. Hancock R. O. The reviewer’ s guide to
quantitative methods in the social sciences (2nd ed.). Routledge.
https://doi.org/10.4324/9781315755649
DeCaro, M. S., Van Stockum, C. A., & Wieth, M. B. (2016). When higher working memory
capacity hinders insight. Journal of Experimental Psychology. Learning, Memory, and
Cognition, 42(1), 39–49. https://doi.org/10.1037/xlm0000152
DeGue, S., Fowler, K. A., & Calkins, C. (2016). Deaths due to use of lethal force by law
enforcement: Findings from the National Violent Death Reporting System, 17 U. S.
States, 2009-2012. American Journal of Preventive Medicine, 51(5), S173–S187.
https://doi.org/10.1016/j.amepre.2016.08.027
Dreyfus, H. L. (2007). The return of the myth of the mental. Inquiry (Oslo), 50(4), 352–365.
https://doi.org/10.1080/00201740701489245
Dubnick. M. J. (2003). Accountability and ethics: reconsidering the relationships. International
Journal of Organization Theory and Behavior, 6(3), 405–441.
https://doi.org/10.1108/IJOTB-06-03-2003-B002
Dubnick. M. J. (2011). Move over Daniel: We need some “accountability space.” Administration
& Society, 43(6), 704–716. https://doi.org/10.1177/0095399711424569
Dubnick, M. J. (2014). Accountability as a cultural keyword. In M. Bovens, R. E. Goodin, & T.
Schillemans (Eds.), Oxford handbook of public accountability (pp. 23-28). Oxford
University Press.
93

Dubnick, M. J. (2020, February 18). Accountability, part 2 [Video]. 2SC@USC
https://2sc.rossieronline.usc.edu/ap/courses/2264/sections/5eca7bc9-d876-4352-a73a-
7d2cda3035a9/coursework/module/cda27692-5402-4364-8578-
54fdad2f309b/segment/c2ce02e5-cdc6-4a00-ac11-48ef27b57bab
Dubnick. M. J., & Justice, J. B. (2006). Accountability and the Evil of Administrative
Ethics. Administration & Society, 38(2), 236–267.
https://doi.org/10.1177/0095399705285999
Dubnick, M. J., & Frederickson, H. G. (2011). Public accountability: Performance measurement,
the extended state, and the search for trust. Kettering Foundation & National Academy of
Public Administration
Dubnick M. J., & Yang, K. (2011). The pursuit of accountability: Promises, problems, and
prospects. In D. C. Menzel & H. L. White (Eds.), The State of Public Administration:
Issues, Challenges, and Opportunities (1st ed.). M. E. Sharpe.
Emergency Vehicle Response. (2020, June 11). First responder vehicle crashes.
https://emergencyvehicleresponse.com/first-responder-vehicle-crashes-higher-than-the-
national-average/
EMS1. (2021, May 27). https://www.ems1.com/ems-products/education/articles/what-is-the-job-
of-a-paramedic-and-what-are-the-requirements-for-certification-SoHHGkJ2os1h1FiH/
Endsley, M. R. (1988) Design and evaluation for situation awareness enhancement. In
Proceedings of the Human Factors Society 32 Annual Meeting (pp. 97-101). Human
Factors Society
Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human
Factors, 37(1), 32–64. https://doi.org/10.1518/001872095779049543
94

Endsley, M. R. (2000). Theoretical underpinnings of situation awareness: A critical review. In M.
R. Endsley and D. J. Garland (Eds.). Situation Awareness Analysis and Measurement.
Lawrence Earlbaum Associates.
Endsley, M. R. (2014). Naturalistic decision-making: Where are we now? In C. E. Zsambok &
G. Klein (Eds.), Naturalistic Decision-making (pp. 269-283). Taylor and Francis.
https://doi.org/10.4324/9781315806129 (1997)
Endsley, M. R., & Roberston, M. M. (2000), Training for situation awareness in individuals and
teams. In M. R. Endsley & D. J. Garlands (Eds.) Situation Awareness Analysis and
Measurement, pp. 3-32
Engel, R. (July 24, 2020) https://www.firerescue1.com/fire-products/online-
training/articles/how-to-join-a-fire-academy-yTvaVBlhv4AnLx7X/
Ericsson, & Charness, N. (1994). Expert performance: Its structure and acquisition. The
American Psychologist, 49(8), 725–747. https://doi.org/10.1037/0003-066X.49.8.725
Frederiksen, & White, B. Y . (1989). An approach to training based upon principled task
decomposition. Acta Psychologica, 71(1), 89–146. https://doi.org/10.1016/0001-
6918(89)90006-1
Fridland. (2014). They’ve lost control: reflections on skill. Synthese (Dordrecht), 191(12), 2729–
2750. https://doi.org/10.1007/s11229-014-0411-8
Frink, D., & Klimoski, R. (1998). Toward a theory of accountability in organizations and human
resources management. Research in Personnel and Human Resources Management, 16,
1-51
95

Gasaway, R. B. (2008). Developing and maintaining: fireground command situation awareness:
Part 1-understanding situation awareness & how it affects your decision-
making. Firehouse, 33(11), 78–.
Gasaway, R. B. (2010). Understanding fireground command: Making decisions under stress. Fire
Engineering, 163(7), 76B–76K.
Geman, S., Bienenstock, E., & Doursat, R. (1992). Neural networks and the bias/variance
dilemma. Neural Computation, 4(1), 1–58. https://doi.org/10.1162/neco.1992.4.1.1
George, D., & Mallery, P. (2008). SPSS for Windows step by step: a simple guide and reference:
15.0 update (8th ed.). Pearson A & B.
Gigerenzer, G. (2008a). Rationality for mortals: How people cope with uncertainty. Oxford
University Press, Incorporated.
Gigerenzer, G. (2008b). Why heuristics work. Perspectives on Psychological Science, 3(1), 20–
29. https://doi.org/10.1111/j.1745-6916.2008.00058.x
Gigerenzer, G. & Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of
bounded rationality. Psychological Review, 103(4), 650–669.
https://doi.org/10.1037/0033-295X.103.4.650
Gigerenzer, G. & Sturm, T. (2012). How (far) can rationality be naturalized? Synthese
(Dordrecht), 187(1), 243–268. https://doi.org/10.1007/s11229-011-0030-6
Gigerenzer, G. & Todd, P. M. (1999). Simple heuristics that make us smart. Oxford University
Press.
Gigerenzer, G., Hertwig, R., & Pachur, T. (2011). Heuristics: The foundations of adaptive
behavior. Oxford University Press.
96

Goldstein, D. G. & Gigerenzer, G. (2002). Models of ecological rationality: The recognition
heuristic. Psychological Review, 109(1), 75–90. https://doi.org/10.1037//0033-
295X.109.1.75
Gopher, D., (1993). The skill of attention control: Acquisition and execution of attention
strategies. In D. E. Meyer & S. Kornblum (Eds.), Attention and Performance XIV4:
Synergies in Experimental Psychology, Artificial Intelligence, and Cognitive
Neuroscience, pp. 299-322. MIT Press.
Gopher, D., Weil, M., & Siegel, D. (1989). Practice under changing priorities: An approach to the
training of complex skills. Acta Psychologica, 71(1), 147–177.
https://doi.org/10.1016/0001-6918(89)90007-3
Grossman, R., & Burke-Smalley, L. A. (2018). Context-dependent accountability strategies to
improve the transfer of training: A proposed theoretical model and research propositions.
Human Resource Management Review, 28(2), 234-247.
https://doi.org/10.1016/j.hrmr.2017.08.001
Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2010). Multivariate data analysis (7th
ed.). Pearson Education, Inc.
Hardy, L., Bell, J., & Beattie, S. (2014). A neuropsychological model of mentally tough
behavior. Journal of Personality, 82(1), 69–81. https://doi.org/10.1111/jopy.12034
Hassin, R. R. (2013). Yes it can: On the functional abilities of the human
unconscious. Perspectives on Psychological Science, 8(2), 195–207.
https://doi.org/10.1177/1745691612460684
Hastie, T., Tibshirani, R., & Friedman, J. H. (2001). The elements of statistical learning: data
mining, inference, and prediction. Springer.
97

Haugland, V . L., & Reime, M. H. (2018). Scenario-based simulation training as a method to
increase nursing students’ competence in demanding situations in dementia care. A mixed
method study. Nurse Education in Practice, 33, 164–171.
https://doi.org/10.1016/j.nepr.2018.08.008
Hayward, R., Asch, S. M., Hogan, M. M., Hofer, T. P., & Kerr, E. A. (2005). Sins of omission:
Getting too little medical care may be the greatest threat to patient safety. Journal of
General Internal Medicine: JGIM, 20(8), 686–691. https://doi.org/10.1111/j.1525-
1497.2005.0152.x
Heidelberg, R. L. (2017). Political accountability and spaces of contestation. Administration &
Society, 49(10), 1379–1402. https://doi.org/10.1177/0095399715581033
Hepler, T. J., & Feltz, D. L. (2012). Take the first heuristic, self-efficacy, and decision-making in
sports. Journal of Experimental Psychology. Applied, 18(2), 154–161.
https://doi.org/10.1037/a0027807
Herman, J. L. (1998). Recovery from psychological trauma. Psychiatry and Clinical
Neurosciences, 52(S1), S98–S103. https://doi.org/10.1046/j.1440-
1819.1998.0520s5S145.x
Hick, W. E. (1952). On the rate of gain of information. Quarterly Journal of Experimental
Psychology, 4(1), 11–26. https://doi.org/10.1080/17470215208416600
Hilal, S. & Litsey, B. (2020). Reducing police turnover: Recommendations for the law
enforcement agency. International Journal of Police Science & Management, 22(1), 73–
83. https://doi.org/10.1177/1461355719882443
Homans, G. C. (1958). Social behavior as exchange. The American Journal of Sociology, 63(6),
597-606. https://doi.org/10.1086/222355
98

Hommel, B. (1998). Automatic stimulus-response translation in dual-task performance. Journal
of Experimental Psychology. Human Perception and Performance, 24(5), 1368–1384.
https://doi.org/10.1037/0096-1523.24.5.1368
Hyman, R. (1953). Stimulus information as a determinant of reaction time. Journal of
Experimental Psychology, 45(3), 188–196. https://doi.org/10.1037/h0056940
Iqbal, K. & Dastgeer, G. (2017). Impact of self-efficacy and retention on transfer of training: The
mediating role of motivation to transfer. The Journal of Management
Development, 36(10), 1270–1282. https://doi.org/10.1108/JMD-06-2015-0087
Iskander, M. (2019). Burnout, cognitive overload, and metacognition in medicine. Medical
Science Educator, 29(1), 325–328. https://doi.org/10.1007/s40670-018-00654-5
Jiang, X. (2022). Obstacles and regulation deconstruction of athletes’ psychological training
based on machine learning algorithm in physical education teaching. International
Transactions on Electrical Energy Systems, 2022. https://doi.org/10.1155/2022/9970811
Johnson, J., & Raab, M. (2003). Take the first: option-generation and resulting choices.
Organization Behavior Humanities Process. 91, 215-229. Doi: 10.1016/S0749-
5978(03)00027-X
Jonides, J., Lewis, R. L., Nee, D. E., Lustig, C. A., Berman, M. G., & Moore, K. S. (2008). The
mind and brain of short-term memory. Annual Review of Psychology, 59(1), 193–224.
https://doi.org/10.1146/annurev.psych.59.103006.093615
Kahneman, D., & Treisman, A. (1984), Changing views of attention and automaticity. In R.
Parasuraman & D. R. Davis (Eds.), Varieties of attention (pp. 29-61). Academic Press
Kalisch, B. J. & Xie, B. (2014). Errors of omission: Missed nursing care. Western Journal of
Nursing Research, 36(7), 875–890. https://doi.org/10.1177/0193945914531859
99

Kantowitz, B. H. & Sorkin, R. D. (1983). Human factors: understanding people-system
relationships. Wiley.
Kass S. J., Herschler, D. A., & Companion, M. A. (1991). Training situational awareness through
pattern recognition in a battlefield environment. Military Psychology, 3(2), 105–112.
https://doi.org/10.1207/s15327876mp0302_3
Kiefer, M. (2012). Executive control over unconscious cognition: Attentional sensitization of
unconscious information processing. Frontiers in Human Neuroscience, 6(2012), 61–61.
https://doi.org/10.3389/fnhum.2012.00061
Klein, G. A. (1988). Naturalistic models of C
3
decision-making. In S. Johnson & A. Levis (Eds.),
Science of command and control: Coping with uncertainty (pp. 86-92). AFCEA
International Press.
Klein, G. A. (1989). Recognition-primed decision (RPD) model of rapid decision making. In G.
A. Klein, J. Orasanu, R. Calderwood, & C. E. Zsambok (Eds.), Decision-making in
action: Models and methods (pp. 138-147). Ablex.
Klein, G. A. (1993). Naturalistic decision making: Implication for design. CSERIAC
Klein, G. A. (2008). Naturalistic decision-making. Hum Factors, 50(3), 456-460.
https://doi.org/10.1518/001872008X288385
Klein, G. A. (2017). Sources of power: How people make decisions (20th ed.). The MIT Press.
Klein, G. A. & Mosier, K. (1995). Applying the naturalistic decision-making perspective to
training. Proceedings of the Human Factors and Ergonomics Society Annual
Meeting, 39(20), 1248–1248. https://doi.org/10.1177/154193129503902001
100

Klein, G. A. & Peio, K. (1989). Use of a Prediction Paradigm to Evaluate Proficient Decision
Making. The American Journal of Psychology, 102(3), 321–331.
https://doi.org/10.2307/1423053
Klein, G. A., Calderwood, R., & Clinton-Cirocco, A. (1986). Rapid decision-making on the fire
ground. Proceedings of the Human Factors Society 30th Annual Meeting, 1, 576-580
Klingberg. (2009). The overflowing brain information overload and the limits of working
memory. Oxford University Press.
Kunde, W., Reuss, H., & Kiesel, A. (2012). Consciousness and cognitive control. Advances in
Cognitive Psychology, 8(1), 9–18. https://doi.org/10.5709/acp-0097-x
Lanza A., Roysircar, G., & Rodgers, S. (2018). First responder mental healthcare: Evidence-
based prevention, postvention, and treatment. Professional Psychology, Research and
Practice, 49(3), 193–204. https://doi.org/10.1037/pro0000192
Lavrakas, P. J. (2008). Encyclopedia of survey research methods. SAGE.
Leung, A. K. Y . & Cohen, D. (2011). Within- and between-culture variation: Individual
differences and the cultural logics of honor, face, and dignity cultures. Journal of
Personality and Social Psychology, 100(3), 507–526. https://doi.org/10.1037/a0022151
Lewin, K., Heider, F., & Heider, G. M. (1936). Principles of topological psychology (1st ed.).
McGraw-Hill Book Co.
Lin, H. H., Lin, T. Y ., Ling, Y ., & Lo, C. C. (2021). Influence of imagery training on adjusting
the pressure of fin swimmers, improving sports performance, and stabilizing
psychological quality. International Journal of Environmental Research and Public
Health, 18(22), 11767–. https://doi.org/10.3390/ijerph182211767
101

Lockton, D. (2012), Simon’s scissors and ecological psychology in design for behavior change.
Available at SSRN: https://ssrn.com/abstract=2125405
Logan, G. D. (1988). Automaticity, resources, and memory: Theoretical controversies and
practical implications. Human Factors, 30(5), 583–598.
https://doi.org/10.1177/001872088803000504
Love, A. M. A., Usher, E. L., Toland, M. D., Railey, K. S., Campbell, J. M., & Spriggs, A. D.
(2020). Measuring police officer self-efficacy for working with individuals with autism
spectrum disorder. Journal of Autism and Developmental Disorders, 51(4), 1331–1345.
https://doi.org/10.1007/s10803-020-04613-1
Maddux, J. E. (2013). Self-efficacy, adaptation, and adjustment: Theory, research, and
application. Springer.
Merino, Y ., Adams, L., & Hall, W. J. (2018). Implicit bias and mental health professionals:
Priorities and directions for research. Psychiatric Services, 69(6), 723–725.
https://doi.org/10.1176/appi.ps.201700294
Millenson, M. L. (1997). Demanding medical excellence: doctors and accountability in the
information age. University of Chicago Press.
Moors, A. (2016). Automaticity: Componential, causal, and mechanistic explanations. Annual
Review of Psychology, 67(1), 263–287. https://doi.org/10.1146/annurev-psych-122414-
033550
Mosier, K. L., & Orasanu, J. (1995). Naturalistic decision-making: A domain-integrated
overview. Proceedings of the Human Factors and Ergonomics Society Annual Meeting,
39(9), 474-477. https://doi.org/10.1177/154193129503900907
102

Mueller, R. O., & Knapp T. R. (2019) Reliability and validity. In G. R. Hancock R. O. The
reviewer’ s guide to quantitative methods in the social sciences (2nd ed.). Routledge.
https://doi.org/10.4324/9781315755649
National University. (2022, December 12). How to become an EMT in California. National
University. https://www.nu.edu/resources/how-to-become-an-emt-in-california/
National Emergency Number Association (2021), 9-1-1 Statistics. NENA.
https://www.nena.org/page/911Statistics
Norman, G. (2010). Likert scales, levels of measurement and the “laws” of statistics. Advances
in Health Sciences Education: Theory and Practice, 15(5), 625–632.
https://doi.org/10.1007/s10459-010-9222-y
Nguyen, T., Lim, C. P., Nguyen, N. D., Gordon-Brown, L., & Nahavandi, S. (2019). A review of
situation awareness assessment approaches in aviation environments. IEEE Systems
Journal, 13(3), 3590–3603. https://doi.org/10.1109/JSYST.2019.2918283
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
Oberauer, K. (2009). Design for a working memory. In B. H. Ross (Ed.), Psychology of learning
and motivation.: (Advances in research and theory) (V ol. 51, pp. 45-100). Academic
Press.
Oberauer, K. (2010). Declarative and procedural working memory: Common principles,
common capacity limits? Psychologica Belgica, 50(3-4), 277–308.
https://doi.org/10.5334/pb-50-3-4-277
Oberauer, K., Farrell, S., Jarrold, C., & Lewandowsky, S. (2016). What limits working memory
capacity? Psychological Bulletin, 142(7), 758–799. https://doi.org/10.1037/bul0000046
103

O’Brien, K. S. & O’Hare, D. (2007). Situational awareness ability and cognitive skills training in
a complex real-world task. Ergonomics, 50(7), 1064–1091.
https://doi.org/10.1080/00140130701276640
O’Connor, A. M. (1995). Validation of a decisional conflict scale. Medical Decision-
making, 15(1), 25–30. https://doi.org/10.1177/0272989X9501500105
O’Neill, J., O’Neill, D. A., Weed, K., Hartman, M. E., Spence, W., & Lewinski, W. J. (2018).
Police academy training, performance, and learning. Behavior Analysis in
Practice, 12(2), 353–372. https://doi.org/10.1007/s40617-018-00317-2
Orasanu, J. (1995). Training for aviation decision-making: The naturalistic decision-making
perspective. Proceedings of the Human Factors and Ergonomics Society Annual Meeting,
39(20), 1258-1262. https://doi.org/10.1177/154193129503902004
Orasanu, J., & Connolly, T. (1993). The reinvention of decision-making. In G. Klein, J. Orasanu,
R., Calderwood, & Zsambok C. E., (Eds.), Decision-making in action: Models and
methods. (pp. 158-171). Norwood, NJ: Ablex.
Peterson, J. B., 12 rules for life: An antidote to chaos. Random House Canada.
Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1991). A manual for the use of
the motivated strategies for learning questionnaire (MSLQ). (ERIC Document
Reproduction Service No. ED338122).
Preston, C (2020, June 28). Police education is broken. Can it be fixed? The Hechinger Report.
https://hechingerreport.org/police-education-is-broken-can-it-be-fixed/
Pylyshyn, Z. W. (2003). Seeing and visualizing: It’ s not what you think. MIT Press.
Quratulain, S., Khan, A. K., Sabharwal, M., & Javed, B. (2021). Effect of self-efficacy and
instrumentality beliefs on training implementation behaviors: Testing the moderating
104

effect of organizational climate. Review of Public Personnel Administration, 41(2), 250–
273. https://doi.org/10.1177/0734371X19876676
Raab, M. & Gigerenzer, G. (2015). The power of simplicity: A fast-and-frugal heuristics
approach to performance science. Frontiers in Psychology, 6, 1672–1672.
https://doi.org/10.3389/fpsyg.2015.01672
Rogers, M. S., McNiel, D. E., & Binder, R. L. (2019). Effectiveness of police crisis intervention
training programs. The Journal of the American Academy of Psychiatry and the
Law, 47(4), 414–421. https://doi.org/10.29158/JAAPL.003863-19
Roscoe, S. N., Cori, L. & Laroche, J., (2001). Predicting human performance, 5th Eds
(Pierrefonds, Quebec: Helio Press).
Ross, L. & Nisbett, R. E. (1991). The person and the situation: perspectives of social
psychology. Temple University Press.
Ruchkin, D. S., Grafman, J., Cameron, K., & Berndt, R. S. (2003). Working memory retention
systems: A state of activated long-term memory. The Behavioral and Brain
Sciences, 26(6), 709–728. https://doi.org/10.1017/S0140525X03000165
Salas, E., Prince, C., Baker, D. P., & Shrestha, L. (1995). Situation awareness in team
performance: Implications for measurement and training. Human Factors, 37 (1), 123-
136.
Saling, L. L. & Phillips, J. G. (2007). Automatic behaviour: Efficient not mindless. Brain
Research Bulletin, 73(1), 1–20. https://doi.org/10.1016/j.brainresbull.2007.02.009
Saus E., Johnsen, B. H., Eid, J., Riisem, P. K., Andersen, R., & Thayer, J. F. (2006). The effect of
brief situational awareness training in a police shooting simulator: An experimental
105

study. Military Psychology, 18(S), S3–S21.
https://doi.org/10.1207/s15327876mp1803s_2
Scott, D., Vangsness, L., & Suss, J. (2022). Perceptual–cognitive expertise in law enforcement:
An object-identification task. Journal of Cognitive Engineering and Decision
Making, 16(3), 157–176. https://doi.org/10.1177/15553434221104600
Shadish, W. R., Cook, T. D., Campbell, D. T. & Campbell, D. T. (2002). Experimental and quasi-
experimental designs for generalized causal inference. Wadsworth/Cengage Learning.
Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of
Economics, 69(1), 99-118. https://doi.org/10.2307/1884852
Simon, H. A. (1979). Rational decision-making in business organizations. The American
Economic Review, 69(4), 493-513.
Simon, H. A. (1990). Invariants of human-behavior. Annual Review of Psychology, 41(1), 1–19.
https://doi.org/10.1146/annurev.ps.41.020190.000245
Singleton, S. (2004). Privacy and twenty-first century law enforcement: accountability for new
techniques. Ohio Northern University Law Review, 30(3), 417–.
Smith, A. (1776). An inquiry into the nature and causes of the wealth of nations. By Adam Smith,
… In three volumes. In Eighteenth Century Collections Online (V ol. 1). Printed for
Messrs. Whitestone, Chamberlaine, W. Watson, Potts, S. Watson [and 15 others in
Dublin].
Souza, A. da S., Oberauer, K., Gade, M., & Druey, M. D. (2012). Processing of representations in
declarative and procedural working memory. Quarterly Journal of Experimental
Psychology (2006), 65(5), 1006–1033. https://doi.org/10.1080/17470218.2011.640403
106

Stajkovic, & Luthans, F. (1998). Social cognitive theory and self-efficacy: Going beyond
traditional motivational and behavioral approaches. Organizational Dynamics, 26(4), 62–
74. https://doi.org/10.1016/S0090-2616(98)90006-7
Stanley, J. & Krakauer, J. W. (2013). Motor skill depends on knowledge of facts. Frontiers in
Human Neuroscience, 7, 503–503. https://doi.org/10.3389/fnhum.2013.00503
Stout, R. J. & Salas, E. (1998). What do we know about training situational
awareness. Proceedings of the Human Factors and Ergonomics Society Annual
Meeting, 42(20), 1371–1373. https://doi.org/10.1177/154193129804202001
Suss, J. & Ward, P. (2018). Revealing perceptual–cognitive expertise in law enforcement: an
iterative approach using verbal-report, temporal-occlusion, and option-generation
methods. Cognition, Technology & Work, 20(4), 585–596.
https://doi.org/10.1007/s10111-018-0493-z
Szmalec, A., Vandierendonck, A., & Kemps, E. (2005). Response selection involves executive
control: Evidence from the selective interference paradigm. Memory & Cognition, 33(3),
531–541. https://doi.org/10.3758/BF03193069
Tobon, S. (2021). Community policing in the developing world: Community policing did not
improve trust or reduce crime. Science (American Association for the Advancement of
Science), 374(6571), 1046–. https://doi.org/10.1126/science.abm4112
Toner, J., Montero, B. G., & Moran, A. (2015). The perils of automaticity. Review of General
Psychology, 19(4), 431–442. https://doi.org/10.1037/gpr0000054
Tschannen-Moran, M. & Gareis, C. R. (2004). Principals’ sense of efficacy: Assessing a
promising construct. Journal of Educational Administration, 42(5), 573–585.
https://doi.org/10.1108/09578230410554070
107

Tversky, A. & Kahneman, D. (1974). Judgment under uncertainty: heuristics and biases. Biases
in judgments reveal some heuristics of thinking under uncertainty. Science (American
Association for the Advancement of Science), 185(4157), 1124–1131.
https://doi.org/10.1126/science.185.4157.1124
Walker, S. E. (2005). The new world of police accountability. SAGE Publications.
https://doi.org/10.4135/9781452204352
Walsh, D. P. J., & Conway, V . (2011). Police governance and accountability: overview of current
issues. Crime, Law, and Social Change, 55(2), 61–86. https://doi.org/10.1007/s10611-
011-9269-6
Washington Post. (April 1, 2022). Number of people shot to death by the police in the United
States from 2017 to 2022, by race [Graph]. In Statista. Retrieved April 03, 2022, from
https://www-statista-com.libproxy2.usc.edu/statistics/585152/people-shot-to-death-by-us-
police-by-race/
Wayne, C., Porat, R., Tamir, M., & Halperin, E. (2016). Rationalizing conflict: The polarizing
role of accountability in ideological decision-making. The Journal of Conflict
Resolution, 60(8), 1473–1502. https://doi.org/10.1177/0022002714564431
Weisfeld-Spolter, S. F., Rippé, C., & Gould, S. (2018). Integrating affect, cognition, and culture
in Hispanic financial planning. International Journal of Bank Marketing, 36(4), 726–743.
https://doi.org/10.1108/IJBM-09-2017-0201
Wickens, C. D. (1984). Engineering psychology and human performance. Charles E. Merrill
Publishing Company.
Wickens, C. D. & McCarly, J. S. (2008). Applied attention theory. CRC Press.
108

Wild, J., Greenberg, N., Moulds, M. L., Sharp, M. L., Fear, N., Harvey, S., Wessely, S., &
Bryant, R. A. (2020). Pre-incident training to build resilience in first responders:
Recommendations on what to and what not to do. Psychiatry (Washington, D.C.), 83(2),
128–142. https://doi.org/10.1080/00332747.2020.1750215
Winter, D. D. N., & Koger, S. M. (2004). The psychology of environmental problems (2nd ed.).
Lawrence Erlbaum
Witztum, A. (2005). Social circumstances and rationality: Some lessons from Adam Smith why
we may not all be equally sovereign. The American Journal of Economics and Sociology,
64(4), 1025-1047. https://doi.org/10.1111/j.1536-7150.2005.00424.x
Woodworth, R.S. (1938). Experimental psychology. Henry Holt and Company.
Wu, W. (2014). Attention (1st ed.). Routledge.
Yates, J. F. & de Oliveira, S. (2016). Culture and decision making. Organizational Behavior and
Human Decision Processes, 136, 106–118. https://doi.org/10.1016/j.obhdp.2016.05.003
Yelon, S. L., & Ford, J. K. (1999). Pursuing a multidimensional view of transfer. Performance
Improvement Quarterly, 12(3), 58–78. https://doi.org/10.1111/j.1937-
8327.1999.tb00138.x
Yelon, S. L., Sleight, D., & Ford, J. K. (2004). Intention to transfer: How do autonomous
professionals become motivated to use new ideas? Performance Improvement
Quarterly, 17(2), 82–103. https://doi.org/10.1111/j.1937-8327.2004.tb00309.x
Zadeh, S. E., Haussmann, R., & Barton, C. D. (2019). Healthcare risk managers’ consensus on
the management of inappropriate behaviors among hospital staff. Journal of Healthcare
Risk Management, 38(4), 32–42. https://doi.org/10.1002/jhrm.21349
109

Zeidan, A. J., Khatri, U. G., Aysola, J., Shofer, F. S., Mamtani, M., Scott, K. R., Conlon, L. W.,
Lopez, B. L., & Runde, D. P. (2019). Implicit bias education and emergency medicine
training: Step one? Awareness. AEM Education and Training, 3(1), 81–85.
https://doi.org/10.1002/aet2.10124
Zsambok, C. E. (2014). Naturalistic decision-making: Where are we now. In C. E. Zsambok &
G. Klein (Eds.), Naturalistic Decision-making (pp. 3-16). Taylor and Francis.
https://doi.org/10.4324/9781315806129

Appendix A: Adaptive Toolbox
Adaptive Toolbox, Heuristic Options Based on Limited Information and/or Limited Time
Heuristic Definition Ecologically rational if: Bold predictions
Recognition heuristic If one of two alternatives is
recognized, infer that it has the
higher value on the criterion.
Recognition validity >.5 Contradicting information
about the recognized object
is ignored, less-is-more
effect if α>β, forgetting is
beneficial.
Fluency heuristic If one alternative is recognized faster
than another, infer that it has the
higher value on the criterion.
Fluency validity >.5 Less-is-more effect,
forgetting is beneficial.
Take the best Infer which of two alternatives has the
higher value by (a) searching
through cues in order of validity, (b)
stopping the search as soon as a cue
discriminates, (c) choosing the
alternative this cue favors.
Cue validities vary highly,
moderate to high
redundancy, scarce
information.
Can predict as accurately as
or more than multiple
regression, neural
networks, exemplar
models, and classification
and regression trees
Tallying To estimate a criterion, do not estimate
weights but simply count the
number of favoring cues.
Cue validities vary little, low
redundancy.
Can predict as accurately as
or more than multiple
regression.
Satisficing Search through alternatives and
choose the first one that exceeds
your aspiration level.
Decreasing populations, such
as those in seasonal
mating pools
Unknown
1/N; equality heuristic Allocate resources equally to each of
N alternatives.
High unpredictability, small
learning sample, large N.
Can outperform optimal
asset allocation models.
110

Heuristic Definition Ecologically rational if: Bold predictions
Default heuristic If there is a default, do nothing about
it.
Values of those who set
defaults match with those
of decision maker,
consequences of choice
hard to predict.
Can predict behavior when
trait and preference
theories fail.
Tit-for-tat Cooperate first, keep a memory of
Size 1, and then imitate your
partner’s last behavior.
If other players also play tit-
for-tat; if the rules of the
game allow only defection
or cooperation, but not
divorce.
Can earn more money than
optimization (backward
induction).
Imitate the majority Look at the majority of people in your
peer group and imitate their
behavior.
Environment is not or only
slowly changing; info
search is costly or time-
consuming.
Mass phenomena, cultural
evolution.
Imitate the successful Look for the most successful person
and imitate his or her behavior.
Individual learning slow, info
search costly and time-
consuming.
Cultural evolution.

Note. From “Why Heuristics Work,” by G. Gigerenzer, 2008, Perspectives on Psychological Science, 3(1), 20–29, p. 23
(https://doi.org/10.1037/0033-295X.103.4.650). Copyright 2008 by Association for Psychological Science.

111
112

Appendix B: Detailed Situational Assessment Levels
The first level in SA is to recognize the status of the elements that are affecting the
immediate environment (Endsley, 2014, Gasaway, 2008b, 2010). The perception of relevance is
essential in that it incorporates all indicators of current importance, similar to what was
previously discussed by Gigerenzer (2008a) as cue analysis. Gasaway (2010) explains that it is
about using all the senses to absorb as much as possible. Consider that a fire incident commander
might need to know what building is on fire, how long the fire has been burning, what units are
on site, what units are en route, where civilians are located, current unit capabilities, etc. There is
no meaning to this information, it is merely a collection of data that creates an immediate
snapshot of the environment as perceived by a decision-maker (Endsley, 2014). In Endsley
(2000), she adds that there is a limit to how much data can be translated into task-relevant
information. So what information is available for Level 2 SA is limited by the decision-maker’s
ability to sift through the noise, because more data does not equate to more information.
The second level in SA is about how to make meaning of the information absorbed. Much
of that information within the environment is disjointed, contains varying levels of importance,
and differs in significance from the objectives of the decision-maker (Endsley, 2014). Pattern
recognition, memory structures, and alignment with goals are connected by experienced
decision-makers to create the ability to project a future yet unrealized (Endsley, 2014; Klein,
1993; Renaud, 2010). For example, Endsley (2014) refers to a situation where a pilot might
recognize that the current location, the current battle status, and the location and formation of
enemy aircraft collectively create a scenario of a specific type of attack. Independently, the
information has little significance but linked together, it means that a ground attack is imminent.
Endsley (2014) adds that a novice might view the Level 1 SA the same as an experienced person
113

but cannot create meaning. Moreover, the meaning is further complicated by the limited ability
of the human brain to collect and process multiple individual pieces of information (Broadbent,
1958; Kantowitz & Sorkin, 1983; Wickens, 1984; Wickens & McCarly 2008; Woodworth, 1938).
The final level in SA is the highest level in which the perception and meaning cultivate a
decision-maker’s ability to project a future environment and directly link it to their goals for
either making a decision or holding on for more information (Endsley, 1995). At this level, time
is both friend and foe depending on how the decision-maker has made meaning. A failure to act
could result in the situation becoming uncontrollable, or conversely, acting too quickly might add
to the chaos of the environment (Endsley, 2014; Klein et al., 1986). At this moment, Gasaway
(2010) highlights that a decision-maker must possess the self-efficacy to rely on what is
colloquially termed “gut feeling” to either decide or not decide based on an incomplete picture.
The “gut feeling” is not random or done without thought. It is heavily influenced by Klein’s
(2017) RPD model and Simon’s (1955, 1979) satisficing, which equates to isolating the mental
model that most closely matches the perceived environment and choosing the best available
course of action. Gasaway (2010) further warns that the litigious nature of American society can
often put the decision-maker in a compromised position because attempting to defend a hunch is
not desirable and only understandable by the person who perceived the environment in question.
The question now becomes one of training decision-makers to recognize decision points and
instilling in them a high enough quantity of mental models to create ease of perception, meaning-
making, and efficient future projection.
114

Appendix C: Self-Efficacy Questionnaire Instructions
The following questions will address what you think your capabilities are regarding high-
stress, time-sensitive situations in which you find yourself having to make quick decisions that
affect you, others, and your immediate environment.
In each of the following survey sets, please indicate your level of confidence at this point
in time in your job experience and training. For best results, please answer as you truly feel, not
how you assume you should feel. Your name and other identifying information will be kept
confidential and will not be released to anyone and any time for any reason. Honest answers will
yield the best results and can or may be used to improve the workplace environment to facilitate
proper training and supervision of all those who work in the first responder community.
As you answer each question, your scenario is as follows:
When arriving on the scene during a critical incident in which time is limited and decisions are
crucial, consider the following statement and assess your level of confidence.
Your degree of confidence will be based on a 10-point scale:
0 1 2 3 4 5 6 7 8 9 10
I cannot I doubt I I’m fairly certain I can
do that can do that I can do that do that
If it is something you know you can do, rate it as 10. If it is something you cannot do, rate it as 0.
If you assess your confidence somewhere in the middle, provide your best judgment between
doubt and fairly certain.

115

Appendix D: Self-Efficacy Questionnaire (Demographics)
The following questions will establish background information that will help contribute
to a deeper evaluation of the data. All questions are optional. (4 questions)
1. Gender
Female
Male
Nonbinary
Prefer to describe ___________
Decline to state

2. Age
Under 25
25–34
35–44
45–54
> 54
Decline to state
3. Race/Ethnicity
African American or Black
American Indian or Alaskan
Native
Asian
Latinx
Native Hawaiian or Other Pacific
Islander
White
Multiracial
Prefer to describe
Decline to state
4. Current employment status
Employed full-time
Employed part-time
Unemployed
Retired
Other
Decline to state
116

Appendix E: Self-Efficacy Questionnaire (Demographics/Screening)
The following questions will establish background information that will help contribute
to a deeper evaluation of the data. If question 1 is answered “not a first responder,” then the
survey will discontinue prior to consent. (9 Questions)
1. First responder employment
Law Enforcement
Fire
Emergency Medical Services
Emergency Medical Technician
Not a first responder

2. Formal Education
High School Diploma or equivalent
Some college or trade/technical school
Trade/technical school certificate
Associates degree
Bachelor’s degree
Master’s degree
Doctoral or professional degree
Prefer to describe _______________

3. Employment as first responder (years)
0–4
5–9
10–14
15–19
20–24
25 or more
4. Rank/Leadership Status

Junior/limited leadership responsibility
Moderate/some leadership responsibility
Senior/positional leadership responsibility
Management/significant leadership position

117

5. Frequency of training received (classroom or on-the-job) in decision-making
protocols (i.e., if this presents, do that). (IG)

Weekly (at least once/week)
Monthly (at least once/month)
Semi-Annual (at least twice/year)
Annual (at least once/year)
Other
Never

6. Frequency of training received (classroom or on-the-job) in situational awareness
(i.e., observational and/or consideration of surroundings). (IP)

Weekly (at least once/week)
Monthly (at least once/month)
Semi-Annual (at least twice/year)
Annual (at least once/year)
Other
Never

7. Frequency of training received (classroom or on-the-job) in tactics and procedures
(i.e., physical techniques and/or use of physical tools). (IA)

Weekly (at least once/week)
Monthly (at least once/month)
Semi-Annual (at least twice/year)
Annual (at least once/year)
Other
Never

8. How often are you supervised on the job?

Daily (at least once/day)
Weekly (at least once/week)
Monthly (at least once/month)
Semi-Annual (at least twice/year)
Annual (at least once/year)
Other
Never

118

9. How long has it been since last training or formal event debrief?

About one day
About one week
About one month
About one year
More than one year
119

Appendix F: Self-Efficacy Questionnaire: Information Gathering
Rate your degree of confidence by recording a number from 0 to 10 using the scale given below:
0 1 2 3 4 5 6 7 8 9 10
I cannot I doubt I I’m fairly certain I can
do that can do that I can do that do that
Information Gathering
How confident are you that you can do the tasks below on a scale of 0–10 with 0 meaning “I
cannot do that” and 10 meaning “I am very confident I can do that.”
Confidence
(0–10)
1. Recognize a time you need to make a decision. (IG) ______
2. Rely on formal training to evaluate a situation. (IG) ______
3. Evaluate a situation based on experience. (IG) ______
4. Evaluate a situation without having to analyze all possible solutions. (IG) ______
5. Identify relevant information in a critical situation. (IG) ______
6. Identify your objectives in a critical situation. (IG) ______
7. Identify when to stop searching for more information. (IG) ______
8. Filter out potentially irrelevant information. (IG) ______
9. Recognize a risk-taking opportunity during a critical situation. (IG) ______
10. Take risks during training. (IG) ______
11. Learn from mistakes made during training. (IG) ______
12. Trust your leader’s input during learning situations. (IG) ______
120

Appendix G: Self-Efficacy Questionnaire: Information Placement
Rate your degree of confidence by recording a number from 0 to 10 using the scale given below:
0 1 2 3 4 5 6 7 8 9 10
I cannot I doubt I I’m fairly certain I can
do that can do that I can do that do that
Information Placement
How confident are you that you can do the tasks below on a scale of 0–10 with 0 meaning “I
cannot do that” and 10 meaning “I am very confident I can do that.”
Confidence
(0–10)
1. Interpret a critical situation. (IP) ______
2. Form your goals in alignment with observations in critical situations. (IP) ______
3. Adjust your situational analysis from one event to the next. (IP) ______
4. Adjust your situational analysis from one moment to the next. (IP) ______
5. Sort relevant and irrelevant information. (IP) ______
6. Make connections between related pieces of relevant information. (IP) ______
7. Use relevant information to project possible future events. (IP) ______
8. Understand how multiple pieces of information create a picture of an event. (IP) ______
9. Assess the accuracy of your goals in the current environment. (IP) ______
10. Assess your situation independently. (IP) ______
11. Assess your situation as part of a group. (IP) ______
12. Evaluate your assessment of an event after the event concludes. (IP) ______
13. Discuss your awareness of a situation with leadership. (IP) ______
14. Discuss your awareness of a situation with peers. (IP) ______
121

Appendix H: Self-Efficacy Questionnaire: Information Action
Rate your degree of confidence by recording a number from 0 to 10 using the scale given below:
0 1 2 3 4 5 6 7 8 9 10
I cannot I doubt I I’m fairly certain I can
do that can do that I can do that do that
Information Action
How confident are you that you can do the tasks below on a scale of 0–10 with 0 meaning “I
cannot do that” and 10 meaning “I am very confident I can do that.”
Confidence
(0–10)
1. Produce the appropriate physical response in a critical situation. (IA) ______
2. Physically act according to relevant information. (IA) ______
3. Act physically with intention in a high-stress critical situation. (IA) ______
4. Respond automatically with expected outcomes in a critical situation. (IA) ______
5. Quickly employ the instruments of your trade automatically. (IA) ______
6. Perform the physical demands of your job. (IA) ______
7. Accurately repeat trained tasks during a critical situation. (IA) ______
8. Rely on your physical (athletic, etc.) training during a critical situation. (IA) ______
9. Switch between physical actions and mental tasks during a critical situation. (IA) ______
10. Switch between physical and verbal actions during a critical situation. (IA) ______
11. Disengage a physical response when no longer necessary during an event. (IA) ______
122

Appendix I: Perception of Organizational Support Questionnaire
Rate your degree of truth by recording a number from 0 to 10 using the scale given below:
0 1 2 3 4 5 6 7 8 9 10
Always Mostly Neither Mostly Always
False False True/False True True

Organizational Accountability
In your role as a first responder, what is your perception of the following activities and support
of your organization?
Truth
(0–10)
1. I feel comfortable taking risks during training. ______
2. My leaders allow me to learn from my mistakes during training. ______
3. My organization encourages trying new tactical methods (physical). ______
4. My organization encourages trying new tactical methods (situational). ______
5. I receive timely feedback from my leaders following training events. ______
6. I am able to provide input to my leaders after training events. ______
7. My leaders seek input following training events. ______
8. Trainers and leaders want me to learn from mistakes made during training events. ______
9. My organization encourages learning from mistakes made during real-time events. ______
10. I can expect to get reprimanded for mistakes made during training events. ______
11. I can expect to get reprimanded for mistakes made during real-time events. ______
12. I can expect, as much as possible, and when possible, to be provided with information that
helps me prepare mentally for real-time events. ______
13. Feel that leadership manages workload with time for training. ______
123

14. Sliding Scale
Approximate the percentage of work time spent training versus working.
0%--------------------------------------------------------------------------------100%

Daily – At least once/daily.
Weekly – At least once/weekly.
Monthly – At least once/monthly.
Annually – At least once/yearly.
Never – Has not occurred in the last year or longer.
15. I am trained (Daily/Weekly/Monthly/Annually/Never) for problem-solving.
16. I am trained (Daily/Weekly/Monthly/Annually/Never) for tactics/procedures.
Open Ended Addition
17. Is there anything you would like to add about your organization or leadership that you
consider useful in the context of the research as you understand it?

Abstract (if available)

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

Gender disparity in law enforcement

PDF

The relationship between parenting styles, career decision self-efficacy, and career maturity of Asian American college students

PDF

The relationship of students' self-regulation and self-efficacy in an online learning environment

PDF

The relationship between ethnicity, self-efficacy, and beliefs about diversity to instructional and transformational leadership practices of urban school principals

PDF

Examining mathematics anxiety and mathematics teaching self-efficacy of elementary school teachers in a Hawaii school district

PDF

The importance of mentoring in leadership self-efficacy for women in supply chain: a qualitative study

PDF

The importance of mentoring in leadership self-efficacy for women in supply chain: a qualitative study

PDF

Examining the pandemic’s impact on remote worker wellness in community colleges: organizational lessons and strategies

PDF

Employing cognitive task analysis supported instruction to increase medical student and surgical resident performance and self-efficacy

PDF

What is the relationship between early childhood teachers' training on the development of their teaching self-efficacy?

PDF

Women of color: self-efficacy and sustainability as administrators in education

PDF

Technology integration and self-efficacy of in-service secondary teachers in an international school

PDF

Structures for change: involving faculty in equity-based decision-making in independent schools

PDF

One Hawai’i K-12 complex public school teachers’ level of computer self-efficacy and their acceptance of and integration of technology in the classroom

PDF

Exploring primary teachers' self-efficacy and technology integration in early reading instruction

PDF

The effect on teacher career choices: exploring teacher perceptions on the impact of non‐instructional workload on self‐efficacy and self‐determination

PDF

What are the relationships among program delivery, classroom experience, content knowledge, and demographics on pre-service teachers' self-efficacy?

PDF

The underrepresentation of women in science, technology, engineering, and mathematics (STEM) leadership positions

PDF

Navigating the academy and beyond: an examination of major and career self-efficacy of Latin* first-generation college students

PDF

The collective efficacy of a Jewish community to protect itself against active threats

Asset Metadata

Creator Guidos, Jason (author)

Core Title Leadership, accountability, and decision-making: An examination of first-responder experience and self-efficacy in real-time decision-making to improve community outcomes

School Rossier School of Education

Degree Doctor of Education

Degree Program Educational Leadership

Degree Conferral Date 2022-12

Publication Date 01/17/2023

Defense Date 12/06/2022

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

Tag accountability,decision-making,first-responders,information action,information gathering,information placement,leadership,OAI-PMH Harvest,self-efficacy,Training

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Brady, Melanie (committee chair), Green, Alan (committee chair), Phillips, Jennifer (committee member)

Creator Email jasonguidos@yahoo.com,jguidos@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC112715984

Unique identifier UC112715984

Identifier etd-GuidosJaso-11417.pdf (filename)

Legacy Identifier etd-GuidosJaso-11417

Document Type Dissertation

Format theses (aat)

Rights Guidos, Jason

Internet Media Type application/pdf

Type texts

Source 20230118-usctheses-batch-1001 (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. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given.

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