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IJEMHHR • VOL. 19, No. 4 • 2017 1
International Journal of Emergency Mental Health and Human Resilience,Vol.19, No. 4, pp 1-9 © 2017 OMICS International ISSN 1522-4821
Challenges and Feasibility of Applying Reasoning and Decision-
Making for a Lifeguard Undertaking a Rescue
*Correspondence regarding this article should be directed to:
david@szpilman.com
ABSTRACT: In areas where lifeguard services operate, less than 6% of all rescued persons need medical
attention and require CPR. In contrast, among areas where no lifeguard services are provided almost 30%
require CPR. This difference indicates in importance of the lifeguard. Lifeguard work requires effective problem
identication, diagnostic strategies and management decisions to be made in high-risk environments, where time
is of the essence. The purpose of this investigation was to assess all variables involved in lifeguard work related
to a water rescue, and how the information obtained could inform lifeguard training and therefore performance.
Methods: By using the drowning timeline, the authors explored all variables involved in a single rescue event
by inviting 12 lifeguards to complete a survey of their professional role using a three-round Delphi survey
technique. The total potential number of decisions for each phase and sub-phases, the number of variables, the
probability of a single event repeating, the duration of each sub-phase and amount of variables demanded per
minute were measured. Each sub-phase was presented as predominantly rational (if less than 1 variable per/min)
or intuitive (if more than 1/min). Results: The variables identied in sub-phases were: “preparation to work” (8
variables and 0.0001 variables/min) and “prevent” (22 variables; 0.03 variables/min); these sub-phases were
predominately considered to lead to rational decisions. The variables identied during “rescue” (27 variables
and 2.7 variables/min) and “rst-aid” (7 variables and 1.7 variables) were predominantly considered intuitive
processes. Conclusion: This study demonstrates the complexity of a decision-making process during the quick,
physically and mentally stressful moments of rescuing someone. The authors propose better decision-making
processes can be achieved by reducing the time interval between identication of a problem and making a
decision. Understanding this complex mechanism may allow more efcient training resulting, in faster and more
reliable decision-makers, with the overall benet of more lives saved.
KEYWORDS: Drowning, Prevention, Preparation, Rescue, Mitigation, Decision-making, Reasoning
David Szpilman*
Medical Director of Brazilian Life Saving Society –
SOBRASA, Study Center - Civil Defense – Rio de Janeiro
City, Brazil
Jenny Smith
Senior Lecturer and Chartered Psychologist – University of
Chichester, UK
Billy Doyle
Senior Lifeguard Piha Lifeguard Service, New Zealand
Rachel Grifths
Communication Director – Aquatic Safety Research Group,
USA
Mike Tipton
Human & Applied Physiology, Extreme Environments Laboratory
Department of Sport & Exercise Science, University of Portsmouth, UK
2
INTRODUCTION
Worldwide there are approximately 42 drowning deaths per
hour each day. This is probably an underestimation of the problem,
even for high-income countries (World Health Organization 2015).
Where lifeguard services operate, less than 6% of all rescued
persons need medical attention and 0.5% require CPR (Szpilman
et al., 2012). By contrast, Venema reported almost 30% of persons
rescued from drowning by bystanders required CPR (Venema et
al., 2018). This difference may be because rescue is delayed when
bystanders undertake a rescue (Szpilman et al., 2012).
Lifeguarding represents a major mitigation of drowning deaths.
However, this is a complex, physically and mentally demanding
task. Following a period of quiet surveillance an emergency
situation arises in which critical decisions must be made and intense
physical actions are completed, many of which must be conducted
sequentially for a successful outcome. Other physiological,
cognitive and experiential factors in a successful rescue include: the
lifeguard’s level of experience (Page et a., 2011; Barcala-Furelos
et al., 2014) mental and physical preparedness; levels of cognitive
and physiological arousal (inuenced by sleep adequacy for
example); levels of energy and hydration and other cognitive and
emotional factors including underlying levels of stress, cognitive
workload, presence of distractions and the lifeguard’s mind-set.
The mental and physical demands of lifeguarding require a
high level of emotional resiliency and commitment to undertake
rigorous physical training. The risk of failure can be mitigated
by frequent skills training and implementation of effective
systems that reduce the likelihood of systematic error, such as:
limiting surveillance times to reduce fatigue; the use of elevated
lifeguard towers to improve surveillance effectiveness and the
use of hazard signs to restrict access to beach dangers. Despite
such mitigations, the criticality and complexity of a lifeguard’s
role can induce tremendous internal pressures. In contrast to a
normal healthcare setting, the environments lifeguards operate in
are largely uncontrolled, chaotic and include many complicating
uncontrollable variables such as surf, rip currents, wind and others.
During a rescue, lifeguards are required to identify problems,
execute diagnostic strategies and select appropriate management
decisions. They must make numerous complex decisions quickly in
a high risk environment that engenders physical and mental stress
with high potential for failure and negative consequences (Page
et al., 2011; Lanagan-Leitzel et al., 2010). The drowning process
from immersion to cardiac arrest usually occurs within seconds to a
few minutes (Szpilman et al., 2014). Early and effective rescue may
interrupt this process and prevent serious consequences, including
the need for resuscitation and life-long medical complications
(Szpilman et al., 2012).
The total number of decisions made by a lifeguard during
a single rescue has never been measured. This number must be
large given that each decision may have at least two alternative
options. Some decisions will be conscious (rational) and others
more subconscious (intuitive) and developed over time due to
conditioning and training (“experience”). Subconscious decision-
making is often described as ‘rule-based reasoning’ and is an
effective and cognitively efcient method of decision-making
(particularly under duress and for solving familiar problems)
compared to a slower and deliberate conscious decision-making
process known as ‘rst principle reasoning’ (Reason et al., 1990).
Reasoning and decision-making can be divided into analytic
(rational) and intuitive (naturalistic). According to Legrenzi P. et
al. “reasoning and decision-making” are alike in that they both
depend on the construction of mental models. One of the most
important mechanisms for effective decision-making is that
individuals are likely to restrict their thoughts to what is explicitly
represented in their models. Reasoning is a cognitive process by
which people start with information and come to conclusions
that go beyond that information. Psychological heuristic methods
(intuitive) are used to speed up the process of nding a satisfactory
What is known about this topic?
• Worldwide there are approximately 42 drowning deaths per hour each day. Drowning is a major cause of death
especially among children.
• In areas where lifeguard services operate, less than 6% of all rescued persons need medical attention and fewer
(0.5%) require CPR. In contrast, in areas where no lifeguard services are provided almost 30% of drowning
victims require CPR. This difference indicates the importance of the lifeguard’s role and the quality of their
training in early detection of drowning.
• Lifeguard work requires effective problem identication, diagnostic strategies, and management decisions to be
made in high-risk environments where time is of the essence.
• A plethora of decisions are required to execute a single rescue event implying a high risk of error.
What the paper adds
• For the rst time, this study claries and demonstrates the complexity of a lifeguards’ decision-making process
during the quick, physically and mentally stressful moments of rescuing someone.
• The authors propose better decision-making processes suggesting to a good (but not ideal) outcome can be
achieved by reducing the time interval between identication of a problem and making a decision.
• The understanding of this complex mechanism and associated variables may result in more efcient training to
develop faster and more reliable decision-makers, and consequently enhance the odds of successful rescue.
Szpilman, Smith, Doyle, Grifths & Tipton • Reasoning and Decision-Making while Facing a Rescue
IJEMHHR • VOL. 19, No. 4 • 2017 3
solution via mental shortcuts to ease cognitive load (Reason et
al., 1990). Heuristic refers to experience-based techniques for
problem solving, learning and discovery that nd a solution which
is not guaranteed to be optimal, but good enough for a given set
of goals (Legrenzi et al., 1993; Wu et al., 2012) and without too
much effort. However, success solving one type of problem does
not predict success solving another (Ilgen et al., 2012). Currently
lifeguards are advised to “think carefully” when confronted with
a problem (i.e., employ analytical reasoning). Based on cognitive
load theory (Van et al., 2010) it is possible that this advice may
overwhelm working memory (Cognitive overload) and therefore be
detrimental, especially when conducting a task such as surveillance
as detriments in signal detection can occur when the observer is
engaged in more than one cognitive task.
The purpose of this investigation was to assess the variables
involved in lifeguard work related to a water rescue in the context
of the drowning timeline (Szpilman et al., 2016) and consider
how the information obtained could inform lifeguard training to
and consequently improve performance. This is the rst time such
a paradigm-based conceptual analysis has been undertaken with
lifeguarding; therefore no previous literature exists on this subject
for lifeguards.
METHODS
Drowning Timeline
The Drowning Timeline is a model (Szpilman et al., 2016)
that provides a description of every component of the drowning
process (e.g., highlighting triggers, actions and interventions from
a temporal perspective). It has a three phase temporal sequence.
The phases are described as “Pre-event”, “Event” and “Post-
event”. The Pre-event phase includes all preparations required to
understand, plan and implement prevention strategies, reaction
and mitigation, and the necessary preventative actions (Active or
Reactive) to minimize the probability of an incident occurring. The
Event phase begins with identication of the need for rescue and
the rescue itself. The mitigation begins during the Event phase and
continues after extrication has ended during the Post-event phase.
The Post-event phase includes the provision of rst-aid and medical
care (mitigations). Using the Drowning Timeline we explored all
of the variables involved in these three phases. The Pre-event phase
was further subdivided into two sub-phases: Preparation to work
and Preparation to prevent/anticipate the rescue. The event phase
included all variables relating to the rescue and the Post-event
phase included all the actions related to mitigation (rst-aid and
medical care).
Survey of the Lifeguard Tasks
Following ethical approval from the scientic committee at
the Brazilian Lifesaving Society, 12 Brazilian surf lifeguards each
with more than ten years of experience (average age 33 years, SD
6 years) were selected to participate using a purposive sampling
strategy. An electronic information sheet was distributed to each
lifeguard and written informed consent was obtained.
A three-round Delphi survey technique was employed. The
Delphi survey is a group facilitation technique which is an iterative
multi-stage process designed to transform opinion into group
consensus (Hasson et al., 2000). During round one, lifeguards were
shown the drowning timeline in an adapted format including all the
phases and sub-phases described above that related to their duties
(actions). Each action-based facet of daily work corresponded to
one phase or another. Participants were asked to identify all the
variables in each group (and alternatives) that would require a
decision (YES or NO). The adapted drowning timeline model was
presented as groups of action variables dened below:
a. Pre-rescue phase-preparation to work: Lifeguard
background (Emotional, physical and technical).
b. Preparation to prevent/anticipate rescue: Includes
transit to work (how difcult and stressful), preparations on work
day at headquarters (well-being and supported), arriving at the
duty, patrolling and identifying the hazards, equipment availability
during a rescue and the ability to identify the victim at risk.
c. The event phase (Rescue) includes: Calling back-
up, running to the rescue, swimming to approach the victim,
approaching the victim, towing and transporting from water to dry
land (Barcala-Furelos et al., 2014).
d. The post-rescue phase includes: Any rst aid actions
(primarily the delivery of basic life support to the drowning victim)
(ILS Board of Directors 2013).
During this round participants were also asked to include or
suggest modication to any variable group or specic variables.
Following the identication of the variables and any possible
alternative responses in round 1, one of the authors (DS), who
has 30 years of experience as a qualied lifeguard, collated the
anonymous data and re-sent an overview to the same 12 participants.
The possible responses for each variable were transformed into
a dichotomous “Yes” or “No” answer. In round 2, participants
identied any potential new variables, qualitative responses or
both. In round 3, participants had a nal chance to gain consensus.
The responses were then collated and analyzed.
The Probability that the Same Event Response can
be repeated
The probability that exactly the same event might be repeated
was used as a way to measure how many variable responses
were involved in each phase/sub-phase. This provided a means
to correlate the difculty to predict responses and therefore train
lifeguards.
Duration Estimation of Each Phase/Sub-phases
The amount of time lifeguards spend in each phase or sub-phase
was estimated based on the longest possible duration determined
from the longest durations recommended by current best published
evidence or practice, or from expert opinion. The duration of the
Pre-event phase-preparation to work was established to be 110
hours (6,600 min), based on the minimum International Lifesaving
Federation (ILS 2013) recommendation for a surf-lifeguard course.
Preparation to prevent/anticipate a rescue was established to be 12
hours (720 mins) or a day on duty (personal reference from the
4 Szpilman, Smith, Doyle, Grifths & Tipton • Reasoning and Decision-Making while Facing a Rescue
Table 1.
Lifeguard timeline conditions (variables) which may affect decision making.
Lifeguard timeline conditions (variables) which may affect decision making
Phase
SUB-PHASES
(variable group number;
variables; probability to
repeat the same event
responses; and time spent)
Variables per minute to
affect making decisions
Timeline action variables group (product of total qualitative response
possibilities)
Variable – qualitative set of response – Yes or No (response number possibilities)
Pre
PREPARATION TO WORK
(1 group; 8 variables; 1/256
probability to repeat the same
event response; and 6,600
minutes)
0,0001 variables/min
Lifeguard background (256)
Adequate technical training? Y vs. N (2)
Adequate physical training? Y vs. N (2)
Adequate work employee? Y vs. N (2)
Adequate paid feeling? Y vs. N (2)
Rest? Y vs. N (2)
Fed appropriately? Y vs. N (2)
Emotional balance? Y vs. N (2)
Healthy - Y vs. N (2)
PREVENT/ANTICIPATE THE
RESCUE AT DAY SHIFT
(5 groups; 22 variables; 1/4.2
million probability to repeat
the same event response;
and 720 minutes)
0,03 variables per minute
Transit to
work (4)
Near (hours)
from work? Y
vs. N (2)
Transit
stressful? Y
vs. N (2)
Preparing
on work day
(HQ) (32)
Personnel
locker? Y vs.
N (2)
Arrive on
time? Y vs.
N (2)
Confortable
environments
(HQ)? Y vs.
N (2)
Daily brieng
prepares for
challenges?
Y vs. N (2)
Time for
training/
working out
before going
on duty? Y
vs. N (2)
Arriving at the
duty, Patrolling
and identifying
the hazards
(1024)
Adequate transit
time allowed to
arrive at duty Y vs.
N (2)
Working with a
partner? Y vs.
N (2)
Personnel fully
equipped? (PPE)
Y vs. N (2)
Familiar with area
? Y vs. N (2)
Adequate
communication
with partner/HQ?
Y vs. N (2)
Tower/vehicle
comfortable and
protective? Y vs.
N (2)
Adequate time to
adjust to work? Y
vs. N (2)
Rough water
conditions? Y vs.
N (2)
Support from
other agencies - Y
vs. N (2)
Hazards signs
available and
appropriate? Y vs.
N (2)
Equipment
availability to
take to rescue
(4)
Appropriate
equipment (ns,
board, PWC...)?
Y vs. N (2)
Difculty of
equipment
choice? Y vs.
N (2)
Identifying the
victim at risk (8)
Easy? Y vs. N (2)
Early? Y vs. N (2)
Good vision? Y vs.
N (2)
longest lifeguard day shift at Copacabana Beach). The Event phase
was estimated by the rescue time duration of 10 min (Reilly et al.,
2006). For the Post-Event phase, rst aid (basic life support), the
mean time of 12 min was estimated based on the average time for
an advanced life support ambulance to arrive on scene (Szpilman,
1997).
IJEMHHR • VOL. 19, No. 4 • 2017 5
Effort and Process for Decision-Making (Intuitive
vs. Rational) (Drew et al., 1985)
Following identication of the number of variables and their
responses, the probability of repeating an event and estimation of
the duration of each phase, the authors estimated the predominance
of rational (less than 1 variable per minute) or intuitive (more
than 1 variable per minute) decision-making. Rational decisions
encompass a range of predictable aspects of day-to-day actions and
decision-making, where the element of time is less critical. Variables
categorized as “Rational” were those that were expected, easy to
predict or train for where time is available to make evaluations
or to conduct training. Variables categorized as “Intuitive” were
those that were unexpected but not necessarily novel and where
time to respond is limited. Intuitive decision-making (heuristic) is
cognitively exible under stress and where time is limited.
Data Analysis
The data were tabulated according to the drowning timeline and
the maximum total number of groups and variables was presented
numerically. The possible responses to each variable within each
group of variables (in each phase/sub-phase) were calculated based
on the probability of a singular combination of events repeating.
Each individual response (Y or N) created multiple combinations
of alternate pathways. The probability of one unique event being
repeated was calculated by multiplying all the variable response
possibilities within each sub-phase together to give the total
number of possible pathways. Assuming all potential options have
been included and that all pathways are equally likely, then the
probability of one pathway (X) being repeated is calculated as
1/X. The total number of variables for each separate sub-phase
was divided by the estimated duration of that sub-phase: each sub-
phase was then presented as predominantly rational (if less than
Event
RESCUE
(6 groups; 27 variables; 1/134
million probability to repeat
the same event response;
and 10 minutes)
2,7 variables per minute
Calling back
up (4)
Easy? Y vs.
N (2)
Quick? Y vs.
(2)
Running (4)
Easy to run?
Y vs. N (2)
Easy to
choose water
entrance? Y
vs. N (2)
Swimming to
approach the
victim
(256)
Properly
equipment-Y vs.
N (2)
Waves diculties?
Y vs. N (2)
Comfortable water
temperature – Y
vs. Not (2)
Good vision? Y vs.
N (2)
Calm weather
conditions – Y vs.
N (2)
Easy entrance?
Y vs. N (2) Victim
Near? Y vs. N (2)
People in the way
obstructing? Y vs.
N (2)
Ap-
proaching
the victim
(128)
Lifeguard
appropri-
ate equip-
ment? Y
vs. N (2)
Victim
Uncon-
scious? Y
vs. N (2)
Victim re-
act? Y vs.
N (2)
Good vic-
tim ota-
tion Y vs.
N (2)
Easy as-
sessment
to the vic-
tim? Y vs.
N (2)
In water
treatment
needed?
Y vs. N (2)
Easy
signaling
condition
from water
to shore?
Y vs. N (2)
Towing
(8)
Near to
dry land?
Y vs. N
(2)
Other
guard
support?
Y vs. N
(2)
Difculty
to tow ? Y
vs. N (2)
Transporting
from water
to dry land
(32)
Near? Y vs.
N (2)
Easy? Y vs.
N (2)
Light victim?
Y vs. N (2)
Easy to
position to
BLS? Y vs.
N (2)
Help
available? Y
vs. N (2)
Post
FIRST AID
(1 group; 7 variables; 1/128
probability to repeat the same
event response; and 12
minutes)
1,7 variables per minute
Supported by other guard/assistance? Y vs. N (2)
Basic life support? Y vs. N (2)
Advanced life support available? Y vs. N (2)
Advanced support needed? Y vs. N (2)
Need to call ambulance? Y vs. N (2)
Laypersons helpful? Y vs. N (2)
Condent of ability to provide life support? Y vs. N (2)
6
1 variable per minute) or intuitive (if more than 1 variable per
minute).
RESULTS
All phases, sub-phases, groups of variables, individual
variables, and their responses throughout a lifeguard’s professional
life, and each probability of a singular event repeating are listed
in Table 1. The total variables (n=64) that may affect or need a
lifeguard to engage in decision-making were considered.
The variables identied in the sub-phases as preparation
to work (8 variables and 0.0001 variables per min) and prevent
(22 variables and 0.03 variables per minute) were predominately
categorized as rational decisions as they involve less than 1 variable
per minute. The variables identied during rescue (27 variables and
2.7 variables per minute) and rst-aid (7 variables and 1.7 variables
per minute) were predominantly categorized as intuitive process (if
any decision-making was required as a response) as they involve
more than 1 variable per minute. Figure 1 shows variables per min
indicating when it is predominantly rational or intuitive decision-
making.
DISCUSSION
This theoretical study has, for the rst time, identied millions
of potential decision pathways and an extremely low probability of
exactly repeating a rescue event using the same decision pathway.
This complexity presents challenges to lifeguard instructors. In
theory, experienced lifeguards reason more effectively, however,
non-technical skills such as effective reasoning (intuitively or
analytically) take time to develop. Is there a method to develop
and train lifeguards to be more effective decision-makers earlier in
their career progression?
Parallels could be drawn between Emergency Medicine and
lifeguards as they share the common goal of saving lives. During
the professional development of emergency department physicians,
learning originates from didactic presentations, role modeling,
case discussions and real-life exposure. Novices integrate
networks of information, associative links, and memories of real
patient encounters to form unique clusters of information for each
diagnosis. Barrows, H.S, & Feltovich, P.J, coined the term “illness
scripts” for these complex collections of data. The illness script
theory assumes that knowledge networks adapted to clinical tasks
develop through experience and operate autonomously beneath
the level of conscious awareness (intuition) (Charlin et al., 2000;
Durning et al., 2013). By contrast, the ocean environment is less
controlled and can be hazardous to lifeguards. In this regard we
can also draw parallels to pre-hospital emergency workers, where
operating in a dangerous environment requires quick decisions and
actions and it is essential to rapidly egress the environment for the
rescuer’s or patient’s safety. Paramedics describe this doctrine as
“load and go” (quickly loading a patient into an ambulance and
departing). The antonym to this doctrine “stay and play” involves
remaining in situ to carry out interventions. Work as a lifeguard is
therefore more akin to the doctrine “load and go” versus “stay and
play” (Wilmink et al., 1996).
Lifeguard work encompasses three main clusters of tasks that
follow the drowning continuum timeline (Szpilman et al., 2016).
Each of these should be optimized by appropriate institutional
polices and training if the highest level of performance is going
to be achieved by lifeguards. Firstly, there is a preparation phase
which includes personal physical and mental well-being, promoting
preventative education, rescue and mitigation. Secondly, a pro-
active phase encompasses prevention and risk management.
Thirdly, a reactive phase includes the rescue and rst aid actions.
Experienced lifeguards accumulate a vast “library” of response
options that can be rapidly and subconsciously (intuitively)
accessed for the purpose of generating hypotheses and diagnostic
decision-making under pressure (Schmidt et al., 1990). These
automatic reasoning processes (intuitive) are non-analytical, rapid,
and require little cognitive effort (Stanovich et al., 2000; Evans,
1984; Evans, 2008; Kahneman, 2011; Sloman, 1996; Croskerry,
2000). In contrast, rational thinking is effortful and employs a
deductive search for a t between the available information and
appropriate scripts which cannot t a dynamic scenario (Stanovich
et al., 2000; Evans, 1984; Evans, 2008; Kahneman, 2011; Sloman,
Szpilman, Smith, Doyle, Grifths & Tipton • Reasoning and Decision-Making while Facing a Rescue
Figure 1. Shows variables/min with predominantly rational or intuitive decision making.
IJEMHHR • VOL. 19, No. 4 • 2017 7
1996; Croskerry, 2000; Stanovich & West, 2000). Novices
employ this analytic mode of reasoning more frequently than their
experienced counterparts. Experienced lifeguards therefore may
have already turned some of the “unpredictable” into “anticipated”
variables and have a potential optimal response ready. However,
while intuitive reasoning is a hallmark of those with experience,
errors may result from overreliance on automatic reasoning (Eva
& Cunnington, 2006).
The authors propose that during most rescue scenarios
lifeguards (like emergency workers) use both systems of thought,
a process known as “dual processing” as this offers the best chance
of success, even for the novice (Norman, 2009; Norman & Eva,
2010; Eva, 2007). It is possible that the combination of automatic
and analytic thinking is more benecial for complex versus simple
cases (Mamede et al., 2008) or when one anticipates difculty
(Mamede, 2008; Gonzalez, 2004). A exible, adaptive, robust
approach that considers multiple criteria and possibilities and uses
rational methods to generate a set of scenarios (or hypotheses)
potentially selected from intuitive reasoning may be more
desirable. In the context of lifeguarding, multi-scenario analysis
might use rational analysis to provide the decision-maker with
multiple hypotheses (North Atlantic Treaty Organization, 2002),
relevant systems (Allen et al., 2006) or “branches and sequels”
of possibilities (North Atlantic Treaty Organization, 2004) versus
an optimal or single answer. The key in decision-making system
design is to provide enough information to give decision-makers
a comprehensive view that mitigates the “fog of war” but not to
overload them with so much information that it creates a “glare of
war” – i.e., information overload.
Understanding the variables involved in the daily work of a
lifeguard and expressing these against time may help the lifeguard
training process (Barcala-Furelos et al., 2014). Lifeguard training
should imitate real life and instructors focus on overarching
principles and teach trouble shooting arising from application of
these principles during various real life scenarios. For example,
teaching basic principles such as keeping otation between the
rescuer and the victim, pausing for assessment a safe distance away
is desirable as these principles are transferrable to a range of similar
situations such as using a different otation device as a barrier orb
when other rescue techniques are used. Once general concepts are
taught and practiced, maximizing teaching variables that are easily
predicted, future decisions can be made more intuitively with less
need for analytical thought, decreasing cognitive load during rescue
and making reasoning more efcient. A decrease in cognitive load
facilitates better capacity for analytical thought required to solve
unexpected or hard variables.
Two epistemological perspectives, objectivist and constructivist
are relevant to lifeguard reasoning. From the objectivist (or logical)
perspective, there is one truth that is revealed or can be discovered
(Driscoll 2005). Learning is considered the process of acquiring
knowledge to discover the one truth. Experience is seen as less
important and lectures presented by experts conveying their ideas
of truth are the pervading instructional method. The constructivist
perspective consists of a compilation of human made constructions
(Tversky & Kahneman, 1974) and not the neutral discovery
of an objective truth (Tversky & Kahneman, 1984). Teaching
emphasizes providing representative experiences whereby learners
can construct meaning. This point of view has led in part to the
emergence of problem-based and case-based learning, a form of
learning where the teacher facilitates learning versus conveying
facts. Decision models must be considered within the context
of the dynamic decision-dense environment lifeguards operate
within. The authors propose that lifeguard education is suited to a
constructivist approach and there is a benet in constructing a series
of rehearsed and tested scripts we have called “rescue scripts”.
These scripts should focus on the context and “boundaries” or
range of acceptable performance in an encounter versus a single
best route.
A classic study by Elstein et al. demonstrated that experts
have more knowledge than novices enabling a higher rate of
diagnostic accuracy, rather than general problem-solving skills.
The amount of knowledge and the manner that it is arranged in
memory facilitates accurate diagnostic reasoning (Ilgen et al.,
2012). Expert physicians are better able to access knowledge
precisely because of experience. In contrast novices may be unable
to connect existing knowledge to a “novel” clinical problem (Ilgen
et al., 2012; Durning et al., 2013). Any constructivist approach
must cater for the surrounding complex environment. Cognitive
and task over-loading is common in the lifeguard environment as
well as the emergency department. A study by a U.S. academic
emergency physician (Brixey et al., 2008) demonstrated that 42%
of tasks were interrupted before completion and when interrupted,
emergency physicians completed one to eight additional activities
before returning to the original task. “Thinking carefully” (using
analytical thought) may contribute to cognitive over-loading in the
emergency department and where lifeguards work, which could
be detrimental. By presenting rescue scripts, novice lifeguards
can acquire validated experiences from experts (who develop the
scripts) and are able to develop individual variation (over time) in
their practice within the acceptable range and boundaries dened
within the rescue script. An expert’s performance by comparison
may fall into one of several equally valid trajectories of acceptable
performance that may not be the ‘one true pathway’ to a solution.
In this regard, clearly dened decisions are probably unlikely
for expert rescuers as he or she may have chosen any number of
pathways (developed over time) to achieve a successful result.
Future Challenges for Lifeguard Education
Educating lifeguards to be effective decision-makers has
cost implications. To our knowledge, no cost-benet-time-effort
analysis investigating the dividends of such training has been
conducted. Unlike industries such as aviation (who invest heavily
in such human factor training) many lifeguard services employ
only part time or seasonal lifeguards. Thus, the potential benets of
such training may not be recognized as a value proposition, despite
strong evidence that human factor training centered on effective
individual and team decision-making processes reduces error and
accidents and improves safety. Any investment that reduces the
need for rescue and provides improved prevention must be of
benet.
Limitations
Dealing with so many variables, this study has several
limitations. These include: the possibility of missing or
8
misinterpreting a variable, the unbalanced weighting of those
variables affecting decision-making or outcome, the over or under-
estimation of the duration of sub-phases, and the self-reported
data provided by ocean lifeguards may not be transferrable to a
water park or swimming pool environment. Also the time duration
of each phase/sub-phase is an estimation based on guidelines and
expert opinion that may vary. Although lifeguard decision-making
does involve a signicant amount of variables, the exact number
of variables per minute may vary, and may be different. Further
limitations include that some variable responses were estimated as
a dichotomous YES or NO response when there may be a more
diverse range of possible responses. In all phases a summary of
the conditions was made and some or many other variables that
were excluded may play a role; as such our approach probably
underestimates the decision-making task of lifeguards. At the
preparation to work phase, we chose to focus strictly on training/
formation time frame instead of including experience before
commencing lifeguard training. Finally, the time spent on one
particular action leading to a question may be much longer than
others issues and some rational decisions may take longer by being
more complex or perceived as more worthwhile or risky.
CONCLUSION
The study has identied that the shorter the time from problem
identication to a decision leading to a good but not ideal outcome,
the better the decision-making process. The authors propose that
understanding this complex mechanism and all of the variables
involved in a singular rescue event might result in more efcient
training in order to produce faster and more reliable decision-
makers, and consequently save more lives from drowning. Due
to the large number of possible choices available to a lifeguard
facing a single rescue event, the authors also propose lifeguards
and lifeguard instructors develop a “rescue script” when training
in order to build resiliency and transform unpredictable variables
into more predictable variables that require less cognitive load to
problem solve. Forging competent and professional lifeguards who
make good decisions while under duress is a desirable objective
but requires more attention. It is hoped that the present study in
identifying the demands, decisions and conceptual model, will
represent the rst step in achieving this objective.
ACKNOWLEDGEMENTS
Peter Davis - Galveston Island Beach Patrol and Vickie
Schafer, Ph.D. - Austin Psychology & Assessment Center
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