Working Memory Capacity, Mental Fatigue, and Human

Performance

Paul Westfield

Mindseye Coaching and Consulting LLC, 2390 N. Reid Hooker Rd, Eads, TN, U.S.A.

Keywords: Working Memory Capacity, WMC, Mental Fatigue, Cognitive Deficits, Working Memory, Executive

Control Inhibition, High-WMC, Low-WMC.

Abstract: Errors in aviation can cause death. When the cause of error is not understood, it cannot be mitigated and will

repeat. This paper will explore an area of error causality that is not addressed or even identified in aviation

training or operations The aviation industry should evaluate their current pilots and establish a hiring

baseline for working memory capacity. This is the first step in understanding and mitigating what may be a

fundamental cause of many accidents and incidents. First, working memory (WM), working memory

capacity (WMC), and mental fatigue (MF) will be defined using current literature. Only one study is

operationally based, the rest are experimentally based. In the referenced literature, WMC was evaluated

using complex span tests (CST) or automated operational span tests (Aospan). Individuals with low WMC

were found to be more likely to be reactive, have slower response times, be more easily affected by

interruptions, and have higher error rates. Individuals with high WMC were more proactive, were less

affected by interruptions, maintained goal focus, and made fewer errors.

INTRODUCTION

Aviation is inherently dangerous. When errors are

made, lives are placed in danger. Crew Resource

Management (CRM) created a way for crews to

communicate more effectively and to include all

relevant information in the decision-making process.

Not much has changed since that time, and accidents

still occur. This discussion will look deeper into the

cognitive processes that drive CRM behaviours and

may explain many of the recurring failures. The

ability of humans to process relevant information

resulting in an acceptable outcome, is variable in

many ways. Humans are individually unique in

cognitive abilities and their expression through

decision-making, which is founded on working

memory capacity (WMC). There are low-WMC and

high-WMC individuals with significant differences

in ability. In addition, humans are variable in

response to fatigue, specifically mental fatigue

(MF), which has a variable impact on low vs high

WMC individuals. Studies now show that these

variables are identifiable and quantifiable. This may

be an open window into understanding how and why

CRM fails. More aviation-specific studies are

needed that will support this focus on cognitive

causality based on WMC and MF variability and

influences.

1.1

Error Causality

All airlines spend millions of dollars and thousands

of hours on simulator instruction, but one common

goal is always present: error elimination. The

challenge is tracing error to its expressed behavior,

then on to the originating causality. A procedural

error in an approach may be identified as a lack of

knowledge of the automation capability of the

aircraft. What cannot be determined superficially is:

why was that knowledge unavailable to the pilot at

that time? Foundationally, behavior causality is

cognitively based, yet there is no formal process in

aviation to evaluate cognitive ability. Instructors

assess and evaluate based on observed human

performance. As design, maintenance, and

automation improved, failure causality was more

directly placed on pilots. Studies suggest that

between 60% and 80% of accidents have human

factor causality (Shappell et al., 2007).

126

Westﬁeld, P.

Working Memory Capacity, Mental Fatigue, and Human Performance.

DOI: 10.5220/0013152600004562

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Cognitive Aircraft Systems (ICCAS 2024), pages 126-133

ISBN: 978-989-758-724-5

1.2

CRM Origins

The crash of United Flight 173 from New York to

Portland, Oregon, ushered in a new era of crew

training designed to eliminate error. The aircraft had

experienced a gear malfunction prior to landing. Air

traffic control gave the crew airspace to hold and

work on the problem. The captain became distracted

by the needs of the cabin crew in their preparation

for the approach. He ignored the statements about

limited fuel made by the cockpit crew during this

time. By the time he realized the severity of the

situation and turned toward the airport, they were

already running out of fuel. Flight 173 crashed in a

neighborhood short of the airport due to fuel

starvation. Ten people died, and dozens were

injured. As a result of the findings of this crash,

Crew Resource Management (CRM) was born. The

goal of CRM is to ensure that safer decisions will be

made with more information and coordination. CRM

is an external view of behaviours centered around

teamwork, leadership, communication, situational

awareness, and decision- making. This approach led

to vast improvements in the leadership gradient and

overall crew collaboration. Unfortunately, errors

continued to occur, and people continued to die. In a

high- reliability industry like aviation, one accident

is consequential.

BACKGROUND

As an instructor/evaluator and teaching Human

Factors, I became interested in a series of five near

catastrophic events that occurred during the go

around phase of flight. A go-around is when the

crew or the controller decide that the aircraft must

break off the approach and fly a specific procedure

instead of landing. This can be directed because the

spacing between landing aircraft is too close, wind

or weather is now beyond landing limits, an aircraft

malfunction, not meeting stable approach criteria, or

many other reasons. The five events were evaluated

for causality commonality. Was there a training,

proficiency, currency, planning, or fatigue issue that

could be credited with explaining why the crews

flew perfectly good aircraft into an undesired aircraft

state (UAS)? The crews were professionally

qualified and experienced, had received good

training with no deficiencies, and were not

physiologically fatigued. The events occurred in

different aircraft, at various locations both domestic

and international. The intersecting commonality was

limited. All UAS events were all at the end of a

flight and required the use of a specific procedure

engaging both implicit autonomic response and

explicit cognitive engagement. All the crews made

serious errors including, power application, system

control, flight path, communication, and others. In

the goal of tracing causality, there seemed to be no

common external factors identified that would

mitigate the developed UAS. An unidentified

influence was likely behind these failed maneuvers.

After doing an informal survey of simulator

instructors, a common experience became clear. In

training for the requirement of a go-around there is a

prescribed procedure that dictates pitch, power,

flight path management, and configuration changes.

There is also a verbal litany that accompanies the

flight path profile with the intent of communicating

the steps as they occur. There were pilots who could

fly the entire go-around procedure perfectly but could

not seem to get the corresponding verbal call outs

correctly. Other pilots got every memory call out

correctly but could not fly the prescribed procedure

profile while doing so. While most pilots seemed to

perform to standards, this limited performance group

was large enough to be identifiable. While this was

completely anecdotal and held no scientific value, it

was the assessment of instructors with thousands of

hours of observations. The differences in performance

behavior could not be explained through error

analysis of CRM, or any other training application.

Boksem and Tops research identify attentional control

decrements due to the impact of mental fatigue

(2008). Further research, presented here, exposed

attentional control decrements as a shared impact of

low-WMC and MF on cognitive performance. This

paper explores the limitations of WMC variability and

the combined impact of MF. There are several

questions that should be answered. First, can

variations in WMC among non-mentally fatigued

individuals impact their performance under high

workloads? Next, could that explain why some pilots

who met application and interview criteria seem to

underperform? Drews and Musters (2015) warn that

individuals who are functioning at their maximum

WMC are likely to have increase error rates and less

effective strategies for task completion. Finally, what

impact, if any, does MF have on the performance of

those with low-WMC vs high-WMC. These questions

must be explored to fully understand the potential for

performance decrements in high workload

environments.

Moreover, if having a specific WMC score has

an impact on human performance, measuring this

prior to employment may provide a benefit to error

reduction and safety.

Working Memory Capacity, Mental Fatigue, and Human Performance

127

Understanding the interaction and integrated

impacts Working Memory Capacity and Mental

Fatigue have on Human Performance must start with

definitions. By providing clarity through definitions,

the nature of the interactions and potential

performance variability can be described with more

specifics.

DEFINITIONS

3.1

Working Memory

Working memory (WM), as defined by Unsworth

and Engle (2008), combines the recall, use, and

management of information relevant to the task at

hand. It has been further defined by including the

ability to keep behaviorally focused on the relevant

information despite distractions (Jarrold & Towse,

2006). Baddeley (2001) considered executive

attentional control as an important agent for

maintaining WM focus. In early research into WM,

the concept of accessing information from long-term

memory (LTM) was developed by Ericsson &

Kintsch, (1995). They differentiate the durability of

long-term working memory (LT-WM) and short-

term working memory (ST-WM) in WM. They

suggest that LT-WM is dependent on attentional

controls, and once available, it must be kept active,

or it is lost. This concept is critical when considering

task interruption and reengagement.

3.2

Working Memory Capacity

Working memory capacity is a newer concept that

explains the personal differences in functionality,

fixed storage, and ability to focus attention

(Shipstead et al., 2016). In earlier work by Unsworth

& Engle (2008, p. 616), the idea of “active

manipulation” is offered as a defining component for

moving WM to WMC. This is the process of

bringing relevant long- term memories forward for

integration. There are strong positive correlations

between WMC and fluid intelligence, offering an

avenue for assessment (Shipstead et al., 2016). Fluid

intelligence is demonstrated by novel problem-

solving methods. Strong capabilities in fluid

intelligence access relevant information from LT-

WM and apply it to the current environment in

creative ways that provide solutions. A significant

aspect of fluid intelligence is the propensity to

identify and activate disparate stored information

that, when integrated, adds to the developed solution

(Shipstead et al., 2016). Jastrzębski, et al. (2018)

suggest that the efficiency of WM is strongly

supported by an individual’s fluid intelligence. Their

work specifically identifies that WMC, and fluid

intelligence are insulated from strategy use and show

interdependence (Jastrzębski, et al., 2018). With

such strong correlations to WMC, future studies of

pilot cognitive abilities should incorporate fluid

intelligence assessments. WMC is the ability to take

in current stimulus held in ST-WM, use executive

control to identify relevant LT-WM information, and

apply attentional controls to keep all the information

available. All this is accomplished while

determining the appropriate response during the

engagement of implicit, automaticity-based

behavior.

WMC Assessment. WMC variation can be

measured and evaluated using complex span tasks

(CST) (Redick et al., 2012). An automated operation

span test (Aospan) has also been used successfully

and is associated with fluid cognition (Unsworth et

al., 2005). The common research employment is to

assess WMC, then invite those in the top and bottom

quartiles for quantitative testing. This process

provides a clear division in capabilities and

performance variations in WMC among the

individuals evaluated (Bafna & Hansen, 2021).

Then, during task loading testing, performance is

related to the WMC scores. Osaka et al. (2021) have

identified brain activity differences between high-

WMC and low-WMC individuals. Their work

indicates that low-WMC individuals appear to

engage more areas of the brain to accomplish certain

tasks than those with high-WMC. High-WMC

individuals showed much higher engagement in the

anterior cingulate cortex (ACC). This may indicate a

need to recruit more areas of the brain in low-WMC

individuals for the same task. The ACC is thought to

have a significant impact on attentional control and

inhibition. Inhibition, in this case, is helpful in

maintaining goal-oriented behavior by inhibiting

nonrelevant stimuli from becoming significant. In

addition, Quaedflieg et al. (2019) show reduced

capabilities in those with low WMC when under

stress. Ahmed and Fockert (2012) use visual flanker

trials in their study of WMC and working memory

load (WML). Consistent with other studies, they

found that “high-WMC individuals were indeed

better able to adjust their attentional window to task-

relevant information compared to low-WMC

individuals” (Ahmed & Fockert, 2012, p. 9). This

visual response study is relevant to the visual

distractions that can occur in the cockpit. Variations

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in both high-WMC and low-WMC individuals have

proven to impact performance. What happens when

they are impacted further by high levels of task

loading?

USAF WMC Assessment. In 1980, while attending

USAF pilot training, I was exposed to a process that

evaluated WMC from an operational performance

perspective without having the scientific definitions

or studies to support it. Everyone was ranked by the

end of pilot training. The ranking was for the

purpose of identifying those with the highest skill

sets. The ranking was from highest to lowest:

fighter/instructor qualified, fighter qualified, and

multicrew qualified. How did they manage to

develop the ranking without the science of WMC? A

pilot candidate had to be exceptionally skilled at

flying to rise above the multicrew ranking to become

fighter-qualified. Next, those with the fighter-

qualified ranking still had to prove their ability to be

instructors as well. The technique the USAF used

was to create a high-task-loaded environment during

challenging flying engagements. They did this by

engaging the student in distracting conversations

while flying a challenging formation rejoin

maneuver or any other challenging flying task. If the

student could still fly the jet well with no

performance loss while engaged in conversation and

other distractions, they were fighter/instructor

qualified. This was an important evaluation, as many

new pilots were brought back and trained as pilot

training instructors. Most of the fighter/instructor-

qualified pilots were selected for F-15, F-16, or

other single-seat high- performance aircraft. The

USAF also required forward air controllers to be

fighter/instructor qualified. Their job was to fly the

OV-10, a single pilot twin engine turboprop, at low

altitude while talking on three different radios,

marking targets on maps, and recording fighter

information. Then the pilot developed attack

headings and providing final attack clearance, a very

task intensive job. The USAF circa 1980 ranking

system was experientially developed and offered

pilots a way to compete for the best assignments.

More importantly, it created a margin of

performance capability and safety for the USAF.

The result was a ranking system based on a pilot’s

ability to maintain attentional focus and keep

relevant information a priority. Military pilot

training is intentionally a culling process with high

washout rates. The candidates had to prove their

capabilities if they wanted to get their wings.

Airline Assessment. Commercial flying is a

multicrew-based operation with international and

federal regulations as well as corporate rules and

guidance. Pilots must meet minimum experience

requirements to be invited to an interview. Pilots

prove their qualifications when they pass the

interview. The training is designed to be the most

efficient in the least amount of time to produce a

safe pilot. The interview process does not

necessarily identify capabilities under stress or high

task loading. The ability of the pilot to operate under

stress is assumed. This assumption is a mistake and

exposes a gap in capability assessment. As aviation

moves into higher levels of complex airspace

management and aircraft automation, this gap should

be eliminated. The importance of eliminating this

gap in assessment becomes stark when the impact of

mental fatigue is considered.

3.3

Mental Fatigue

Mental fatigue is differentiated from both physical

fatigue and sleep-loss fatigue. While both conditions

may contribute to mental fatigue, it does not require

their presence. Task loading induced mental fatigue

can be categorized as acute mental fatigue. Other

forms of mental fatigue can be injury or illness

induced (Bafna & Hansen, 2021). Here, the term

mental fatigue (MF) will refer to acute task-loaded

mental fatigue. MF can be identified by many

different cognitive test variations that identify

deviations correlated to task level increases. MF can

develop during short periods of high task loading

and does not require prolonged periods of work

(Boksem & Tops, 2008). MF is further defined

based on physiology and energy use. The

biochemical activity of energy use in the brain under

high demand can produce sleep regulatory

substances, including adenosine, which shut down

that part of the brain. This inhibitory effect may be

contributory to MF decrements (Kumar et al., 2013).

The ACC (anterior cingulate cortex) is an area of

the brain where the impact of excess adenosine may

directly impact WMC and information processing.

Darnai et al. (2023) identify that as MF rises,

activity in the ACC and other non-task-specific areas

decreases. High-WMC individuals have increased

activity in the ACC as compared to low-WMC

individuals during complex-span tasks (Osaka et al.,

2021). This may result in improved executive

function and goal-directed behavior by high-WMC

individuals. In addition, Osaka et al. (2021) identify

the importance of the ACC in central executive

functions, a key component of WMC. Moreover,

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129

elevated levels of adenosine may directly affect

effort-based decision-making (Martin et al., 2018).

Proper decision-making requires all components of

WMC, including drawing explicit memories from

long-term memory. Anything that degrades

motivation or allows irrelevant information into the

processing process can disrupt this process. This is

an effortful activity engaging in goal-centered

processing, which is an executive function required

to ensure proper response inhibition. The brain

engages in filtering processes that inhibit

inappropriate or irrelevant responses. Chen, et al.

(2021) produced an electroencephalographic study

engaging participants in task interruption trials. To

induce mental fatigue, they used the AX continuous

performance task. A negative effect of interruption

on WM was identified in non-MF participants. They

also noted that: “In the current study we found that

high WMC individuals were indeed better able to

adjust their attentional window to task relevant

information compared to low WMC individuals…”

(Chen et al., 2021, p. 9). This finding is consistent

with other forms of testing that have identified the

importance of attentional control associated with

WMC (Ahmed & Fockert, 2012; Baddley, 2001;

Engle, 2002; Kane and Engle, 2002). Guo et al.

(2018) support this and determined that in addition

to degraded and delayed response inhibition, there

also appeared to be a reduction in the allocation of

attentional resources. When referring to the

definition of WM above, the impact of attentional

focus and control on relevant information is

identified as essential for WM maintenance and

function. WMC, then, must have those components

available to effectively engage in the active

environment. Adenosine buildup from high

cognitive activity and task loading-induced MF may

have a negative impact on the functionality of WMC

through various channels. This impact is associated

with the ability to accurately process the information

required for an effective response. Loss of executive

attentional control, an effect of MF, appears to allow

irrelevant information to drive inappropriate

reactions or delayed responses. In addition, MF has

been shown to create resistance toward increasing

effort during task accomplishment (Lorist et al.,

2000). This is consistent with the concept that MF

results in reduced motivation and effort for task

completion (Boksem & Tops, 2008). Lorist et al.

(2000) show how mentally fatigued subjects move

toward stimulus-based reactions and away from

WMC-based responses. This may be due to the loss

of the capability of executive control to exclude

irrelevant stimulus. This loss of executive control

through MF has been shown to affect the allocation

of information resources of WM through

electroencephalogram testing (Yang, et al., 2021).

Goal-directed behavior is a key component of

executive control, where inhibition of irrelevant

information maintains goal focus. Reduced

executive control resulting from MF actions is

driven more by “…situational or external cues, even

when this is inappropriate” (van der Linden et al.,

2003, p. 47). This can be translated behaviorally as

reactions rather than responses. Reactions tend to be

explicit in nature, rapid, and without effortful

thought. A response takes time and includes explicit

memory recall and cognitive processing. The former

may or may not produce a positive outcome; the

latter is an attempt to produce a desired outcome.

When a response becomes too effortful and

irrelevant stimuli are present, an erroneous reaction

can occur. The data shows that there are limits to

WMC. When increased task loading develops into

MF, information processing declines, resulting in

degraded decision- making. While heuristics are not

assessed here, they are less effortful processes in

decision-making and often inaccurate, based on

previous experience or framing. The influence of

MF on perseverance may also show up as

confirmation bias: not making the effort to explore

all the data before committing to inclusion.

DISCUSSION

Proactive and reactive control are defined by

Wiemers and Redick (2018). They describe

proactive control as using available information to

infuse or prepare for a response before a reaction is

needed, resulting in faster response times and greater

accuracy. Alternatively, they explain reactive control

as not engaging relevant information until a critical

stimulus appears, then trying to retrieve the

information and select an appropriate response,

which can lead to slower response times and less

accurate responses. In addition to other influences,

Wiemers and Redick (2018) identify WMC as an

influence in the use of proactive or reactive control.

An important concept they present warns that just

because low- WMC individuals are less likely to use

proactive control, it does not mean that they are

incapable of using it. More practice or time on-task

training may improve their use (Wiemers & Redick,

2018).

Möckel et al. (2015) also identified how task

loading can lead to WM, action control, and

attention deficits. They further add that MF may add

ICCAS 2024 - International Conference on Cognitive Aircraft Systems

130

to the difficulty of staying focused on the relevant

information (Möckel et al., 2015). Looking at this

another way, irrelevant information or stimulus may

become engaged in the process of human

performance and degrade available WMC

throughput. Considering WMC limits, if additional

irrelevant data is added to the processing

requirement, it seems likely that there will be an

increase in errors. Interruptions have been associated

with error causality. Aviation is fraught with

interruptions. Drews and Musters (2015) conclude

that higher WMC reduces the impact of

interruptions. Interruptions increase cognitive

demand and can create capacity interference. Key to

their findings is that it is the irrelevant information

in an interruption that creates cognitive overload.

This ties the impact of MF to the degraded inhibition

of irrelevant information. Kane and Engle (2002)

promote a strong executive attention component in

WMC. They define executive attention as:

“a capability whereby memory representations

are maintained in a highly active state in the

presence of interference, and these representations

may reflect action plans, goal states, or task-relevant

stimuli in the environment” (p. 638).

Kane and Engle support their position and

further claim that active maintenance and distractor

blocking function as the core of WMC through the

activity of executive attention (2002). Recall that

MF can degrade executive attention and allow non-

relevant stimulus considerations to increase

perceived task loading. This perception influences

the effort projection and can reduce motivation for

perseverance. Kane and Engle (2002) suggest that

active maintenance of information is most critical

when interference and distractions are present. This

brings focus to the concept that high-WMC

individuals perform better during distractions due to

stronger executive control inhibiting nonrelevant

stimuli.

Unsworth and Robison (2020) explored WMC

during extended vigilance tests. This is suggestive of

a pilot’s requirement to monitor aircraft systems for

hours during cruise. They found that while the

results for both low and high WMC individuals were

similar early on, as time went on the low-WMC

individuals experienced a greater performance loss

over the high- WMC individuals (Unsworth &

Robison, 2020). Studies indicate performance

decrements in low- WMC individuals in both short

term, high task loading, and long term, time-on-task

events.

Research must provide solutions that will

function in future proposed cognitive environments.

Tools are now available that can identify high-WMC

candidates for task-challenged positions like

piloting. By eliminating those who will commit

more errors based on their limited WMC, aviation

organizations will improve safety margins.

Individual variations in WMC must be managed by

creating a working environment that minimizes

distraction potential, a key error contributor. There

may also be ways to train more efficient strategies

for low-WMC individuals and reduce reaction-based

decision-making (Drews & Musters, 2015).

Westbrook et al. (2018) looked at emergency

department physicians. They shadowed thirty-six

physicians over 120 hours. While this is a small

study, it has immense potential to guide future

studies in aviation. They assessed the physicians

WMC levels using OSPAN, with error rates

correlated to interruptions and multitasking. They

identified prescribing errors and clinical errors.

Prescribing errors increased in association with

multitasking; interruptions, however, during this

task, failed to have an effect. When trying to

accomplish multiple tasks simultaneously during

administrative prescribing duties, error rates were

high. It was discovered that for every one-point

increase in the OSPAN WMC score, the decrease in

error rate was 2%. A higher WMC produced fewer

errors (Westbrook et al., 2018).

Westbrook et al. found that clinical errors,

however, significantly increased with interruptions.

While error rates also increased with physician age,

they were inversely proportionate to physician

seniority. WMC was also associated with clinical

errors. A 19% reduction in error rate was observed

for each ten-point increase in the OSPAN WMC

score (2018). Westbrook et al. (2018) indicate that

their study showed a direct connection between error

rates and WMC, where those with low WMC made

more errors.

This is one of very few operational assessments

of WMC, specifically in a high-task-loaded

environment comparable to aviation. The correlation

is significant. In their conclusion, Westbrook et al.

make several points worth considering. They point

out that accepted practices of interruptions and

multitasking had a negative impact and should raise

questions about those traditional strategies (2018).

This is also good guidance for aviation. Next, they

demonstrated that high-WMC individuals are better

at operating in this high-task-loaded environment

(Westbrook et al., 2018). Pilots and physicians have

been compared many times based on personality

types and the stress and task load of their jobs. Tests

are available to determine WMC variance. The

Working Memory Capacity, Mental Fatigue, and Human Performance

131

evidence suggests high-WMC individuals are less

error prone. Testing pilots could be a powerful tool

for error, incident, and accident prevention.

Human performance in aviation is subject to

many influences and variables. The environment is

ever- changing, with variations in weather

conditions, maintenance restrictions, and changes to

NOTAMs (Notices to Airmen), routes, approaches,

and personnel. Often, crews meet for the first time

an hour before a flight that can take them halfway

around the world through many challenges.

Regulations and procedures are designed to

structuralize behavior as much as possible. CRM

and Threat and Error Management are tools and

performance aids designed to minimize error-

producing behaviors. What if the ultimate error-

producing causality is currently invisible to our

system of analysis? After an error has occurred,

cognitive evaluation is not historical and provides

little value to an investigation. During interviews

pilots are eyewitness, and eyewitnesses have been

shown to be the least reliable source in

investigations. The information gathered event by

event will be unique to the individual with no way to

associate that to the general pilot population.

Identifying individual WMC in advance, provides

added value to a Safety Management System.

Testing on a broad-based level will produce data that

will reflect the general population of pilots and

allow for system-wide responses.

CONCLUSIONS

As aviation moves to higher levels of automation

with increased specificity of cognitive focus,

matching capabilities to requirements becomes a

safety issue. Low-WMC individuals are identified as

having higher error rates and longer response times.

Their ACC activation levels are lower, and they are

more susceptible to distraction and irrelevant

stimuli, especially after high task loading and MF

onset. High-WMC individuals demonstrate higher

levels of perseverance and increased goal-oriented

focus despite distractions and irrelevant stimuli.

Their response times are faster, and they have fewer

errors. Additionally, studies have shown a strong

correlation between WMC and fluid intelligence.

Before there can be procedural development or

performance filtering, there must be more direct

studies involving active pilots from major airlines as

well as air traffic controllers. Using available CST

and Aospan testing, the WMC and fluid intelligence

of the current employees can be ascertained. If

validated, training studies should be developed to

explore the effectiveness of providing low-WMC

individuals with alternative strategies that will

prevent reactive behaviors. Alternately, based on the

data results, it may be effective to develop a

screening process for high-WMC, high-fluid-

intelligence candidates. A WMC score scale

included in the interview process would bias the

selection to those who are more capable of operating

in a high-task- loaded, high-interruption profession

with reduced error potential. The benefits, projected

forward, may allow reduced training times, more

complex operations, reduced errors, and improved

safety.

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