IMPACT OF FATIGUE AND SLEEPINESS ON THE
INCIDENCE OF OCCUPATIONAL ACCIDENTS IN
THE PREPARATION, CONSTRUCTION AND
MANUFACTURE OF THE TIRE INDUSTRY
IMPACTO DE LA FATIGA Y LA SOMNOLENCIA EN
LA INCIDENCIA DE ACCIDENTES LABORALES EN LA
PREPARACIÓN, CONSTRUCCIÓN Y FABRICACIÓN DE
LA INDUSTRIA DEL NEUMÁTICO
Ciro Martinez Oropesa
Universidad Autónoma de Occidente, Colombia
pág. 8744
DOI: https://doi.org/10.37811/cl_rcm.v9i4.19450
Impact of Fatigue and Sleepiness on the Incidence of Occupational
Accidents in the Preparation, Construction and Manufacture of the tire
Industry
Ciro Martinez Oropesa
1
cmartinezo@uao.edu.co
https://orcid.org/0000-0001-9168-998X
Universidad Autónoma de Occidente
Colombia
ABSTRACT
The research focused on analyzing the influence of long working hours on safety in the tire
industry, especially in preparation and manufacturing areas. Rather than assuming fatigue as a
given problem, the objective was to understand how physical and mental exhaustion relate to workplace
mistakes and accidents, based on workers' real experiences. A total of 160 employees, all working
shifts longer than 10 hours, participated by completing two standard questionnaires: the
Karolinska Sleepiness Scale and the Chalder Fatigue Scale. To bring out that larger context,
some follow-up interviews were conducted as well, in which workers described of fatigue in
their own terms. Accident records from the year before were thrown into the mix, and all of it
was run through SPSS. The findings were not surprising, but they were dramatic nonetheless:
increased levels of fatigue were highly correlated with an increase in errors, who were fatigued
respiratory rate. The results also suggested that fatigue is one of the major contributors to
human error and causing workplace accidents in the organizations with high-intensity work and
long and hard workdays. It is a common assumption that longer working hours may negatively
affect both the physical and mental ability of workers.
Keywords: fatigue, tiredness, workplace errors, long shifts, safety
1
Autor principal
Correspondencia: cmartinezo@uao.edu.co
pág. 8745
Impacto de la Fatiga y la Somnolencia en la Incidencia de Accidentes
laborales En la Preparación, Construcción y Fabricación de la Industria
del Neumático
RESUMEN
La investigación se centró en analizar la influencia de las largas jornadas laborales en la seguridad en
la industria del neumático, especialmente en las áreas de preparación y fabricación. En lugar de asumir
la fatiga como un problema dado, el objetivo era comprender cómo se relaciona el agotamiento físico
y mental con los errores y accidentes en el lugar de trabajo, basándose en las experiencias reales de los
trabajadores. Un total de 160 empleados, todos con turnos de trabajo de más de 10 horas, participaron
completando dos cuestionarios estándar: la Escala de Somnolencia Karolinska y la Escala de Fatiga
Chalder. Para ampliar ese contexto, también se realizaron algunas entrevistas de seguimiento, en las
que los trabajadores describieron la fatiga en sus propios términos. Se añadieron los registros de
accidentes del año anterior a la mezcla, y todo se procesó a través de SPSS. Los hallazgos no fueron
sorprendentes, pero sí drásticos: el aumento de los niveles de fatiga se correlacionó altamente con un
aumento de los errores, que eran la frecuencia respiratoria fatigada. Los resultados también sugieren
que la fatiga es uno de los principales factores que contribuyen al error humano y causan accidentes
laborales en organizaciones con trabajo de alta intensidad y jornadas largas y duras. Es común suponer
que una jornada laboral más prolongada puede afectar negativamente la capacidad física y mental de
los trabajadores.
Palabras clave: fatiga, cansancio, errores laborales, turnos largos, seguridad
Artículo recibido 24 julio 2025
Aceptado para publicación: 27 agosto 2025
pág. 8746
INTRODUCTION
Thus, in the same way that market changes have burdened production lines as volumes have
grown over time, this pressure has caused a substantial migration of operational activities. But
the workers we spoke to struggled to keep up with the pace, and it was especially difficult with
physically grueling jobs, handling and inspecting raw materials, packaging and even during
breaks — many of which grew shorter or vanished altogether as time went on. In a report from
If Insurance in 2022, fatigue was primarily related to long work hours, uncertain hours, and
arduous workmanship. Quite commonly, these arrived together with both a mental as well as
a physical tiredness.
This kind of fatigue did corrupt performance in labour intensive and high-risk sectors, such as
construction and transportation, and raised doubts as to safety of working conditions. Fatigue
did more than just drain the body; it also impaired mental performance. Reaction times were
slower and staying focused was harder, both conditions that can make people prone to errors.
Although people often use the words fatigue and sleepiness to mean the same thing, they are
actually quite different. Sleepiness often results from lack or poor quality of sleep, but fatigue
can persist despite a good night’s rest. Sleep problems, like insomnia or sleep apnea, were
often part of this ongoing battle.
The relationship between the fatigue and microsleep occurrence to human error and workplace
accidents has been also discussed in the literature, especially in tire manufacturing and design
environments. Specific examples of errors traced back to fatigue or brief involuntary sleep episodes
were discussed in relation to critical operational tasks.
These findings helped shape the motivation for the current study, which aimed to uncover the
underlying factors behind workplace mistakes and incidents.
Both fatigue and sleepiness represented significant hazards to workplace safety, each doing so in its
own manner. Fatigue showed up as a factor in incidents that were usually the result of certain work
patterns, some of which could have been remedied by adjusting schedules (especially when it came to
shift work) or by making other organizational changes.
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Sleepiness showed up in incidents that were mostly the result of personal factors—like poor sleep
quality or health conditions that affected sleep—that are difficult to "fix." Not surprisingly, the
combination of fatigue and sleepiness posed the greatest threat.
Fatigue frequently led to operational mistakes, disrupted production flow, and increased accident rates.
Employees who were both physically and mentally exhausted found it difficult to remain alert and were
more likely to be injured or cause harm—particularly when operating machinery in high-pressure
environments.
Schutte (2010) categorized the risks of fatigue into personal, workplace, and external factors. Personal
elements included an individual’s age, health status, and adaptability.
Within the workplace, issues such as rotating shifts, excessive workloads, or the nature of the task itself
exacerbated fatigue. External pressures like limited recovery time, second jobs, sleep problems, or long
commutes further hindered proper rest and recovery.
Momentary microsleep episodes some of which lasted just a few seconds had already led to serious
accidents while doing precision work like welding, machine operation, and assembly. Chronic muscle
pain was the usual outcome if rest was in short supply. As production pressures mounted, mistakes
inevitably increased, eventually bogging down operations and compounding workload pressures. As
job demands increased, employees burned out more quickly and had more difficulty sustaining
productivity levels throughout the day.
Once burnout occurred, it was nearly impossible to concentrate and be productive. Chronic fatigue led
to absences, on-the-job accidents, and even quits—each of which involved costs in finding and training
replacements.
Errors and redoes not only added to the cost of production—they undermined the organization's
competitive edge. To keep pace, employees generated sleep disorders and extreme exhaustion, leaving
restorative sleep a rare commodity. This destructive spiral often found its way into more serious
conditions, such as heart disease and chronic stress. Burned out under the constant pressure, burnout
spread through teams, with rising anxiety and falling morale.
The effect of fatigue did not stay confined within the work environment. They traveled with employees
back home, spoiling relationships and reducing the quality of sleep.
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Lack of sleep made individuals more irritable and distracted, which impacted performance at work and
personal health. Companies that overlooked the signs of fatigue exposed themselves to legal risk,
regulatory audits, and the potential loss of certifications. Weak quality controls resulted in defective
products, costly recalls, and reputational damage. Left unmanaged, fatigue not only threatened worker
health but also jeopardized a company’s overall performance and safety record.
Fatigue and human performance
Fatigue seemed to set in when people increasingly overworked themselves, overtired their
systems and simply did not get sufficient sleep to complete the vital repair job their body
required. Fatigue was more than just feeling tired – it was fatigue that affected someone’s
ability to function effectively at work and in sleeping, and doing things that they needed to do.
This disorder generally manifested itself in 2 ways, physical and psychological. Somatically,
fatigue made subjects tired after they made an effort, decreasing their level of energy and ability
to exert further effort. From a mental perspective, it added up in the course of focusing or
deliberating, until one’s attention or emotional control wore thin. Where the two types of
fatigue overlapped, their effect was usually quite striking.
Fatigue had a marked effect on physical function as described by Cooper and Taylor (2021)
other muscles that grew weary lost their normal strength and coordination, increasing the risk
of injury. Attention span and memory — both crucial for accuracy and safety in challenging
duties — also took a hit. This is consistent with prior work from
Williamson & Friswell (2013) revealing that long work hours with reduced sleep could lead to
cognitive impairment that paralleled the effects of alcohol. They observed how mental
exhaustion caused workers to act on impulse and not reflect on the consequences.
Recent findings (Behrens, Husmann & Weippert, 2022) suggest that the cognitive flexibility
and inhibitory control are impaired in the fatigued individuals, leading to slower response times
during tasks and suboptimal decisions overall, for these authors echoed a lot of those same
problems, detailing how fatigue delayed mental processing and increased the difficulty of self-
control—especially in high-pressure positions that needed fast and accurate thinking.
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According The Guardian (2024) mental tiredness rewired the brain to behave in ways similar
to when it was tired from lack of sleep. That was why some workers could not focus or control
themselves under stress. Oklahoma State University researchers even suggested that tiredness
and energy danced as separate emotional and biological systems, not as opposites. For others,
low energy manifested as an unwillingness to engage with people, or to cooperate.
People had trouble making decisions or passing on a message when mental fatigue was an
issue. Which is why more and more of those companies who were keen on having real, practical
solutions eradicate fatigue and improve in-work productivity, began to learn from the patterns
even more.
Fatigue and workplace accidents
There was a large body of evidence that suggested a strong link between fatigue and workplace
incidents. In health care, for example, long, grueling shifts had frequently been associated with
clinical errors. Analogous patterns were evident in the transport sector, where drivers and
dispatchers consistently experienced dips in alertness, particularly following indigent and
insufficient sleep (Philip et al., 2014).
Fatigued employees were far more likely—almost 62% more likely—to cause workplace
accidents (If Insurance, 2022).
Research suggested that between 5% and 25% of workplace accidents might be attributable to
fatigue. Indeed, one in eight accidents were thought to have been due to tiredness.
Specifically, drowsy driving continued to be a significant contributor to traffic mortality
reports from the CDC (2023) it was crucial to realize that fatigue didn’t just depend on the
number of hours people worked. How those hours were distributed across the day, or the week,
made a significant difference, as well.
Disorientation of natural sleep-wake rhythms along with night work shifts and varying
schedules resulted in reduced effectiveness and attention (Åkerstedt, 2007; Folkard & Tucker,
2003). Mental fatigue led to err with repeating tasks that demanded continuous attention,
especially at night time. Far too many employees were racking up far more sleep debt than
they even knew.
pág. 8750
Even worse was the duration of these effects. External pressures like constant noise or bright
light only added to the load, making it increasingly difficult for staff to quiet their thoughts or
respond quickly when the job called for scrutiny.
The fatigue takes place each time someone working overtime or pushed past their breaking
point, or missed sleep, it n't only that feeling of lethargy because it was ruining their capacity
to get things done in the course of normal daily activities, whether at work or outside it. Fatigue
to separate into two: physical and mental, after lots of work, physical fatigue made you feel
pooped and slowed you down, ruining the physical side of things.
On the other hand, jobs that force you to think a lot and make difficult decisions almost all day
end up exhausting people, with a significant impact on concentration and constant mood
swings.
In the presence of both forms, the combined effects were synergistically enhanced. Fatigue
critically attenuated physical capability (Cooper & Taylor, 2021).
Also decreased muscle strength, and coordination made them more prone to injure themselves.
And then again, both attention and memory were also substantially disrupted by tiredness. It
has been brought to light how the lack of sleep and long shifts, could mimic the effect of
alcohol (Williamson & Friswell 2013). Reaction time got really slow. It was dangerous in
delicate work demanding wide-awake eyes.
As Cooper & Taylor called it (2021), physical strength particularly struggled with fatigue.
Muscles fatigued, they surrendered strength and lost coordination, increasing the likelihood of
injury. Cognitive abilities also sang the blues when tired attention and memory both crucial
when trying to get the work done just so.
As the Van Dongen et al. (2003) observed that the ‘behaviorally fatigued’ worker at times
made decisions quickly without stopping to think, even impulsively passing over a thought
process.
The cognitive functions necessary for top performance are affected adversely by mental
fatigue, as demonstrated by Recent studies (Behrens, Husmann &Weippert, 2022).
pág. 8751
The fatigue did in fact slow thinking and, alas, impaired restraint, a valuable piece of
information, especially in jobs that require unerring precision as well as quick thinking with
the argued that mental fatigue dramatically alters how our brains work, and replication in the
sleep. (The Guardian, 2024). This shift kind of explain why the lost to those pressures usually
drifted, and had difficulty containing their behavior. As a matter of fact, Oklahoma State
University researchers claimed that energy and fatigue aren't two ends of a spectrum of a single
emotional or biologic state.
There was generally lots of irritability and – naturally – non-compliant behavior when energy
levels were low. Emotional exhaustion – which eventually made it hard to think straight, to,
well, communicate – you know the one we all have. A better understanding of these specific
activities was crucial for the development of practicable strategies to alleviate fatigue in work.
A number of studies have already found a strong connection between fatigue and workplace
accidents. For instance, long working hours in the medical field often led to mistakes during
patient care.
The same phenomena emerged in other industries; they mentioned as troublesome complaints
in the transport sector, with many drivers and dispatchers reporting they found it difficult to
pay attention, particularly after insufficient sleep (Philip et al., 2014).
The proof was pointing to a clear risk: workers who said that they felt tired were 62 pct more
likely to suffer accidents at work (If Insurance, 2022).
Other estimates were even higher, noting that 5% to 25% of crashes involved fatigue as a
contributing factor. In reality, one out of eight of the accidents reported was suspected to
involve fatigue and fatigue driving was still among the most lethal reasons for road-way
crashes leading to fatality (CDC, 2023).
Crucially, the issue wasn’t simply the length of time someone worked, but how that time was
organized. Disturbances to the body’s natural sleep-wake pattern, such as irregular schedules
and night shifts, had a pronounced effect on decision-making and performance (Åkerstedt,
2007; Folkard & Tucker, 2003).
pág. 8752
Activities that were performed during these least ideal hours – especially repetitive tasks –
were more likely to be error-prone, often due to fatigue. Few staff appreciated the rate at which
sleep debt would accumulate and they tended to underestimate how lasting its effects could
be.
Environmental stimuli like background noise or excessively intense light only compounded
the cognitive load, making it more difficult simultaneously to stay awake and to perform well
under stress.
This study set out to explore how fatigue and sleepiness might be linked to accidents in the tire
manufacturing industry. The researchers aimed to quantify both physical and mental exhaustion using
the Chalder Fatigue Scale and to measure sleepiness through the Karolinska Sleepiness Scale (KSS).
At the same time, they reviewed workplace incident reports from the previous year.
Besides, the study explored the amount of sleep workers usually had before beginning work and whether
the behavior was associated with self-reported levels of fatigue. Identifying recurring patterns was
aimed at developing useful insights that would reduce fatigue and lead to improved working conditions.
METHODOLOGY
A quantitative approach was employed to explore the relationship between fatigue, drowsiness, and
operational errors within tire production facilities. To ensure meaningful representation, the researchers
utilized a stratified random sampling method, which accounted for variations in shift schedules and
levels of job experience. To make a good sample, a stratified random sampling was what they went
with, huh. This helped consider shift schedules and job experience.
The following criteria were used to determine which workers were excluded.
Selected individuals had to meet certain standards. Only employees with six months of experience and
over 18 years of age were selected.
Workers, who’ve had some nasty sleep issues before, and also people already dealing with tough
chronic health problems, like diabetes, were kept out. Anyone receiving medical treatment potentially
messing with their wakefulness, they too were not considered.
pág. 8753
Study variables
The research centered around three main categories of variables. Independent variables included
elements the researchers tracked or categorized for their potential influence—such as the duration of
work shifts. Dependent variables captured the outcomes being measured, like the frequency of
workplace incidents or operational mistakes. Control variables, including environmental conditions like
lighting and temperature, were kept stable throughout the study to more accurately isolate the effects of
fatigue. Careful identification and consistent monitoring of these variables were essential to ensuring
that the results remained reliable and meaningful. A summary of all variables used is provided in table1.
Table 1: Variables and measurement instrument
Guy
Variables
Measuring instrument
Dependent
Number of work accidents and operating errors
reported
Company accident log and error
reporting
Independent
Cumulative Fatigue (CFQ)
Chalder Fatigue Scale (CFQ)
Independent
Sleepiness during the shift
Karolinska Sleepiness Scale (KSS)
Independent
Hours of sleep before the shift
Self-reported hours slept
Moderator
Shift Type (Day/Night)
Company registration
Moderator
Shift length: 8 h vs. 12 h.
Company registration
Moderator
Frequency of breaks and rests: Evaluate
whether there are rest breaks and their duration.
Company registration
Moderator
Working conditions: Lighting, noise,
temperature, and ergonomics of the workplace.
Company registration
Procedure
The study unfolded over four well-defined phases, each carefully planned to maintain methodological
integrity and consistency from start to finish.
Phase 1: Preparation, the research team received formal permission from the company and
approval from the institutional ethics committee before beginning data collection. Concur-
rently, training sessions in the fatigue and sleepiness ratings were conducted to ensure con-
sistency across the evaluators. This first stage was critical to establish a solid foundation for
data consistency and process synchronization.
Phase 2: Data collection at this phase of the study, workers were given surveys at the start and
end of their shift. Meanwhile, on-site observers entered and monitored conditions in real time
pág. 8754
in the workplace, and reported any unusual occurrences or accidents. In order to supplement
the data set, the researchers also looked at crash records from the previous year and results of
previous internal investigations. Other pieces of information came from employee work sched-
ules and records of reported work errors.
The researchers also collected environmental data — including light levels and temperature
changes, as well as how much noise there was — to see how the environment might have
affected alertness and job performance overall.
Phase 3: Data analysis after collecting and processing the data, the authors performed descrip-
tive and inferential statistics. Summary statistics — averages and standard deviations — gave
a broad sense of how fatigue was experienced by the work force. T test and analysis of variance
(ANOVA) were used to analyze the differences among groups. They also constructed regres-
sion models to determine if increased hours on the job were significantly associated with errors
or errors of commission.
Phase 4: Correlation modeling in the last stage of the work the researchers built models that
find explanation to the correlation between fatigue and performance. Over these models we
examined the association of fatigue not only to physical symptoms, but also to objective
measures of job performance.
The findings contributed to an understanding of fatigue impairment to safety and performance,
with practical implications for the development of mitigation strategies in these field settings.
Instruments used for data collection A 3-part structured survey was employed:
▪ Demographic and professional information (age, years of experience and type of shift.
▪ Chalder fatigue scale (CFQ, 11 items, Likert type).
▪ Karolinska sleepiness scale (KSS): A 9-point scale quantifying momentary drowsiness as-
sessed at three time points during the shift. Pittsburgh Sleep Quality Questionnaire: For
assessment of sleep hygiene of workers.
The Karolinska sleepiness scale (KSS)
The KSS item assesses the subject's experience of general sleepiness. Subjective KSS is a
subjective rating scale to evaluate sleepiness and fatigue in real‐time.
pág. 8755
It is commonly utilized in studies on fatigue among shift workers, drivers, pilots, and machin-
ery workers (Kaida, Takahashi, Åkerstedt, Nakata, Otsuka, Haratani & Fukasawa, 2006). The
KSS is a 9‐point rating of the level of fatigue at a particular time of day. See table 2.
Table 2 Description of the fatigue level
Punctuation
Description of the fatigue level
1
Very alert
2
Alert
3
Quite alert
4
A little tired
5
Tired, but effortlessly staying awake
6
Tired, struggling to stay awake
7
Very tired, with a tendency to fall asleep
8
Extremely tired, difficulty staying awake
9
Very sleepy, struggling to stay awake
Application Form
▪ Administered at different times during the work shift (e.g., at the beginning, middle, and end of the
shift).
▪ Self-administered.
Calculation and Interpretation
▪ Low scores (1-4): Indicate acceptable levels of alertness.
▪ Medium scores (5-6): Indicate moderate fatigue, which may affect concentration.
▪ High scores (7-9): Indicate severe fatigue and a high risk of operational errors.
Chalder Fatigue Scale (CFQ – Chalder Fatigue Questionnaire)
A more detailed instrument for assessing physical and mental fatigue. It is useful for measuring fatigue
accumulated over time, rather than a single state. The scale contains 11 items, divided into two main
dimensions:
▪ Physical fatigue (7 items): Assesses energy, strength, and physical endurance.
▪ Mental fatigue (4 items): Assesses concentration, memory, and mental clarity.
The participants responded to each item based on how they felt over the past week. See table 3.
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Table 3 Description of the fatigue level, punctuation and score
Punctuation
Answer (Score)
1
0 = No; 1 = More than usual; 2 =
Much more than usual; 3 = Much
more than usual
2
0-3
3
0-3
4
0-3
5
0-3
6
0-3
7
0-3
8
0-3
9
0-3
10
0-3
11
0-3
To measure the evolution of fatigue over time.
Calculation and interpretation
▪ Likert method (0-3)
▪ Answers "No" or "Same as always" = 0 points
The values of each item are added together. Total score range: 0-33.
▪ 0-10: Low level of fatigue.
▪ 11-20: Moderate fatigue.
▪ 21-33: Severe fatigue.
Accident rate: The objective of this analysis is to evaluate the frequency of workplace accidents that
have resulted in incidents in a tire manufacturing plant with more than 500 workers dedicated to product
preparation, construction, and manufacturing.
The most common types of accidents are examined, as well as their relationship to human factors, such
as fatigue and workload, and strategies to mitigate these risks are proposed.
Annual accident rate. The accident rate was calculated based on the following standard formula:
Frequency Index =
Total number of
(accidents resulting
in sick leave)
X 1,000,000 =
Man-hours worked
Source: OSHA (1970)
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RESULTS AND DISCUSSION
Data collected in the last year:
▪ Total number of accidents with sick leave: 95.
▪ Hours worked in the plant: 1,800,000.
Frequency Index
(
____95____
1,800,000
)
X
1,000,000=
52.78
Interpretation
The frequency index obtained (52.78) indicates that approximately 53 accidents occurred for every
million hours worked. This value is higher than the manufacturing industry standards, where a rate
above 35 is considered critical.
Human errors associated with accidents: After analyzing the reports of associated causes, the following
human errors were identified as the main causes of accidents in tire manufacturing. See table 4.
Table 4 Human errors associated with accidents
Human error
Incident
correlation rates
An illustration of an occurrence
Tiredness and sleepiness
37%
A vulcanizing machine operator experiences a loss of
control due to delayed reaction times.
Inadequate attention
25%
A safety signal is missed by the operator, and as a
result, the hydraulic press is activated while the
object is still in its danger zone.
Errors occur during
equipment operation.
18%
Failing to adjust the tire cutter properly can result in
limb entrapment.
Neglect of safety
protocols.
12%
Failing to wear heat-resistant gloves during the
vulcanizing process leads to burns.
Poor communication
8%
Mistakes made during the handovers of shifts can
result in machinery being unintentionally activated.
More than half of the workers (58%) worked shifts of more than 10 hours, which led to an increase in
accumulated fatigue and a decrease in alertness.
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▪ Extreme heat and rigorous working conditions in the vulcanization areas could have affected the
concentration, thereby increasing the likelihood of errors.
▪ Increasing production targets placed a significant burden on employees, which affected compliance
with safety procedures.
▪ Heavy workload: Production targets and performance goals, especially the production cycle time
per product produced, increased pressure on employees, which also contributed to a decrease in
accountability for compliance with safety protocols.
For the Cumulative Weekly Fatigue Score (CFQ) and Karolinska Sleepiness Scale (KSS) measures of
the central tendency and dispersion were calculated for both scales. KSS statistics (3-point sleepiness
during the shift). See tables 5 and 6.
Table 5 Measures of the central tendency b
Time of the turn
Media (x
)
Standard Deviation (σ)
Minimum
Maximum
Start of the shift
3.2
1.1
1
7
Mid-shift
5.6
1.4
2
8
End of the shift
7.3
1.6
3
9
Table 6 Measures of the dispersion
Item
Media (x
)
Standard deviation (σ)
Physical Fatigue
12.1
4.2
Mental Fatigue
9.4
3.5
Total CFQ
21.5
6.7
Initial interpretation: Sleepiness increased throughout the shift, and cumulative fatigue levels were in
the moderate-high range.
Group comparison (repeated measures ANOVA and t- student). See table 7
▪ Hypothesis: Fatigue measured by KSS increases significantly between the beginning and the end
of the shift.
▪ Proof: Repeated measures ANOVA (since KSS is measured at three points in the shift).
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Table 7 ANOVA results for the KSS
Source of variation
Sum of the squares
gl
Mean square
F
p-value
Between shift moments
315.4
2
157.7
23.4
< 0.001
Errors
1060.8
318
3.34
Interpretation: Since p < 0.05, it is concluded that there are significant differences in sleepiness
throughout the shift.
Correlation between cumulative fatigue (CFQ) and sleepiness (end-of-shift KSS). See table 8.
▪ Hypothesis: Operators with higher cumulative fatigue (CFQ) tend to report higher levels of end-of-
shift sleepiness (KSS).
▪ Proof: Pearson correlation coefficient (r).
Table 8 Results of the CFQ vs. correlation KSS end of shift
Variables
r (Pearson correlation coefficient)
p-value
CFQ Total vs. KSS Final
0.62
< 0.001
Interpretation
There was a moderate-to-high positive correlation between cumulative fatigue and sleepiness at the end
of the shift. The higher the weekly fatigue, the greater the sleepiness at work.
Linear regression to predict fatigue based on sleep hours. See table 9.
Hypothesis: The amount of sleep before the shift influences fatigue as measured by the CFQ.
Table 9 Linear regression to predict fatigue
Variables
Coef . (β)
Standard error
t
p-value
Intercept (β₀)
25.3
1.7
14.88
< 0.001
Hours of sleep (β₁)
-2.1
0.5
-4.20
< 0.001
Interpretation:
Each additional hour of sleep reduced fatigue by 2.1 points on the CFQ scale.
Factor analysis to identify fatigue dimensions. See table 10.
▪ Hypothesis: The CFQ scale has two dimensions (physical fatigue and mental fatigue).
▪ Proof: Principal component analysis (PCA).
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Table 10 PCA results (Factor Loading Matrix)
Item
Factor 1
(Physical Fatigue)
Factor 2
(Fatigue mental)
"I feel exhausted"
0.78
0.20
"I have a hard time doing things"
0.82
0.18
"I feel physically weak"
0.76
0.23
"I have trouble concentrating"
0.25
0.74
"I have trouble remembering things"
0.30
0.71
Interpretation: It is confirmed that fatigue is divided into physical and mental, with items well grouped
in each factor.
Final analysis
▪ Momentary fatigue (KSS): Increases significantly throughout the shift (p < 0.001).
▪ Cumulative fatigue (CFQ): It correlates with sleepiness at the end of the shift (r = 0.62, p < 0.001).
▪ Hours: They are a significant predictor of cumulative fatigue (β₁ = -2.1, p < 0.001).
▪ Physical and mental fatigue: These are confirmed as separate dimensions in the CFQ.
Table 11 Final results (logistic regression)
Variables
B ( Coef .)
Exp (B) (OR)
p-value
KSS final
0.45
1.57
0.002
CFQ total
0.30
1.35
0.015
Hours of sleep
-0.20
0.81
0.042
Night shift
0.60
1.82
0.005
Interpretation:
The results of the analysis indicated several interesting patterns concerning the associations
between fatigue, sleepiness and workplace safety. A workplace accident was 57% more likely
for each 1-point increase in KSS. Likewise, regarding the Chalder Fatigue Questionnaire
(CFQ), the odds of an accident increased by about 35% for each additional point. Conversely,
for every extra hour of sleep obtained prior to a shift steadily was associated with a 19% lower
risk of accidents. Workers on night shifts were at significantly higher risk — roughly 82 percent
higher — for workplace incidents than those on day shifts.
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Reported fatigue based on the Chalder Scale showed 72% respondents recorded high levels of
fatigue. Additionally, 64% of the sample reported high scores on the KSS, indicating signifi-
cant sleepiness while at work.
There was a significant correlation between burnout symptoms and operational errors (r = 0.68,
p < 0.01), suggesting a strong association. About 43% of the reported accidents were sus-
pected to related either to lessened concentration, impaired judgment, delayed reactions, or any
combination of these suggestions of weakened mental net by fatigue and burnout.
Workers who worked more than 12 hours per shift were 2.5 times as likely to have an accident,
an odds within a 95% confidence interval (such as those offered by the 1.8–3.6).
These results pointed out the importance of developing proper workplace fatigue management
programs. University of Michigan (2022) worked High-quality recommendations included
more evenly distributing work, frequent rest breaks, enhanced sleep at work and healthier sleep
of workers. Additional advice from Themis Advocates Group (2023) reiterated the importance
of adopting fatigue risk management systems with the ability to identify and manage fatigue -
related hazards.
The creation of long-term fixes would require ongoing vigilance and the constant fine-tuning
of day-to-day methods of operating.
There were a number of practical solutions thought to have potential, such as minimizing pro-
longed overtime, changing shift cycles to minimize recovery time, and introducing wellness
programs targeting sleep hygiene, nutrition, and stress management. Adjustments in the work-
place — such as good lighting, the right ergonomics and low levels of background noise — are
also thought to help reduce levels of fatigue.
Finally, the research suggested that specific skill teaching modules such as fatigue awareness
and sleep health should also be provided for managers and employees. Establishing a collective
understanding of the physical and psychological effects of fatigue: this was considered neces-
sary in order to build a safer, more productive working environment.
Practical interventions it was possible to achieve successful fatigue management in tire build-
ing based on four thematic areas:
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Scheduling shifts and workforce management
▪ Rotations of duty shifts were organized in a good way to prevent long-term accumulation
of fatigue.
▪ Night shifts were limited to a maximum of three consecutive nights to allow for sufficient
recovery between shifts.
▪ Workers were granted regular breaks — typically every 90 to 120 minutes — to help main-
tain energy and keep their heads in the game during long shifts.
▪ Programs were established to help workers recover physically and mentally between peri-
ods of work.
▪ Rest areas have been designed to allow the human factor to predominate, controlling light
and temperature in order to make the comfort of employees a point of focus.
▪ Working at night, workers were told to take short naps of around 20 minutes to refresh their
wakefulness without disrupting sleep cycles.
Assessment and monitoring of fatigue
▪ Tests measuring the workers’ cognitive alertness were conducted prior to and after their
shifts to determine their state of mind and preparedness.
▪ The CFQ and KSS were used to screen all high-risk fatigue at work employees.
▪ Fatigue detection sensors installed on crucial machinery to detect fatigue in the operator in
real time to preempt safe pro interventions.
Training and awareness
▪ Training sessions were held with employees learning the importance of a good sleep routine
and tips on how to recover effectively.
▪ Treatment of fatigue and the importance of safety were included as part of the company’s
usual training so that all crew members would be trained to identify and deal with fatigue
when it arose.
Environmental modifications
▪ The illumination inside of the night shifts worked areas were strictly controlled to alleviate
the effects of dim lighting and improve visibility and eye fatigue of the workers.
pág. 8763
▪ A more general soft background music (or low-level background noise) was played in the
workplace to help workers stay focussed and alert during working hours.
CONCLUSIONS
The data obtained in the present study have thus confirmed the main hypothesis that job burnout
in industrial workplaces is a significant predictor of the likelihood of human errors.
A significant association between KSS and the Chalder fatigue scale scores and the number of
errors committed by staff was noted. Fatigue was also identified as one of the main contributors
to work accidents, as 43% of accidents described were associated with fatigue symptoms (e.g.
lower attentiveness and reaction time).
In particular, workers with shifts lasting longer than 12 hours were more at risk. When looking
at people working more than 10 hours a day, with this increased risk for such a policy, it also
reinforces the relationship between duration of the shift and risk of injury.
In order to effectively address these issues, it was suggested that companies should reengineer
shift rosters, introduce enforced breaks and institute wellbeing programs targeted at promoting
rest and rejuvenation.
A standardized fatigue risk management system would offer an organized method of recogniz-
ing early markers of fatigue and of adapting rest times for the individual. Finally, fatigue was
found to be a key consideration for safety, performance and health in high demand manufac-
turing work.
The integration of evidence-based strategies to mitigate fatigue can help organizations protect
their workers, optimize operational performance, and develop a healthier work environment.
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