ORIGINAL ARTICLE
Poor Work–Life Balance May Lead to Impaired Cognitive
Function in Bus Drivers
Dong-Wook Lee, MD, Yun-Chul Hong, PhD, Hwo-yeon Seo, MD, Sung-joon Cho, PhD, Soo-hyun Nam, MSc,
Cham-Jin Park, MD, and Nami Lee, PhD
Downloaded from https://journals.lww.com/joem by BhDMf5ePHKav1zEoum1tQfN4a+kJLhEZgbsIHo4XMi0hCywCX1AWnYQp/IlQrHD3vZhfaAjmmeMVghJEHvmwdMapeoDn+9R9ELHyRa3fnA2GAfX3OeZdfg== on 08/07/2020
Objective: This study aimed to investigate how work–life balance (WLB)
corresponds to cognitive functions and which mental health conditions play a
mediating role in this association among Korean bus drivers. Methods: The
cognitive failures questionnaire (CFQ) was administered to 347 bus drivers
in Seoul, Korea. The differences in the CFQ and WLB scores were examined
by analysis of covariance, and a structural equation model (SEM) was
constructed for investigating the mediating role of mental health indices
between WLB and CFQ scores. Results: Compared with the highest subjective work–life balance group, the lowest group had significantly higher
CFQ scores. In the SEM, anxiety was a mediating variable between
subjective work–life balance and CFQ scores. Conclusions: Work–life
balance is associated with cognitive failures among Korean bus drivers,
and anxiety was a key mediating mental health indicator.
Keywords: anxiety, cognitive function, mental health, professional drivers,
work–life balance
W
ork–life balance (WLB) has been defined as ‘‘an individual’s ability to meet their work and family commitments, as
well as other non-work responsibilities and activities.’’1 This concept encompasses a balance between family, community, work, and
one’s own private life.2 WLB is the subjective perception that work
and nonwork activities are compatible and harmonious according to
one’s life priorities.3 It has been found that a poor WLB is negatively
associated with job satisfaction and life satisfaction.4,5 Recently,
several studies have reported that WLB is associated with sleep
disturbances or disorders, depressive mood, sickness absence, substance abuse, and subjective health-related symptoms.6– 9 All these
negative physical and psychological health outcomes could affect
job performance.
From the Department of Preventive Medicine, College of Medicine, Seoul
National University, Seoul, Republic of Korea (Dr Lee, Dr Hong, and Dr
Park); Public Health Medical Service, Seoul National University Hospital,
Seoul, Republic of Korea (Dr Seo); Department of Psychiatry, Kangbuk
Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul,
Republic of Korea (Dr Cho); Human Rights Center, Seoul National University Hospital, Seoul, Republic of Korea (Ms Nam and Dr Lee); and Department of Psychiatry, Seoul National University Hospital, Seoul, Republic of
Korea (Dr Lee).
Ethical approval: This study was approved by the Institutional Review Board
(IRB) of the Seoul National University Hospital (IRB No. C-1803-077-930).
This study was supported by donation funds of Seoul national university hospital
from Soo-Bum Lee.
The authors report no conflicts of interest.
Informed consent: Informed consent was obtained from all individual participants
included in the study.
Clinical significance: Our study found that subjective work–life balance is
associated with cognitive function measured by using cognitive failures
questionnaire. We suggest that improving work–life balance among bus
drivers would be an effective way to decrease traffic accidents related to
cognitive function.
Supplemental digital contents are available for this article. Direct URL citation
appears in the printed text and is provided in the HTML and PDF versions of
this article on the journal’s Web site (www.joem.org).
Address correspondence to: Nami Lee, PhD, Department of Psychiatry, Seoul
National University Hospital, Daehak-ro 103, Chongno-gu, Seoul 03080,
Republic of Korea (nami6107@naver.com).
Copyright ß 2019 American College of Occupational and Environmental
Medicine
DOI: 10.1097/JOM.0000000000001675
e406
Professional bus drivers have unique job requirements, which
include transporting a number of unspecified persons and driving
longer distances and for longer hours than other professional drivers
do. These unique characteristics make them more vulnerable to
accidents at work than other professions.10 In the United States,
69,000 bus accidents occurred in 2016, and 225 cases were fatal.11 In
Korea, 20,074 fatal and nonfatal traffic accidents caused by professional bus drivers occurred in 2017, usually accompanied by passenger injury. Although efforts to improve vehicles and safety devices are
necessary, more attention needs to be given to the drivers because 70%
of traffic accidents are attributed to cognitive failures.12 Cognitive
failures are defined as failures in perception, memory, and motor
functioning in which the action does not match the intention, and are
known as the most frequent cause of industrial accidents.13,14
In 2018, the Korean government introduced a 52-hour workweek rule to enhance the well-being of workers and ensure safer
working conditions, which seemed essential to lessen traffic accidents
and prevent road rage or violence against passengers. However, in
2019, trade unions including over 41,000 bus drivers threatened to go
on strike for their income loss caused by decreased working hours.15
For bus drivers in Korea, sufficient income to support their family may
be more strongly required than working less and having more private
time for their WLB. Without consensus on the importance and
consequence of WLB, public strategies and efforts aimed at improving the working conditions and health of ordinary workers may prove
futile. In view of making the workplace safe for workers, we focused
on WLB as an important factor affecting workers’ performance,
especially regarding accident prevention.
By focusing on WLB, we specifically sought to elucidate the
relationship between professional bus drivers’ subjective well-being
and safety at work. A decreased WLB has been reported as a factor
accounting for the decreased performance of workers.16,17 Recently,
it was reported that WLB is associated with cognitive function and
driving behavior, which may be strongly related to accident-proneness in professional drivers.18 The WLB of professional drivers has
been suggested as an important condition for the prevention of
sickness and accidents.19 Although WLB is known to be associated
with some medical and psychological conditions, which are known
as plausible factors in traffic accidents, it has not been studied
whether and how professional bus drivers’ WLB is associated with
their cognitive function regarding accident prevention.
We hypothesized that an impaired WLB causes increased
cognitive errors due to anxiety, depression, sleep disorders, and
substance abuse. Considering the abovementioned hypothesis, we
performed a survey among professional drivers to investigate (1) the
association between WLB and cognitive function measured by the
cognitive failures questionnaire (CFQ), (2) the association between
WLB and mental health indices, and (3) the possible pathway for the
effects of WLB on cognitive functions via mental health.
METHODS
Study Population
The target population was 16,753 city bus drivers belonging
to 68 companies in Seoul, South Korea, who were members of the
JOEM Volume 61, Number 10, October 2019
Copyright © 2019 American College of Occupational and Environmental Medicine. Unauthorized reproduction of this article is prohibited
JOEM Volume 61, Number 10, October 2019
Work–Life Balance and Cognitive Failures
labor union of bus drivers in Seoul. City bus companies in Seoul are
administrated by the city transportation office of the Seoul metropolitan government, who oversee the working hours and shift
patterns of bus drivers and routes of city bus lanes. Therefore,
the target population, city bus drivers in Seoul, had similar weekly
working hours up to 52 hours and two shifts (morning time, 8 hours
between 05:00 and 15:00; afternoon time, 8 hours between 15:00
and 01:00). Distances of city bus lanes are quite different from each
other, but are controlled in the range of 2 to 4 hours. With the
cooperation of the labor union, we recruited participants from 38
companies from July 13 to 18, 2018. We sampled 10 participants per
company whose schedules enabled them to participate in the survey.
The participants voluntarily filled out a self-administered questionnaire after reading the information about the survey. Of the 377 bus
drivers who participated in the study, those with incomplete answers
for WLB, cognitive, or mental health indices, as well as those with
missing information regarding age, sex, marital status, height,
weight, smoking status, alcohol consumption, or exercise, were
excluded. The final sample size used in the study was 347. This
study was approved by the Institutional Review Board of the Seoul
National University Hospital (IRB No. C-1803-077-930).
problems with daytime functioning, noticeability of sleep problems
by others, and distress caused by sleep difficulties. Those with ISI
scores of 15 or higher can be classified as having insomnia.27 The
Korean version of the ISI has been assessed for reliability and
validity.28
The Korean version of the Alcohol Use Disorder Identification Test (AUDIT-K) was used to assess the severity of alcohol use,
and problematic drinking was classified as an AUDIT-K score of 12
or above.29,30
Work–Life Balance
The mean values and standard deviations of subjective WLB
and CFQ scores were calculated according to sex, age (<40, 40 to
49, 50 to 59, and 60 years), years of bus driving experience (<10,
10 to 19, 20 to 29, and 30 years), BMI (<25 and 25), education
(elementary school or below, middle school, high school, and
college or above), household income (USD1300 to 2800;
USD2801 to 4200; USD4201 to 6400; and USD >6400 per month),
marital status (married, separated, widowed, divorced, and single),
smoking status, and disease status (hypertension, diabetes, dyslipidemia, coronary heart disease, stroke, depression, and sleep disorders). We used Student t tests and analysis of variance (ANOVA)
to compare the differences in WLB and CFQ scores according to
demographic variables.
Next, we calculated the mean and standard deviation of the
CFQ scores according to quartiles of subjective WLB scores and
quartiles of work–time control. Subsequently, we performed analysis of variance with covariance (ANCOVA) to compare the differences in CFQ scores after adjusting for age,sex, years of bus driving
experience, and diagnosed diseases. Covariates were identified
based on a review of a recent investigation of factors related to
CFQ scores in industry employees.31 Next, we calculated the mean
values of scores on the subjective assessment of WLB and the CFQ
according to mental health indices. ANCOVA was performed to
evaluate the relationship of CFQ and subjective WLB scores
according to mental health indices, with adjustment for age, sex,
years of bus driving experience, and diagnosed diseases.
After exploring the associations between WLB, mental
health concerns, and cognitive failures, we used structural equation
modeling (SEM) to investigate the direct effects of the subjective
assessment of WLB on cognitive failures and the indirect effects of
subjective WLB on cognitive failures in relation to the mental health
indices. SEM is a multivariate statistical analysis tool for estimating
the relationships among multiple variables simultaneously, in a
single analysis. Statistical analyses were performed using SAS
PROC TTEST, SAS PROC ANOVA, and SAS PROC GLM procedures (Version 9.4; SAS Institute Inc., Cary, NC), and SPSS
AMOS (Version 25.0; IBM, SPSS Inc., Chicago, IL). Statistical
significance was defined as two-sided P 0.05.
WLB was evaluated by the following sentence: ‘‘Please rate
the current state of your WLB from 0 to 100.’’ We measured work–
time control using a six-item scale developed by Ala-Mursula
et al,20 which was a modification of a standard survey instrument
of Statistics Finland. The participants were asked to indicate their
control over the following factors of their working schedules: (1) the
start and end times of a workday, (2) taking breaks during a
workday, (3) opportunity for handling private matters during a
workday, (4) scheduling of shift work, (5) scheduling of vacations
and paid days off, and (6) the taking of unpaid leave. The responses
were measured on a 10-point scale between 1 (cannot control at all)
and 10 (completely control), and the mean of the six items was used
in the analysis.
Cognitive Failures Questionnaire
The CFQ is a self-administered questionnaire for measuring
the degree of usual cognitive errors in daily life.13 The CFQ consists
of 25 items that assess perception, memory, and motor lapses in
daily life. CFQ items are answered on a five-point Likert scale of 0
(never) to 4 (very often), and the maximum score is 100.13,21 The
reliability and the validity of the Korean version of the CFQ have
been established.22
Mental Health Indices
The Patient Health Questionnaire (PHQ-9) was used to
measure depression. The PHQ-9 was developed as a diagnostic,
self-report tool for identifying depression, based on the criteria for
diagnosing depression from the 4th edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental
Disorders. The Korean version of the PHQ-9 has been validated, and
the optimal cutoff for screening for depressive disorders in Korea
was suggested as a score of 5.23,24
The Beck Anxiety Inventory (BAI) consists of a 21-item
questionnaire to measure the severity of anxiety symptoms.
Responses are rated on a four-point (0 to 3) Likert scale, and scores
can range from 0 to 63. Participants who score 10 or higher are
classified as having more than minimal anxiety.25 The Korean
translated version of the BAI has been validated.26
The Insomnia Severity Index (ISI), a self-report tool designed
to assess the severity of insomnia, is composed of seven items, each
scored on a five-point Likert scale. ISI measures the severity of
problems with sleep onset, sleep maintenance, and early morning
awakening, as well as sleep dissatisfaction, interference of sleep
ß
Other Variables
Demographic variables including age, sex, education, household income, marital status, and years of bus driving experience
were obtained. Anthropometric information (height in centimeters
and weight in kilograms), current smoking status, and medical
history (hypertension, diabetes, dyslipidemia, coronary heart disease, stroke, depression, and/or sleep disorders diagnosed by a
physician) were collected through self-reported questionnaires.
We calculated body mass index (BMI) based on the participants’
self-reported values.
Statistical Analysis
RESULTS
Table 1 lists the characteristics of the study population. The
mean WLB scores were significantly different according to years of
bus driving experience (P ¼ 0.013) and current smoking status
(P ¼ 0.006). The mean CFQ score was 18.1 (10.8), and differences
2019 American College of Occupational and Environmental Medicine
e407
Copyright © 2019 American College of Occupational and Environmental Medicine. Unauthorized reproduction of this article is prohibited
JOEM Volume 61, Number 10, October 2019
Lee et al
TABLE 1. Characteristics and Cognitive Failures Questionnaire Scores of the Participants
Subjective Work–Life Balance (0 – 100)
Total
Sex
Male
Female
Age, y
<40
40–49
50–59
60
Years of bus driving experience, y
<10
10–19
20–29
30
BMI, kg/m2
<25
25
Education
Elementary school
Middle school
High school
College
Household income (USD)
1333–2766
2767–4198
4199–6436
>6436
Civil status
Married
Separated
Widowed
Divorced
Single
Current smoking
No
Yes
Hypertension
Yes
No
Diabetes
Yes
No
Dyslipidemia
Yes
No
Coronary heart disease
Yes
No
Stroke
Yes
No
Depression
Yes
No
Sleep disorders
Yes
No
CFQ
n (%) [or Mean SD]
Mean SD
347 (100.0)
71.4 15.6
331 (95.4)
16 (4.6)
52.0 6.2
5 (1.4)
125 (36.0)
184 (53.0)
33 (9.5)
15.9 7.3
74 (21.3)
171 (49.3)
87 (25.1)
15 (4.3)
24.7 2.8
206 (59.4)
141 (40.6)
71.4 15.6
70.9 14.9
0.906
18.1 10.9
16.8 10.7
0.620
68.0 22.8
69.6 15.6
72.2 14.9
74.4 17.6
0.298
18.6 16.7
17.3 11.4
18.6 9.8
17.8 13.4
0.800
72.9 16.4
73.2 14.2
66.7 16.4
70.9 17.0
0.013
17.6 11.0
18.0 11.1
19.5 9.8
13.1 12.0
0.188
70.6 15.6
72.5 15.5
0.269
17.6 10.7
18.8 11.1
0.317
7
44
252
44
(2.0)
(12.7)
(72.6)
(12.7)
75.7 23.2
70.0 16.2
70.9 15.4
75.0 14.4
0.307
12.3 11.3
17.8 11.9
18.1 10.6
19.2 10.9
0.474
99
164
78
6
(28.5)
(47.3)
(22.5)
(1.7)
73.4 14.3
70.3 16.1
70.7 16.0
77.5 14.1
0.305
17.4 11.4
17.6 10.8
20.3 10.2
13.3 8.1
0.151
295
9
4
24
15
(85.0)
(2.6)
(1.2)
(6.9)
(4.3)
71.5 15.8
66.1 16.5
72.5 15.0
71.8 15.6
71.0 11.8
0.786
18.0 13.6
17.7 10.5
24.3 15.6
35.5 18.8
17.3 7.5
0.003
237 (68.3)
110 (31.7)
72.9 14.5
68.1 17.3
0.006
17.6 10.8
19.1 10.9
0.248
95 (27.4)
252 (72.6)
70.7 17.1
71.6 15.0
0.623
16.7 9.5
18.6 11.3
0.058
25 (7.2)
322 (92.8)
73.7 14.4
71.2 15.7
0.437
19.3 11.7
18.0 10.8
0.592
61 (17.6)
286 (82.4)
69.0 17.1
71.9 15.2
0.179
17.2 8.9
18.3 11.2
0.491
5 (1.4)
342 (98.6)
78.0 11.0
71.3 15.6
0.339
14.0 11.7
18.1 10.8
—
2 (0.6)
345 (99.4)
70.0 14.1
71.4 15.6
0.900
7.5 0.7
18.1 10.8
—
1 (0.3)
346 (99.7)
90.0
71.3 15.6
48
18.0 10.7
—
10 (2.9)
337 (97.1)
67.5 14.4
71.5 15.6
P
Mean SD
P
18.1 10.8
0.424
23.9 12.1
17.9 10.8
0.084
Significant P values (0.05) are in bold.
CFQ, cognitive failures questionnaire.
in CFQ scores were significant according to smoking status
(P ¼ 0.024) and marital status (P ¼ 0.003).
Table 2 shows the indices for WLB of the study population.
Differences in CFQ scores were significant only with respect to the
subjective scores of WLB and were not significantly influenced by
e408
ß
weekly working hours or work–time control. Compared with the
lowest quartile of subjective WLB scores, the third (P ¼ 0.004) and
fourth quartiles ( P < 0.001) showed significantly lower CFQ scores
after adjusting for age, sex, years of bus driving experience, and
diagnosed disease status.
2019 American College of Occupational and Environmental Medicine
Copyright © 2019 American College of Occupational and Environmental Medicine. Unauthorized reproduction of this article is prohibited
JOEM Volume 61, Number 10, October 2019
Work–Life Balance and Cognitive Failures
TABLE 2. Indices for Work–Life Balance and Cognitive Failures Questionnaire Scores of the Participants
CFQ
n (%) [or Mean SD]
Subjective work–life balance
Q1 (20–60)
Q2 (63–70)
Q3 (73–80)
Q4 (85–100)
Weekly working hours
Q1 (40.0–49.5)
Q2 (50.0–51.0)
Q3 (52.0–55.0)
Q4 (56.0–80.0)
Work-time control
Q1 (1.0–1.7)
Q2 (1.8–2.7)
Q3 (2.8–4.2)
Q4 (4.3–9.3)
71.4 15.6
97 (28.0)
84 (24.2)
97 (28.0)
69 (19.9)
52.4 7.1
77 (22.2)
77 (22.2)
109 (31.4)
84 (24.2)
3.2 1.7
82 (23.6)
94 (27.1)
84 (24.2)
87 (25.1)
Mean SD
P
20.9 9.6
18.8 12.0
16.4 11.0
15.6 9.9
(Ref.)
0.154
0.004
<0.001
16.1 9.2
18.8 12.5
18.6 11.5
18.5 9.6
(Ref)
0.083
0.103
0.116
17.9 10.6
16.8 10.1
19.6 10.1
18.1 12.4
(Ref)
0.603
0.255
0.858
Significant P values (0.05) are in bold.
Results of the analysis of covariance with covariates (ANCOVA) adjusting for age, sex, working duration, diagnosed disease status (eg, hypertension, diabetes, dyslipidemia,
coronary vessel disease, stroke, depression, and sleep disorders).
CFQ, cognitive failures questionnaire; Ref., reference; SD, standard deviation.
The results of the subjective WLB scores and differences in
CFQ scores according to the mental health indices are given in
Table 3. Depressive status, anxiety, insomnia, and alcohol use
disorder were significantly associated with higher CFQ scores.
These mental health indices were also significantly associated with
poorer subjective assessment of WLB.
Finally, SEM analysis was performed to investigate how
subjective assessment of WLB and work–time control are associated with cognitive failures (Fig. 1). In this model, mild depressive
status (PHQ-9 5), mild anxiety status (BAI 10), insomnia (ISI
15), and problematic drinking (AUDIT-K 12) were considered
as potential mediating variables in the association between WLB
and cognitive failures. The results showed good model fit with a
comparative fit index of 0.998 and a root mean square error of
approximation of 0.22. The indirect effects of WLB were significant, but the direct effects were not significant (b ¼ –0.037,
P ¼ 0.835). WLB was significantly and negatively associated with
depression (b ¼ –0.011, P < 0.001), anxiety (b ¼ –0.006,
P < 0.001), insomnia (b ¼ –0.007, P < 0.001), and alcohol use
disorder (b ¼ –0.002, P < 0.001). In this model, among the mental
health indices, only anxiety had significant indirect effects in the
association between WLB and CFQ scores (b ¼ 8.914, P ¼ 0.004).
We carried out sensitivity analyses after excluding widowed or
divorced participants, as they displayed significantly higher CFQ
scores than married, separated, or single participants, but the results
were robust and concurrent with the main analyses (Supplementary
Tables 1 to 2, http://links.lww.com/JOM/A592 and Supplementary
Figure 1, http://links.lww.com/JOM/A592). The SEM analysis
results were also robust, as anxiety had significant indirect effects
with respect to WLB and CFQ scores (b ¼ 9.274, P ¼ 0.002).
DISCUSSION
Self-reported poor WLB of professional bus drivers suggests
that the participants subjectively feel their lives are not sufficiently
TABLE 3. Mental Health Indices, Cognitive Failures Questionnaire Scores, and Subjective Work–Life Balance of the Participants
CFQ
n (%)
Depression (PHQ-9)
<5
232 (66.9)
5
115 (33.1)
Anxiety (BAI)
<10
282 (81.3)
10
65 (18.7)
Insomnia (ISI)
<15
189 (54.5)
15
158 (45.5)
Alcohol use disorder (AUDIT-K)
<12
77 (22.2)
12
270 (77.8)
Subjective Work–Life Balance
Mean SD
P
Mean SD
P
14.7 9.0
24.8 11.1
<0.001
75.3 13.6
63.5 16.2
<0.001
15.6 9.0
28.9 11.4
<0.001
73.0 15.1
64.5 15.7
<0.001
15.1 10.5
21.6 10.2
<0.001
75.3 14.4
66.7 15.7
<0.001
15.5 11.6
18.8 10.5
0.014
75.1 14.8
70.3 15.6
0.036
Significant P values (0.05) are in bold.
Results of the analysis of covariance with covariates (ANCOVA) adjusting for age, sex, working duration, diagnosed disease status (eg, hypertension, diabetes, dyslipidemia,
coronary vessel disease, stroke, depression, and sleep disorders).
AUDIT-K, Korean version of the Alcohol Use Disorders Identification Test; BAI, Beck Anxiety Inventory; CFQ, cognitive failures questionnaire; ISI, Insomnia severity index;
PHQ-9, Patient Health Questionnaire; SD, standard deviation.
ß
2019 American College of Occupational and Environmental Medicine
e409
Copyright © 2019 American College of Occupational and Environmental Medicine. Unauthorized reproduction of this article is prohibited
JOEM Volume 61, Number 10, October 2019
Lee et al
FIGURE 1. Structural equation model of work-life balance, cognitive failures, and mental health indices. AUDIT-K, Korean version
of the Alcohol Use Disorders Identification Test; AUDIT-K, the Korean version of the alcohol use disorders identification test; BAI,
Beck Anxiety Inventory; BAI, Beck anxiety inventory; ISI, Insomnia Severity Index; ISI, Insomnia severity index; PHQ-9, Patient
Health Questionnaire.
stable, secure, and healthy, due to the loss of balance between work
and life. We found associations among WLB, depression, anxiety,
insomnia, alcohol use disorder, and cognitive failures in professional bus drivers. After adjusting for possible confounding variables, higher subjective WLB scores were significantly associated
with lower cognitive failures in bus drivers. We also found that
anxiety is a key mediating factor in the relationship between WLB
and cognitive failures. To the best of our knowledge, this is the first
study of the relationship between WLB and cognitive function
among bus drivers.
Cognitive failures, as the major cause of driver errors and
violations, could result in serious damage to passengers and pedestrians.32 In their meta-analysis, Arthur et al reported cognitive
ability as one of the predictors of driving accidents.33 Larson
et al studied 159 male Navy recruits in the United States and
reported that participants who had experienced causing a traffic
accident had significantly higher CFQ scores than participants who
had not.34 A study with 160 Iranian professional drivers reported
that total CFQ scores were strongly associated with driving errors.35
Previous studies support that low CFQ scores, associated with poor
subjective WLB, are potential risk factors for driving accidents
caused by professional bus drivers.
Neurologically, chronic stress-related conditions, ‘‘allostatic
load,’’ could induce structural remodeling of areas of the brain that
are important for cognitive function, including the hippocampus, the
amygdala, and the prefrontal cortex.36 With anxiety symptoms, the
insula cortex and the right amygdala are activated, and the posterior
cingulate cortex is deactivated.37 Anxiety influences the processing
of the stimulus-driven attentional system and goal-directed attention; therefore, healthy cognitive function supported by goaldirected attention cannot be well sustained. Without compensatory
strategies, such as enhanced effort, anxiety impairs performance
effectiveness.38 Epidemiologic studies also reported that anxiety or
worry has negative effects on processing efficiency for high-attentional or short-term memory demands by causing deficits in the
storage and processing capacities of the working memory system.39
Anxious patients show poorly regulated attention mechanisms,
inhibited performance on attentional tasks, and poor ability to
utilize attentional resources.40 In this context, anxiety could play
an important role regarding accident-proneness.
We also found that poor WLB was associated with the onset
of depression, anxiety, insomnia, and alcohol use disorders in our
e410
ß
sample. For testing our hypothesis, which is related to WLB,
cognitive function, and mental health, we selected four disease
entities that are most prevalent and significantly impair common
people’s competencies. We excluded other serious psychotic and
organic brain diseases that are rarely found among regularly working populations. We found that poor WLB was positively associated
with depression, anxiety, insomnia, and alcohol use disorders in our
sample, which confirms the findings of previous studies on the
relation between WLB and mental health indices.
Such findings are compatible with the studies on the similar
topics of other workers. Among US nurses, work–family conflict is
significantly associated with depressive symptoms.41 A cohort
study with a representative national sample of 2700 employed
adults in the United States reported that work–family conflict is
a risk factor for mood, anxiety, and substance dependence disorders.42 Another longitudinal study revealed that improvements in
work–family conflict are associated with improved mental health.43
Although several studies have reported the association
between WLB and patterns of safety behaviors,19,44 to our knowledge, it was not yet reported that subjective WLB itself was directly
or indirectly (or both) associated with CFQ scores in relation to
driving accidents. It is important to improve professional bus
drivers’ WLB, which will help to prevent traffic incidents and
improve the safety of transportation services. The result that anxiety
is a key mediating factor between WLB and cognitive failures
implies that job-stress intervention and counseling programs in the
workplace to ameliorate anxiety, one of the important target symptoms, would be beneficial for preventing traffic accidents caused by
bus drivers, and better service for passengers.45 Providing a psychological buffer for workers facing the dilemma between work and
life commitments and lessening anxiety will be an important goal
for the workplace health promotion program.46 In addition, in our
study, bus drivers who smoke reported significantly lower WLB.
These results suggest that promoting a smoking cessation program
in the workplace could be beneficial to the WLB of bus drivers, as it
has positive effects on anxiety symptoms.47 Moreover, the anxiety
treatment process may be helpful to the smoking cessation process,
especially for professional bus drivers.
Our study has several strengths. First, to our knowledge, it is
the first to investigate the association between WLB and cognitive
failures in bus drivers. Second, we used validated tools to assess
cognitive function in daily life (CFQ) and mental health (PHQ-9,
2019 American College of Occupational and Environmental Medicine
Copyright © 2019 American College of Occupational and Environmental Medicine. Unauthorized reproduction of this article is prohibited
JOEM Volume 61, Number 10, October 2019
BAI, ISI, and AUDIT-K) which offer stronger sensitivity and
specificity than nonvalidated methods regarding the relation among
cognition, anxiety, and other mental illness. Third, the complete
survey response rate was as high as 91.3%. Both high response rate
and high complete response rate help ensure minimal selection bias,
as it suggests that few respondents were reluctant to finish the
survey due to a specific or consistent reason.
Our study has several limitations that need to be considered in
the interpretation of our findings. First, we chose only one question
for the subjective evaluation of WLB because grading a subjective
feeling is an important index. Although WLB of an individual
cannot be evaluated without considering an individual’s subjective
outlook on his/her life, well-validated and widely used tools for
measuring WLB will be necessary for further quantitative analysis.
Second, we did not explore the specific determinants for subjective
WLB. In the future, the relationship between work–family conflict
and cognitive failure needs to be examined using a multidimensional measure of work–family conflict.48 Third, our study was
designed as a cross-sectional study; thus, we could not conclude the
directions of causality of the relationships between subjective WLB,
mental health, and cognitive failures. As we have discussed, mental
health indices and CFQ scores are closely correlated, and WLB may
also be closely associated with mental health indices. Although the
SEM results showed the best-fit results for our data, reverse
causation should be considered in our cross-sectional study. Fourth,
we targeted bus drivers in a metropolitan city; therefore, it is
difficult to generalize our results to bus drivers in other areas, such
as smaller cities or the countryside or other countries. Finally, the
issue of the sex-related medical issues in work–life conflicts were
not addressed because the sex ratio of the study participants was
highly uneven, as most Korean bus drivers are male, although the
sex difference in perceiving and experiencing WLB and mental
disorders are significantly different.49
CONCLUSIONS
We found associations between the WLB, mental health
indices, and cognitive failures of Korean bus drivers. Anxiety
was a key mediating mental health issue between WLB and
cognitive failures. Our findings suggest that improving WLB among
bus drivers would be an effective way to decrease traffic accidents
related to cognitive function.
REFERENCES
1. Delecta P. Work life balance. Int J Curr Res. 2011;3:186–189.
2. Guest DE. Perspectives on the study of work-life balance. Soc Sci Inform.
2002;41:255–279.
3. Kalliath T, Brough P. Work–life balance: a review of the meaning of the
balance construct. J Manage Org. 2008;14:323–327.
4. Carlson DS, Grzywacz JG, Michele Kacmar K. The relationship of schedule
flexibility and outcomes via the work-family interface. J Manage Psychol.
2010;25:330–355.
5. Wayne JH, Musisca N, Fleeson W. Considering the role of personality in the
work–family experience: relationships of the big five to work–family
conflict and facilitation. J Vocat Behav. 2004;64:108–130.
6. Salo P, Ala-Mursula L, Rod NH, et al. Work time control and sleep
disturbances: prospective cohort study of Finnish public sector employees.
Sleep. 2014;37:1217–1225.
7. Hämmig O, Gutzwiller F, Bauer G. Work-life conflict and associations with
work- and nonwork-related factors and with physical and mental health
outcomes: a nationally representative cross-sectional study in Switzerland.
BMC Public Health. 2009;9:435.
8. Antai D, Oke A, Braithwaite P, Anthony D. A ‘balanced’life: work-life
balance and sickness absence in four Nordic countries. Int J Occup Environ
Med. 2015;6. 667-205-622.
9. Wang J, Afifi TO, Cox B, Sareen J. Work-family conflict and mental
disorders in the United States: cross-sectional findings from The National
Comorbidity Survey. Am J Ind Med. 2007;50:143–149.
ß
Work–Life Balance and Cognitive Failures
10. John L, Flin R, Mearns K. Bus driver well-being review: 50 years of research.
Transp Res Part F Traffic Psychol Behav. 2006;9:89–114.
11. Blower D, Green P. Type of motor carrier and driver history in fatal bus
crashes. Transp Res Record Jo Transp Res Board. 2010;37–43.
12. Treat JR, Tumbas NS, McDonald ST, et al. Tri-level study of the causes of
traffic accidents. Bloomington, Indiana: Indiana University; 1979.
13. Broadbent DE, Cooper PF, FitzGerald P, Parkes KR. The cognitive failures
questionnaire (CFQ) and its correlates. Br J Clin Psychol. 1982;21:1–16.
14. Wagenaar WA, Hudson PT, Reason JT. Cognitive failures and accidents. Appl
Cogn Psychol. 1990;4:273–294.
15. Hyun-bin K. Nationwide bus strike looming large. The Korea Times, Seoul,
Korea; 2019.
16. Blazovich JL, Smith KT, Smith M. Employee-friendly companies and worklife balance: Is there an impact on financial performance and risk level?
Journal of Organizational Culture Communications and Conflict.
2013;18:1–13.
17. Whiston SC, Cinamon RG. The work–family interface: Integrating research
and career counseling practice. Career Dev Q. 2015;63:44–56.
18. Abdoli N, Farnia V, Delavar A, et al. Poor mental health status and aggression
are associated with poor driving behavior among male traffic offenders.
Neuropsychiatr Dis Treat. 2015;11:2071–2078.
19. Wei W, Guo M, Ye L, Liao G, Yang Z. Work-family conflict and safety
participation of high-speed railway drivers: job satisfaction as a mediator.
Accid Anal Prev. 2016;95:97–103.
20. Ala-Mursula L, Vahtera J, Kivimäki M, Kevin MV, Pentti J. Employee
control over working times: associations with subjective health and sickness
absences. J Epidemiol Community Health. 2002;56:272–278.
21. Meiran N, Israeli A, Levi H, Grafi R. Individual differences in self reported
cognitive failures: the attention hypothesis revisited. Pers Individ Dif.
1994;17:727–739.
22. Lee A-H, Park H-S, Ahn I-S, Chang W-H, Yun-He K. A Study on a Koreantranslated Version of the Cognitive Failures Questionnaire. J Korean Soc
Occup Ther. 2011;19:117–129.
23. Han C, Jo SA, Kwak J-H, et al. Validation of the Patient Health Questionnaire-9 Korean version in the elderly population: the Ansan Geriatric study.
Compr Psychiatry. 2008;49:218–223.
24. Park S-J, Choi H-R, Choi J-H, Kim K, Hong JP. Reliability and validity of the
Korean version of the Patient Health Questionnaire-9 (PHQ-9). Anxiety
Mood. 2010;6:119–124.
25. Beck AT, Steer RA. Manual for the Beck Anxiety Inventory. San Antonio, TX:
Psychological Corporation; 1990.
26. Yook SP, Kim ZS. A clinical study on the Korean version of Beck Anxiety
Inventory: comparative study of patient and non-patient. Korea J Clin
Psychol. 1997;16:185–197.
27. Bastien CH, Vallières A, Morin CM. Validation of the Insomnia Severity
Index as an outcome measure for insomnia research. Sleep Med.
2001;2:297–307.
28. Cho YW, Song ML, Morin CM. Validation of a Korean version of the
insomnia severity index. J Clin Neurol. 2014;10:210–215.
29. Saunders JB, Aasland OG, Babor TF, De la Fuente JR, Grant M. Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol
consumption-II. Addiction. 1993;88:791–804.
30. Lee BO, Lee CH, Lee PG, Choi MJ, Namkoong K. Development of Korean
version of alcohol use disorders identification test (AUDIT-K): its reliability
and validity. J Korean Acad Addict Psychiatry. 2000;4:83–92.
31. Mahdinia M, Mirzaei Aliabadi M, Darvishi E, Mohammadbeigi A, Sadeghi
A, Fallah H. An investigation of cognitive failures and its related factors in
industry employees in Qom Province, Iran, in 2016. J Occup Health
Epidemiol. 2017;6:157–164.
32. Wickens CM, Toplak ME, Wiesenthal DL. Cognitive failures as predictors of
driving errors, lapses, and violations. Accid Anal Prev. 2008;40:1223–1233.
33. Arthur W, Barret GV, Alexander RA. Prediction of vehicular accident
involvement: a meta-analysis. Hum Perform. 1991;4:89–105.
34. Larson GE, Merritt CR. Can accidents be predicted? An empirical test of the
Cognitive Failures Questionnaire. Appl Psychol. 1991;40:37–45.
35. Allahyari T, Saraji GN, Adi J, et al. Cognitive failures, driving errors and
driving accidents. Int J Occup Saf Ergon. 2008;14:149–158.
36. McEwen BS. Protective and damaging effects of stress mediators: central
role of the brain. Dialogues Clin Neurosci. 2006;8:367.
37. Martin EI, Ressler KJ, Binder E, Nemeroff CB. The neurobiology of anxiety
disorders: brain imaging, genetics, and psychoneuroendocrinology. Psychiatric Clin. 2009;32:549–575.
2019 American College of Occupational and Environmental Medicine
e411
Copyright © 2019 American College of Occupational and Environmental Medicine. Unauthorized reproduction of this article is prohibited
JOEM Volume 61, Number 10, October 2019
Lee et al
38. Eysenck MW, Derakshan N, Santos R, Calvo MG. Anxiety and cognitive
performance: attentional control theory. Emotion. 2007;7:336.
39. Eysenck MW, Calvo MG. Anxiety and performance: the processing efficiency theory. Cogn Emot. 1992;6:409–434.
40. Robinson OJ, Vytal K, Cornwell BR, Grillon C. The impact of anxiety upon
cognition: perspectives from human threat of shock studies. Front Hum
Neurosci. 2013;7:203.
41. Zhang Y, Duffy JF, De Castillero ER. Do sleep disturbances mediate the
association between work-family conflict and depressive symptoms among
nurses? A cross-sectional study. J Psychiatr Ment Health Nurs.
2017;24:620–628.
42. Frone MR. Work–family conflict and employee psychiatric disorders: the
national comorbidity survey. J Appl Psychol. 2000;85:888.
43. Cooklin AR, Dinh H, Strazdins L, Westrupp E, Leach LS, Nicholson JM.
Change and stability in work-family conflict and mothers’ and fathers’
mental health: Longitudinal evidence from an Australian cohort. Soc Sci
Med. 2016;155:24–34.
e412
ß
44. Greubel J, Arlinghaus A, Nachreiner F, Lombardi DA. Higher risks when
working unusual times? A cross-validation of the effects on safety, health,
and work-life balance. Int Arch Occup Environ Health. 2016;89:1205–1214.
45. Martin A, Sanderson K, Cocker F. Meta-analysis of the effects of health
promotion intervention in the workplace on depression and anxiety symptoms. Scand J Work Environ Health. 2009;35:7–18.
46. Proudfoot D, Kay AC. How perceptions of one’s organization can affect
perceptions of the self: membership in a stable organization can sustain
individuals’ sense of control. J Exp Soc Psychol. 2018;76:104–115.
47. Taylor G, McNeill A, Girling A, Farley A, Lindson-Hawley N, Aveyard P.
Change in mental health after smoking cessation: systematic review and
meta-analysis. BMJ. 2014;348:g1151.
48. Barnett RC, Baruch GK. Women’s involvement in multiple roles and
psychological distress. J Pers Soc Psychol. 1985;49:135.
49. Mishra R. Gender differences in work-life balance: comparative study of
public and private sector bank employees. Indian J Community Psychol.
2014;10:88–95.
2019 American College of Occupational and Environmental Medicine
Copyright © 2019 American College of Occupational and Environmental Medicine. Unauthorized reproduction of this article is prohibited