Field ReportIndustrial Health 2024, 62, 67–76

Characteristics of mental disorders among
information technology workers in 238 compensatedcases in Japan
Yuki TAKAHASHI1*, Toru YOSHIKAWA2, Kenji YAMAMOTO1 and Masaya TAKAHASHI2
1
2

Department of Psychiatry, Tokai University School of Medicine, Japan
Research Center for Overwork-Related Disorders, National Institute of Occupational Safety and Health, Japan
Received November 10, 2022 and accepted April 4, 2023
Published online in J-STAGE April 13, 2023
DOI https://doi.org/10.2486/indhealth.2022-0197

Abstract: This study aimed to investigate the circumstances, characteristics, and background factors of mental disorders within the information technology (IT) industry, which is known for thefrequent occurrence of mental disorders from overwork and poor psychosocial work environment.
The study analyzed 238 cases of mental disorders and suicides in the IT industry from fiscal years
2010 to 2018 on the database constructed by the Japan Research Center for Overwork-Related
Disorders. The results showed a higher number of cases among men (n=178, 74.8%) and an increasing number among women. The data for diagnosis of mental diseases indicated a high numberof depressive episodes (150 cases, 63.0%). Regarding work-induced psychological burden, 37 cases(15.5%) reported “extremely long working hours” for “special events” and 65 cases (27.3%) reported “constantly long working hours”. For “specific events”, 87 cases (36.6%) reportedly “caused(major) changes in the content and amount of work”. Among women, 13 cases (21.7%) of “sexual
harassment” (SH), which showed an increasing trend. Therefore, in the IT industry, the working
hours must be properly managed. Mental health measures should also accompany improved psychosocial environment in the workplace, and prohibition of SH at work in particular.
Key words: Information technology (IT) industry, Mental disorders, Mental health, Psychology,
Sexual harassment

Introduction
In 2015, the Ministry of Health, Labour and Welfareof Japan published the General Principles on Measures
to Prevent Death from Overwork to eliminate death fromoverwork and aimed for a society where people can continue to work in good health in a fulfilled manner1).
Besides other industries such as transportation, educa*To whom correspondence should be addressed.
E-mail: tacker-kitinosuke@tokai-u.jp©2024 National Institute of Occupational Safety and Healthtion, food service, medical care, construction, and the
media, death from overwork, known as “Karoshi”, occurs
frequently in the information technology (IT) industry
too1). Indeed, according to FY 2018 industry (intermediateclassification) statistics on death from overwork, the IT
industry ranked eighth, with 23 cases of workers’ demanding compensation for mental disorders 2). Stakeholders
have called for measures to improve work environmentand safeguard workers’ health in the information and telecommunications industry, including system engineers (SEs)and programmers (PGs)3–10).
Previous researches indicate that workers in this indus-

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68
try are overworked and placed in harsh working environments owing to factors such as strict deadlines, customer
service, and sudden changes in specifications11, 12). Meanwhile, the demand for human resources in this industry
is expected to increase, and estimates indicate a shortageof approximately 300,000 people in 2020 and 450,000
people in 2030 in Japan13). Therefore, an urgent issue isthe review of and improvement in the excessive workload
required of SEs and PGs, along with the implementationof measures for preventing mental disorders.
The analysis of mental disorders, such as death fromoverwork of workers in the IT industry, can help understand working patterns that anticipate the future working
styles of workers, ultimately contributing to the preventionof death by overwork. Furthermore, as the demand forhuman resources in the IT industry is expected to increase
further in the future, it is expected that there will be an
analysis of industrial accident certification cases in the IT
industry.
The previous report by our research team has analyzed
mental disorders among workers in the IT industry forthe period 2010–201514); Kan reported that 3/4 of mental
disorders were depressive episodes, and suicide wasaround 30%14). However, factors other than their genderand overtime are not clear. In recent years, there has beena growing interest in harassment and mental disorders, andby examining factors other than the amount of overtime,gender differences, and the actual state of suicide, including cases from 2015 onward, we can provide insights that
contribute to countermeasures. Focusing on cases of mental disorders that arise due to overwork being recognized
as industrial accidents that lead to death in 2010–2018, ourstudy aimed to clarify the actual circumstances and characteristics of mental disorders, such as death by overwork
among SEs and PGs, and provide insights to formulate
countermeasures.

Methods
Data source and procedures
From 2010 to 2018, labor bureaus across Japan and theLabor Standards Inspection Office at the Research Center
for Overwork-Related Disorders (RECORDs) of the National Institute of Occupational Safety and Health, Japan(JNIOSH), collected the documents of compensation claim
reports about occupational accident recognition cases formental disorders that should be compensated about as
defined in the workers’ compensation system in Japan andrelated materials.

Y TAKAHASHI et al.
We subsequently constructed a database on death by
overwork by quantifying the contents of the survey reportsthat facilitated statistical processing. In this study, we
focused on the information and communication industry in
the Japan Standard Industrial Classification (major classification), which corresponds to the IT industry. We analyzed
a total of 238 cases of mental disorders from the databasein a previous five-year period (FY 2010–2014, 124 cases)
and in the most recent four years (FY 2015–2018, 114
cases).
We extracted the following work features from thesurvey reports: SEs were mainly engaged in information
processing, system design, software, etc.; and PGs weremainly engaged in the manufacturing process (programming, testing, etc,) in system development after receiving
the design from SEs. Mental disorders were classified
based on Chapter 5, “Mental and behavioral disorders(F00-F99)” in the International Statistical Classificationof Diseases and Related Health Problems (ICD-10) 10th
Revision (revised 2003).
This research was conducted with the approval of theInstitutional Review Board of the National Institute ofOccupational Safety and Health of Japan in the Japan Organization of Occupational Health and Safety (notification
number: 2021N26). The database used in this study did
not contain any personal information, such as names, addresses, telephone numbers, or other identify information.
Analysis method
We analyzed SEs, PGs, and other occupations in theinformation and communication industry. Based on thecontents of the survey reports, analyses were conductedaccording to sex, age at onset, size of workplace, occupation, disease, general items (e.g., working conditions),
occupational accident recognition factors, and number ofovertime hours. The analysis involved the collection of basic data from the database in a previous five-year period (FY
2010–2014, 124 cases) and in the most recent four years(FY 2015–2018, 114 cases), and analysis of the factors
contributing to the prevention of death from overwork,and focusing on changes from previous reports 14). The
analysis of psychosocial factors caused to mental disorders
was limited to those of cases that were recognized by the“Recognition Criteria for Mental Disorders Caused by
Psychological Stress” (henceforth, “Recognition Criteria”), which was established by Japan Ministry of Health,Labour and Welfare in December 2011.
We used the data listed in the survey reports for the
information and communications industry and the occupaIndustrial Health 2024, 62, 67–76

69

MENTAL DISORDERS AT WORKERS IN JAPANtions of the victims. However, for the SEs and PGs, somedata were changed to occupation that were considered appropriate per the analyzer’s reading of the survey reports.
Moreover, in this study, we adopted the following definition of sexual harassment (SH): physical contact with thechest, waist, etc., and sexual behavior toward workers in
the workplace, resulting in disadvantageous working conditions or harm to the working environment. Additionally,rape (sexual coercion) was defined as follows: forcing awoman to commit sexual acts against her will by using
violence, threats, or the insanity of the other party15).

Results
Overview of the mental disorders cases
Size of workplace, industry, occupation, and labor
management
The cases tended to be employed at workplaces with
100–499 people (69 cases, 29.0%), with the number ofcases in relatively large-scale workplaces being prominent.
With regards to occupations, 83 cases (34.9%) were SEs
and 16 cases (6.7%) were PGs.
For prescribed holidays, 160 cases (67.2%) had complete
five-day workweeks. Concerning the status of attendance
management, reporting by the employee was the mostcommon at 135 cases (56.7%), followed by confirmationby the manager (81 cases, 34.0%), use of time cards (58cases, 24.4%), and confirmation using an attendance book
(51 cases, 21.4%). Moreover, employment regulations(95%: none, excluding those that had no description) andwage regulations (93.3%: none, excluding those that had
no descriptions) were enacted in almost all cases.
Sex, age at onset, life or death, and disease at time ofdecision
Table1 shows the sex, age at onset, life or death, anddisease at the time of case decision. We observed anincreasing number of cases in women (The proportion of
women was 19.4% from 2010 to 2014 and 28.9% from2015 to 2018) and a high occurrence of mental disorders
in those aged 30–39 yr. More than one-fifths (21.4%) of
the cases ended in death (suicide). The most prevalentdisease was mood (affective) disorders, particularly depressive episode. Neurotic, stress-related, and somatoform
disorders were also reported, which included cases ofadjustment disorders.
Work-related adverse events by sex
Tables 2 and 3 show the occupational accident recogni-tion factors for men and women, respectively.
When describing work-induced psychological burdenof the “special events”, “extremely long working hours”
accounted for 30 cases (16.9%) among men and 7 cases(11.7%) among women. As many as 54 cases (30.3%)
among men and 11 cases (18.3%) among women wereobserved for “constantly long working hours”.
For “specific events,” 87 cases (36.6%) reportedly“caused (major) changes in the content and amount ofwork”. Among women, five (8.3%) cases of “rape” werereported (“rape” is included in the “extreme psychologicalburden” of Table 3. “Extreme psychological burden” is an
occupational illness or injury that is life-threatening, extremely painful or leaves a residual disability that renders
one permanently incapable of working. However, from2010 to 2018, all cases were rapes of women.), as well
as 13 cases (21.7%) of “sexual harassment” (SH), whichshowed an increasing trend (14.8% in 4 cases from 2010
to 2014 and 27.3% in 9 cases from 2015 to 2018).
Sexual harassment and rape
Table 4 shows data on SH15). SH cases were reported by
women in their 20s and 30s. The perpetrators were directsuperiors and business owners. In most cases, the attack
occurred during working hours. Among the 13 cases ofSH, one case led to counseling by an industrial physician
and consultation with a psychiatrist after a stress check,and two cases led to a consultation with a psychiatrist
through a women’s counseling office (compliance desk).
Rape perpetrators were found to be the client in three ofthe five cases. Many of them progressed by starting withsexual behavior and physical contact and culminating inforced sexual acts. Most of the victims reported developing post-traumatic stress disorder.

Discussion
This study investigated the picture and background of
psychosocial factors causing workers’ compensation owing to mental disorders in the IT industry.
The results clarified that cases of mental disorders due
to overwork generally involved men employees (74.8%),
but the number of cases involving women employees
trended upward over time (The proportion of womenwas 19.4% from 2010 to 2014 and 28.9% from 2015 to2018). Remote working may continue to increase in the
future, depending on the impact of COVID-19. Remote
working is said to allow people to spend more time doing
chores and other chores by reducing commuting time16).

5 (38.5)
2 (15.4)
2 (15.4)

10 (45.4)
3 (13.6)
1 (22.7)

30–39

40–49

50–59

4 (18.1)
0 (0.0)3 (13.6)
0 (0.0)0 (0.0)0 (0.0)0 (0.0)F43.0 Acute stress reaction

F43.1 Post-traumatic stress disorder

F43.2 Adjustment disorders

F43.9 Reaction to severe stress, unspecified

F45 Somatoform disorders

F48 Other neurotic disorders

F2 Scizophrenia*F3 and F4 diseases with a total of less than 1% are excluded.

2 (15.4)

7 (31.8)

F40–F48: Neurotic, stress-related and somatoform disorders

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (7.7)1 (7.7)

10 (76.9)

15 (68.1)

F32 Depressive episode0 (0.0)0 (0.0)11 (84.6)

4 (30.8)

F31 Bipolar affective disorder

F30–F39: Mood (affective) disorders

15 (68.1)

3 (13.6)

Dead

Psychiatric disorders

19 (86.4)Life

9 (69.2)

4 (30.8)8 (36.4)

Life or dead

0 (0.0)0 (0.0)3 (23.0)

10 (77.0)

20–29

5 (22.7)

17 (77.3)

13 (100)
(5.4)

2011
n (%)

10–19

Age

Women

Men

Sex

22 (100)
(9.2)

2010
n (%)

Sex, age, life or dead, psychiatric disorders of the mental disorders cases

Number of cases (% by year)

Table 1.

1 (2.9)0 (0.0)1 (2.9)2 (5.8)2 (5.8)0 (0.0)0 (0.0)6 (17.1)

27 (77.1)

1 (2.9)28 (80.0)

12 (34.3)

23 (65.7)

3 (8.6)

12 (34.3)

10 (28.6)

10 (28.6)

0 (0.0)6 (17.1)

29 (82.9)35 (100)(14.7)2012n (%)

0 (0.0)0 (0.0)0 (0.0)1 (4.5)5 (22.7)

0 (0.0)1 (4.5)7 (31.8)

14 (63.6)

1 (4.5)15 (68.1)

2 (9.1)20 (90.9)

0 (0.0)5 (22.7)

13 (59.1)

4 (18.2)

0 (0.0)8 (36.4)

14 (63.6)

22 (100)
(9.2)

2013
n (%)

0 (0.0)0 (0.0)1 (3.1)1 (3.1)6 (18.6)

1 (3.1)2 (6.2)11 (57.9)

20 (62.5)

0 (0.0)21 (65.6)

10 (31.2)

22 (68.8)

5 (15.6)

6 (18.8)

9 (28.1)

12 (37.5)

0 (0.0)5 (15.7)

27 (84.3)

32 (100)(13.4)2014n (%)

0 (0.0)2 (6.6)

1 (3.3)1 (3.3)7 (23.3)

0 (0.0)0 (0.0)12 (40.0)

17 (56.7)

1 (3.3)18 (60.0)

6 (20.0)24 (80.0)

4 (13.3)

6 (20.0)

11 (36.7)

9 (30.0)0 (0.0)5 (16.7)

25 (83.3)

30 (100)(12.6)2015n (%)

0 (0.0)3 (11.1)

1 (3.7)0 (0.0)4 (14.8)

1 (3.7)0 (0.0)9 (33.3)

17 (63.0)

0 (0.0)18 (66.7)

6 (22.2)

21 (77.8)

3 (11.1)

9 (33.3)

7 (25.9)

8 (29.6)

0 (0.0)8 (29.7)

19 (70.3)

27 (100)(11.3)2016n (%)

0 (0.0)1 (2.9)2 (5.8)0 (0.0)9 (26.5)

1 (2.9)0 (0.0)14 (41.2)

19 (55.9)

1 (2.9)20 (58.8)

4 (11.8)30 (88.2)

4 (11.8)

13 (38.2)

9 (26.4)

7 (20.6)

1 (0.4)10 (29.4)

24 (70.6)

34 (100)(14.3)2017n (%)

0 (0.0)0 (0.0)1 (4.3)1 (4.3)6 (26.1)

3 (13.0)

1 (4.3)12 (52.1)

11 (47.8)

0 (0.0)11 (47.8)

4 (17.4)

19 (82.6)

0 (0.0)6 (26.1)

5 (21.7)

12 (52.2)

0 (0.0)10 (43.5)

13 (56.5)

23 (100)
(9.7)

2018
n (%)

1 (0.4)6 (2.5)7 (2.9)6 (2.5)42 (17.6)

7 (2.9)9 (3.8)80 (33.6)

150 (63.0)

4 (1.7)157 (66.0)

51 (21.4)

187 (78.6)

22 (9.2)

62 (26.1)

79 (33.2)

74 (31.1)

1 (0.4)60 (25.2)

178 (74.8)

238 (100)
100%

Total
n (%)

70
Y TAKAHASHI et al.

Industrial Health 2024, 62, 67–76

Labor accident recognition factors (men)Not statedConstant long working hours

1 (10.0)0 (0.0)0 (0.0)0 (0.0)5. Being held responsible for accidents and incidents that occurred at the company

6. I lost a lot of money on the work I was involved in

0 (0.0)17. Worked continuously for more than two weeks

0 (0.0)0 (0.0)0 (0.0)1 (3.4)0 (0.0)0 (0.0)1 (3.4)0 (0.0)2 (6.8)2 (6.8)1 (3.4)0 (0.0)2 (6.8)4 (13.8)

8 (27.6)

1 (3.4)0 (0.0)1 (3.4)0 (0.0)1 (3.4)3 (10.3)

0 (0.0)0 (0.0)15 (51.7)

6 (20.7)

0 (0.0)6 (17.1)

29 (82.9)35 (100)(14.7)2012n (%)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (7.1)1 (7.1)0 (0.0)0 (0.0)1 (7.1)1 (7.1)6 (42.9)

1 (7.1)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (7.1)8 (57.1)

2 (14.3)

0 (0.0)8 (36.4)

14 (63.6)

22 (100)
(9.2)

2013
n (%)

0 (0.0)0 (0.0)1 (3.7)

4 (14.8)

0 (0.0)0 (0.0)1 (3.7)2 (7.4)1 (3.7)0 (0.0)3 (11.1)

2 (7.4)8 (29.6)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)2 (7.4)9 (33.3)

3 (11.1)

0 (0.0)5 (15.7)

27 (84.3)

32 (100)(13.4)2014n (%)

0 (0.0)0 (0.0)0 (0.0)1 (4.0)0 (0.0)1 (4.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)2 (8.0)1 (4.0)9 (36.0)0 (0.0)1 (4.0)0 (0.0)0 (0.0)1 (4.0)0 (0.0)0 (0.0)0 (0.0)6 (24.0)

10 (40.0)

0 (0.0)5 (16.7)

25 (83.3)

30 (100)(12.6)2015n (%)

1 (5.3)0 (0.0)1 (5.3)2 (10.5)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (5.3)1 (5.3)2 (10.5)

7 (36.8)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)5 (26.3)

5 (26.3)

0 (0.0)8 (29.7)

19 (70.3)

27 (100)(11.3)2016n (%)

0 (0.0)0 (0.0)0 (0.0)4 (16.7)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)4 (16.7)

0 (0.0)12 (50.0)

1 (4.2)

1 (4.2)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)7 (29.2)2 (8.3)0 (0.0)10 (29.4)

24 (70.6)

34 (100)(14.3)2017n (%)

0 (0.0)0 (0.0)0 (0.0)2 (15.4)

0 (0.0)0 (0.0)1 (7.7)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)9 (69.2)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (7.7)0 (0.0)4 (30.8)

1 (7.7)0 (0.0)10 (43.5)

13 (56.5)

23 (100)
(9.7)

2018
n (%)

1 (0.6)

1 (0.6)3 (1.7)15 (8.4)

1 (0.6)

1 (0.6)5 (2.8)7 (3.9)2 (1.1)1 (0.6)

14 (7.9)

10 (5.6)

69 (38.8)

4 (2.2)2 (1.1)2 (1.1)0 (0.0)2 (1.1)4 (2.2)1 (0.6)4 (2.2)54 (30.3)

30 (16.9)

0 (0.0)60 (25.2)

178 (74.8)

238 (100)
100%

Total
n (%)

load becomes “strong”.
*2 Working more than 80 h of overtime a month: over 120 h in nearest two months or over 100 h in nearest three months are criterias for the intensity of the psychological load assumes to “strong”.

*1 Extreme long hours: to exceed approximately 160 h in the month or 120 h in three weeks immediately preceding the onset of illness, or to a similar extent during a period of less than this for the intensity of the psychological

0 (0.0)36. Subjected to sexual harassment

0 (0.0)1 (5.9)0 (0.0)30. Trouble with one’s boss

0 (0.0)0 (0.0)0 (0.0)2 (11.8)

25. One’s own promotion

29. (Severely) harassed, bullied, or assaulted

31. Trouble with colleagues

0 (0.0)0 (0.0)24. Being discriminated against or treated disadvantageously in the course of
employment for reasons such as being a non-regular employee

1 (10.0)0 (0.0)1 (5.9)0 (0.0)21. There was a reassignment.

0 (0.0)0 (0.0)1 (10.0)0 (0.0)4 (40.0)0 (0.0)0 (0.0)0 (0.0)1 (10.0)

22. Relocation

0 (0.0)0 (0.0)0 (0.0)6 (35.3)

15. There was an event that caused a (large) change in work content and workload.

16. Working more than 80 h of overtime a month *2

19. Change in pace of work and activity

1 (5.9)12. Receipt of complaints from customers and business partners

20. Forced retirement

0 (0.0)

11. To receive unreasonable orders from customers and business partners

9. The quota was not met

0 (0.0)0 (0.0)4. Made a serious business mistake, such as affecting the management of thecompany

0 (0.0)1 (5.9)0 (0.0)2. Experienced and witnessed tragic accidents and disasters

0 (0.0)Not stated

1 (10.0)0 (0.0)3 (23.0)

10 (77.0)

13 (100)
(5.4)

2011
n (%)

3. Caused a serious accident resulting in injury or death or serious accident related
to workSpecific events (No incidents in total are omitted.)

Not stated

Extreme psychological burden

Extreme long hours*1

0 (0.0)5 (22.7)

Evaluation of a particular event

17 (77.3)

Men

22 (100)
(9.2)

2010
n (%)

Women

Sex

Number of cases (% by year)

Table 2.

MENTAL DISORDERS AT WORKERS IN JAPAN71

Not statedConstant long working hours

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)4. Made a serious business mistake, such as affecting the management of thecompany

5. Being held responsible for accidents and incidents that occurred at the company

8. Hard-to-achieve quota

0 (0.0)1 (33.3)
0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)19. Change in pace of work and activity

20. Forced retirement

21. There was a reassignment

22. Relocation

24. Being discriminated against or treated disadvantageously in the course of
employment for reasons such as being a non-regular employee

0 (0.0)17. Worked continuously for more than two weeks

0 (0.0)3 (60.0)0 (0.0)0 (0.0)1 (20.0)

29. (Severely) harassed, bullied, or assaulted

30. Trouble with one’s boss

31. Trouble with colleagues

36. Subjected to sexual harassment

1 (16.7)

0 (0.0)1 (16.7)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (16.7)

1 (16.7)

1 (16.7)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)3 (50.0)

1 (16.7)

0 (0.0)6 (17.1)

29 (82.9)

2012
n (%)

1 (12.5)

0 (0.0)0 (0.0)1 (12.5)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)6 (75.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)2 (25.0)

1 (12.5)

0 (0.0)8 (36.4)

14 (63.6)

2013
n (%)

1 (3.1)0 (0.0)1 (3.1)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)2 (6.3)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (3.1)1 (3.1)0 (0.0)0 (0.0)5 (15.7)

27 (84.3)

2014
n (%)

2 (40.0)0 (0.0)0 (0.0)1 (20.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)2 (40.0)0 (0.0)5 (16.7)

25 (83.3)

2015
n (%)

1 (12.5)

0 (0.0)1 (12.5)

2 (25.0)0 (0.0)0 (0.0)0 (0.0)1 (12.5)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)3 (37.5)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (12.5)

1 (12.5)

1 (12.5)

8 (29.7)

19 (70.3)

2016
n (%)

2 (20.0)0 (0.0)0 (0.0)1 (10.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (10.0)0 (0.0)4 (40.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)3 (30.0)

2 (20.0)

1 (10.0)

10 (29.4)

24 (70.6)

2017
n (%)

4 (40.0)0 (0.0)0 (0.0)1 (10.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)1 (10.0)0 (0.0)3 (30.0)

10 (43.5)

13 (56.5)

2018
n (%)

13 (21.7)

0 (0.0)3 (5.0)9 (15.0)0 (0.0)0 (0.0)0 (0.0)1 (1.7)

1 (1.7)0 (0.0)2 (3.3)

1 (1.7)18 (30.0)

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)2 (3.3)

11 (18.3)

7 (11.7)5 (8.3)60 (25.2)

178 (74.8)

Total
n (%)

load becomes “strong”.
*2 Working more than 80 h of overtime a month: over 120 h in nearest two months or over 100 h in nearest three months are criterias for the intensity of the psychological load assumes to “strong”.

*1 Extreme long hours: to exceed approximately 160 h in the month or 120 h in three weeks immediately preceding the onset of illness, or to a similar extent during a period of less than this for the intensity of the psychological

0 (0.0)0 (0.0)0 (0.0)0 (0.0)25. One’s own promotion

0 (0.0)0 (0.0)0 (0.0)0 (0.0)0 (0.0)16. Working more than 80 h of overtime a month *2

1 (33.3)

0 (0.0)0 (0.0)1 (20.0)

12. Receipt of complaints from customers and business partners

0 (0.0)0 (0.0)0 (0.0)0 (0.0)15. There was an event that caused a (large) change in work content and workload

11. To receive unreasonable orders from customers and business partners

9. The quota was not met

0 (0.0)0 (0.0)3. Caused a serious accident resulting in injury or death or serious accident related
to work
0 (0.0)0 (0.0)1 (33.3)

Not stated

0 (0.0)0 (0.0)3 (23.0)

10 (77.0)

2011
n (%)

2. Experienced and witnessed tragic accidents and disasters

Specific events (No incidents in total are omitted)

Not stated

Extreme psychological burde

Extreme long hours*1

0 (0.0)5 (22.7)

Evaluation of a particular event

17 (77.3)

2010
n (%)

Men

Labor accident recognition factors (women)

Women

Sex

Table 3.

72
Y TAKAHASHI et al.

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MENTAL DISORDERS AT WORKERS IN JAPAN
Table 4.

Sexual harassment and rape
Sexual harassment (n=13)
n (%)

Age

Job type

Opponent

Contents*

Psychiatric disorders

Work place scale

Other event

During and outside business hours

Rape (n=5)
n (%)

Total (N=18)
n (%)

10–19

0 (0.0)0 (0.0)0 (0.0)20–29

9 (69.2)

4 (80.0)

13 (72.2)

30–39

4 (30.8)

1 (20.0)

5 (27.8)

40–49

0 (0.0)0 (0.0)0 (0.0)50–59

0 (0.0)0 (0.0)0 (0.0)SEs·PGs

4 (30.8)

2 (40.0)

6 (33.3)

Sales force

5 (38.5)

1 (20.0)

6 (33.3)

HP Production director

0 (0.0)1 (20.0)

1 (5.6)

Clerical position

2 (15.4)

0 (0.0)2 (11.1)

News business

0 (0.0)1 (20.0)

1 (5.6)Web designer

2 (15.4)

0 (0.0)2 (11.1)Boss

8 (61.5)

1 (20.0)9 (50.0)

Employer

2 (15.4)

1 (20.0)

3 (16.7)

Client0 (0.0)3 (60.0)

3 (16.7)

Colleague

2 (15.4)

0 (0.0)2 (11.1)

Unknown

1 (7.7)0 (0.0)1 (5.6)

Sexual behavior

12 (92.3)

3 (60.0)

15 (83.3)
11 (61.1)

Physical contact

6 (46.2)

5 (100.0)

Secret filming

2 (15.4)

0 (0.0)2 (11.1)

Others (e-mail, telephone, stalking, etc.)

2 (15.4)

0 (0.0)2 (11.1)

Depressive episode6 (46.2)

0 (0.0)6 (33.3)

Post-traumatic stress disorder

2 (15.4)4 (80.0)

6 (33.3)

Adjustment disorders

4 (30.8)

1 (20.0)

5 (27.8)

Reaction to severe stress

1 (7.7)0 (0.0)1 (5.6)

Less than 10

0 (0.0)1 (20.0)

1 (5.6)10–49

3 (23.1)

1 (20.0)

4 (22.2)

50–99

1 (7.7)

1 (20.0)

2 (11.1)

100–499

3 (23.1)

1 (20.0)

4 (22.2)

500–999

3 (23.1)

0 (0.0)3 (16.7)

More than 1,000

3 (23.1)

1 (20.0)

4 (22.2)

No description/Unknown

0 (0.0)0 (0.0)0 (0.0)More than 80 h of overtime per month

1 (7.7)0 (0.0)1 (5.6)

Major changes in work content and workload

2 (15.4)

0 (0.0)2 (11.1)

Trouble with colleagues

1 (7.7)0 (0.0)1 (5.6)

Trouble with one’s boss

1 (7.7)0 (0.0)1 (5.6)

Sexual harassment

0 (0.0)1 (20.0)

1 (5.6)None

8 (61.5)

4 (80.0)

12 (66.7)

In time10 (76.9)

2 (40.0)

12 (66.7)

Out of time

3 (23.1)

3 (60.0)

6 (33.3)

Some of the contents overlap. For example, if sexual behavior and physical contact are found in one case, both are described.

Therefore, the number of women workers may increase in
the future. The age of onset was high among those in their30s. More than one-fifths (21.4%) of the cases ended indeath (suicide). In the study sample, there were 150 casesof depressive episodes (63.0% of victims) and 42 cases ofadjustment disorder. The number of adjustment disordercases showed an upward trend, which may be attributed

to the widespread use of terms such as developmental
disorders (e.g., autism spectrum disorder17) and attentiondeficit/hyperactivity disorder18, 19)) and adjustment disorder20, 21). With the spread of these terms, the threshold for
consultation with psychiatrists is lower than before, andearly visits are increasing. Many of the cases included inthis study are thought to be diagnosed with adjustment

74
disorder because of obvious stressors such as changes in
the content and quantity of work and long working hours.
In terms of work-related adverse events for the current
cases in IT industry, “extremely long working hours” in“special events” and “events that caused (major) changes
in the content and amount of work” in “specific events”,
are the main factor. Also, “rape” of women and especially“SH”, which is on the rise every year, is an issue that can’t
be overlooked.
These results suggest the importance of the following
two actions for SEs and PGs. The first action prioritizes,
reduction and strict management of working hours. Compliance with the Labor Standards Act and Industrial Safety
and Health Act and implementation of measures against
heavy workload are required22). Previous reports have alsosuggested that strict delivery deadlines, customer support,
and sudden changes in specifications are relevant factors9, 10). Therefore, companies must set delivery deadlines
with sufficient time to prevent overwork after discussing
with the ordering party, as well as determine the progressof work and implement measures such as extending
deadlines and expanding the team when the amount ofwork is expected to increase owing to sudden changes in
specifications. The validity of specifications should be
confirmed at the design stage to prevent sudden changes
in specifications. Moreover, companies should implement
work within the prescribed working hours to the extent
possible in the event of a problem.
The second action relates to measures against sexual
harassment and rape, cases of which are increasing yearly.
The analysis results in Table 4 suggested the following—
first, young women workers (particularly those in their20s) are at a very high risk of SH and rape, Furthermore,
workplaces with large operation of more than 500 workers
were more prone to SH and rape (SH and rape rates were
two out of 29 (6.9%) in workplaces with <10 workers,
four out of 52 (7.7%) in workplaces with 10–49 workers,
two out of 26 (7.7%) in workplace with 50–99 workers,
four out of 69 (5.8%) in workplace with 100–499 workers,
and seven out of 56 (12.5%) in workplaces >500 workers). Additionally, perpetrators were overwhelmingly inhigher positions, such as superiors or business owners.
Many cases occurred among salespeople, whose positional
relationship (hierarchical relationship) in the job is thought
to have a large impact. More than 2/3 of SH/rape cases
occurred during office hours.
Indeed, according to a previous report, SH is more
likely to occur in a clear hierarchical relationship (difference in status) and people in a weaker position23). SH has

Y TAKAHASHI et al.
a wide range of effects on workers, including a depressedmood, eating disorders, alcoholism, and damage to selfesteem24–28). As such, measures against SH are important.
However, there have been cases in which victims could notreport such incidents for fear of secondary damage27, 28).
Therefore, companies must recognize the following
points regarding SH and rape: young women workers
are more likely to be at risk of SH/rape in workplace oflarge business (more than 500 people) during office hours.
Furthermore, as reported in previous studies on the effectiveness of measures, companies must strictly deal withSH and rape and disseminate clear policies, such as taking
disciplinary action against perpetrators29). Stress checks
must be enhanced and the system must be strengthened forproviding early and immediate relief to victims. Moreover,companies should focus on workers’ interactions during
and outside working hours. Other essential measures are
the establishment of a system that protects the privacyof victims of SH, a consultation desk for women, and anawareness campaign of the guarantee that consultations
will never lead to disadvantages at work.
Limitation
This study has some limitations. In this study, we usedcases that were recognized as occupational accidents fromthe survey reports created in the process of the Labor
Standards Inspection Office determining the presence orabsence of work-related causes. We conducted investigations based on the contents of these survey reports. Therefore, our materials lacked information for preventing deathfrom overwork, such as improving the setting of working
hours and work environment, identifying problems in theworkplace, and establishing a mental and physical healthmanagement system (including the presence or absence oftreatment). The actual circumstances and characteristicsof the cases could not have been fully explained. Furthermore, the analysis covered cases in which workers’
compensation was applied for and approved. As such,data comprising biased—cases that applied for workers’
compensation but not approved (that is, cases that were
not recognized as work-related injuries or commuting
injuries) were not included in this analysis. Therefore, by
not including these cases, we expected to see a decreasein adjustment disorders cases and an increase in disorders,such as depression and anxiety disorders, which occur
largely due to personal factors. Additionally, in somecases, detailed descriptions were not included in thereports, leading to insufficiency in data for accurate extraction. Lastly, there was a limited number of cases for SEs
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75

MENTAL DISORDERS AT WORKERS IN JAPANand PGs, which limited comparisons with cases for otheroccupations. However, to date, no detailed analyses havebeen conducted in Japan among SEs and PGs in cases thatwere recognized as occupational accidents. Our study thus
proposed points to consider creating a better working environment that could promote the physical and mental healthof workers engaged in the information and communicationindustry—mainly, SEs and PGs.

Conclusions
Our study clarified some of the actual circumstancesand background factors of mental disorders due to overwork and inadequate psychosocial conditions at work in
the IT industry, which had not been analyzed with respect
to the enactment of the Act Promoting Measures to Prevent Death and Injury from Overwork. Regarding mental
disorders in the IT industry, cases among women stoodat 25.2% of the total but showed an increasing trend. The
age of disease onset was in the 30s to 40s, clarifying thatyounger individuals are more affected. For both sexes, themental disorder factors included (major) changes in thecontent and amount of work, and there were many casesof long working hours (including continuous and overtimework) as well as changes in departments and work locations. Furthermore, for women, the number of SH and rapecases increased yearly. These results suggested that the IT
industry needs measures against heavy workloads leading
to long working hours and poor mental health. The current data also highlight the effort to improve psychosocial
environment at work, which targets the prevention of SH,
as well.

Funding
This study was supported by the Industrial Disease
Clinical Research Grants from the Ministry of Health, Labour and Welfare, Government of Japan (150903-01 and
180902-01).

Conflict of Interest

2)

3)

4)

5)
6)

7)

8)

9)

10)

11)

12)

None declared.

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