Work Stressors, Drinking with Colleagues after Work, and Job Satisfaction among White-Collar Workers in Japan

Substance Use & Misuse, 35(5) . 737-756. 2000

Work Stressors, Drinking with Colleagues after Work, and Job Satisfaction among White-collar Workers in Japan

Akihito Hagihara, Ph.D., M.P.H.;’* KimioTarumi, M.D., Ph.D.,* and Koichi Nobutomo, M.S., M.D., Ph.D:’

’ Kyushu University Graduate School of Medicine, Department of Health Services Management and Policy, 3-1-1 Maiadashi, Higashi-Ku, Fukuoka 812-8582, Japan

University of Environmental and Occupational Health, Iseigaoka, Yahatanishi-ku, Kita-Kyushu, Japan

ABSTRACT

Although previous studies have examined the buffering effects of social support and coping style on the relationship between stress and alcohol consumption, they have typically relied on analysis of variance (ANOVA) or regression analysis. In addition, few studies have examined the potential stress-buffering effects of drinking with coworkers after work on the relationship between job stress and job dissatisfaction. In the present study, using a signal detection analysis, we evaluated the interactions of drinking with coworkers after work and work-stressor variables among Japanese white-collar workers (M = 397) in 1997. The analysis was performed for two groups of subjects divided based on their status in the company. This was necessary because in Japan the obligations to drink

*To whom requests for reprints should be addressed.

I37

Copyright 0 2000 by Marcel Dehker. Inc www.dekker.com

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738 HAGIHARA, TARUMI, A N D NOBUTOMO

socially increase with one’s rising status in the company. In both the “staff members and lower-level managers” and “middle-level and higher-level managers’ groups, an interaction between work-stressor variables and drinking variables was observed. The findings imply that drinking with coworkers after work ameliorated the sense of job dissatisfaction, but only among those subjects who already had lower levels of work stressors. For subjects with high levels of work stressors, attitudes toward drinking with coworkers were unrelated to job satisfaction levels.

Key words. Job satisfaction; Drinking after work; Signal detection analysis; Stress-buffering effects

INTRODUCTION

The majority of studies on alcohol have generally been performed with an awareness that alcohol consumption often brings about negative behavioral, mental, and physical effects (Wills, 1986; Beck et al., 1993; Abbey et al., 1993; Yang et al., 1996; Laurent et al., 1997). However, alcohol consumption can have both positive and negative effects. As for a positive effect, at least two theoretical perspectives indicate the possibility that alcohol reduces the level of stress. The tension reduction theory proposes that alcohol lessens the intensity of negative emotions such as fear, distress, tension, and depression, and that people drink alcohol for its tension-reducing properties (Cappell and Greeley, 1987). Social learning theory posits that individuals are more likely to drink in response to stress-producing stimuli when they lack other more appropriate coping responses (Pearlin and Radabaugh, 1976; Violanti et al., 1983; Herald and Conlon, 1981; Abrams and Paymond, 1987). In addition, moderate drinking has been shown to be associated with good mental health (Nishio et al., 1994) as well as good physical health (Kannel, 1967; Klatsky et al., 1974). As for the negative effects of drinking, numerous studies have reported that excessive drinking is closely related to cancer, liver diseases, coronary heart disease, deformity, and accidental death (US Department of Health, Education and Welfare, 1975; Pel1 and D’Alonzo, 1973; Schmidt, 1980; Stason et al., 1976).

As indicated by studies of the relationship between drinking and society or culture (Bacon, 1976; Bales, 1946; Health, 1976; Stivers, 1976) and of the effect of the occupational community on drinking (Cosper, 1979), the mean- ing of alcohol consumption and its effect on mental health might vary among cultures or communities. In Japanese companies, for example,

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WORK STRESSORS. DRINKING. A N D IOB SATISFACTION 739

male employees quite often drink with their colleagues or bosses after work. According to a survey by the Kirin Brewery Co. Ltd., in 1997, male workers reported that they drank with coworkers 3.4 times per week (Kirin Brewery Co. Ltd., 1998). Such after-work drinking with coworkers or families might help workers express their feelings, potentially leading to stress reduction. Japanese employees also have active friendships with their co-workers and form communities outside their workplaces, and drinking within these small communities after work is also frequent. These social occasions involving drinking generally last from 1.5 to 4 hours, and take place between once a month and twice a week, depending upon the type of workplace. On these occasions, drinking until one is intoxicated is considered bad manners.

In Japanese companies the system for allocating work/tasks to employees is very flexible (Yoshida and Tanaka, 1985; Okuda, 1982). In principle, each employee is in charge of his/her own work. In reality, however, in addition to performing their own work, workers in a work group often collaborate to complete tasks of the work group. Since the outline of the tasks of a work group is vague, the decision as to who will be in charge of the work is often made quite arbitrarily (Ishida, 1983). In these workplaces the relationships among coworkers is decided by emotional factors in addition to efficiency and cost factors. Harmony among the employees is also very important (Yoshida and Tanaka, 1985). Thus, drinking with coworkers after work is thought to have a positive role in fostering harmony among coworkers and in deciding who will be in charge of group collaborations. The function of such drinking with coworkers after work is to enhance cooperation and smooth interpersonal relationships in the workplace. As noted earlier. drinking has several positive effects in reducing the level of mental stress (Cappell and Greeley, 1987; Pearlin and Radabaugh, 1976; Violanti et al., 1983; Herald and Conlon, 1981; Abrams and Paymond, 1987; Nishio et al., 1994). Therefore, in this present study we examined whether alcohol drinking under certain social conditions has positive effects. Specifically, we tested whether after-work alcohol drinking among white- collar Japanese employees serves as a stress buffer or, more generally, has a positive aspect on one’s work, thereby increasing the employee’s overall job satisfaction.

The term “job satisfaction” is generally held to indicate a subject‘s feeling of being satisfied with his or her job. A relationship between job satisfaction/dissatisfaction and mental stress has been reported (Cohen and Edwards, 1989; Cohen and Wills. 1985; Karasek and Theorell. 1990). In work situations, depending on the types of work stressors, position, age, etc., it is probable that drinking with coworkers after work might selectively interact with particular stressors and have stress-buffering effects. thereby affecting job satisfaction. I t is necessary to identify how buffering factors,

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740

- Job satisfaction Mental stress

HAGIHARA, TARUMI, AND NOBUTOMO

Occupational stressors Work autonomy Repetitive work Difficult work Time pressure

etc.

Fig. 1. Stressor-stress model of the role of occupational stressors in job satisfaction and mental health.

such as drinking with coworkers, interact with work stressors and lead to an increased or decreased satisfaction toward a job (Orpen, 1982). Figure 1 presents a stressor-stress model of the role of occupational stressors in job satisfaction and mental health, based on similar conceptualizations (Cooper, 1986; French et al., 1982). Occupational stressors generally have detrimental effects upon job satisfaction and mental health, leading to either job dissatisfaction or increased mental stress. However, although the mechanisms have not been fully revealed (Wheaton, 1985), personality factors such as Type A behavior and coping style or social support mitigate or moderate the detrimental effects of work stressors upon job satisfaction and mental health. In studies of stress buffering, the same conventional methodology has generally been used. The common statistical procedures to test for stress-buffering effects include analysis of variance (ANOVA) (two-way) with a stress variable and an independent variable (IV) as factors, and a multiple regression analysis with the cross-product term (stress x IV) entered into the equation after terms for the direct effects of stress and IV are performed (Cohen and Wills, 1985). However, conventional statistical procedures such as ANOVA, multiple regression analysis, and log-linear models cannot deal well with higher-order interactions of variables (Winkleby et al., 1994). In the present study, therefore, we used a signal detection analysis method to analyze our data concerning work stressors and job satisfaction among white-collar workers. Although signal detection analysis is a type of analytic method, this analysis copes far better with

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WORK STRESSORS. D R I N K I N G . A N D JOB SATISFACTION 74 I

colinearity than do linear models (Kraemer, 1988, 1992; Winkleby et al., 1994).

METHODS

Subjects

The subjects of this study were Japanese male white-collar workers (20 to 64 years of age) at the head office of one of Japan’s leading steel companies in Osaka, Japan. Since an annual health checkup of company employees is mandatory by the Labor Act in Japan, the occupational health workers of the company were able to make use of this opportunity and collect data concerning physical and mental health status of workers including work stressors, mental stress, and potential stress-buffering factors such as drinking habits. During their annual health checkup i n July 1997, relevant data were collected From 40s (87.1%) of all male subjects (17 = 465). In the analysis, 397 responses with no missing data were used.

Measurements

In the present study. self-administered questionnaires were distributed to assess attitudes toward drinking in business situations, job satisfaction, and work stressors. The qiiestionnaire consisted of 17 items for the evaluation of mental health status and 30 items for the evaluation of recent health status and personal health practices. Attitudes toward drinking in business situations were measured by a three-item index. This index evaluated how often subjects have drinking opportunities per week, and how positively they regard these drinking opportunities. Cronbach’s alpha value for this scale was 0.74. Each item of this scale had four multiple choice answers: “almost everyday,” “4 to 5 days per week,” “2 to 3 days per week,“ and “ I day or less per week“ for drinking opportunities. and “Agree completely,” “Agree,” “Do not agree.“ and ”Disagree completely” for the remaining two items. The possible total scores ranged from 3 to 12. Higher scores indicate positive attitudes toward drinking with coworkers after work, which means that the subject often has drinking opportunities with coworkers and sees these drinking opportunities a s positive. Lower scores indicate negative attitudes toward drinking with coworkers after work, which means that the subject seldom has drinking opportunities with coworkers and sees the drinking opportunities as less positive. The minimum and maximum drinking scores of the subjects were 3 and 12. respectively, and the mean and median were 8.10 and 8. respectively.

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7 42 HAGIHARA, TARUMI, A N D NOBUTOMO

Because of practical reasons, it has been argued that specific stress measures should be used whenever possible (Dearborn and Hastings, 1987; Krause, 1986; Palmore et al., 1979). The advantages of studies using specific types of measures sensitive to stressors are as follows (Quittner et al., 1990): this approach 1) provides a framework for identifying situation- specific stressors, 2) indicates stressors that need some type of intervention, 3 ) facilitates a matching of the types of supports and support providers, and 4) consequently leads to more effective support intervention. In the present study, 10 items for work stressors from four categories, and also working hours and commuting time, were included in the questionnaire. The four categories of work stressors were 1) work autonomy, 2) time pressure, 3 ) specialty of work, and 4) work role ambiguity. These items are summarized by the status of the subjects in the company in Table 1. Items 4, 6, and 7 in the table regard work autonomy; items 8, 11, and 13 are for time pressure; item 5 concerns the nature of work specialty; and items 9 and 10 are for work role ambiguity. The items used in the present questionnaire for work stressors covered a wide range of work-elated stressors common in white- collar work situations and have been shown to be related to heavy drinking [work autonomy (Ragland et al., 1995), time pressure (Wilsnack and Wilsnack, 1992), specialty of work (Allamani et al., 1988), and work ambiguity (Ragland et al., 1995)]. All of these items were multiple choice ques- tions with four possible answers (“Agree completely,” “Agree,” “Do not agree,” “Disagree completely”).

Job satisfaction was measured by a four-item index. This item evaluates the extent to which a subject is satisfied with his job. Cronbach’s alpha value for this scale was 0.86. Each item of this scale had four multiple choice answers (“Agree completely,” “Agree,” “Do not agree,” and “Disagree completely”), and the possible scores ranging from 4 to 16. Higher scores indicate a higher level of job satisfaction, and lower scores indicate a lower level of job satisfaction. The minimum and maximum job satisfaction scores of the subjects were 4 and 16, respectively, and the mean and median were 9.84 and 10, respectively.

Statistical Procedure

The nature of work and social drinking in work settings in Japan varies greatly depending on the position of a subject in the company. Therefore, the present analysis was performed within two employee groups, divided by the status of the respondents. One group consisted of staff members and lower-level managers, and the other group consisted of middle- and higher- level managers. To examine how individual work stressors and social drinking interact, the signal detection analysis by Kraemer was used (1988, 1992;

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Tabl

e 1

Pro

files

of E

mpl

oyee

Gro

ups'

Staf

f m

embe

rs a

nd

Mid

dle-

leve

l an

d lo

wer

-leve

l m

anag

ers

(N =

I 89

) hi

gher

-leve

l m

anag

ers

(N =

208

) p-

valu

e

1.

Age

(ye

ars)

2.

C

omm

utin

g tim

e (m

inut

es)

3.

Wor

king

hou

rs (

hour

s)

4.

Littl

e w

ork

auto

nom

y (%

) 5.

W

ork

requ

ires

new

kno

wle

dge

(YO

) 6.

Fi

xed

wor

k pr

oced

ure

(YO

) 7.

R

epet

itive

wor

k (Y

O)

8.

Wor

k ha

s de

adlin

e (Y

O)

9.

Wor

k di

rect

ion

is no

t con

cret

e (%

) 10

. W

ork

role

is n

ot c

lear

(%

) 11

. W

ork

need

s to

be

done

qui

ckly

(%

) 12

. W

ork

is di

ffic

ult

(Yn)

13

. T

ime

to c

ompl

ete

wor

k is

not

enou

gh (

YO

)

Wor

k st

ress

ors:

Soci

al d

rink

ing:

14

. A

ttitu

des

tow

ard

drin

king

in b

usin

ess

situ

atio

ns

1,

Job

satis

fact

ion

hide

pend

enr

Vari

able

s 35

.26

rt 8

.70

53.9

6 rt

18.8

9 9.

741

1.38

32.2

8 85

.71

17.0

0 29

.63

83.6

0 49

.21

24.3

4 94

.18

33.3

3 65

.08

8.13

+ 1.

44

Dep

ende

n I

Vuri

able

9.

67 k I .

99

46.2

2 f 6.

28

61.2

4 1 22

.02

9.22

i 1.

24

15.3

8 75

.96

4.81

25

.00

85.5

8 50

.00

15.3

8 97

.60

28.8

5 57

.69

8.07

+ I .

08

9.98

f 1.

82

0.00

01

0.00

04

0.00

01

0.00

1 0.

014

0.00

1 0.

301

0.58

5 0.

874

0.02

5 0.

084

0.33

4 0.

131

0.63

0.12

P

2:

U

a C

hi-s

quar

e te

st w

as u

sed

for w

ork

stre

ssor

s, a

nd S

tude

nt's

t-te

st w

as u

sed

for

the

rem

aini

ng c

onti

nuou

s va

riab

les.

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744 HAGIHARA, TARUMI, AND NOBUTOMO

Winkleby et al., 1994). Signal detection analysis has been performed as a form of recursive partitioning and has provided useful results, especially when many interactions are expected (Kraemer, 1988). Significant interactions of social drinking and work stressors are thought to be detected as the results of higher order interactions of multiple independent variables (Wheaton, 1985). However, common statistical analyses such as ANOVA or regressioii analysis are not useful in dealing with higher-order interactions because not every possible combination of the variables listed in Table 1. for instance, can be tested adequately; the interpretation of such higher levels of interaction would be confusing in a regression analysis, and there is usually a problem with multicolinearity. In addition, the number of factors that can be examined by ANOVA is limited.

Thus, signal detection analysis was performed in the present study for two groups divided by the status of the subjects. We are indebted to Kraemer for the model which focuses on the parameters of sensitivity and specificity. Briefly, sensitivity is defined as the probability of job dissatisfaction among individuals with work stressors. Specificity is defined as the probability of job satisfaction among those without work stressors. The selection of a stressor significantly related to job dissatisfaction should be based on a measure that includes both sensitivity and syecij7city. Kraemer advocates such an optimal measure (1998, 1992; Winkleby et al., 1994).

Each variable in Table 1, including age, work stressors, attitudes toward drinking in business situations, and job satisfaction, was entered into the model along with minimal and maximal values and intermediate cutoff points. There were four cutoff points of items related to work stressors (“Agree completely,” “Agree,” “Do not agree,” and “Disagree completely”) as well as four cutoff points for “Age” ~ O S , 30s, 40s and 50s). As for commuting time and working hours, these variables were divided into two categories by 60 minutes and 9 hours, respectively. Concerning attitudes toward drinking in business settings, the variables had three cutoff points (scores of -7, 7-8, 8-9, and 9-). As for job satisfaction, the workers whose scores were 10 (median) or less were defined as those who were dissatisfied with their jobs (‘?oh dissatisfaction”), and those whose scores were more than 10 (median) were defined as those who were satisfied with their jobs. With respect to the probability of job dissatisfaction, based upon the measure, the algorithm of the signal detection model was used to check each variable and the possible cutoff points to determine the optimally efficient variable and its cutoff point. After the first optimally efficient variable (which is optimally sensitive and optimally specific) is selected along with its cutoff point, the signal detection program beings to examine separately the next most optimally efficient variable and its cutoff point in each of the newly divided subgroups. With respect to all remaining variables, this pro-

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WORK STRESSORS, D R I N K I K G . A N D JOB SATISFACTION 745

cedure is repeated separately until one of the following happens (Winkleby et al., 1994): 1) no further predictors exist in a newly divided subgroup, 2)no more significant variables are detected at a level o f p < .01. or 3) the number of subjects in the newly divided group becomes too small.

In sum, based upon the probability of job dissatisfaction (the score on the four-item scale was 10 or less). we used this method and the stressor and social drinking variables in Table 1 to best divide the sample into subgroups which are maximally discriminated from each other and mutually exclusive.

For ease of interpretation with respect to the results obtained in this study, a profile of each group divided by the signal detection analysis is provided. Chi-square tests for categorical variables and an ANOVA (one- way for continuous variables were performed.

RESULTS

Table 1 summarizes the data of age, commuting time, working hours, work stressor items, attitudes toward drinking with coworkers after work, and job satisfaction among “staff members and lower-level managers” and “middle- and higher-level managers.” The staff members and lower-level managers were younger (35.26 vs 46.22) ( p = .0001), worked longer (p = .0004), and spent less time commuting ( p = .OOOl) . As for work stressors, a significantly larger percentage of employees who perceived work stressors was observed among the staff members and lower-level managers.

Figures 1 and 2 show the results of an optimally efficient algorithm for identifying distinct subgroups based on the probability of reporting job dissatisfaction among the staff members and lower-level mangers and the middle- and higher-level managers, respectively.

As shown in Fig. 2, of the staff members and lower-level managers, 47.1 % were dissatisfied with their jobs. The most optimally efficient variable that distinguished between those who were satisfied with their jobs and those who were not was the work role (“work role is not clear,” p < .OOOl) . Among the 143 subjects whose work role was clear, 37.1% of the workers were dissatisfied with their job. Among those whose work role was not clear, 78.3% of the workers were dissatisfied with their job. Next, we focus exclusively on detecting the most optimally efficient variable among those whose work role was clear. Drinking with coworkers after work (“attitudes toward drinking after work”) was the best predictor (17 < .025). This variable divided the group into two groups consisting of those who were positive toward drinking with coworkers after work (Group 1) and those who were negative toward drinking (Group 3 ) . Among Group I , 31.5% of the workers were dissatisfied with their job. Among Group 3, 54.3% of the workers were

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746 HACIHARA, TARUMI, AND NOBUTOMO

Total sample (N=189) Job dimatisfaction: 47.1%

I Clear work role

Job dissatisfaction: 78.3% Job dissatisfaction: 37.1%

I I COncRte work direction ( x e4.55, pc0.05) aRer work

Attitude8 tow& drinLing

( Xz=5.89, pgO.025)

/ \ Positive (N=lO8) Negative (N=35) Yes (N=8)

’ . I)

No (N=38) / \ Group 4 G ~ O U P a

Group 3 Gmup 1

Fig. 2. The results of signal detection analysis for staff members and lower-level managers.

dissatisfied with their job. In other words, among those staff members and lower-level managers whose work role was clear, having a positive attitude toward drinking with coworkers was significantly related to higher job satisfaction.

Among those whose work role was not clear, the most optimally efficient variable was work direction (“concrete work direction”) ( p < .05). This variable divided the group into two groups: those whose work direction was concrete (Group 2) and those whose work direction was not concrete (Group 4). In Group 2, 50.0% of the workers were dissatisfied with their job. In Group 4, 84.2% of the workers were dissatisfied with their job.

As shown in Fig. 3, of the middle- and higher-level managers, 44.2% were dissatisfied with their job. The most optimally efficient variable that distinguished between those who were satisfied with job and those who were not was work autonomy (“having autonomy in work,” p < .0001). Among those who did not have autonomy in work (Group 4), 90.6% of the workers were not satisfied with their job. Next, we focused exclusively on detecting the most optimally efficient variable among workers who had autonomy in work. The work role (“clear work role”) was found to be the most optimally efficient variable ( p < .001). This variable divided the group into two subgroups: those who reported that their work role was not clear (Group 30 and those whose work role was clear. Among those whose work role was clear, the most optimally efficient variable was attitudes toward drinking with coworkers (“attitudes toward drinking after work”) ( p < .05). This variable divided with coworkers after work (Group 1) and those who were negative toward drinking with coworkers after work (Group 2). In

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WORK STRESSORS. DRINKING, AND JOB SATISFACTION 141

Total sample (N=208) Job dissatisfaction: 44.2%

I Having autonomy in work

Job dissatisfaction: 35.8%

I Group 4 Clear work mle (xz=15.09, p<O.Ool)

No (N=20) / \ Yes (N=156)

Job disaatisfaction: 30.8% . . .

I Group 3 Attitudes towards drinking after work (Z *=4.09, pGO.05)

/ \ - Negative (N=37) Positive (N=119)

Group 2 Group 1

Fig. 3. The results of signal detection analysis for middle- and higher-level managers.

Groups 1, 2, and 3, 23.5, 40.5, and 75.0% of the workers were dissatisfied with their jobs, respectively.

Tables 2 and 3 present the profiles of the above subgroups identified by the signal detection analysis among the staff members and lower-level managers, and the middle- and higher-level managers, respectively. The profiles of the staff members and lower-level managers presented in Table 2 indicate that Groups 1 and 4 drank the most often (3.58 and 3.64 times per week, respectively). In contrast, Groups 2 and 3 drank only 1.06 and 2.29 times per week, respectively. What is interesting is that Groups 1 and 4 are so different. Group 1 is the group that reported the lowest amount of job dissatisfaction and the lowest levels of work stressors in terms of work load, job autonomy, and work procedure. This group also reported the most positive attitude toward drinking with coworkers (mean = 8.82). In contrast, Group 4 is the group that reported the highest amount of job dissatisfaction and the highest levels of work stressors in terms of an unclear work role and direction. However, as with Group 1, they too have a fairly positive attitude toward drinking with coworkers (mean = 7.97). Therefore, the subjects who drank the most often were those who had the lowest and the highest levels of job dissatisfaction and work stressors.

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Tab

le 2

Cha

ract

eris

tics

of S

ubgr

oups

Div

ide

d b

y S

igna

l Det

ectio

n A

naly

sis:

Sta

ff M

embe

rs a

nd L

ower

-Lev

el M

anag

ers

(n =

189

)a

4

%

Gro

up I

Gro

up 2

G

roup

3

Gro

up 4

p-

valu

e

I. N

umbe

r 2.

Pr

eval

ence

of j

ob d

issa

tisfa

ctio

n (Y

O)

I,

Age

(ye

ars)

2.

C

omm

utin

g tim

e (m

inut

es)

3.

Wor

king

hou

rs (

hour

s)

4.

Littl

e w

ork

auto

nom

y (Y

O)

5.

6.

Fixe

d w

ork

proc

edur

e ("I

n) 7.

R

epet

itive

wor

k ('10)

8.

Wor

k ha

s de

adlin

e (%

) 9.

10

. 1 I

. 12

. W

ork

is di

ffic

ult (

46)

13.

14.

Wor

k st

ress

ors:

Wor

k re

quir

es n

ew k

now

ledg

e ('Y

O)

Wor

k di

rect

ion

is no

t co

ncre

te (

YO

) W

ork

role

is n

ot c

lear

(70)

Wor

k ne

eds

to b

e do

ne q

uick

ly (

%)

Tim

e to

com

plet

e w

ork

is no

t eno

ugh

("YO)

Atti

tude

s to

war

d dr

inki

ng in

bus

ines

s si

tuat

ions

So

cial

dri

nkin

g:

108

8 35

38

31

.5

50.0

54

.3

84.2

24.0

7 89

.81

9.26

29

.63

82.4

I 30

.56

95.3

7 33

.33

62.9

6

0 8.82

32.2

5 59

.38

9.31

75.0

0 87

.50

12.5

0 37

.50

87.5

0 0

100

100 62.5

0 62

.50

5.75

35.4

3 56

.00

9.74

3 I .4

3 91

.43

20.0

0 34

.29

74.2

9 62

.89

97.1

4 28

.57

60.0

0

0 6.64

34.0

8 55

.92

9.92

47.3

7 68

.42

42.1

1 23

.68

94.7

4 10

0 I0

0 86x4

31

.58

76.3

2

7.97

Vuric

ihle

.7 R

elat

ing

to D

rink

ing

Huh

it.sh

1.

Fr

eque

ncy

of d

rink

ing

per

wee

k' 3.

58

1.06

2.

29

3.64

2.

Q

uant

ity

of d

rink

ing

per

occa

sion

d 1.

20

0.93

1.

18

1.23

'' Chi

-squ

are

test

was

use

d fo

r w

ork

stre

ssor

s. a

nd a

one

-way

AN

OV

A w

as u

sed

for

the

rem

aini

ng c

onti

nuou

s va

riab

les.

T

hese

var

iabl

es w

ere

not

incl

uded

in

the

sign

al d

etec

tion

anal

ysis

. T

his

vari

able

is o

ne o

f th

e th

ree-

item

bat

tery

to

eval

uate

atti

tude

s to

war

d dr

inki

ng w

ith c

owor

kers

aft

er w

ork.

Q

uant

ity i

s in

dica

ted

by o

ne c

up o

f sa

ke (

180

niL

, abo

ut 2

5 m

g of

alc

ohol

).

< 0.

01

NS

NS

NS

< 0.

01

< 0

.01

< 0

.01

NS

NS

$ <

0.01

0

NS

$ 4

m

< 0.

01

5 N

S P

NS

>

< 0.

0001

c 5 -1

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Tabl

e 3

Cha

ract

eris

tics

of S

ubgr

oups

Div

ided

by

Sig

nal D

etec

tion

Ana

lysi

s: M

iddl

e-Le

vel a

nd H

ighe

r-Le

vel M

anag

ers

(n =

208)a

Gro

up 1

G

roup

2

Gro

up 3

G

roup

4

[I-v

alue

1.

Num

ber

2.

Prev

alen

ce o

f job

dis

satis

lhct

ion

(%)

1.

Age

(ye

ars)

2.

C

omm

utin

g tim

e (m

inut

es)

3.

Wor

king

hou

rs (

hour

s)

4.

Littl

e w

ork

auto

nom

y (‘Y

o)

5.

6.

Fixe

d w

ork

proc

edur

e (Y

n)

7.

Rep

etiti

ve w

ork

(Yn)

8.

W

ork

has

dead

line

(YO

) 9.

10

. 11

. 12

. W

ork

is di

ffic

ult

(YO

) 13

.

Wor

k st

ress

ors:

Wor

k re

quir

es n

ew k

now

ledg

e (‘V

’n)

Wor

k di

rect

ion

is n

ot c

oncr

ete

(%)

Wor

k ro

le is

not

cle

ar (

YO

) W

ork

need

s to

be

done

qui

ckly

(“In

)

Tim

e to

com

plet

e w

ork

is no

t en

ough

(‘Y

O)

119

37

23.5

40

.5

hdep

ctid

iw t

Varic

ihie

s 46

.25

46.7

6 61

.54

59.4

6 9.

17

93

5

0 78.9

9 I .

68

15.9

7 85

.71

41.1

8

99. I

6 30

.25

55.4

6

0

0 8 I .o

x 2.

70

40.5

4 91

.89

43.2

4

97.3

0 35

.14

54.0

5

0

Soci

al d

rink

ing:

14

. A

ttitu

des

tow

ard

drin

king

in

busi

ness

situ

atio

ns

8.63

6.

42

Vari

able

s R

elat

ing

to D

rink

itig

Hub

its’

I.

2.

Freq

uenc

y of

dri

nkin

g pe

r w

eek‘

Q

uant

ity o

f dr

inki

ng p

er o

ccas

iond

4.

35

3.36

1.

53

I .64

20

75.0

47.1

0 62

.25

8.93

0 0 75.0

0

25.0

0 80

.00

80.0

0

90.0

0 10

.00

80.0

0

100 7.

89

3.98

I .

20

32

90.6

44.9

5 56

.69

9.42

I00 59

.38

21.8

8 40

.63

81.2

5 71

.88

37.5

0 96

.88

28.1

3 56

.25

7.68

3.58

1.

63

< 0

.01

NS

NS

NS

< 0

.01

NS

<

0.01

<

0.01

N

S <

0.0

1 <

0.0

1 N

S N

S N

S

< 0.

0001

NS

NS

’’ Chi

-squ

are

test

was

use

d fo

r w

ork

stre

ssor

s, a

nd a

one

-way

AN

OV

A w

as u

sed

for

the

rem

aini

ng c

onti

nuou

s va

riab

les.

’T

hese

var

iabl

es w

ere

not

incl

uded

in

the

sign

al d

etec

tion

anal

ysis

.

“Qua

ntit

y is

ind

icat

ed b

y on

e cu

p of

sak

e (1

80m

L. a

bout

25m

g of

alc

ohol

).

Thi

s va

riab

le is

one

of

the

thre

e-ite

m b

atte

ry t

o ev

alua

te a

ttit

udes

tow

ard

drin

king

with

cow

orke

rs a

fter

wor

k.

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Table 3 presents the group profiles for the middle- and higher-level managers. The pattern is somewhat different. In this case the frequency of drinking did not differ significantly from group to group. All of these subjects drank frequently, averaging about 4 times a week. This may be due to behavioral expectations for higher-status workers. If we compare the groups on other dimensions, we see that Group 1 had the lowest job dissatisfaction and the lowest work stressors in terms of autonomy, fixed work procedures, repetitive work, and work direction. They also had the most positive attitude toward drinking with coworkers (mean = 8.63). In contrast. Group 4 was the least satisfied, and tended to perceive work stress regarding fixed work procedures, repetitive work, and ambiguous work directions. They also had a significantly less positive attitude toward drinking with coworkers than did Group 1 (mean = 7.68). Despite these differences among all of the groups, there were no significant differences in terms of drinking frequency or amount.

DISCUSSION

Past alcohol consumption studies have tended to examine the buffering effects of coping style (Frone and Windle, 1997; Breslin et al., 1995) and social support (Peirce et al., 1996) on the stress-alcohol consumption relationship within the framework of a regression analysis or ANOVA. However, as we have noted regarding the role of drinking with coworkers after work in Japanese companies, drinking with coworkers after work might have positive effects by lessening the levels of work stressors and increasing the level of job satisfaction. To our knowledge, no studies have examined stress-buffering effects of drinking with coworkers after work on the work stressor-job dissatisfaction relationship. In the present study we examined how drinking with coworkers after work relates to work stressors and produces stress-buffering effects. With the use of a signal direction analysis, several optimally efficient variables including work stressors and drinking after work were detected. As Figs. 2 and 3 show, there was a similarity between the two algorithms. That is, an interaction between a work stressor variable and a drinking variable was observed. In Fig. 2, among the subjects whose work role was clear, those who had a positive attitude toward drinking after work were significantly less likely to feel job dissatisfaction than those who had a negative attitude toward drinking after work (31.5 vs 54.3%, p < .05). We found a similar pattern in Fig. 3. Among the employees who had work autonomy and a clear work role, those who had a positive attitude toward drinking after work were significantly less likely to feel job dissatisfaction than those who had a negative attitude

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WORK STRESSORS, DRINKING, AND JOB SATISFACTION 751

toward drinking after work (23.5 vs 40.5%, p < .05). Among the staff members and lower-level managers, the workers in Groups 1 and 2 had work stressors such as work autonomy, work requiring new knowledge, and time pressure (Table 2). Among the middle- and higher-level managers, the workers in Groups 1 and 2 also had work stressors such as work requiring new knowledge, repetitive work, work deadlines, time pressure, and difficult work (Table 3).

While employees in European or American companies perform their own work essentially by themselves. employees in Japanese companies often collaborate to perform group tasks other than their own jobs (Yoshida and Tanaka, 1985; Okuda, 1982; Ihida, 1983). Frequent partici- pants in drinking occasions with coworkers after work are more likely to get feedback on their job performance and on new knowledge required for work, among other benefits such as promoting smooth interpersonal relationship (Yoshimori, 1984). In view of the effects of the drinking habits among Japanese workers. the positive effects of alcohol (Cappell and Greeley, 1987; Pearlin and Radabaugh, 1976; Violanti et al., 1983; Herald and Conlon, 1981; Abranis and Paymond, 1987; Hishio et al., 1994) and the findings shown in Figs. 2 and 3 imply that drinking with coworkers after work ameliorates a sense of job dissatisfaction among workers who have low levels of work stressors, although the present data are cross sectional.

When stress-buffering effects of drinking with coworkers after work on job dissatisfaction are implied typically within the framework of a signal detection analysis, the following interaction between a work stressor and a drinking variable could be expected. To take the algorithm of the signal detection analysis of the staff members and lower-level managers as an example (Fig. 2), a drinking variable should have been detected as an optimally efficient variable among the subjects whose work role is not clear. In addition, the subjects with positive attitudes toward drinking with coworkers should have been less likely to be dissatisfied with their jobs than those with negative attitudes toward drinking with coworkers after work. This was not the case. I n the present study, every interaction of a drinking variable was related to the nonexistence of a specific stressor (“clear work role” among the staff members and lower-level managers, and among the middle- and higher-level managers) (Figs. 2 and 3). Thus. the results indicate that a positive attitude toward drinking habits with coworkers tends to decrease job dissatisfaction among workers who do not sutrer from certain types of work stressors (i.e.. an unclear work role or lack of job autonomy). However, among those who suffer these stressors, drinking habits do not serve to counteract their deleterious effects.

Numerous studies have reported that higher stress leads to increased alcohol consumption (Abbey et al., 1993: Hassong and Chassin, 1994; Mills

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752 HAGIHARA. TARUMI, A N D NOBUTOMO

et al., 1993). Job satisfaction has also been shown to be closely related to mental stress (Cohen and Edwards, 1989; Cohen and Wills. 1985: Karasek and Theorell, 1990). In agreement with these findings, Group 4 in both the staff/lower-level and middle-/higher-level groups had the highest level of job dissatisfaction aiid drank quite often (3.64 times per week among the staff members and lower-level managers, and 3.58 times per week among the middle and higher-level managers) (Tables 2 and 3 ) . However, Group 1 of both the staff/lower-level and middle-/higher-level groups with the lowest job dissatisfaction also drank often (3.58 times per week among the staff members and lower-level managers and 4.35 times per week among the middle- and higher-level managers). Thus, we see a complex relationship between alcohol consumption, work stress, and job satisfaction. Some workers appear to drink because they have stress, but the drinking did not serve to reduce the stress (in terms of decreasing their dissatisfactjon). Other workers drink not because of stress, but the drinking seems to decrease their job dissatisfaction level.

We believe that the approach using specific stress measures in the present study can provide information far beyond descriptive use, although signal detection analysis is a type of analytic technique. For example, the Group 3 middle- and higher-level managers did not have a clear work role even though they had work autonomy. Effective interventions for this group would include making their work role clear (Fig. 3). The Group 4 staff members and lower-level managers had vague work roles and abstract work directions. Effective interventions for this group would be to clarify their work role and work direction. More effective stress management is possible based on the results of this type of study, using specific stress measures.

Finally, there are several limitations to this study. First, the findings concerning the positive effects of drinking after work on job dissatisfaction were obtained in a Japanese company; the Japanese work environment is not a widely encountered model. The significance of drinking varies among societies and cultures (Bacon, 1976; Bales, 1946; Health, 1976; Stivers, 1976). Therefore, the external validity of this study might be limited. Second, the subjects of the present study were male white-collar workers. Hence, the findings of this study might be applicable solely to other male white-collar workers. In conclusion, we were able to analyze the stress-buffering effects of drinking with coworkers after work on job dissatisfaction within the framework of a signal detection analysis. The results demoii- strated several higher-order interactions of drinking with coworkers and work stressors. To confirm the stress-buffering effect of drinking with coworkers, an outcome study using objective measures for work-stressors is needed. In addition, although the study focused specifically on the positive

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WORK STRESSORS. DRINKING. AND JOB SATISFACTION 753

effects of after-work drinking with coworkers in relation to job satisfaction, other aspects of drinking. such as the effects on family life and physical health of workers, also need to be studied. This is a suggested topic for future study.

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YOSHIMORI, K. ( 1984) Europrun Spirit and Management Style. Tokyo, Keizai Shinpou (in Japanese).

THE AUTHORS

Akihito Hagihara, is an associate professor at Kyushu University Graduate School of Medicine, Department of Health Services Management and Policy. He received his Ph.D. in medical science from the Osaka University Medical School in Osaka, and his M.P.H. in health behavior and health education from the University of Michigan, School of Public Health. His research interests include stress processes, occupational stress, and health communication.

Kimio Tarumi, is an associate professor at the University of Environmental and Occupational Health. He received his Ph.D. in medical science from the Kyoto Prefectural University of Medicine. His research interests include occupational health, occupational stress, and the relationship between life- style and health.

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756 HAGIHARA. TARUMI, AND NOBUTOMO

Koichi Nobutomo, is a full professor at Kyushu University Graduate School of Medicine, Department of Health Services Management and Policy. He received his M.D. and Ph.D. in medical science from the Kyushu University of Medical School in Fukuoka, and his M.S. in epidemiology from Harvard University, School of Public Health. His research interests include health policy, health administration, and health communication.

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Documents

Work Stressors, Drinking with Colleagues after Work, and Job Satisfaction among White-Collar Workers in Japan