Cross-cultural adaptation and validation of the Job Content Questionnaire (JCQ-22)

Abstract

BACKGROUND:

Although the Job Content Questionnaire (JCQ-22) has been translated into numerous languages and applied in various countries, its cultural applicability in China remains unclear.

OBJECTIVE:

To adjust the JCQ-22 for cross-cultural use and optimize the scoring method for suitability for Chinese working populations.

METHODS:

We first used the original JCQ-22 questionnaire to measure occupational stress. Cross-cultural adjustment involved reorganization of scale items (adjusted-I scale) and deletion of inefficient redundant items during reorganization of scale items (adjusted-II scale). Structural validity and the relationship between stress and health outcomes (insomnia and self-conscious symptoms) before and after adjustment were compared.

RESULTS:

Exploratory factor analysis revealed that the two-factor cumulative variance contribution rate of job demand and control of the adjusted-II scale was 52.47%, compared with 48.44% and 48.44% in the original version and adjusted-I scale, respectively. Among the 16 fitness indicators in confirmatory factor analysis, 9 items of the adjusted-II scale met the standard, compared with 4 items of the original and adjusted-I scales. The Pearson’s correlation coefficients between occupational stress and insomnia as well as self-conscious symptoms from the adjusted-II scale were 0.15 and 0.32, respectively, which were higher than those of the original scale (0.10 and 0.20). Receiver operating characteristic analysis revealed that the adjusted-II scale exhibited a better area under the curve and Youden index values than the original scale.

CONCLUSION:

The adjusted-II scale exhibited superior structural validity with more reasonable health outcome predictions and fewer items, making it more suitable for measuring occupational stress in Chinese populations.

Keywords

Occupational stress cultural applicability health outcome prediction efficiency

1 Introduction

At present, because of the industrial structure of the Chinese economy, a large number of people work in industrial jobs. Traditional occupational diseases such as pneumoconiosis and occupational poisoning in this population have not been effectively controlled. At the same time, new occupational psychosomatic diseases caused by complex factors such as social environments and organizational structures are increasing in this group [1].

Occupational psychological disorders involving occupational stress are increasingly prominent, becoming a serious challenge to the health of some occupational groups. Recent data indicate that mental disorders are responsible for an increasingly major disease burden in China [2]. Mental stress caused by overwork leads to 60% to 80% of occupational accidents and absenteeism in Taiwan, China [3]. Physical health monitoring of this group has achieved close to full coverage, but mental health monitoring has not yet been comprehensively promoted. Therefore, it is of great significance and practical value to carry out research on occupational physical and mental diseases represented by occupational stress among Chinese working populations and formulate physical and mental health monitoring methods for the working population.

To date, the JCQ has been validated in Western and Asian countries and translated into a number of languages to meet the needs of the target populations. Although a large number of validation studies have been conducted in different working populations in Asian countries, because of changing working conditions over time and in response to changes in the culture and lifestyle of younger generations in these countries, cultural bias is likely to affect the results [4]. Job stress has grown as an important occupational health issue, attracting increasing concern in China. However, previous studies have reported that the validity and reliability of the JCQ have not been well tested [5] and have pointed out several problems in its application. It is not yet clear whether the JCQ can be applied to Chinese working populations in a Chinese cultural context and enterprise system, although some studies have been conducted in post-communist countries in Europe [6].

Previous studies have shown that translation bias and differences between various versions of the JCQ in cross-cultural applications lead to differences in the measurement effects of the JCQ between countries and languages [7]. Of the more than 20 translated versions of the JCQ currently available, most were developed in the United States and Western European countries. Although several versions in different languages have been developed and validated in South-East Asian countries, including Thai and Malay versions, it remains uncertain whether the JCQ is applicable in low- and middle-income countries in South-East Asia, such as Vietnam [8]. Few studies have examined cross-language differences of different versions of the JCQ in Asian cultural contexts or in industrialized European countries. Thus, the robustness of cross-national or cross-regional mean comparisons of the JCQ questionnaires remains unclear. Even when the JCQ is used in comparative studies of psychosocial work hazards in European countries, cross-language differences still need to be considered. In addition to research examining differences in the measurement effects of the JCQ, there have been no previous international translation validation studies [9]. Few studies have examined cross-language or cross-national differential item functioning (DIF) of the JCQ, statistically or qualitatively [7].

JCQ is widely used in China, because of its clear structure and concise content [2,3,10 , 2,3,10]. Previous studies have shown that although the validity and reliability of the Chinese version of the JCQ meet the psychometric requirements, the correlation coefficient and α coefficient of some items remain low because of cultural differences between the country of origin and the country of use of the JCQ [6]. In addition, it has been reported that individual items have weak correlations with other items in the Chinese version of the scale, causing misunderstanding or difficulty answering [3,10, 3,10]. Therefore, further adjusting the items related to cultural factors in the scale is important before promoting its use [11].

In the current study, we reorganized and deleted some items in the scale, and we restructured the questionnaire and its items through cross-cultural adjustment to make it more suitable for Chinese workers in terms of logical structure and understanding. In addition, previous studies have confirmed that occupational stress can lead to negative physiological and psychological effects, including insomnia, depression and anxiety [12 –14]. Thus, we sought to evaluate the measurement effects of the adjusted questionnaire and the original questionnaire by examining whether the results could effectively express the relationships between occupational stress and the changes described above. Thus, this study aimed to adjust the JCQ-22 for cross-cultural use and optimize the scoring method for suitability for Chinese working populations.

2 Subjects and methods

2.1 Sampling frame and participants

The subjects were cluster sampled from workers who participated in an occupational health examination at a tertiary A-level hospital. Permission to conduct this research was obtained from the Ethics Committee of West China School of Public Health, Sichuan University (No. 201503100012). The experimenters introduced the research to each subject, who then signed an informed consent form. All data were strictly confidential and were used for the purposes of the current study only. In order to estimate the sample size required for the study, based on the mean scores of Job Demand and Control in JCQ-22 obtained from a large sample survey in China [15], we set the level of type I error (α) and type II error (β) to 0.05, and set the allowable observation error to 5%. The sample size calculated with the free software EpiCalc 2000 (Version 1.02, Joe Gilman and Mark Myatt, 1998, Brixton Books) was 606, multiplied by the design coefficient of 1.1 to 666, considering the loss of follow-up and other factors, increased by 10% to 727. Combined with the actual situation of cluster sampling, the actual sample size of this study is 807, which can ensure the effectiveness of the research results.

The study included 807 subjects aged 18–62 years (M = 32.75, SD = 8.262). 70.4% of subjects were men and 29.6% were women. According to the 2015 edition of classification of occupations of the People’s Republic of China, the study population included workers from nine industry sectors: electrical appliance manufacturing, the petrochemical industry, chemical manufacturing, (metal/non-metal) mineral products manufacturing, equipment manufacturing, waste disposal, the power industry, medicine, and the retail services industry.

2.2 Measuring instruments

To verify whether there were cross-cultural differences in the use of the JCQ scale in China, the current study used the JCQ-22 original scale to measure occupational stress. According to the possible cultural understanding deviation in the cognitive survey and the bias in the actual measurement, the original scale was adjusted, and performance was compared before and after adjustment. In our study, the Athens Insomnia Scale-5 (AIS-5) was used to measure insomnia, and the Symptom Check List-90 (SCL-90) was used to measure self-conscious symptoms.

2.2.1 Job Content Questionnaire-22 (JCQ-22)

The occupational stress questionnaire used in the study was the Chinese version of JCQ-22, which was translated by Dr. Li Jian of Kunming Medical University with the authorization of Dr. Robert Karasek, the developer of JCQ [16]. The JCQ-22 consists of three domains (job demands [D], control [C] and social support [S]) containing five, nine and eight items, respectively, with 22 items in total. Items in the scale are scored using a Likert scale in which 1 indicates that the subject strongly disagrees and 4 indicates that the subject strongly agrees. The score for each domain is the sum of its item scores; the higher the score, the higher the degree of the domain measured [17, 18]. The user manual of the original JCQ-22 questionnaire did not clearly set internal confirmatory items. All items of the original JCQ-22 questionnaire were scored and were valid items [16].

2.2.2 Athens Insomnia Scale-5 (AIS-5)

The Athens Insomnia Scale-5 (AIS-5) is an international survey scale of insomnia that consists of guidelines and five items. Subjects use Likert-type scales to indicate how severely certain sleep difficulties have affected them during the past month. Scores range from 0 (indicating that the item in question has not been a problem) to 3 (indicating more acute sleep difficulties). The insomnia score is the sum of the scores of five items [19, 20].

2.2.3 SCL-90

The SCL-90 is the most widely used clinical examination scale for mental disorders and diseases. According to a comprehensive literature analysis, the four domains of the scale (somatization, compulsion, depression and anxiety) are closely related to occupational stress [21 –23], and each domain of the scale can be used independently. Therefore, 45 questions (including the four domains above) were selected from the scale to measure the self-conscious symptoms of the subjects. Items in the scale are scored using a Likert scale in which 1 indicates that the item in question has not been a problem, and 5 indicates that the problem is serious. The sum of the scores of each item in a domain is the domain score, and the sum of the scores of each domain is the total score. The total score is the sum of 45 item scores. Higher total scores indicate more serious self-conscious symptoms.

2.3 Strategies for cross-cultural adjustment of the JCQ-22

2.3.1 The formation process of the cross-cultural adjustment strategy of JCQ-22

When we used the JCQ-22 to measure occupational stress among Chinese workers, the results revealed problems of cultural applicability. During the investigation, we interviewed some subjects, and there was a deviation in understanding the items, mainly as follows. Although the items of learning new things, repetitive work, required creativity and high skill level belong to the domain of control, most subjects reported that they considered the above items to measure the requirements of the awareness and ability of workers. This was inconsistent with the expected measurement purpose of the items and affected the structural validity of the scale. Because the eight items of the social support domain in the JCQ-22 conformed to Chinese cultural habits, there was no deviation in understanding in the survey and no need to adjust the items. Therefore, cross-cultural adjustment included two domains: job demands (D) and control (C) (Table 1).

Table 1
Distribution of items included in the adjustment of the JCQ-22

Item Content Domain

D1 Work fast Demand (D)

D2 Work hard Demand (D)

D3 No excessive work Demand (D)

D4 Enough time Demand (D)

D5 Conflicting demands Demand (D)

C6 Learn new things Control (C)

C7 Repetitive work Control (C)

C8 Requires creative Control (C)

C9 High skill level Control (C)

C10 Variety Control (C)

C11 Develop own abilities Control (C)

C12 Allow own decisions Control (C)

C13 Little decision of freedom Control (C)

C14 Lot of say Control (C)

Item	Content	Domain
D1	Work fast	Demand (D)
D2	Work hard	Demand (D)
D3	No excessive work	Demand (D)
D4	Enough time	Demand (D)
D5	Conflicting demands	Demand (D)
C6	Learn new things	Control (C)
C7	Repetitive work	Control (C)
C8	Requires creative	Control (C)
C9	High skill level	Control (C)
C10	Variety	Control (C)
C11	Develop own abilities	Control (C)
C12	Allow own decisions	Control (C)
C13	Little decision of freedom	Control (C)
C14	Lot of say	Control (C)

In the Chinese cultural context, active learning of work content and acceptance of repetitive work were usually used as important standards to evaluate whether a worker was positive and hardworking, which were spiritual indicators. Creativity and the pursuit of high technology were important embodiments of whether a worker pursued excellence. All these had little to do with control (C). In addition, the research showed that China is a collectivistic country that reflects the subordination of individual goals to group goals [24], so Chinese workers’ task autonomy was limited, which was regarded as a key predictor of turnover intention [25]. Based on these, the following two adjustment strategies were generated: Strategy-I was to reorganize the scale items, and Strategy-II was to delete inefficient redundant items during the reorganization of scale items.

2.3.2 The adjustment strategy I

The first adjustment strategy (adjustment strategy I) was to rearrange the scale items to construct the adjusted-I scale. According to Chinese cultural understanding, four items (c6, c7, c8 and c9) were transferred to the domain of job demands (D) (Fig. 1).

Fig. 1

Diagram showing adjustment strategy I (adjusted-I) and factor load distribution of scales.

2.3.3 The adjustment strategy II

The second adjustment strategy (adjustment strategy II) was to delete inefficient or redundant items and rearrange the items to construct the adjusted-II scale. According to the adjusted-I scale defects and the actual task autonomy of Chinese workers, four items (d4, c7, c8 and c13) were deleted, and c6 was transferred to the domain of job demands according to the Chinese cultural context (Fig. 2).

Fig. 2

Diagram showing adjustment strategy II (adjusted-II) and factor load distribution of scales.

2.4 Optimization of the scoring method of the adjusted scale

After adjustment of the original scale, it was necessary to revise the scoring method of the adjusted scale in accordance with changes in the items and the scale structure. The scoring method used in the original scale only considers information related to job demands and control, excluding information related to social support. However, previous studies reported that social support is a protective factor against occupational stress [26, 27]. On the basis of the three domains of the JCQ-22, we assumed two effects in the current study: an additive effect and a multiplicative effect [28]. According to whether the standard score or absolute score was used in the calculation, four calculation formulas were constructed to compare the calculation results with those of the original scale (Table 2).

Table 2
Comparison of the scoring methods between the original and adjusted scales*

Adjustment Score type Effect assumption Calculation formula

Original scale Absolute score – D/(C5/9)

Adjusted scale Absolute score Additive effect 2D/(C + S)

Multiplicative effect D²/(CS)

Standard score Additive effect (2(D/5))/((C/5)+(S/8))

Multiplicative effect (D/5)²/((C/5)(S/8))

Adjustment	Score type	Effect assumption	Calculation formula
Original scale	Absolute score	–	D/(C*5/9)
Adjusted scale	Absolute score	Additive effect	2D/(C + S)
		Multiplicative effect	D²/(C*S)
	Standard score	Additive effect	(2*(D/5))/((C/5)+(S/8))
		Multiplicative effect	(D/5)²/((C/5)*(S/8))

*D indicates the score for job demands, C indicates the score for control, S indicates the score for social support.

2.5 Statistical analysis

Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to compare the scale structures of the adjusted-I and adjusted-II scales with the original version of the scale. The adjusted and original scales were used to calculate the occupational stress level, and correlation analyses of health outcomes (insomnia and self-conscious symptoms) reported by subjects were performed. According to the relationship intensity, the rationality of the outcome prediction of the scales was evaluated, and the stress scoring method was optimized. Receiver operating characteristic (ROC) analysis was used to evaluate the prediction efficiency of the scales. The significance level was 0.05 (two-tailed). Cronbach’s α was used to evaluate the reliability of the scales before and after adjustment.

3 Results

3.1 Changes of scale structure after adjustment strategy I

Because the data structure of the adjusted-I scale was the same as that of the original version, after EFA analysis, the factor eigenvalues, contribution and factor load values of job demands (D) and control (C) of the two scales were identical, and the cumulative variance contributions of the two scales were both 48.44%. However, Fig. 1 shows that the factor load structure of the adjusted-I and original scales did not match the domain settings well. This result indicated that the factor load values of d4 and c8 did not match the classification well, and the factor load values of c14 were low, as shown in Fig. 1.

3.2 Improvement of the scale structure after adjustment strategy II

There were five items in the domains of job demands (D) and control (C) on the adjusted-II scale, which were more balanced in structure. The cumulative variance contribution of job demands (D) and control (C) was 52.47%, which is higher than that of the adjusted-I and original scale (48.44%) and significantly improved the degree of explanation. The factor load distribution of the two domains (D and C) in the adjusted-II scale was more balanced than that of the adjusted-I scale (48.44%) and original scale (48.44%), and the factor structure represented by the items had clearer differentiation, as shown in Fig. 2.

3.3 Comparison of the structural goodness of fit and reliability of the original scale (JCQ-22) and adjusted scales (adjusted-I and adjusted-II)

Among the 16 CFA analysis results, 9 results of the adjusted-II scale met the fitting criteria, which was significantly greater than that of the adjusted-I and original scales, both of which produced 4 results that met the criteria. Moreover, the results of the adjusted-II scale that did not meet the fitting criteria were closer to the fitting criteria than those of the other two scales (Table 3). This finding indicated that the fitting effect of the adjusted-II scale was better than that of the adjusted-I and original scales, with a lower level of error. Because the original and adjusted-I scale only had different item combinations, the data were consistent, and Cronbach’s α was the same, both of which were 0.921. The Cronbach’s α of the adjusted-II scale was 0.911, with little change. Although the items were reduced, the reliability had little change and had good popularization. Therefore, the results revealed that the adjusted-II scale was the optimal scale after cultural adaptation.

Table 3
Comparison of the CFA analysis results among the adjusted-I, adjusted-II and original scales*

Statistics Fitting criteria Original scale Adjusted-I scale Adjusted-II scale

Absolute indexes of fit

RMR <0.05 0.04* 0.04* 0.03*

RMSEA <0.08 0.12 0.12 0.09

GFI >0.90 or above 0.83 0.86 0.94*

AGFI >0.90 or above 0.76 0.8 0.91*

Relative indexes of fit

NFI >0.90 or above 0.74 0.77 0.9

RFI >0.90 or above 0.69 0.72 0.86

IFI >0.90 or above 0.76 0.78 0.91*

TLI(NNFI) >0.90 or above 0.71 0.74 0.88

CFI >0.90 or above 0.76 0.78 0.91*

Simple indexes of fit

PGFI >0.50 or above 0.6* 0.62* 0.58*

PNFI >0.50 or above 0.62* 0.64* 0.68*

PCFI >0.50 or above 0.63* 0.65* 0.69*

CN >200 78 87 161

χ2/df <2.00 13.91 12.48 7.53

AIC Theoretical model value is less than independent model value and saturated model value 1114.91 < 4115.25 1006.40 < 4115.25 297.92 < 2494.67

1114.91 > 210 1006.40 > 210 297.92 > 110

CAIC Theoretical model value is less than independent model value and saturated model value 1281.35 < 4195.60 1172.84 < 4195.60 418.44 < 2552.07*

1281.35 > 812.63 1172.84 > 812.63 418.44 < 425.66*

Statistics	Fitting criteria	Original scale	Adjusted-I scale	Adjusted-II scale
Absolute indexes of fit
RMR	<0.05	0.04*	0.04*	0.03*
RMSEA	<0.08	0.12	0.12	0.09
GFI	>0.90 or above	0.83	0.86	0.94*
AGFI	>0.90 or above	0.76	0.8	0.91*
Relative indexes of fit
NFI	>0.90 or above	0.74	0.77	0.9
RFI	>0.90 or above	0.69	0.72	0.86
IFI	>0.90 or above	0.76	0.78	0.91*
TLI(NNFI)	>0.90 or above	0.71	0.74	0.88
CFI	>0.90 or above	0.76	0.78	0.91*
Simple indexes of fit
PGFI	>0.50 or above	0.6*	0.62*	0.58*
PNFI	>0.50 or above	0.62*	0.64*	0.68*
PCFI	>0.50 or above	0.63*	0.65*	0.69*
CN	>200	78	87	161
χ2/df	<2.00	13.91	12.48	7.53
AIC	Theoretical model value is less than independent model value and saturated model value	1114.91 < 4115.25	1006.40 < 4115.25	297.92 < 2494.67
		1114.91 > 210	1006.40 > 210	297.92 > 110
CAIC	Theoretical model value is less than independent model value and saturated model value	1281.35 < 4195.60	1172.84 < 4195.60	418.44 < 2552.07*
		1281.35 > 812.63	1172.84 > 812.63	418.44 < 425.66*

*Indicates that the fitting criteria were met.

3.4 Measurement of occupational stress-related health outcomes

3.4.1 Insomnia

The average AIS-5 score of 807 subjects was 3.03±2.82. In this study, P75 (the 75th percentile of the score) was used as the dividing value. If the score exceeded this value, it was considered to indicate insomnia, and if it was less than or equal to this value, it was considered to indicate that there was no insomnia. To further understand the insomnia status of subjects, AIS-5 scores were used to evaluate sleep quality. Higher scores indicated worse quality of sleep.

3.4.2 Self-conscious symptoms

The average scores for self-conscious symptoms and each domain of 807 subjects were self-conscious symptoms 59.19±18.41, somatization 15.66±5.10, compulsion 14.27±4.81, depression 16.89±5.73 and anxiety 12.36±4.11. In this study, the 75th percentile of the score (P75) was used as the dividing value. If the score was greater than this value, it was considered that the symptom was obvious, and if it was less than or equal to this value, it was considered that the symptom was not obvious. To further understand the situation of self-conscious symptoms, the severity of self-conscious symptoms was evaluated by the scores. Higher scores indicated more serious symptoms.

3.5 Optimization of the scoring method of the adjusted-II scale

According to the strength of the relationship between occupational stress and its health outcomes, the rationality of prediction of the adjusted-II and original scales was compared, and the stress scoring method was optimized.

An analysis of the strength of the correlation between occupational stress and its health outcomes (insomnia, self-conscious symptoms, with four domains of somatization, compulsion, depression and anxiety) revealed that the correlation coefficients calculated from the four formulas above and the original formula were all significant. The correlation coefficient of the adjusted-II scale was the highest under the assumption of multiplicative effects, and the results were the same whether absolute scores or standard scores were used. This finding indicated that the adjusted-II scale had better outcome correlations under the multiplicative effects assumption (Table 4). Because absolute scores and standard scores were equivalent in the multiplication calculation, the adjusted-II scale and formula D2/(C*S) were used to calculate occupational stress scores in this study.

Table 4
The correlation coefficients between occupational stress level from different scoring methods and health outcomes

Scoring methods Correlation coefficient

Somatization Compulsion Depression Anxiety Self-conscious Insomnia

symptoms

Original scale

Absolute score 0.16 0.19 0.20 0.19 0.20 0.10

Adjusted-II scale

Absolute score and additive effect 0.18 0.25 0.29 0.25 0.26 0.15

Absolute score and multiplicative effect 0.23 0.28 0.37 0.32 0.32 0.15

Standard score and additive effect 0.17 0.24 0.26 0.23 0.25 0.14

Standard score and multiplicative effect 0.23 0.28 0.37 0.32 0.32 0.15

Scoring methods	Correlation coefficient
Original scale
Absolute score	0.16**	0.19**	0.20**	0.19**	0.20**	0.10**
Adjusted-II scale
Absolute score and additive effect	0.18**	0.25**	0.29**	0.25**	0.26**	0.15**
Absolute score and multiplicative effect	0.23**	0.28**	0.37**	0.32**	0.32**	0.15**
Standard score and additive effect	0.17**	0.24**	0.26**	0.23**	0.25**	0.14**
Standard score and multiplicative effect	0.23**	0.28**	0.37**	0.32**	0.32**	0.15**

**P < 0.01.

ROC analysis was used to evaluate the prediction efficiency of the original and adjusted-II scales. The AUC and Youden index scores from the adjusted-II scale were greater than or equal to those from the original scale for each health outcome, all of which were significant (Table 5). Therefore, the adjusted-II scale could predict the health outcomes of occupational stress more effectively than the original scale.

Table 5

The ROC analysis results of the original scale and the adjusted-II scale

Health outcomes	Stress scale	Cutoff	Sensitivity	Specificity	Youden index	AUC	P
Somatization	Original scale	0.91	0.55	0.63	0.18	0.60	<0.001
	Adjusted-II scale	1.21	0.70	0.48	0.18	0.60	<0.001
Compulsion	Original scale	0.85	0.73	0.47	0.20	0.61	<0.001
	Adjusted-II scale	1.23	0.70	0.49	0.20	0.61	<0.001
Depression	Original scale	0.85	0.72	0.47	0.19	0.62	<0.001
	Adjusted-II scale	1.51	0.46	0.78	0.24	0.64	<0.001
Anxiety	Original scale	0.85	0.68	0.46	0.14	0.59	<0.001
	Adjusted-II scale	1.55	0.42	0.79	0.20	0.61	<0.001
Self-conscious symptoms	Original scale	0.87	0.62	0.54	0.15	0.59	<0.001
	Adjusted-II scale	1.51	0.42	0.78	0.20	0.62	<0.001
Insomnia	Original scale	1.00	0.22	0.86	0.08	0.55	0.018
	Adjusted-II scale	1.19	0.64	0.48	0.12	0.56	0.007

On the basis of the above research results, the adjusted-II scale was named the Chinese cultural adaptation version of the JCQ (JCQ-CCA), and the formula D2/(C*S) was used as the scoring method.

4 Discussion

The Job Demands-Control Model and its extended version, the Demand-Control-Support (DCS) Model, proposed by Karasek et al. are the most widely used models in the field of occupational stress research [8 , 30]. The Job Content Questionnaire (JCQ) was originally developed in the United States on the basis of these models. Because of its simplicity, reliability and validity, the JCQ has become one of the most commonly used instruments for measuring occupational stress [31]. For over 40 years, occupational stress studies using the JCQ and its derivative versions have been carried out in various working populations in Spain, Greece, Thailand, Brazil, Malaysia, Vietnam, Iran and the United States [4 , 32–34]. These studies have revealed that high levels of occupational stress have negative effects on cardiovascular, musculoskeletal and mental health [4 , 30–32]. To date, the JCQ has been translated into 23 languages [35]. A Chinese version of the questionnaire has also been developed [36].

Although the JCQ has been translated into a range of languages and used in various countries, some problems remain regarding its cultural applicability. Standardized translation procedures, such as translation and back translation by bilingual translators, can effectively reduce the differences in understanding of items between different cultures [37]. However, because of cultural differences among translators, the translation of items and options is not perfect, and differences in understanding still exist [38 –40]. In addition, if there are ambiguous words in the original items, misunderstanding can be amplified by translation into the target cultural context. All these factors lead to measurement bias of the same questionnaire between the original cultural context and the target cultural context [35, 41]. To date, most research results have come from Western employment contexts [7], raising concerns about the validity of the JCQ in different cultural settings [42].

The measurement effect of the questionnaire is closely related to cultural applicability. A study of the mainland Chinese version of the JCQ questionnaire revealed that two items (repetitive work and enough time) had correlations with other items that were lower than 0.2, indicating that these two items resulted in poor internal consistency in the JCQ. Only these two items had negative factor loadings, indicating that they had different properties from other items. In addition, the item of no excessive work was not strongly related to the JCQ scale. Thus, the findings suggested that these three items might not be appropriate for the Chinese (mainland) working population [10, 43]. Therefore, it is necessary to consider the characteristics of Chinese culture and adjust the JCQ questionnaire in the domains of control and job demands before popularizing the scale in mainland China.

By constructing the adjusted-I scale, consistency between the measurement purpose of the questionnaire and the information obtained was ensured in Chinese language habits. By constructing the adjusted-II scale, not only were language habits straightened out, but the two domains of job demand and control had the same weight in the questionnaire, the overall questionnaire structure was more balanced, and the degree of interpretation was also improved. The problems of cultural debugging and result balance of items have been basically solved, the evaluation performance of occupational stress has been improved, and the questionnaire was more concise, which was conducive to improving compliance. On the basis of the above mathematical and statistical inference, starting from the professional cognition that stress, insomnia and conscious symptoms were closely related, the adjustment effect of the original and the adjusted-II scale was tested by comparing the correlation between occupational stress and its health effect under different effect models, and it was confirmed that the adjusted-II scale items had good outcome correlation.

The JCQ has been reported to have similar problems in other Asian countries and has made corresponding cultural applicability adjustments. A study of nurses conducted in Vietnam reported that the cross-cultural validity of the JCQ needs to be verified [8]. In an EFA of the 22-item JCQ, a factor model with three dimensions was consistent with the theoretical construction of the DCS model, with two exceptions. One exception was the item of conflict-free needs, which was reported to have low loading values and to be prone to deviation in understanding. The authors of the Taiwan-JCQ study noted that language and terminology occasionally influenced responses to this question, leading to misunderstanding in interpretation. The other exception was the item of variety, which can be regarded as an evaluation of workload. The authors suggested that the decision latitude scale of the JCQ should be revised or reorganized to consider specific characteristics of nursing jobs. Removing the items of variety and separating task-level (e.g., allowing workers to make their own decisions and have many say) and team-level (e.g., little freedom in decision-making) decision authority may improve the measurement of decision latitude among nurses using the JCQ [3 , 33]. In addition, two items (repetitive work and little decision freedom) were only weakly correlated with other items on the decision latitude scale, which would not be retained in the Vietnamese version of JCQ [8]. This is similar to the strategy used in the current study.

Similar problems have been reported in European countries [35]. A study examined cross-language differences in the meaning of 27 JCQ items and their impact on the scale mean values from five European countries. Despite the very similar factor structure among the samples, 36–39% of the total tested items showed cross-language DIF. The study findings suggested that cross-language differences, from translation or from cultural norms, at least among European languages, should be considered in any international comparative study using JCQ scales [7]. In a Greek study, the JCQ scale was modified in accordance with cultural differences, after which the structure of the GJCQ was slightly different from that of the original scale. However, the results revealed that the GJCQ had satisfactory reliability and validity among Greek health workers and could be safely used as a measure of psychosocial characteristics in the workplace [30].

Taken together, the findings discussed above suggest that it is necessary and feasible to make appropriate cross-cultural adjustments to the original JCQ questionnaire to improve its applicability for target populations in various countries. In the current study, we adjusted and optimized the JCQ-22, which is widely used in China, according to cultural adaptation, to construct the JCQ-CCA and included social support in the comprehensive assessment of occupational stress [44]. The results revealed that the JCQ-CCA had better structural validity and outcome relevance and was more in line with Chinese cultural understanding habits. We found that it was beneficial to reduce the information collection bias caused by understanding deviations and that the adjusted measure was more convenient for population-based studies and health monitoring. In addition, the results verified that when the structure of the two domains of the scale (job demands and control) were more balanced by deleting redundant items, the multiplicative effect assumption had a stronger correlation with occupational stress health outcomes than the additive effect assumption [41]. The debugging path of evaluation and structure optimization used in the current study may provide a useful reference methodology and inform the future development of an original, modular and concise Chinese occupational stress questionnaire.

4.1 Limitations of the study

This study had some limitations. First, this study mainly adopted a cross-sectional survey. Because exposure and influencing factors existed at the same time, it was difficult to determine the exact causal relationship. Prospective research could be used in the follow-up research [45]. Second, in the selection of subjects, the cluster sampling was adopted. The subjects came from the health examination population in different fixed institutions for a period of time. Although the implementation of the study was reliable, it may lead to certain sampling errors [46]. Finally, because occupational stress and its health effects, such as insomnia and conscious symptoms, were related to psychological factors, there may be some same-source bias. Through the comparison and inspection of different questionnaires, we found that there were few items that may produce same-source bias, and there was no high correlation between the scales, with limited homology [47].

5 Conclusions

The JCQ-CCA was constructed by cultural adaptation and optimization according to Chinese language and thinking habits, following the JCQ-22. The adjusted scale performed better than the original scale in terms of structural goodness of fit and had fewer items, providing a useful reference for the development of a new Chinese occupational stress scale.

In the current study, the JCQ-CCA exhibited better correlations and prediction effects on occupational stress-related health outcomes (insomnia and self-conscious symptoms) compared with the original scale. In addition, assessment with the JCQ-CCA was more in line with the complex objective reality of the occurrence and development of occupational stress.

The debugging path of structural optimization and questionnaire comparison adopted in this study provided a better methodological reference for different countries to debug or develop occupational stress questionnaires that are more suitable for their own culture. At the same time, based on the overall physical and mental health of workers, in the future, it can be considered to comprehensively analyze the questionnaire measurement results of occupational stress and its health-related effects (insomnia, self-conscious symptoms, etc.) to build a stress-related health risk index to predict the stress-related health risks of workers.

Ethical approval

This study was approved by the Ethics Committee of West China School of Public Health, Sichuan University (No. 201503100012).

Informed consent

Informed consent was obtained from all participants in this study.

Conflict of interest

The authors declare no conflict of interest.

Footnotes

Acknowledgments

The authors would like to thank all participants in this study, as well as those who provided help.

Funding

This study was supported by the Scientific Research Fund for Young Teachers of Sichuan University (No. 2015SCU11009), the Scientific Research Project of Health Commission of Sichuan Province (No. 17PJ451) and the Scientific Research Project of Department of Education of Sichuan Province (No. 17ZB0247).

References

, Tan

, Zhao

. The association between occupational stress and psychosomatic wellbeing among Chinese nurses: A cross-sectional survey. Medicine. 2019;98(22).

Huang

, Wang

. Prevalence of mental disorders in China: A cross-sectional epidemiological study. Lancet Psychiatry. 2019;6(3):211–24.

Chien

T-W

, Lai

W-P

, Wang

H-Y

, Hsu

S-Y

, Vasquez Castillo

, Guo

H-R

, Chen

, Su

. Applying the revised Chinese Job Content Questionnaire to assess psychosocial work conditions among Taiwan’s hospital workers. BMC Public Health. 2011;11(1):1–8.

Amin

, Quek

, Oxley

, Noah

, Nordin

. Validity and reliability of Malay version of the Job Content Questionnaire among public hospital female nurses in Malaysia. Int J Occup Environ Med. 2015;6(4):232–42.

Xin

, Gu

, Gao

. Job strain and hypertension risk in Capital Steel and Iron Company in Beijing. Zhonghua Yi Xue Za Zhi. 2001;81(18):1110–2.

, Yang

, Liu

, Xu

, Cho

. Psychometric evaluation of the Chinese (Mainland) version of Job Content Questionnaire: A study in university hospitals. Ind Health. 2004;42(2):260–7.

Jiang

, Wu

, Hu

, Chen

, Liu

, Zhou

, Chen

, Xu

. Association for combined exposure to job strain, shift work on mental health among Chinese railway workers: A cross-sectional study. BMJ Open. 2020;10(10):e037544.

Sasaki

, Imamura

, Watanabe

, Huong

, Kuribayashi

, Sakuraya

, Thu

, Quynh

, Kien

, Nga

, Giang

. Validation of the Job Content Questionnaire among hospital nurses in Vietnam. J Occup Health. 2020;62(1):e12086.

Kristensen

. Job stress and cardiovascular disease: A theoretic critical review. J Occup Health Psych. 1996;1(3):246–60.

10.

Cheng

, Luh

, Guo

. Reliability and validity of the Chinese Version of the Job Content Questionnaire in Taiwanese workers. Int J Behav Med. 2003;10(1):15–30.

11.

Sha

, Liu

, Li

, Na

. The validation of Chinese Version of Job Content Questionnaire in Health Professionals. Chin Occup Med. 2003;30(3):24–7.

12.

Kploanyi

, Dwomoh

, Dzodzomenyo

. The effect of occupational stress on depression and insomnia: A cross-sectional study among employees in a Ghanaian telecommunication company. BMC Public Health. 2020;20(1):1–10.

13.

Chylova

, Nezkusilova

. Occupational stress in risk professions: Personal resources as mediators of anxiety and depression. Ceskoslovenska Psychologie. 2020;64(4):421–36.

14.

Kim

S-Y

, Shin

Y-C

, Oh

K-S

, Shin

D-W

, Lim

W-J

, Kim

E-J

, Cho

, Jeon

. The association of occupational stress and sleep duration with anxiety symptoms among healthy employees: A cohort study. Stress Health. 2020;36(5):675–85.

15.

Shen

Yang

, Jiang

Ying

, Na

He-ya

, et al. Occupational stress and its influencing factors among working populations in four cities, China. Chin J Public Health. 2018;34(2):199–203.

16.

Sha

Yan

, Liu

Ping

, Li

Jian

, et al. The validation of Chinese Version of Job Content Questionnaire in Health Professionals. China Occupational Medicine. 2003;30(3):24–27.

17.

Ikeda

, Eguchi

, Hiro

, Mafune

, Koga

, Nishimura

, Nakashima

. Work-family spillover, job demand, job control, and workplace social support affect the mental health of home-visit nursing staff. J UOEH. 2021;43(1):51–60.

18.

Santavirta

. Construct validity and reliability of the Finnish version of the Demand-Control Questionnaire in two Samples of teachers and 630 nurses. Educ Psychol. 2003;23(4):423–36.

19.

Sierra

, Guillen-Serrano

, Santos-Iglesias

. Insomnia severity index: Some indicators about its reliability and validity on an older adults sample. Revista De Neurologia. 2008;47(11):566–70.

20.

Chen

, Lin

, Pan

, Zeng

, Zhang

, Hu

, Yu

, Wu

. Insomnia partially mediates the relationship between pathological personality traits and depression: A case-control study. PeerJ. 2021;9:e11061.

21.

Yun

, Choi

. Effects of emotional labor, job stress and burnout on somatization in nurses: In convergence era. J Digital Convergence. 2015;13(10):415–24.

22.

Kim

, Jang

S-N

. The relationship between job stress, job satisfaction, and the Symptom Checklist-90-Revision (SCL-90-R) in marine officers on board. J Prev Med Public Health. 2016;49(6):376–85.

23.

Sapini-Vilus

, Cotter

. Does a brief mindfulness-based stress reduction program have an effect on job stress, depression, and anxiety on staff of an acute care behavior health unit? Nurs Res. 2019;68(2):E176–E7.

24.

Liu

, Spector

, Liu

, Shi

. The Interaction of Job Autonomy and Conflict with Supervisor in China and the United States: A Qualitative and Quantitative Comparison. Int J Stress Manage. 2011;18(3):222–45.

25.

Wang

, Jiang

, Mao

. Job Autonomy and Turnover Intention among Social Workers in China: Roles of Work-to-family Enrichment, Job Satisfaction and Type of Sector. J Soc Serv Res. 2020;46(6):862–76.

26.

Park

, Kawata

, Hirosawa

, Hwang

. Relationships between tenure in the company, job stress, social support, job satisfaction and life satisfaction through comparison with Japan and South Korea office workers. Int J Psychol. 2016;51:77–8.

27.

Lambert

, Minor

, Wells

, Hogan

. Social support’s relationship to correctional staff job stress, job involvement, job satisfaction, and organizational commitment. Soc Sci J. 2016;53(1):22–32.

28.

Haeusser

, Mojzisch

, Niesel

, Schulz-Hardt

. Ten years on: A review of recent research on the Job Demand-Control (-Support) model and psychological well-being. Work Stress. 2010;24(1):1–35.

29.

Vastamaki

, Vastamaki

, Laimi

, Saltychev

. Confirmatory factor analysis of the Finnish Job Content Questionnaire (JCQ) in 590 professional musicians. Int J Occup Env Med. 2017;8(3):174–80.

30.

Alexopoulos

, Argyriou

, Bourna

, Bakoyannis

. Reliability and validity of the Greek Version of the Job Content Questionnaire in Greek Health Care Workers. Saf Health Work. 2015;6(3):233–9.

31.

Schmidt

, Scheiter

, Neubauer

, Sieverding

. Demands, decision latitude, and stress among university students: Findings on reliability and validity of a questionnaire on structural conditions (StrukStud) based on the Job Content Questionnaire. Diagnostica. 2019;65(2):63–74.

32.

Kaewanuchit

, Sawangdee

. A path model of job stress using Thai Job Content Questionnaire (Thai-JCQ) among Thai immigrant employees at the central region of Thailand. Iran J Public Health. 2016;45(8):1020–8.

33.

Guerra Mutro

, Spiri

, Monti Juliani

CMC

, Mangini Bocchi

, Bernardes

, Trettene

ADS

. Adaptation and validation of the Brazilian Portuguese version of the Leader Empowering Behavior scale. Rev Bras Enferm. 2020;73(5).

34.

Barzideh

, Choobineh

, Tabatabaee

. Job stress dimensions and their relationship to musculoskeletal disorders in Iranian nurses. Work-a Journal of Prevention Assessment & Rehabilitation. 2014;47(4):423–9.

35.

Choi

, Bjorner

, Ostergren

P-O

, Clays

, Houtman

, Punnett

, Rosengren

, De Bacquer

, Ferrario

, Bilau

, Karasek

. Cross-language differential item functioning of the Job Content Questionnaire among European countries: The JACE Study. Int J Behav Med. 2009;16(2):136–47.

36.

Mbada

, Awokoya

, Oyewole

, Idowu

, Akinsulore

, Fatoye

, Oke

, Fatoye

. Translation, cross-cultural adaptation and psychometric evaluation of Yoruba version of the Short-Form 12 Health Survey. Ann Ig. 2021;33(3):254–67.

37.

Eum

K-D

, Li

, Jhun

H-J

, Park

J-T

, Tak

S-W

, Karasek

, Cho

. Psychometric properties of the Korean version of the job content questionnaire: Data from health care workers. Int Arch Occup Environ Health. 2007;80(6):497–504.

38.

Kanaan

, Khraise

, Almhdawi

, Natour

, Oteir

, Mansour

. Arabic translation, cross-cultural adaptation, and psychometric properties of the low back pain knowledge questionnaire. Physiother Theor Pr. 2021;23:1–11.

39.

Wagner

, Gandek

, Aaronson

, Acquadro

, Alonso

, Apolone

, Bullinger

, Bjorner

, Fukuhara

, Kaasa

, Leplège

. Cross-cultural comparisons of the content of SF-36 translations across 10 countries: Results from the IQOLA project. J Clin Epidemiol. 1998;51(11):925–32.

40.

Bader

, Jobst

, Zettler

, Hilbig

, Moshagen

. Disentangling the effects of culture and language on measurement noninvariance in cross-cultural research: The culture, comprehension, and translation bias (CCT) procedure. Psychol Assess. 2021;33(5):375–84.

41.

Petersen

, Groenvold

, Bjorner

, Aaronson

, Conroy

, Cull

, Fayers

, Hjermstad

, Sprangers

, Sullivan

. Use of differential item functioning analysis to assess the equivalence of translations of a questionnaire. Qual Life Res. 2003;12(4):373–85.

42.

Bernardes Santos

, de Araujo

, Carvalho

, Karasek

. The job content questionnaire in various occupational contexts: applying a latent class model. BMJ Open. 2017;7(5):e013596.

43.

Niedhammer

. Psychometric properties of the French version of the Karasek Job Content Questionnaire: A study of the scales of decision latitude, psychological demands, social support, and physical demands in the GAZEL cohort. Int Arch Occup Environ Health. 2002;75(3):129–44.

44.

Valadez-Torres

, Maldonado-Macias

, Garcia-Alcaraz

, Camacho-Alamilla

, Avelar-Sosa

, Balderrama-Armendariz

. Analysis of burnout syndrome, musculoskeletal complaints, and job content in middle and senior managers: Case study of manufacturing industries in Ciudad Juarez, Mexico. Work-a Journal of Prevention Assessment & Rehabilitation. 2017;58(4):549–65.

45.

Lopez-De-Uralde-Villanueva

, Notario-Perez

, del Corral

, Ramos-Diaz

, Acuyo-Osorio

, La Touche

. Functional limitations and associated psychological factors in military personnel with chronic nonspecific neck pain with higher levels of kinesiophobia. Work-a Journal of Prevention Assessment & Rehabilitation. 2017;58(3):287–97.

46.

Chung

RYN

, Liao

, Fong

. Data Collection for Migrant Live-In Domestic Workers: A Three-Stage Cluster Sampling Method. American Behavioral Scientist. 2020;64(6):709–21.

47.

George

, Pandey

. We Know the Yin-But Where Is the Yang? Toward a Balanced Approach on Common Source Bias in Public Administration Scholarship. Rev Public Pers Adm. 2017;37(2):245–70.