Abstract
Background and Purpose. Workers with musculoskeletal symptoms are often advised to cope with their symptoms by changing their working technique and by using lifting equipment. The main objective of this study was to test the hypothesis that negative social and organizational factors where people are employed may prevent workers from implementing these coping strategies. Subjects and Methods. A total of 1,567 automobile garage workers (72%) returned a questionnaire concerning coping with musculoskeletal symptoms and social and organizational factors. Results. When job demands, decision authority, social support, and management support related to health, environment, and safety (HES) were used as predictor variables in a multiple regression model, coping as the outcome variable was correlated with decision authority, social support, and HES-related management support (standardized beta=.079, .12, and .13, respectively). When an index for health-related support and control was added to the model, it correlated with coping (standardized beta=.36), whereas the other relationships disappeared. Discussion and Conclusion. Decision authority and social support entail health-related support and control that, in turn, influences coping.
- Automobile
- Back school
- Coping
- Musculoskeletal symptoms
- Psychosocial
- Work
In industrialized countries, musculoskeletal disorders account for a large number of workers' compensation days and disability. The multifactorial cause of musculoskeletal disorders is widely recognized, and attention has been focused by several researchers on the individual, physical, and psychosocial factors that may contribute to the development of these symptoms.1–10 Some studies1,11–13 have shown that social and organizational factors at work such as a high workload and pacing (tempo or speed) and lack of social support are associated with musculoskeletal symptoms. These factors may also be important to other workers such as automobile mechanics.14,15 In addition to social and organizational factors, several ergonomic factors such as awkward working positions, holding of loads, and task invariability are regarded as important risk factors for musculoskeletal symptoms.2,3 Workers in automobile repair garages often have to assume and maintain awkward working positions,14,16 and this may be one reason why musculoskeletal symptoms are common among this group.14,15,17,18
Workers performing strenuous work are often advised to prevent problems and to cope with musculoskeletal symptoms by changing their working technique, using lifting equipment, taking breaks, and avoiding strenuous work tasks.19–21 They have also been encouraged to discuss problems and interventions related to health and work environment with their colleagues and management.20,22 It is common to group strategies for coping into emotion-focused or problem-focused strategies.23–25 The strategies for coping with musculoskeletal symptoms that involve changes in movement may be regarded, in our opinion, as problem-focused strategies. Reviews of stress research24,26 have concluded that coping behaviors influence health. The use of different strategies may be determined by social and organizational factors27–31 or personal attributes and skills.23,26,32–34 Karasek and Theorell's35 job demands-control-support model predicts that jobs with high mental demands and with high decision latitude or control or high social support, called “active jobs,” lead to learning, motivation, and workers who are more active. We believe that workers in active jobs may be more likely than those in passive jobs to try to change the working environment and physical workload by using problem-focused strategies.
The results of a study by Torp et al31 indicated that workers in active jobs use more problem-focused coping strategies when experiencing musculoskeletal symptoms compared with workers in passive jobs (ie, jobs with low demands and low control). In that study, control and social support were not defined in the manner used by Karasek and Theorell35 but were defined as existing when opportunities to perform different kinds of pain-and strain-reducing actions occurred while the worker experienced musculoskeletal symptoms. The opportunity to reduce pace, for example, was defined in our study as “control,” and the opportunity to get help for strenuous work tasks was defined as “social support.”
We wanted to replicate the study by Torp et al,31 but we wanted to use predictor measures not so closely related to having musculoskeletal symptoms as the measures used in that study. Therefore, the objective of our study was to examine the relationships between social and organizational factors at work and the strategies of workers in automobile garages (ie, automobile mechanics, workers repairing automobiles damaged by collision, sprayers) for coping with musculoskeletal symptoms while they were at work. Coping, as the outcome variable, was measured by a revised version of the index used by Torp et al.31 Questions from the Swedish version of the Job Content Questionnaire (JCQ) were used to measure demands, control, and social support.36,37 Two other indexes were constructed for measuring management support related to health, environment, and safety (HES) and health-related support and control. In addition, to test the relationships between social and organizational factors and coping, we investigated the reliability and validity of measurements obtained with all of the different indexes.
Material and Methods
Study Population and Data Collection
A cross-sectional study was performed. A questionnaire was sent to 2,174 workers in 237 automobile garages in Norway. All of the garages were members of the Norwegian Association of Motorcar Dealers and Service Organization. Workers from 122 garages participated in a course for managers regarding how to organize the health and safety activities in the workplace in small and medium-sized companies. The purpose of health and safety activities is to reduce occupational injuries and diseases. As part of an intervention project, another 115 “control” garages were selected from the association's list of members. All of the workers at the garages, except for warehouse and office workers, were asked to answer a questionnaire before the interventions and at the end of the interventions 1 year later. Data obtained initially were used in this study to investigate the relationships between the variables. To evaluate the 1-year stability of the variables, data from the second study were also used.
The participation rate was 72% (n=1,567). The average age was 34 years (SD=11, range=18–66), the mean period of employment in the current occupation was 13 years (SD=10.2, range=0–46), and 98% of the participants were men. Seventy-seven percent of the participants were employed as mechanics, workers repairing automobiles damaged by collision, or paint sprayers; 17% were supervisors or foremen; and 13% had other work tasks (such as vulcanization or auto electricity work). Some respondents reported more than one occupation. The supervisors and foremen were included because many of them repair cars in addition to their supervisory work. The workers gave their consent for participating in the study by filling out the questionnaire. In a letter accompanying the questionnaire, they were informed that participation was voluntary.
Measures
The theoretical model of our study was developed from the job demands-control-support model described by Karasek and Theorell.35 The items that form the predictor variables (ie, job demands, decision authority, and social support) were collected from a Norwegian translation of the Swedish version of the Job Content Questionnaire (JCQ).36,37 For all of the predictor variables, the responses were graded on a 7-point scale ranging from 1 (“do not agree”) to 7 (“agree”). The scores were summarized, and a higher total score on the indexes indicated more job demands, better decision authority, more social support, more HES-related management support, and more health-related support and control. No missing substitution was performed for the indexes in this study. All of the indexes and items are presented in Table 1. The participants were also asked about their age, gender, profession, and years of employment in their current profession.
Outline of Indexes and Items
The job demands index in the Swedish version of the JCQ consists of 5 items.36 We chose to use the 2 items that we believed best measured job demands for workers in garages. According to Karasek,37 control or decision latitude is a composite of 2 related, but theoretically distinct, constructs: the worker's authority to make decisions on the job (decision authority) and the breadth of skills used by the worker on the job (skill discretion). We chose to use the 2 questions in the Swedish version of the JCQ that purport to measure decision authority. The 4 questions for measuring job demands and decision authority in this study were changed from questions to statements, as in the American version of the JCQ37 and in the Swedish version for measuring social support.36
The response scale was changed from the original 4-point scale to a 7-point scale. Social support was measured by the 6 statements used in the Swedish version. This response scale also was changed from the 4-point scale to a 7-point scale. The questions were changed to statements to better fit the style of the rest of the questionnaire. The response scale was changed to a more graded scale so that changes could be detected more efficiently in a prospective study.
We constructed the 9-item index for HES-related management support for this study based on our knowledge and experience gained in preventive work in occupational health services. We excluded 2 items of the index that originally were meant to measure HES-related management support because they reduced the internal consistency (Cronbach alpha). These 2 items measure different underlying concepts, and the interpretation of the results involving this index would have been difficult if these 2 items had been kept in the index. We also constructed the 3-item index measuring health-related support and control for this study. These 2 predictor variables were included in the study because we regarded them as resources more closely related to coping with physical strain and musculoskeletal symptoms than control and social support as defined by Karasek and Theorell.35
Coping strategies (the outcome variable) were measured by an index of 10 items (Tab. 1). We asked the workers what they did when they experienced bodily pain or stiffness that troubled them at work for days or weeks. The workers responded to this item either by answering that the item was of no relevance because they never had bodily pain or stiffness that troubled them at work or by giving their response to whether or not they used the 10 different coping strategies (Tab. 1). The responses were graded from 1 (“never”) to 7 (“often”). The scores were summarized, and a higher total score indicated a more active way of coping with musculoskeletal symptoms. The items have all been used in other studies on coping with musculoskeletal symptoms.30,31 The original index contained 11 items, but we excluded 1 item because it reduced the internal consistency (Cronbach alpha).
Data Analysis
When constructing indexes, we believe it is important that the individual items included in the index reflect a common underlying construct if they are supposed to reflect only one construct. To test this internal consistency of the different indexes in our study, Cronbach alpha values were calculated. A high alpha value (eg, α=.70–.90) indicates that the different items measure different aspects of the same construct. The alpha value, in our opinion, should not be too high, because we believe the items then measure the same element and therefore fewer items probably would suffice. The 1-year stability was measured using Pearson correlation coefficients between scores obtained at the 1-year interval. Because the mean scores of the indexes were very similar, this indicated to us no systematic change in the scoring. Exploratory factor analysis was used to assess the factorial structure of the instrument. A Kaiser Varimax rotation served to extract the factors. A Pearson correlation analysis was performed to test correlations among all of the variables. This analysis was done to investigate the nature of the relationships between the indexes and the background variables and the relationships among the predictor variables. A multiple regression analysis was used to investigate the relationships between the outcome variable (coping with musculoskeletal symptoms) and the predictor variables (social support, control, job demands, HES-related management support, and health-related support and control). The level of significance was set at .05. The analysis was performed using the SPSS 7.5.1 computer package.38,*
Results
The values of internal consistency (Cronbach alpha) for all of the indexes are presented in Table 1. Of the 6 indexes, 5 had alpha values between .76 and .90. The 2 items measuring job demands showed low internal consistency, with an alpha value of .32. The following 2 items were deleted from the original HES-related management support index because they reduced the index's internal consistency: (1) “It is difficult to get acceptance for proposals to improve the working environment” and (2) “Proposing improvements to the working environment can adversely affect my relationship with management.” The item “Doing physical exercise during work” was excluded from the original coping index for the same reason. The correlations of the 1-year stability test are also presented in Table 1. Job demands showed the lowest correlation (r=.47), and HES-related management support showed the highest correlation (r=.66). No systematic differences could be seen between the group of workers who answered only the first questionnaire and the group of workers who answered both the first and second questionnaires.
A principal components analysis with Kaiser Varimax rotation was carried out on the single items used in the predictor variables (Tab. 2). The analysis yielded 5 factors with eigenvalues of ≥1.0. These factors accounted for 64.5% of the variance. By including all variables with rotated factor loadings higher than .40, a structure of factors emerged that fit well with the 5 theoretically constructed factors: social support, decision authority, job demands, HES-related management support, and health-related support and control.
Factor Loadings in a Principal Components Analysis (Kaiser Varimax Rotation) on the Single Items of the Predictor Variablesa
Table 3 shows the results of a correlation analysis including both the outcome variable and the predictor variables. Age, years in the current profession, and gender are also included. Except for job demands, there were positive correlations among all the predictor variables. There were negative correlations between job demands and the other predictor variables. The correlations among social support, HES-related management support, and health-related support and control were relatively high (r=.54–.59).
Pearson Correlations Among Variables (n=1,567)a
There were correlations between an active way of coping and both low demands/high decision authority and high social support. Younger workers regarded their work environment as less strenuous and slightly more supportive than the older workers did, whereas the older workers reported more decision authority at work. There were no correlations between coping with musculoskeletal symptoms and age, years in the current profession, and gender.
Of the 1,567 workers, 352 (22%) reported that they never experienced bodily pain or stiffness that troubled them at work. Coping with musculoskeletal symptoms was measured among the remaining 1,215 workers. The coping strategies “ask colleagues for help,” “change working technique,” and “use equipment to reduce physical strain” were used most often among the workers (average scores=5.6, 5.5, and 5.1, respectively). “Discuss the problems with the health and safety deputy,” “work on tasks that are less strenuous,” and “take more or longer breaks” were the least used strategies (average scores=2.8, 2.8, and 2.9, respectively).
Because the social and organizational factors thought to influence the workers' coping strategies were intercor-related, we used a multiple regression analysis to examine this relationship (Tab. 4). In such a multivariate analysis, the effect of each of the independent variables, the social and organizational factors, is adjusted for the effects of the other variables. To test the job demands-control-support model, we first included the variables job demands, decision authority, and social support as independent variables (model 1). This analysis showed relationships between an active use of coping strategies and high social support and high decision authority, with standardized beta values of .18 and .10. These standardized beta values measure the correlation between each of the single predictors and the coping variable.
Multiple Regression Analysis With Coping as Outcome Variable and Job Demands; Decision Authority; Social Support, Health, Environment, and Safety (HES)–Related Management Support; and Health-Related Control and Support as Predictor Variables (n=1,215)a
The relationship between low job demands and coping that was shown in the bivariate correlation analysis (Tab. 3) disappeared when the 3 variables were added simultaneously to the regression model. Interactions among the 3 variables were tested by adding multiplicative terms of the respective variables in the regression model. None of these interaction terms were significant. When HES-related management support was added to the model (model 2), this variable also showed a positive relationship with coping, with a standardized beta value of .13. The relationships between coping and the 2 predictor variables decision authority and social support were slightly reduced, but still significant. When health-related support and control was added to the model (model 3), the other positive relationships were reduced to almost nil, whereas health-related support and control correlated relatively well, with a standardized beta value of .36.
The 3 variables of the job demands-control-support model explained 6% of the variation in how the workers coped with their musculoskeletal symptoms (model 1). When HES-related management support was included, the model explained 7% (model 2). Model 3, with health-related support and control as the only significant variable, explained 14%.
Discussion
Reliability and Validity
The factorial validity seems to be satisfactory, as job demands, decision authority, and social support, in addition to the other 2 theoretically proposed predictor variables, were retained. The low correlations among the variables (r=−.11, −.36, and .38, respectively) also support the relative independence of the 3 dimensions. The values for internal consistency (Cronbach alpha) of social support and decision authority were .76 and .90, respectively, which is regarded as satisfactory.39 Other studies on validity and reliability of data obtained with the American and the Swedish versions of the JCQ have shown similar results.35,36,40–46 The job demands index had a low alpha value (α=.32) and, therefore, seems not quite satisfactory for measuring job demands as defined by Karasek and Theorell.35 This index, therefore, might need modification. To our knowledge, the Swedish version of the JCQ has not been tested for 1-year stability. Brisson et al45 evaluated the 1-year stability of a French translation of the American version of the JCQ and found correlations of .59 for decision authority and .65 for job demands. The correlation for decision authority in the study by Brisson et al was similar to the correlation in our study, whereas the correlation for job demands was higher in their study than in our study.
The indexes for HES-related management support and health-related support and control were constructed for this study. The psychometric properties of these indexes (Cronbach alpha, 1-year stability, and factorial validity) were as good as or better than those for job demands, decision authority, and social support in this study. Both variables correlated higher with social support than did decision authority and job demands. We expected this because the 3 variables were meant to measure different kinds of support. The outcome variable (coping with musculoskeletal symptoms at work) was a modification of the index used by Torp et al31 and showed slightly better internal consistency than in that study. The Cron-bach alpha and the 1-year stability of this index were similar to those of the other indexes used in the present study.
Adequate reliability for an instrument depends on the purpose of the measure. According to Stewart et al47 and Helmstadter,48 reliability values between .50 and .60 should suffice for group comparisons such as those in our study. The 1-year stability correlations were in this range, and therefore indicate satisfactory test-retest reliability.
The psychometric properties evaluated here seem satisfactory for all except one of the indexes measured among garage workers. We do not know whether the instrument could be used among other groups of workers. The positive correlations between the predictor variable and the outcome variables were in accordance with what was hypothesized, and this finding strengthens the conclusion that the instrument seems to have validity. Because many workers participated in the study and the response rate was satisfactory, it seems reasonable that the results may be generalized to other workers in organized garages in Norway. Musculoskeletal symptoms are common among many different groups of workers,2,3,49,50 and everyone with work-related musculoskeletal symptoms has to cope with these symptoms in one way or another. We believe that other groups of workers with similar physical work would behave similar to the workers in this study. This study was performed in Norway. Job demands, decision authority, social support, and management support are subjective measures shown to be important for workers' health and coping in several different countries.1,23,25,31,35,44,51 In addition, the validity and reliability of the JCQ have been tested and found to be satisfactory in Europe, America, and Asia.35,36,42–46 Therefore, we believe that the results of this study also can be relevant for workers outside Norway.
Social and Organizational Factors at Work and Coping
The results of our study indicate that decision authority, social support, HES-related management support, and health-related support and control appear to affect how workers in garages cope with their musculoskeletal symptoms. Health-related support and control seems to be the most important factor. Included in this factor was the opportunity to get help from supervisors to reduce workloads and from coworkers to discuss health problems with management and to take necessary breaks when experiencing health problems at work.
The bivariate correlations showed relationships between an active way of coping with musculoskeletal symptoms and low demands/high decision authority, high social support, high HES-related management support, and high health-related support and control. When job demands, decision authority, and social support were added to the regression model, the relationship between coping and job demands disappeared. The job demands-control-support model proposes an interaction effect of the 3 variables on health and motivation.35 No such interaction effects were seen in this study.
The lack of an interaction effect may have been due to too little variation in the variables, because all of the participants had relatively similar work. Nevertheless, other studies40,51,52 have also failed to show the proposed interaction effects. Social support (eg, general support from coworkers and supervisors, team spirit) showed the strongest relationship with how workers coped with their musculoskeletal symptoms. Several authors13,52–55 have emphasized the importance of this factor to both health and coping. The 3 variables accounted for 6% of the variance. A higher R2 value might have been attained if the job demands index had had better psychometric properties and if control had been measured with both decision authority and skill discretion.35,36
When HES-related management support was added to the model, the effect of decision authority and social support on coping was reduced slightly. Nevertheless, decision authority, social support, and HES-related management support had independent effects on the workers' coping. When health-related support and control was added, however, these relationships disappeared. Health-related support and control correlated relatively highly with coping (standardized beta=.36). The model explained a total of 14% of the variance. One possible explanation for why this variable seemed to explain all the other variables' effect on coping could be that decision authority, social support, and HES-related management support entail a feeling of health-related support and control that, in turn, affects how the workers cope with musculoskeletal symptoms. This interpretation is supported by the results found by Torp et al31 on automobile mechanics' coping with musculoskeletal symptoms. In that study, control and social support were defined similarly to how health-related support and control was defined in this study. The variation of job demands, control, and social support explained as much as 31% of the variation in coping with musculoskeletal symptoms. When investigating factors that are important for how patients or workers can cope with musculoskeletal symptoms, it seems to be important to ask specific questions regarding support and control related to having these symptoms, and not only general questions about, for example, team spirit and job satisfaction.
The predictor variables (job demands, decision authority, social support, HES-related management support, and health-related support and control) explained 14% of the variation in coping. Other factors expected to influence coping, such as personality, experience, education, physical work environment, and types of symptoms, were not included in this study. In addition, only garage workers were sampled, which presumably leads to a restriction of variance in the predictor variables. This low variability might lead to an underestimation of the investigated effects. Furthermore, low correlations may still represent substantial effects for the extremes of a population. That is, the use of coping strategies may be markedly limited among the rather few workers experiencing poor psychosocial work environments.
Because of our study's cross-sectional design, firm conclusions about causal relationships between social and organizational factors and coping with musculoskeletal symptoms cannot be drawn. Nevertheless, the findings are consistent with theories35,56 and the results of other studies27,28,30,54,57,58 on relationships between work environment and other types of coping.
Our results indicate that negative social and organizational factors at work may limit the use of problem-focused strategies taught in “back schools” such as changing working technique, using equipment to reduce physical strain, and taking breaks.59 This might explain why Linton and Kamwendo19 and King20 found that back schools have limited effects on the prevalence of musculoskeletal symptoms. Burton et al60 argued that ergonomic interventions to alter physical stress through, for example, back schools and redesigning workstations should be accompanied with psychosocial approaches. Such psychosocial approaches may increase the workers' control over their own work environment, letting the workers participate in planning and organization of their workstation, and may increase managers' understanding of the importance of health and work safety and thus increase the management support. This is in accordance with Westgaard and Winkel,61 who concluded after reviewing 92 intervention studies on the reduction of work-related musculoskeletal symptoms that organizational culture intervention with highly committed stakeholders using multiple interventions to reduce identified risk factors has the best chance of success. Included in the organizational culture interventions were studies emphasizing participatory ergonomics with team building and involving workers to determine or implement ergonomic solutions.
Clinical Implications
We found positive relationships between social and organizational factors at garages in Norway and the workers' use of problem-focused coping strategies when experiencing musculoskeletal symptoms. The implications of such a finding may be that health care professionals who advise workers on coping with musculoskeletal symptoms should investigate the workers' opportunities to perform the suggested activities before they can expect positive results based on their advice. In addition to giving the workers ergonomic training such as back schools, it may also be necessary to improve social and organizational factors at the companies. This can best be done, in our opinion, by increasing the management's knowledge about the impact of the work environment on workers' health and health-related behaviors.
We believe it is important that supervisors discuss health and environmental problems with workers experiencing musculoskeletal symptoms. Then appropriate actions can be taken so that the workers can stay at work despite having pain. Without the management's commitment to health and safety activities, we argue that interventions are not likely to be successful. Problems related to musculoskeletal disorders should be discussed among the workers, and our data indicate that routines for how management and coworkers can help in the rehabilitation of workers with musculoskeletal symptoms should be developed in cooperation between workers and management. In Scandinavia, it is common for physical therapists to work in occupational health services where they mainly deal with primary and secondary prevention of musculoskeletal disorders. Within such a system, it is relatively easy for the physical therapists to combine ergonomic training of individuals and groups of workers with work aiming at improving social and organizational factors. For physical therapists working outside corporate structures, it seems important to us to establish cooperative arrangements with ergonomists, occupational psychologists, and physicians working on health prevention within the companies. In countries where occupational health services do not exist, or do not have direct access to the workers and management, we believe that it is important to establish such services if work-related musculoskeletal symptoms are to be prevented in an efficient way. We believe that these professionals need the expertise of physical therapists in the prevention of musculoskeletal disorders, probably the most costly work-related health problem in the Western world.
Interventions and longitudinal studies are needed to reach firm conclusions on the causal relationships between social and organizational factors and coping with musculoskeletal symptoms. An example of an intervention study could be to randomly assign patients to 2 different groups—one group with an ordinary back school program and another group with the same back school program in addition to an intervention program for supervisors. In this latter program, the supervisors could be taught how to give support to workers with back problems, how to encourage coworker support, and how to increase the workers' possibilities and interest in improving both the physical and psychosocial work environments. In addition to providing information about causal relationships between social and organizational factors and coping, the results of such an intervention study could suggest how physical therapists would get the best clinical results of back schools.
Footnotes
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All authors provided concept/research design, writing, and data analysis. Mr Torp and Dr Moen provided project management and fund procurement. Mr Torp provided data collection, and Dr Moen provided institutional liaisons. Dr Riise and Dr Moen provided consultation (including review of manuscript before submission). Berit Larsen provided clerical support.
This study was approved by the Regional Ethics Committee and by the Data Inspectorate in Norway.
This project was funded by a grant from the Confederation of Norwegian Business and Industry.
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↵* SPSS Inc, 444 N Michigan Ave, Chicago, IL 60611.
- Received February 23, 2000.
- Accepted December 13, 2000.
- Physical Therapy
References
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