Job Stress and Cardiovascular Disease: A Theoretic Critical Review

Transcription

1 Journal of Occupational Health Psychology 1996, Vol. 1, No. 3, Copyright 1996 by the Educational Publishing Foundation /96/S3.00 Job Stress and Cardiovascular Disease: A Theoretic Critical Review Tage S. Kristensen National Institute of Occupational Health During the last 15 years, the research on job stress and cardiovascular diseases has been dominated by the job strain model developed by R. Karasek (1979) and colleagues (R. Karasek & T. Theorell, 1990). In this article the results of this research are briefly summarized, and the theoretical and methodological basis is discussed and criticized. A sociological interpretation of the model emphasizing theories of technological change, qualifications of the workers, and the organization of work is proposed. Furthermore, improvements with regard to measuring the job strain dimensions and to sampling the study base are suggested. Substantial improvements of the job strain research could be achieved if the principle of triangulation were used in the measurements of stressors, stress, and sickness and if occupation-based samples were used instead of large representative samples. Since 1980 the job strain model (Karasek, 1979; Karasek & Theorell, 1990) has completely dominated the empirical research on job stress and cardiovascular diseases. As most readers will know, the model operates with two dimensions: job decision latitude and psychological demands (Figure 1). According to the model, workers exposed to the combination of high psychological job demands and low decision latitude (high job strain) have an increased risk of psychological strain and a number of somatic diseases, notably cardiovascular diseases. The model was introduced by Karasek (1979) and further developed and tested by Karasek and Theorell (1990). Later Johnson and colleagues elaborated the model with a workplace social support dimension (Johnson & Hall, 1988) and developed a job exposure matrix system for studying psychosocial exposures over a life course (Johnson, Hall, Stewart, Fredlund, & Theorell, 1991; Johnson & Stewart, 1993). Today, only about 15 years after the introduction of the job strain model (Karasek, 1979; Karasek & Theorell, 1990), the amount of studies using the model is so overwhelming that a review would be a colossal task for any individual. Job strain has been associated not only with psychological strain and cardiovascular diseases but also with musculoskeletal disorders, diabetes, cancer, psychiatric illness, gastrointestinal illness, occupational and traffic accidents, suicides, total mortality, alcohol-related diseases, absence from work, use of medicine, sleeping problems, depression, reproductive problems, anxi- Correspondence concerning this article should be addressed to Tage S. Kristensen, National Institute of Occupational Health, Lerso Parkalle 105, DK-2100 Copenhagen O, Denmark. Electronic mail may be sent via Internet to amilpost@uts.uni-c.dk. ety, work satisfaction, quality of life, and many more problems (Kristensen, 1995). A number of reviews covering the literature on job strain and cardiovascular diseases have, however, been published (Karasek & Theorell, 1990; Kristensen, 1989a, 1994b, 1995; Landsbergis et al., 1993; Schnall, Landsbergis, & Baker, 1994; Theorell & Karasek, 1996). In these reviews the authors concluded that the large majority of empirical studies support the job strain hypothesis but also that the mechanisms are poorly understood and that a number of methodological and theoretical problems remain to be solved. Since the writing of the above-mentioned reviews, two more empirical studies have been published (Alterman, Shekalle, Vernon, & Burau, 1994; Hammar, Alfredsson, & Theorell, 1994). These two studies both found a rather weak association between job strain and coronary heart disease. It is not the purpose of this article to present another review of the literature on job strain and cardiovascular diseases. In fact, it seems to become increasingly clear that more studies based on representative samples of employees and the measurement of perceived job strain with the Job Content Questionnaire (JCQ; Karasek, 1985) will not contribute substantially to researchers' knowledge in this important field. The well-deserved success of the job strain model has resulted in a large number of "me too" studies using similar or identical methods. It is my belief that a thorough discussion of theoretical and methodological questions is a prerequisite for further progress in this research. In contrast to other critics of the job strain model and literature (Fletcher & Jones, 1993; Muntaner & O'Campo, 1993), my assumption is that the job strain model is a very fruitful basis for further research. In fact, it is the high 246

2 SPECIAL SECTION: STRESS AND CARDIOVASCULAR DISEASE 247 Low Psychological demands High The learning and motivation diagonal High Low strain Active Decision latitude Low Passive quality of the model and the whole literature on job strain that makes it worth criticizing and developing. In the following I first focus on what I consider to be the main problems of the job strain research: the measurement of the basic job strain dimensions and the use of representative samples. I then suggest a sociological interpretation of the job strain model and a methodological framework for future studies. I concentrate on the job strain model because it dominates the thinking in this field today. Other models, such as the effort-reward imbalance model suggested by Siegrist (1996), have so far had a much smaller impact, but many of the points made in the following ought to be relevant for these models as well. It is my hope that readers will find it useful to read this article together with the overview by Kasl (1996) in an earlier issue of this journal. I have avoided topics covered so well by Kasl such as, for example, the topic of interaction and the historic development of the research on job stress and cardiovascular diseases. The Conceptualization and Measurement of Psychosocial Exposures In the job strain literature the basic classification of individuals has been performed in two ways: the Figure!. The job strain model. High strain The strain diagonal subjective or individual method and the job method. These methods are described in detail by Karasek and Theorell (1990) and elsewhere. Briefly, the subjective method is based on the individual person's responses to a number of questions on job demands, decision latitude, and perhaps social support. On the basis of his or her own replies the person is given a scale value on each of the dimensions applied and hence a position in the job strain matrix. According to the job method the respondents or cohort members are classified according to their job. For each job, average values for the job strain dimensions are calculated on the basis of the questionnaire responses of the people reported to have that particular job. (Usually a minimum number, such as five people for each job, has been required to avoid unreliable estimates.) Thus, both of these methods are based on questionnaire data. The two methods have often been called, respectively, the subjective method and objective method. In the following I do not use these concepts because they lead to misunderstandings. I agree completely with Frese and Zapf (1988, p. 377) who wrote, "It is not quite clear what is meant by 'objective' or 'subjective' in the stress field. Indeed, we think that there is some muddled thinking going on in this area." The "muddled thinking" is due to the fact that the terms

3 248 KRISTENSEN objective and subjective may be used in at least three different ways: (a) To describe phenomena. Subjective phenomena are, for example, emotions, attitudes, and thoughts, whereas objective phenomena are things, actions, physical processes, and so forth, (b) To describe methods. Subjective methods are methods that are depending on and influenced by the individual observer, whereas objective methods ideally reach the same results regardless of the researcher's preferences, (c) To describe coherent "knowledge systems. "Objective knowledge is knowledge collected through established scientific methods and acknowledged by the scientific community, whereas examples of the opposite could be myths, ideologies, fallacies, and superstition (Kristensen, 1995). It should be clear from this discussion that the subjective and the objective methods are both objective in the sense that explicit rules and guidelines for measuring job strain exist. In the following the subjective method is called the individual method, and job strain measured with this method is labeled self-rated or perceived job strain. The objective method is called the average method. Both methods have shortcomings and are discussed below. The Individual Method In this article the term stressor is used for any factor in the environment that increases the risk of stress in the exposed individual, and stress is defined as an individual state characterized by a combination of arousal and displeasure. A very powerful tradition in stress research has emphasized that a given factor may be a stressor to one person but not to another, depending on how the factor is perceived and appraised by the individual (Lazarus & Folkman, 1984). Following this line of thought, it has been argued that the "correct" thing to measure is the stressor as it is perceived by the individual. I disagree with this line of thought for several reasons. First, it leads to circular arguments. If one says that "a stressor is not a stressor until it is experienced as such," one is assuming what one should show through research. Second, the very perception and appraisal processes stressed so strongly by Lazarus and others can only be studied if the stressor is measured independently of the exposed individual. By doing so researchers can identify exposed people who report no stressors and unexposed who in spite of that perceive stressors. Third, the notion that people perceive and evaluate a potential stressor introduces a potential "rationalistic" bias in stress research. It should be evident to most scholars in this field that human beings exposed to stressors deny, exaggerate, misinterpret, repress, explain away, and so forth. Fourth, most people are exposed to many stressors and often at the same time. No person exposed to many stressors will be able to perceive and appraise the relative importance of many simultaneous stressors. In the Empirical examples section I demonstrate with a number of empirical examples the importance of measuring stressors independently of the exposed person. Empirical examples. In a recent Danish study of nurses, job strain was measured with the individual method (Andersen, 1995). Approximately 60% of the nurses found the work pace or time pressure "much too high" or "somewhat too high," and about 40% reported that they had trouble doing their work properly because they were too busy. In the discussion following the report it was concluded that the work pressure of the nurses was due to "the public policy of reduction" and that a probable solution would be to hire more nurses. However, a thesis published a few years ago (Vallgarda, 1992) showed that the number of nurses at Danish hospitals had more than doubled during the years and that in the same period the number of medical doctors had more than tripled. During the same 30 years there had been a slight decrease in the number of bed days. This thesis was not very welcome in the medical community because it showed that the rhetoric about drastic cutbacks was false. From a research point of view it should be clear that the perceived high psychological demands of the nurses cannot be properly understood and interpreted unless it is evaluated in the light of the dramatic improvement of the nursetpatient ratio during the last 30 years. The challenge of the hospital sector seems to be that the perceived psychological demands increase as the number of colleagues increases (and not the number of patients). In a Swedish questionnaire study answers to questions concerning workplace exposures were compared for the years 1970 and 1980 (Bolinder, Magnusson, Nilsson, & Rehn, 1981). The two studies used the same questions, and the samples were drawn in the same way. It was found that all workplace exposures had "increased" from 1970 to Examples are noise (41% to 54%), draft (40% to 45%), humidity (9% to 17%), solvents (8% to 21%), and acids (8% to 14%). The proportion who reported stress and psychological demands increased from 31% to 52%. The respondents were also asked whether they thought that the same exposures had

4 SPECIAL SECTION: STRESS AND CARDIOVASCULAR DISEASE 249 changed for better or worse in recent years. The striking result was that all of the exposures were perceived as having changed for the better. For example, 32% thought that the noise level had decreased, whereas only 6% thought that it had increased. According to work environment experts most of the above-mentioned exposures had probably decreased during the 10 years. Hence, researchers have three results for the development during the same period of time. Without going deeper into a discussion of these very interesting findings, it should be clear that the increase in exposures found when comparing the two groups of respondents should not be taken at face value. In the Danish part of the WHO project MONICA (Netterstr0m, Kristensen, Damsgaard, Olsen, & SJ01, 1991), the respondents were classified in the four job strain groups according to the individual as well as the average method (Netterstr0m et al., 1991). It was a striking finding that respondents with a given job such as nurse, policeman, cleaner, or teacher could be found in all four of the perceived job strain groups. When comparing the number of high-strain people identified through the two methods, it was found that 101 people had high job strain according to the individual method and 209 according to the average method. Only 38 people were identified as being in high-strain jobs by using both methods. Clearly, such a low degree of correspondence indicates serious validity problems. In the study of Danish slaughterhouse workers 81 very precise job titles were identified (Kristensen, 1991, 1994a). All workers with the same job title worked under exactly the same conditions with regard to temperature, noise, work pace, salary system, degree of repetitiveness, technology, ergonomic conditions, and so forth. This situation provided a unique opportunity for studying the workers' questionnaire answers with regard to psychosocial working conditions. To evaluate a possible information bias, I compared the workers who answered yes to a question about perceived stress with the workers who answered no. This was done for 10 specific jobs with very high degrees of homogeneity and with at least 59 respondents. Some of the main results are shown in Table 1. The table shows that workers who reported the symptom "stress" also reported the work pace to be "much too fast" more than twice as often as workers without perceived stress. For "monotonous work" the prevalence was 24% higher among workers with stress than among workers without stress while the differences were smaller for the remaining questions in the table. The table shows two Table 1 Psychosocial Exposures Among Male Slaughterhouse Workers in 10 Specific Jobs Question and response Median prevalence ratios How is the normal work pace? Much too fast 2.08 Is your work varied or monotonous? Rather-very monotonous 1.24 Are you exposed to cold at work? Yes 1.17 If you need to go on a private errand can you then leave your work for half an hour without special permission? No 1.08 How much influence do you have on how you do your work? Very little-no influence 1.07 Can you more or less decide when to have breaks during work? No 1.04 Note. Prevalence of reporting psychosocial exposures in workers who report the symptom stress compared with workers who do not report stress. N = 1,355 ( workers in each job). important findings: There was a tendency toward positive information bias for all of the questions, but the strength of this tendency varied considerably from item to item. The strongest bias was found with the demand question about work pace, and the lowest with the decision latitude question about breaks during work. It should, however, be borne in mind that the small tendency toward bias in each of the decision latitude questions was added up when a scale value for decision latitude was calculated. The analyses shown in Table 1 were repeated for other symptoms, and the picture was clear: When analyzing workers with identical exposures, workers with psychic or somatic symptoms reported significantly more exposures than workers without symptoms. The four examples given here illustrate that job strain research based exclusively on perceived job strain will be inconclusive and possibly seriously biased. This does not imply that perceived job strain should be abandoned in research but only that this measure cannot stand alone. I return to the question of supplementary methods. The triviality trap. Kasl (1987) wrote, The sheer volume of studies which has been generated by cross-sectional retrospective designs, in which only self-reports of independent, intervening, and outcome variables are correlated to each other, is so enormous that they have created their own standard of "acceptable" methodology. Journal editors (presumably quite

5 250 KRISTENSEN aware of methodological limitations) may be reluctant to put a moratorium on a methodology which was "acceptable" only yesterday, (p. 308). Only 1 year later in their essay on methodological issues in stress research Frese and Zapf (1988) wrote, The methodological reasons for using objective measures are intimately related to the problem that trivial correlations could occur between subjective stress measures and ill-health either because of method variance or because there is an overlap between the items in terms of content. Only objective measures lead the way out of this triviality trap. (p. 377). This means that associations between perceived job stressors and self-reported symptoms or conditions such as stress, fatigue, depression, heart symptoms, or illness behaviors should not be interpreted as associations between work and health. Rather, these associations show that people who report symptoms have higher probability of reporting exposures than people who do not report symptoms. Seen as associations, they are trivial. They only convey information when they are not present. In this case, there probably is a measurement problem. An example illustrates that the triviality trap is still topical. In a recent cross-sectional study of job strain and health-related quality of life (HRQL; Lerner, Levine, Malspesis, & D'Agostino, 1994), job strain was measured with the JCQ, and HRQL with the Short Form 36 Questionnaire (SF-36; Ware, 1993). For all the nine subscales of the SF-36, associations between high job strain and low HRQL were found. These "trivial correlations" were reported as the main findings. Moreover, Lerner et al. wrote, "Mean SF-36 scores were consistently lowest among workers in the high-strain jobs" (p. 1582). This is, in my opinion, a biased way of presenting the results. In fact, the jobs of these people were not included in the analyses, only a number of perceived job stressors. A more correct way of reporting this would be that workers who reported high job strain also reported low HRQL. The authors also wrote, "Job strain had its largest impact on mental health" (p. 1582). In other words, Lerner et al. assumed that the associations found are causal. In studies such as those indicated above, three errors were made: (a) Associations between selfreported exposures and symptoms were regarded as associations between work and well-being or health (the triviality trap), (b) perceived job strain was regarded as a job exposure, and (c) statistical associations were regarded as causal. In this way a study of a number of self-reported phenomena in a population sample is transformed into an etiological study of workplace exposures and health outcomes. It should be emphasized that this study is by no means unique. Studies using the same methods and making the same methodological errors are still being published in the best journals. It is often assumed that the triviality trap is only a problem in cross-sectional and retrospective studies. This is, however, not the case. If a prospective study has bias in the measurement of baseline exposures, this bias will follow the study for the rest of its days. The problem with bias is that it cannot be controlled for in the design or analyses. It is very likely that people with poor well-being or with a subclinical disease overreport psychosocial exposures and that other respondents underreport, and there is no way of controlling for this differential misclassification. One could of course control for psychological well-being or other similar measures at baseline, but such procedures probably would bias the results in the opposite direction by controlling for intermediate variables. The only way to identify over- and underreporters is to have independent measures of the exposures. Other methodological problems. A few other methodological problems in connection with the individual method deserve to be mentioned. They have to do with the individual questions in the questionnaires used and with the international translation procedures. With regard to the questions, the JCQ (Karasek, 1985) operates with response categories of the type strongly agree, agree, disagree, and strongly disagree. Thus, the response categories are worded as opinions or attitudes. In the Whitehall II Study (Marmot et al., 1991), the categories often, sometimes, seldom, and never/almost never were used for the job strain questions, and similar options were used in a number of Swedish studies such as the wolf and sheep studies (in progress). In these studies it was the duration of exposure that was measured. In the Danish slaughterhouse study and in other Danish studies the response categories indicated differences in the intensity of exposure, for example, great influence, some influence, very little influence, no influence or much too fast, a little too fast, just right, a little too slow, and much too slow (Kristensen, 1994a). According to most writers in this field the optimal way of measuring stressors is to measure frequency and duration as well as intensity (see, for example, Dewe, 1991). It therefore presents a major problem that the most widely used questionnaire is unclear on this point and that other questionnaires only attempt to measure one aspect of the exposures. To my knowledge no researchers have tried to compare and

6 SPECIAL SECTION: STRESS AND CARDIOVASCULAR DISEASE 251 evaluate these different methods; such studies are badly needed. Another problem is the translation procedure when questionnaires are used in many cultures and countries. It is well known that translations and adaptions of questionnaires for use in other cultures are long and very resource-demanding processes (see, e.g., Ware et al., in press, about the translation procedure used for the SF-36 questionnaire). An example from the Danish version of the JCQ (Karasek, 1985) shows what the result can be when such procedures are not followed. One question reads as follows (in my backward translation): "Question: You are not asked to perform an unreasonable amount of work. Answer: Agree very much, agree, disagree, disagree very much." In this case there are two negations in the question and one possible negation in the response categories, which is a violation of one of the most basic rules of questionnaire construction. As far as I know no international translation validation studies have been performed with the many national versions of the JCQ. The Job Method The job method, according to which all respondents in a given occupation are classified as being exposed to the same degree of job strain, solves a number of the problems mentioned above but introduces some new problems. The main problem is that a classification based on national job coding systems or other similar systems will result in jobs that are much too heterogeneous. A few examples will illustrate the magnitude of the problem. In Netterstr0m's study (Netterstr0m & Juel, 1988) of busdrivers the cohort of busdrivers was divided into drivers on high- versus low-traffic intensity routes. The analyses showed relative risks for acute myocardial infarction of 6.2 for high-traffic intensity drivers in the Copenhagen area and 4.4 for provincial towns when compared with the drivers in lowintensity areas. In a job classification these groups of bus drivers with dramatically different acute myocardial infarction risks would have been grouped together as having the same job strain. A similar difference in acute myocardial infarction risk between central and peripheral routes has been found in several other countries as well. In a Belgian study of bank clerks Kornitzer, Kittel, and colleagues (Kittel, Kornitzer, & Dramaix, 1980; Kornitzer, Dramaix, & Gheyssens, 1979) compared the incidence of acute mycocardial infarcation among employees from a private bank with a semipublic savings bank. The two cohorts lived in the same geographical area and were very similar in other respects. The relative risk of acute myocardial infarction was 2.1 for 5 years of follow-up and 1.7 for 10 years of follow-up when the private bank employees were compared with the employees in the savings bank. This difference was explained by greater competitiveness and job stress in the private bank. Again, these two groups would have been classified as having the same job strain in a job classification. In the already mentioned Danish study of slaughterhouse workers (Kristensen, 1994a) the study group comprised one "official" job title: slaughterhouse work. It turned out that this title covered a large number of specific job functions with very different degrees of job strain. On a 0-10 point scale measuring decision latitude, the male jobs went from average values of 3 to 9; on the psychological demand 0-2 point scale, the jobs went from 0.2 to 1.5. This very large variation would have been diluted in a national job classification. Furthermore it was shown that male slaughterhouse workers in high-strain jobs had a cardiovascular disease symptoms prevalence of 17% against 9% in workers in low-strain jobs. (The four cardiovascular disease symptoms earlier used by Karasek, Baker, Marxer, Ahlbom, andtheorell, 1981, were used in these analyses.) It is noteworthy that the three job titles in the above-indicated examples are relatively precise. Other titles such as office clerk, waiter, foreman, physician, public official, or engineer probably hide even greater variations. Thus, the bias toward the null caused by the use of this method will be very substantial. This conclusion is supported by the relatively low relative risks values found in studies using the job method such as the recent studies by Hammaretal. (1994) and Alterman et al. (1994). This dilution bias is further aggravated by the large random variations that were due to the small number of workers (as low as five) in each job category. The Use of Representative Samples It is quite common that writers of epidemiologic articles stress that their study population is a representative sample of some larger group, for example, national population. Often it is implicitly understood that representativeness is a sign of high study quality. In my opinion this idea reflects a missing distinction between the requirements of descriptive and etiologic studies. In descriptive epidemiology representativeness is usually very important, but in etiologic research one of the most important features is that the exposure variable should

7 252 KRISTENSEN be measured as precisely as possible and that the study base should represent as large an exposure contrast as possible. Moreover, researchers should distinguish between representativeness and generalizability. A sample may be representative for, for example, the Swedish male population aged years, but the study results may still not be generalizable to women or to other races, age groups, or cultures. The idea of sampling large groups of individuals in etiologic studies originated in the American cardiovascular cohort studies of the Framingham type (see, e.g., Kannel & Eaker, 1986). These studies were well suited to the study of individual risk factors with a reasonable variation in the populations studied. This research tradition resulted in a very individualistic (and sometimes victim blaming) ideology of cardiovascular disease prevention. Figure 2 illustrates the problem of small exposure contrast in population-based studies. The average values for the four strain groups are quite close to the population average. The problem becomes even bigger if the strain group is compared with the three nonstrain groups taken together. With such a small exposure contrast it becomes very difficult to show associations and easy to commit Type II errors. Another problem with the population-based study is that it leads to individualistic thinking. Job strain is a structural, not an individual, characteristic and therefore it should be measured at the structural level. The solution to these problems is indicated in the other half of Figure 2: the occupation-based study. The sample unit should be specific jobs or occupations, and these should be selected in advance so that they represent extremes on one or more of the Low strain Active exposure variables supplemented with a few jobs with medium exposure. With an occupation-based approach it would be possible to operate with three different measures of job strain for each individual: perceived job strain, average job strain, and independent measures of job strain. (The latter is discussed below in more detail.) In other words, the methodological principle of triangulation could be used (see, e.g., Cox & Ferguson, 1994). Triangulation means that a phenomenon is measured in three different ways. If all three methods yield the same result, this is a good indicator of high validity, if not, the discrepancies should be scrutinized. The method of triangulation would also make it possible to study people who perceive their job stressors differently from their colleagues, for example, people in low-strain jobs who perceive high strain, and vice versa. Such analyses are only possible if the jobs included are very well described and homogeneous and if the number of workers in each job category is large enough to permit meaningful analyses. The occupation-based approach has been used by a few researchers, but none of the studies performed so far has been optimal as seen from a job strain point of view. Theorell et al. (1990) did a study on six rather specific occupations: freight handlers, aircraft mechanics, air traffic controllers, physicians, waiters, and symphony musicians. However, the exposure contrast was very low, in particular with regard to job demands. Average values on the demand scale, with a range of 5-20, went from 12.9 to Moreover the number of people in each occupation was rather small (maximum was 30). This study should be considered as a very stimulating pilot study. In the Whitehall II Low strain Active Passive High strain Passive High strain Occupation-based study Population-based study Figure 2. The difference between occupation-based and population-based studies of job strain. Theoretical examples.

8 SPECIAL SECTION: STRESS AND CARDIOVASCULAR DISEASE 253 Study, Marmot et al. (1991) studied employees working in the London offices of 20 civil service departments. A classification of six rather homogeneous employment categories was used to elucidate the importance of the social gradient for health outcomes. When these employment categories were analyzed according to the job strain model, it turned out that the social gradient followed the activepassive diagonal and not the strain diagonal, as was perhaps expected by the researchers. (The diagonals are shown in Figure 1.) The senior executive officers (Category 1) had very active jobs, whereas the clerical officers (Category 6) had very passive jobs. The other categories were evenly and stepwise distributed on the active-passive diagonal between these extremes. This means that all of the employment categories had the "same" degree of job strain if job strain is defined as the ratio between demands and control. Hence, the job strain model cannot contribute to an explanation of the Whitehall social gradient with regard to cardiovascular diseases or other diseases. Still, the Whitehall I and II Studies (Marmot, Shipley, & Rose, 1984; Marmot et al., 1991) represent important steps in the right direction for occupational cardiovascular epidemiology. To my knowledge no occupation-based studies with large well-defined groups and sufficient job strain exposure contrast have been performed so far. A Sociological Interpretation of the Job Strain Model The job strain model (Karasek, 1979; Karasek & Theorell, 1990) has been interpreted in many ways in High the literature from a description of psychological states to a model of the organization of work. Perhaps the somewhat ambiguous use of the term strain as describing an individual state (psychological strain) as well as a job category (job strain) has contributed to these different interpretations. In the following I suggest a purely sociological interpretation of the model (Figure 3). Dahlstrom, Gardell, Rundblad, Windgardh, and Hallin (1966) presented a model of technical change and the organization of work based on the pioneering work of Bright (1958). The model operates with craftman 's work (production of single units and low level of mechanization), tempowork (mass production and medium level of mechanization), and surveillance work (continuous production and high level of mechanization). This model has been further developed to fit the job strain model in Figure 3. Craftman's work corresponds to low-strain jobs, tempowork to high-strain jobs, and surveillance work to passive jobs. The fourth category, qualified work, corresponds to active jobs. The three arrows represent three actual historical processes: (a) mechanization of skilled craftman's work and the parallel dequalification and Taylorization of work (F. W. Taylor, 1914); (b) requalification of work through self-governing groups, job enrichment, and so forth; and (c) automation of work and the parallel reduction of the work force. A sociological interpretation of the job strain model emphasizes that job strain should not be understood as just another "cardiovascular risk factor" such as body mass index or tobacco smoking. Job strain should be seen as a phenomenon related to the structural and technological development in the Work intensity & demands Low Craftman's work High Qualified work Influence & level of qualification of workers Low Surveillance work K^ 2 3 Tempo work Figure 3. A sociological interpretation of the job strain model. 1 = mechanization; 2 = job enrichment; 3 = automation.

9 254 KRISTENSEN production process. By embedding the model in sociological theory about technology and work organization it becomes clear that one does not change job strain in any way similar to the way in which one stops smoking. An example can illustrate this point: The job strain diagonal from low to high job strain represents an actual historical process the dequalification and intensification of work by using the principles of F. W. Taylor (1914) and Henry Ford's assembly lines. This, in fact, has been one of the most significant historical processes of this century. The passive-active (or learning) diagonal, on the other hand, does not represent any historical process. The two arrows issuing from the tempowork represent one of the present challenges of work environment: the polarization into stimulating and interesting work for one group of workers and passive and monotonous work for another group. By regarding the job strain model (Karasek, 1979; Karasek & Theorell, 1990) as a model of work organization and technological changes it becomes possible to connect the job strain literature (which so far has been mainly medical and psychological in orientation) to a large theoretical literature on alienation, power, qualifications, workers' collectives, labor conflicts, management, and so forth (see, e.g., Blauner, 1964; Braverman, 1974; Bright, 1958; Dahlstrom et al., 1966; Johnson & Johansson, 1991). Space does not allow further elaboration of these important issues. Let it suffice with one empirical example. In the Danish slaughterhouse study the workers were asked what skills they needed to perform their jobs adequately (Kristensen, 1994a). The questionnaire operated with two types of skills: specific skills (e.g., knowledge about the production) and nonspecific skills (e.g., speed and accuracy). Table 2 shows that workers with high decision latitude needed a balanced blend of the two types of skills, whereas workers with low decision latitude needed almost no specific skills but many of the nonspecific skills. Thus, decreasing decision latitude was associated with fewer specific skills but more nonspecific skills at the same time. This is in accordance with the general theories of workers' qualifications. In the job strain literature the nonspecific skills have usually been overlooked. In the Danish slaughterhouse industry the nonspecific skills play a very important role for the selection of workers. When 10 new workers are needed for high-strain jobs the factories have to take in more than 100 potential workers for training. Only about 10% turn out to have the necessary speed, endurance, agility, and ability to adapt. In fact, the recruitment processes for these jobs are at least as selective as for many highly qualified professions. These primary selection processes for high-strain jobs are often neglected in the job strain research. The 3-S Matrix for Measurements of Stressors, Stress, and Sickness The 3-S matrix (Kristensen, 1995) is a matrix representing the ways in which the three main concepts in the previous discussion, stressors, stress, and sickness, should be measured and associated (Figure 4). The main idea is that the principle of triangulation should be used when measuring all of the main concepts. In the following I explain the matrix in some detail and some of the perspectives are discussed. (The matrix has been mentioned previously [Kristensen, 1995] but not explained in detail.) Measuring the Job Stressors Work stressors should be measured in three ways: independent, self-rated, and average. Independent measures are measures that can be performed independently of the people being studied. Examples Table 2 Association Between Decision Latitude and Average Number of Skills Needed at Work for Danish Slaughterhouse Workers Specific skills Nonspecific skills High Index of decision latitude Note. N 4,828. Specific skills = knowledge about the production, professional skills and experience, and independence; nonspecific skills = speed, agility, ability to adapt oneself, routine, accuracy, and endurance Low Total

10 SPECIAL SECTION: STRESS AND CARDIOVASCULAR DISEASE 255 STRESSORS STRESS SICKNESS of such measures are STRESSORS STRESS SICKNESS Independent Self-rated Average Physiological Self-rated Behavior Disease Illness Functional ability I 1 Self-rated 2 10! f I o S I i = if l! Figure 4. The 3-S matrix for possible studies of relationships between stressors, stress, and sickness (Kristensen, 1995). cyclus time as a measure of repetitiveness number of incoming flights as a measure of demands (air traffic controllers) traffic intensity as a measure of demands (bus drivers) work descriptions for assembly line workers as a measure of decision latitude time study experts' ratings as a measure of work pace (piece rate work) number of nights slept away from home as a measure of demands (commercial travellers) number of phone calls as a measure of demands (telephone operators) machine pacing as a measure of decision latitude tight time schedules as a measure of decision latitude deadlines as a measure of demands number of clients or patients as a measure of demands The self-rated and the average methods have been described above. In an optimal study design the work stressors should be measured in all of the three different ways. None of these ways is superior to the others, but the theoretical and methodological strength of a study is enhanced greatly by using all three in the same study. So far nobody has done so to my knowledge. It should be pointed out that the independent method does have a major weakness: It is often very difficult to find independent measures of job stressors that can be used in studies of very different job categories. These measures are often better suited for studies within a certain domain (such as comparing bus drivers in high- and low-traffic intensity routes). On a more sophisticated level it could be argued that the questionnaire methods (self-rated and average) have the same problem because a given question, for example, about work pace, might be perceived and interpreted very differently by respondents with different types of jobs. This problem, however, tends to be concealed by the questionnaire method because all of the respondents answer the same questions. Thus, the questionnaire creates an artificial world of data in which the demands on a seamstress can be compared with the demands on a movie star. Measuring Stress As mentioned in the introduction I define stress as an individual state characterized by the combination of arousal and displeasure. In the stress literature this concept has been used to describe environmental factors, an individual state, and the interphase between these two. I do not go into this seemingly endless discussion but only emphasize that it is of vital importance that the environment side is conceptualized and measured independently of the person side. As with stressors, stress can be elucidated in

11 256 KRISTENSEN three different ways: by measuring physiologic factors, self-rated stress, and stress-related behavior. The most commonly used physiologic factors are stress hormones such as adrenaline, noradrenaline, and cortisol, but a number of others such as blood pressure, skin temperature, HbA^, fibrinogen, blood clotting factors, heart rate, and blood lipids have been used as well (see, e.g., Sapolsky, 1994). A large number of scales and instruments exist for the measurement of self-rated stress. In my opinion it is important to be able to distinguish between the two basic dimensions, degree of arousal and pleasuredispleasure (Russell, 1980; Matthews, Jones, & Chamberlain, 1990; Warr, 1990, 1994), between emotional, cognitive, and, somatic symptoms (Setterlind & Larsson, 1995), and, of course, between acute and chronic stress. In animal studies and human experimental studies, fight and flight behaviors are used as valid measures of stress. In free-living humans the relationships between stress and behavior are, of course, much more complicated, and it is difficult to identify valid behavioral indicators of stress. A number of widely used behavioral indicators of stress such as alcohol consumption, smoking, use of tranquilizers, and short spells of absence from work are related to stress but are also influenced by a large number of other individual and social factors. Perhaps the recording of the above-mentioned factors should be supplemented with observational studies of more subtle forms of behavior at the worksite such as friendly and unfriendly gestures, mutual help, smiling and laughing, harassment, quarrels, and arguments. In the Danish slaughterhouse study (Kristensen, 1994a) the respondents were asked an open question about how work influenced family life. The word used much more often than any other was "irritability." This result suggests that stress-related behavior in the family might be a topic worth pursuing. Measuring Sickness It has proved extremely difficult to reach consensus amongst researchers regarding the definitions of such central concepts as disease, illness, and sickness. In the following I use these terms as suggested by Field (1976), D. C. Taylor (1979), Idler (1979), and Blackwell (1981): Disease is the diagnosis given by a medical doctor (such as acute myocardial infarction or diabetes), and illness is a concept describing the person's own perceptions of his or her health. Illness can cover an overall description (such as global self-rated health) as well as a number of specific symptoms (such as low back pain, headache, pain in the chest, etc). In practice the distinction may not always be so sharp. For instance, researchers sometimes ask their respondents to report diseases ("Did a doctor ever tell you that you had, for example, diabetes"), and doctors often use selfreported symptoms to make a diagnosis the most extreme examples being angina pectoris and bronchitis. The third important health concept is functional (dis)ability; that is the degree to which the person is able to perform daily activities of work, family life, and leisure time. I suggest sickness as a concept covering all of the three specific concepts: disease, illness, and functional disability. Here I am talking about three continuous variables describing the health situation of an individual. The challenging situations occur when there is substantial lack of agreement between the three. If, for example, the person feels very ill while the doctor cannot find any "objective" disease, then what is the explanation? Is the person a hypochondriac or simulating a disease, or is the doctor's knowledge and capabilities incomplete? (The discussion of fibromyalgia in a number of countries is an illustration of such a situation.) Using the 3-S Matrix There is nothing new about the 3-S matrix (Kristensen, 1995). All of the above-indicated questions have been discussed intensely for many years by scholars in the psychosocial field. The purpose of the matrix is to contribute to a more structured discussion of these issues and to serve as a checklist for researchers planning new empirical projects. In principle an optimal study ought to include all of the cells in the matrix. In practice this will not be possible for a number of reasons. However, in collective research effort researchers should try to cover all of the cells, and the matrix can serve as a reminder of the fields of research in which more research is particularly important. An important principle in the 3-S matrix is triangulation. This principle is applied three times: with stressors (Cells 2, 3, and 11), stress (Cells 26, 27, and 32), and sickness (Cells 41, 42, and 44). (The cells in the matrix represent associations between the nine concepts. Thus, for example, Cell 28 represents analyses of associations between physiologic stress and disease.) With regard to stressors, the three methods can be used independent, self-rated, and average to assess the degree of job strain in an individual's job and also to compare jobs in a population. By studying inconsistencies the measures can be further developed and refined. For instance,

12 SPECIAL SECTION: STRESS AND CARDIOVASCULAR DISEASE 257 Theorell and Karasek (1996) mentioned the large variation of psychological demands and of support within occupations. It is still not known, however, whether this variation is due to variations in perception or to variations in actual demands. This is, of course, a very central question theoretically as well as in practice. By using all three methods in the matrix this question can be answered. The cells in the diagonal of the matrix (Cells 1, 10, 18,..., 45) represent ways in which the different measures relate to themselves, in other words, studies of reliability, precision, and validity. In the book by Karasek and Theorell (1990) it is mentioned that the JCQ was used by over 40 research groups in seven countries. This questionnaire was developed in the United States in the 1960s long before the job strain model. Perhaps more effort should have been put into developing a reliable and valid instrument and less effort put into the empirical testing (see also Kasl's, 1996, comments on the wording of many of the JCQ questions). At any rate, the high Cronbach's alpha coefficients sometimes reported for the job strain scales should not be used as "proof" of high validity. The triviality trap is represented by Cells 13 (associations between self-rated stressors and selfrated stress), 16 (associations between self-rated stressors and illness), and 34 (associations between self-rated stress and illness). In my opinion such associations, especially in cross-sectional studies, should not be reported as genuine findings but perhaps as "tests" of validity. In spite of many warnings in the methodological literature this still happens very often. It should be emphasized that the triviality trap also covers other self-reported measures such as quality of life, life or work satisfaction, depression scales, and so forth. To avoid possible misunderstanding I would like to stress that these measures are in no way trivial in themselves. The triviality trap only relates to the associations between them. So far the job strain literature has focused on the associations between job strain and cardiovascular diseases (Cells 15 and 22) and on possible physiological and behavioral mechanisms (Cells 12, 14,19, and 21), but other cells in the matrix suggest intriguing fields for future research. Examples are Cell 28 (the associations between stress hormones or other physiologic stress indicators and the development of cardiovascular diseases), Cells 9, 17, and 24 (the association between job strain and functional (dis)ability), Cells 8 and 23 (the association between job strain and self-rated health), and Cell 33 (the association between self-rated stress and future disease). Before ending this discussion of the 3-S matrix (Kristensen, 1995) two of the most puzzling results from recent research on job stress and cardiovascular diseases should be mentioned. Winkleby, Ragland, and Syme (1988) studied San Francisco urban bus drivers and found an inverse relationship between reported job stressors and blood pressure. In other words, the higher the blood pressure, the fewer the reported job stressors. In the Danish bus driver study Netterstr0m and Suadicani (1993) found that drivers who perceived the job as varied and who were satisfied with the job had significantly elevated risks for coronary heart disease. These findings have been considered at odds with other research findings in the field. Before concluding this it should, however, be borne in mind that both of these studies operate within relatively homogeneous populations with similar work stressors. (In the Netterstr0m and Suadicani study, the authors even controlled for traffic intensity in the multivariate analysis.) This means that job stressors, measured independently, to a large degree were held constant and that the variation was due to individual dispositions and attitudes. Seen in this way, as restricted studies nested in a job with high job strain, the studies can be interpreted as studies of individual coping mechanisms and hypertensioncardiovascular diseases. Conclusions The theoretical, methodological, and empirical work done by Karasek, Theorell, Johnson, Siegrist, and others (e.g., Johnson & Hall, 1988; Karasek & Theorell, 1990; Siegrist, 1996; Theorell & Karasek, 1996) in the field of work stress and cardiovascular diseases during the last years has been of great importance. Researchers now have a substantial body of scientifically based knowledge, the research activity is large, international collaboration in the field is increasing, and preventive initiatives inspired by this research have been taken in many countries and even at higher levels such as, for example, the European community. The job strain research is one of the cornerstones of psychosocial medicine today together with the research on social class, social support, and perhaps also self-rated health (Idler, 1992). Psychosocial medicine is often attacked for being of lower quality, of producing less convincing results, or both than traditional biomedical research and in particular genetic research. In my opinion this criticism is completely unfounded. In fact, psychosocial medicine probably has greater impact on attitudes and preventive practice as well as higher methodologi-

13 258 KRISTENSEN cal quality than other fields of medicine if one considers the very limited resources used for this research. One of the great challenges for future efforts is to continue improving the research quality, and one of the roads to this is through constructive criticism. The purpose of this article is to contribute to higher research quality. A possible way to achieve this could be to launch studies based on carefully selected occupations (or jobs) representing large exposure contrasts instead of performing studies on representative samples of individuals. An example of such focused, occupationbased research is the Finnish study on carbon disulphide and coronary heart diseases (Hernberg, Tolonen, & Nurminen, 1976; Nurminen & Hernberg, 1985). The study base of this excellent study was small (343 exposed workers and 343 referents), but it convinced researchers around the world about the causal role of carbon disulphide for the development of coronary heart disease (Kristensen, 1989b). Other similar examples are Morris's studies on physical activity and Hogsted's on dynamite workers (Kristensen, 1989a, 1989b). In other words, research on job stress and cardiovascular diseases should adopt some of the designs of occupational medicine (Hernberg, 1992) and not stick to the traditional design of cardiovascular epidemiology. Furthermore, the principle of triangulation should be used in the measurements of stressors, stress, and sickness. Special emphasis should be placed on the measurement of stressors. It is my firm conviction that the theoretical and methodological confusion is larger in the field of stressor measurement than in any of the other fields of this research. Also, the very thoughtful suggestions of Phillips and Smith (1993) should be considered carefully. Phillips and Smith proposed that prospective epidemiological studies should use more resources on repeated and accurate measurements of the risk factors and less resources on large sample sizes. The critique and suggestions of Phillips and Smith are completely in accordance with the conclusions of this article. Finally, the use of occupation-based samples and the measurement principle of triangulation should be combined with worksite interventions whenever possible (Karasek & Theorell, 1990; Theorell, 1993). 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