The stress concept

Various definitions of stress have been formulated since the concept was first named and described by Hans Selye (Selye 1960). Almost invariably these definitions have failed to capture what is perceived as the essence of the concept by a major proportion of stress researchers.

The failure to reach a common and generally acceptable definition may have several explanations; one of them may be that the concept has become so widespread and has been used in so many different situations and settings and by so many researchers, professionals and lay persons that to agree on a common definition is no longer possible. Another explanation is that there really is no empirical basis for a single common definition. The concept may be so diverse that one single process simply does not explain the whole phenomenon. One thing is clear—in order to examine the health effects of stress, the concept needs to include more than one component. Selye’s definition was concerned with the physiological fight or flight reaction in response to a threat or a challenge from the environment. Thus his definition involved only the individual physiological response. In the 1960s a strong interest arose in so-called life events, that is, major stressful experiences that occur in an individual’s life. The work by Holmes and Rahe (1967) nicely demonstrated that an accumulation of life events was harmful to health. These effects were found mostly in retrospective studies. To confirm the findings prospectively proved to be more difficult (Rahe 1988).

In the 1970s another concept was introduced into the theoretical framework, that of the vulnerability or resistance of the individual who was exposed to stressful stimuli. Cassel (1976) hypothesized that host resistance was a crucial factor in the outcome of stress or the impact of stress on health. The fact that host resistance had not been taken into account in many studies might explain why so many inconsistent and contradictory results had been obtained on the health effect of stress. According to Cassel, two factors were essential in determining the degree of a person’s host resistance: his or her capacity for coping and his or her social supports.

Today’s definition has come to include considerably more than the physiological “Selye stress” reactions. Both social environ-mental effects as represented by (for instance) life events and the resistance or vulnerability of the individual exposed to the life events are included.

Figure 1. Components of stress in the stress-disease model of Kagan and Levi (1971)

In the stress-disease model proposed by Kagan and Levi (1971), several distinctions between different components are made (figure 1). These components are:

• stressful factors or stressors in the environment— social or psychological stimuli that evoke certain harmful reactions
• the individual psychobiological programme, predetermined both by genetic factors and early experiences and learning
• individual physiological stress reactions (“Selye Stress” reactions). A combination of these three factors may lead to
• precursors which may eventually provoke the final outcome, namely 
• manifest physical illness.

It is important to note, that—contrary to Selye’s beliefs—several different physiological pathways have been identified that mediate the effects of stressors on physical health outcomes. These include not only the originally described sympatho-adreno-medullary reaction but also the action of the sympatho-adreno-cortical axis, which may be of equal importance, and the counterbalance provided by parasympathetic gastrointestinal neurohormonal regulation, which has been observed to dampen and buffer the harmful effects of stress. In order for a stressor to evoke such reactions, a harmful influence of the psychobiological programme is required— in other words, an individual propensity to react to stressors has to be present. This individual propensity is both genetically determined and based on early childhood experiences and learning.

If the physiological stress reactions are severe and long-standing enough, they may eventually lead to chronic states, or become precursors of illness. An example of such a precursor is hypertension, which is often stress-related and may lead to manifest somatic disease, such as stroke or heart disease.

Another important feature of the model is that the interaction effects of intervening variables are anticipated at each step, further increasing the complexity of the model. This complexity is illustrated by feed-back loops from all stages and factors in the model to every other stage or factor. Thus the model is complex—but so is nature.

Our empirical knowledge about the accuracy of this model is still insufficient and unclear at this stage, but further insight will be gained by applying the interactive model to stress research. For example, our ability to predict disease may increase if the attempt is made to apply the model.

Empirical evidence on host resistance

In our group of investigators at the Karolinska Institute in Stockholm, recent research has been focused on factors that promote host resistance. We have hypothesized that one such powerful factor is the health-promoting effects of well-functioning social networks and social support.

Our first endeavour to investigate the effects of social networks on health were focused on the entire Swedish population from a “macroscopic” level. In cooperation with the Central Swedish Bureau of Statistics we were able to evaluate the effects of self-assessed social network interactions on health outcome, in this case on survival (Orth-Gomér and Johnson 1987).

Representing a random sample of the adult Swedish population, 17,433 men and women responded to a questionnaire about their social ties and social networks. The questionnaire was included in two of the annual Surveys of Living Conditions in Sweden, which were designed to assess and measure the welfare of the nation in material as well as in social and psychological terms. Based on the questionnaire, we created a comprehensive social network interaction index which included the number of members in the network and the frequency of contacts with each member. Seven sources of contacts were identified by means of factor analysis: parents, siblings, nuclear family (spouse and children), close relatives, co-workers, neighbours, distant relatives and friends. The contacts with each source were calculated and added up to a total index score, which ranged from zero to 106.

By linking the Surveys of Living Conditions with the national death register, we were able to investigate the impact of the social network interaction index on mortality. Dividing the study population into tertiles according to their index score, we found that those men and women who were in the lower tertile had an invariably higher mortality risk than those who were in the middle and upper tertiles of the index score.

The risk of dying if one was in the lower tertile was four to five times higher than in the other tertiles, although many other factors might explain this association such as the fact that increasing age is associated with higher risk of dying. Also, as one ages the number of social contacts decrease. If one is sick and disabled, mortality risk increases and it is likely that the extent of the social network decreases. Morbidity and mortality are also higher in lower social classes, and social networks are also smaller and social contacts less abundant. Thus, controlling for these and other mortality risk factors is necessary in any analysis. Even when these factors were taken into account, a statistically significant 40% increase in risk was found to be associated with a sparse social network among those in the lowest third of the population. It is interesting to note that there was no additional health-promoting effect of being in the highest as compared to the middle tertile. Possibly, a great number of contacts can represent a strain on the individual as well as protection against harmful health effects.

Thus, without even knowing anything further about the stressors in the lives of these men and women we were able to confirm a health-promoting effect of social networks.

Social networks alone cannot explain the health effects observed. It is probable that the way in which a social network functions and the basis of support the network members provide are more important than the actual number of people included in the network. In addition, an interactive effect of different stressors is possible. For example the effects of work-related stress have been found to worsen when there is also a lack of social support and social interaction at work (Karasek and Theorell 1990).

In order to explore the issues of interaction, research studies have been carried out using various measures for assessing both qualitative and quantitative aspects of social support. Several interesting results were obtained which are illustrative of the health effects that have been associated with social support. For example, one study of heart disease (myocardial infarct and sudden cardiac death) in a population of 776 fifty-year-old men born in Gothenburg, randomly selected from the general population and found healthy on initial examination, smoking and lack of social support were found to be the strongest predictors of disease (Orth-Gomér, Rosengren and Wilheemsen 1993). Other risk factors included elevated blood pressure, lipids, fibrinogen and a sedentary lifestyle.

In the same study it was shown that only in those men who lacked support, in particular emotional support from a spouse, close relatives or friends, were the effects of stressful life events harmful. Men who both lacked support and had experienced several serious life events had more than five times the mortality of men who enjoyed close and emotional support (Rosengren et al. 1993).

Another example of interactive effects was offered in a study of cardiac patients who were examined for psychosocial factors such as social integration and social isolation, as well as myocardial indicators of an unfavourable prognosis and then followed for a ten-year period. Personality and behaviour type, in particular the Type A behaviour pattern, was also assessed.

The behaviour type in itself had no impact on prognosis in these patients. Of Type A men, 24% died as compared to 22% of Type B men. But when considering the interactive effects with social isolation another picture emerged.

Using a diary of activities during a regular week, men partici-pating in the study were asked to describe anything they would do in the evenings and weekends of a normal week. Activities were then divided into those that involved physical exercise, those that were mainly involved with relaxation and performed at home and those that were performed for recreation together with others. Of these activity types, lack of social recreational activity was the strongest predictor of mortality. Men who never engaged in such activities—called socially isolated in the study—had about three times higher mortality risk than those who were socially active. In addition, Type A men who were socially isolated had an even higher mortality risk than those in any of the other categories (Orth-Gomér, Undén and Edwards 1988).

These studies demonstrate the need to consider several aspects of the psychosocial environment, individual factors as well as of course the physiological stress mechanisms. They also demonstrate that social support is one important factor in stress-related health outcomes.

Back

Most previous stress theories were developed to describe reactions to “inevitable” acute stress in situations threatening biological survival (Cannon 1935; Selye 1936). However, the Demand/Control model was developed for work environments where “stressors” are chronic, not initially life threatening, and are the product of sophisticated human organizational decision making. Here, the controllability of the stressor is very important, and becomes more important as we develop ever more complex and integrated social organizations, with ever more complex limitations on individual behaviour. The Demand/Control model (Karasek 1976; Karasek 1979; Karasek and Theorell 1990), which is discussed below, is based on psychosocial characteristics of work: the psychological demands of work and a combined measure of task control and skill use (decision latitude). The model predicts, first, stress-related illness risk, and, secondly, active/passive behavioural correlates of jobs. It has mainly been used in epidemiological studies of chronic disease, such as coronary heart disease.

Pedagogically, it is a simple model which can help to demonstrate clearly several important issues relevant for social policy discussions of occupational health and safety:

1. that the social organizational characteristics of work, and not just physical hazards, lead to illness and injury
2. that stress-related consequences are related to the social organization of work activity and not just its demands
3. that work’s social activity affects stress-related risks, not just person-based characteristics
4. that the possibility of both “positive stress” and “negative stress” can be explained in terms of combinations of demands and control
5. that can provide the simple model—with basic face validity—to begin discussions on personal stress response for shop-floor workers, clerical staff and other lay people for whom this is a sensitive topic.

Beyond the health consequences of work, the model also captures the perspectives of the work’s organizers who are concerned with productivity results. The psychological demand dimension relates to “how hard workers work”; the decision latitude dimension reflects work organization issues of who makes decisions and who does what tasks. The model’s active learning hypothesis describes the motivation processes of high performance work. The economic logic of extreme labour specialization, the past conventional wisdom about productive job design is contradicted by adverse health consequences in the Demand/Control model. The model implies alternative, health-promoting perspectives on work organization which emphasize broad skills and participation for workers, and which may also bring economic advantages for innovative manufacturing and in service industries because of the increased possibilities for learning and participation.

Hypotheses of the Demand/Control Model

Psychosocial functioning at the workplace, based on psychological demands and decision latitude

Job strain hypothesis

The first hypothesis is that the most adverse reactions of psychological strain occur (fatigue, anxiety, depression and physical illness) when the psychological demands of the job are high and the worker’s decision latitude in the task is low (figure 1, lower right cell). These undesirable stress-like reactions, which result when arousal is combined with restricted opportunities for action or coping with the stressor, are referred to as psychological strain (the term stress is not used at this point as it is defined differently by many groups).

Figure 1. Psychological demand/decision latitude model

For example, the assembly-line worker has almost every behaviour rigidly constrained. In a situation of increased demands (“speed-up”), more than just the constructive response of arousal, the often helpless, long-lasting, and negatively experienced response of residual psychological strain occurs. When the lunch-time rush occurs (Whyte 1948), it is the restaurant worker who does not know how to “control” her customers’ behaviour (“get the jump on the customer”) who experiences the greatest strain on the job. Kerckhoff and Back (1968) describe garment workers under heavy deadline pressure and the subsequent threat of layoff. They conclude that when the actions normally needed to cope with job pressures cannot be taken, the most severe behavioural symptoms of strain occur (fainting, hysteria, social contagion). It is not only the freedom of action as to how to accomplish the formal work task that relieves strain, it may also be the freedom to engage in the informal “rituals”, the coffee break, smoke break or fidgeting, which serve as supplementary “tension release” mechanisms during the work day (Csikszentmihalyi 1975).These are often social activities with other workers— precisely those activities eliminated as “wasted motions” and “soldiering” by Frederick Taylor’s methods (1911 (1967)). This implies a needed expansion of the model to include social relations and social support.

In the model, decision latitude refers to the worker’s ability to control his or her own activities and skill usage, not to control others. Decision latitude scales have two components: task authority—a socially predetermined control over detailed aspects of task performance (also called autonomy); and skill discretion— control over use of skills by the individual, also socially determined at work (and often called variety or “substantive complexity” (Hackman and Lawler 1971; Kohn and Schooler 1973)). In modern organizational hierarchies, the highest levels of knowledge legitimate the exercise of the highest levels of authority, and workers with limited-breadth, specialized tasks are coordinated by managers with higher authority levels. Skill discretion and authority over decisions are so closely related theoretically and empirically that they are often combined.

Examples of work’s psychological demands—“how hard you work”—include the presence of deadlines, the mental arousal or stimulation necessary to accomplish the task, or coordination burdens. The physical demands of work are not included (although psychological arousal comes with physical exertion). Other components of psychological job demands are stressors arising from personal conflicts. Fear of losing a job or skill obsolescence may obviously be a contributor. Overall, Buck (1972) notes that “task requirements” (workload) are the central component of psychological job demands for most workers in spite of the above diversity. While simple measures of working hours, in moderate ranges, do not seem to strongly predict illness, one such measure, shiftwork—especially rotating shiftwork, is associated with substantial social problems as well as increased illness.

While some level of “demands” is necessary to achieve new learning and effective performance on the job (i.e., interest), too high a level is obviously harmful. This has implied the inverted “U-shaped” curve of “optimal” level of demands in the well known General Adaptation Syndrome of Selye (1936) and related, classic theories by Yerkes and Dodson (1908) and Wundt (1922) on stress and performance.* However, our findings show that most work situations have an overload, rather than an underload, problem.

* Although Selye’s “U-shaped” association between demands and stress purported to be unidimensional along a stressor axis, it probably also included a second dimension of constraint in his animal experiments - and thus was really a composite model of stress-related physiological deterioration - potentially similar to the high demand, low control situation, as other researchers have found (Weiss 1971).

Active learning hypothesis

When control on the job is high, and psychological demands are also high, but not overwhelming (fig. 34.2 upper right cell) learning and growth are the predicted behavioural outcomes (i.e., the active learning hypothesis). Such a job is termed the “active job”, since research in both the Swedish and American populations has shown this to be the most active group outside of work in leisure and political activity, in spite of heavy work demands (Karasek and Theorell 1990). Only average psychological strain is predicted for the ‘active job’ because much of the energy aroused by the job’s many stressors (“challenges”) are translated into direct action—effective problem solving—with little residual strain to cause disturbance. This hypothesis parallels White’s “concept of competence” (1959): the psychological state of individuals in challenging circumstances is enhanced by increasing “demands”, an environment-based theory of motivation. The model also predicts that the growth and learning stimuli of these settings, when they occur in a job context, are conducive to high productivity.

In the Demand/Control model, learning occurs in situations which require both individual psychological energy expenditure (demands or challenges) and the exercise of decision-making capability. As the individual with decision-making latitude makes a “choice” as to how to best cope with a new stressor, that new behaviour response, if effective, will be incorporated into the individual’s repertoire of coping strategies (i.e., it will be “learned”). The potential activity level in the future will be raised because of the expanded range of solutions to environmental challenges, yielding an increase in motivation. Opportunities for constructive reinforcement of behaviour patterns are optimal when the challenges in the situation are matched by the individual’s control over alternatives or skill in dealing with those challenges (Csikszentmihalyi 1975). The situation will not be unchallengingly simple (thus, unimportant) nor so demanding that appropriate actions can not be taken because of high anxiety level (the psychological “strain” situation).

The Demand/Control model predicts that situations of low demand and low control (Figure 1 opposite end of diagonal B) cause a very “unmotivating” job setting which leads to “negative learning” or gradual loss of previously acquired skills. Evidence shows that disengagement from leisure and political activity outside the job appear to increase over time in such jobs (Karasek and Theorell 1990). These “passive” job, may be the result of “learned helplessness”, discussed by Seligman (1975) from a sequence of job situations which reject worker’s initiatives.

The fact that environmental demands can thus be conceptualized in both positive and negative terms is congruent with the common understanding that there is both “good” and “bad” stress. Evidence that at least two separable mechanisms must be used to describe “psychological functioning” on the job is one of the primary validations of the multidimensional “Demand/ Control” model structure. The “active”-“passive” diagonal B implies that learning mechanisms are independent of (i.e., orthogonal to) psychological strain mechanisms. This yields a parsimonious model with two broad dimensions of work activity and two major psychological mechanisms (the primary reason for calling it an “interaction” model (Southwood 1978)). (Multiplicative interactions for the axes is too restrictive a test for most sample sizes.)

Clarifying Demand and Control definitions

The Demand/Control model has sometimes been assumed to be congruent with a model of “demands and resources”, allowing a simple fit with currently common “cost/benefit” thinking—where the positive “benefits” of resources are subtracted from the negative “costs” of demands. “Resources” allows inclusion of many factors outside the worker’s immediate task experience of obvious importance. However, the logic of the Demand/ Control model hypotheses cannot be collapsed into a unidimensional form. The distinction between decision latitude and psychological stressors must be retained because the model predicts both learning and job strain—from two different combinations of demands and control which are not simply mathematically additive. Job “control” is not merely a negative stressor, and “demands and challenges” associated with lack of control are not associated with increased learning. Having decision latitude over the work process will reduce a worker’s stress, but increase his learning, while psychological demands would increase both learning and stress. This distinction between demands and control allows understanding of the otherwise unclear prediction of the effects of: (a) “responsibility”, which actually combines high demands and high decision latitude; (b) “qualitative job demands”, which also measures the possibility of decision making about what skills to employ; and (c) “piece work”, where the decision latitude to work faster almost directly brings with it increased demands.

Expanding the Model

Social support hypotheses

The Demand/Control model has been usefully expanded by Johnson by the addition of social support as a third dimension (Johnson 1986; Kristensen 1995). The primary hypothesis, that jobs which are high in demands, low in control—and also low in social support at work (high “iso-strain”) carry the highest risks of illness, has been empirically successful in a number of chronic disease studies. The addition clearly acknowledges the need of any theory of job stress to assess social relations at the workplace (Karasek and Theorell 1990; Johnson and Hall 1988). Social support “buffering” of psychological strain may depend on the degree of social and emotion integration and trust between co-workers, supervisors, etc.—“socio-emotional support” (Israel and Antonnuci 1987). Addition of social support also makes the Demand/Control perspective more useful in job redesigning. Changes in social relations between workers (i.e., autonomous work groups) and changes in decision latitude are almost inseparable in job redesign processes, particularly “participatory” processes (House 1981).

However, a full theoretical treatment of the impact of social relations on both job stress and behaviour is a very complex problem which needs further work. The associations with measures of co-worker and supervisor interactions and chronic disease are less consistent than for decision latitude, and social relations can strongly increase, as well as decrease, the nervous system arousal that may be the risk-inducing link between social situation and illness. The dimensions of work experience that reduce job stress would not necessarily be the same dimensions that are relevant for active behaviour in the Demand/Control model. Facilitating collective forms of active behaviour would likely focus on the distribution of and ability to use competences, communication structure and skills, coordination possibilities, “emotional intelligence skills” (Goleman 1995)—as well as the trust important for social support.

Occupation and psychosocial job characteristics

Job characteristics can be displayed in a four quadrant diagram using the average job characteristics of occupations in the US Census occupation codes (Karasek and Theorell 1990). The “active” job quadrant, with high demand and high control, has high-prestige occupations: lawyers, judges, physicians, professors, engineers, nurses and managers of all kinds. The “passive” job quadrant, with low demands and low control, has clerical workers such as stock and billing clerks, transport operatives and low status service personnel such as janitors. The “high strain” quadrant, with high demands and low control, has machine-paced operatives such as assemblers, cutting operatives, inspectors and freight handlers, as well as other low-status service operatives such as waiters or cooks. Female-dominated occupations are frequent (garment stitchers, waitresses, telephone operators and other office automation workers). “Low strain” self-paced occupations, such as repairmen, sales clerks, foresters, linemen and natural scientists, often involve significant training and self-pacing.

Thus, executives and professionals have a moderate level of stress, and not the highest level of stress, as popular belief often holds. While “managerial stress” certainly exists because of the high psychological demands that come with these jobs, it appears that the frequent occasions for decision-making and deciding how to do the job are a significant stress moderator. Of course, at the highest status levels, executive jobs consist of decision-making as the primary psychological demand, and then the Demand/ Control model fails. However, the implication here is that executives could reduce their stress if they made fewer decisions, and lower status workers would be better off with more decision opportunities, so that all groups could be better off with a more equal share of decision power.

Men are more likely than women to have high control over their work process at the task level, with a difference as great as wage differentials (Karasek and Theorell 1990). Another major gender difference is the negative correlation between decision latitude and demands for women: women with low control also have higher job demands. This means that women are several times as likely to hold high strain jobs in the full working population. By contrast, men’s high demand jobs are generally accompanied by somewhat higher decision latitude (“authority commensurate with responsibility”)

Theoretical linkages between the Demand/Control model and other theoretical perspectives

The Demand/Control models arises out of theoretical integration of several disparate scientific directions. Thus, it falls outside the boundaries of a number of established scientific traditions from which it has gained contributions or with which it is often contrasted: mental health epidemiology and sociology, and stress physiology, cognitive psychology and personality psychology. Some of these previous stress theories have focused on a person-based causal explanation, while the Demand/Control model predicts a stress response to social and psychological environments. However, the Demand/Control model has attempted to provide a set of interfacing hypotheses with person-based perspectives. In addition, linkage to macro social organizational and political economic issues, such as social class, have also been proposed. These theoretical integrations and contrasts with other theories are discussed below at several levels. The linkages below provide the background for an extended set of scientific hypotheses.

Contrast between the Demand/Control model and the cognitive psychological model

One area of stress theory grows out of the currently popular field of cognitive psychology. The central tenet of the cognitive model of human psychological functioning is that it is the processes of perception and interpretation of the external world that determine the development of psychological states in the individual. Mental workload is defined as the total information load that the worker is required to perceive and interpret while performing job tasks (Sanders and McCormick 1993; Wickens 1984). “Overload” and stress occur when this human information processing load is too large for the individual’s information processing capabilities. This model has enjoyed great currency since modelling human mental functions in the same rough conceptual model as modern computers utilize, and thus fits an engineering conception of work design. This model makes us aware of the importance of information overloads, communication difficulties and memory problems. It does well in the design of some aspects of human/computer interfaces and human monitoring of complex processes.

However, the cognitive psychological perspective tends to downplay the importance of “objective” workplace stressors, for example, and emphasize instead the importance of the stressed individuals’ interpretation of the situation. In the cognitive-based “coping approach”, Lazarus and Folkman (1986) advocate that the individual “cognitively reinterpret” the situation in a way that makes it appear less threatening, thus reducing experienced stress. However, this approach could be harmful to workers in situations where the environmental stressors are “objectively” real and must be modified. Another variant of the cognitive approach, more consistent with worker empowerment, is Bandura’s (1977) “self-efficacy /motivation” theory which emphasizes the increases in self-esteem which occur when individuals: (a) define a goal for a change process; (b) receive feedback on the positive results from the environment; and (c) successfully achieve incremental progress.

Several omissions in the cognitive model are problematic for an occupational health perspective on stress and conflict with the Demand/Control model:

• There is no role for the social and mental “demands” of work that do not translate into information loads (i.e., no role for tasks which require social organizational demands, conflicts and many non-intellectual time deadlines).
• The cognitive model predicts that situations which require taking a lot of decisions are stressful because they can overload the individual’s information-processing capacity. This directly contradicts the Demand/Control model which predicts lower strain in demanding situations that allow freedom of decision making. The majority of epidemiological evidence from field studies supports the Demand/Control model, but laboratory tests can generate decision-based cognitive overload effect also.
• The cognitive model also omits physiological drives and primitive emotions, which often dominate cognitive response in challenging situations. There is little discussion of how either negative emotions, nor learning-based behaviour (except for Bandura, above) arise in common adult social situations.

Although overlooked in the cognitive model, emotional response is central to the notion of “stress”, since the initial stress problem is often what leads to unpleasant emotional states such as anxiety, fear and depression. “Drives” and emotions are most centrally affected by the limbic regions of the brain—a different and more primitive brain region than the cerebral cortex addressed by most of the processes described by cognitive psychology. Possibly, the failure to develop an integrated perspective on psychological functioning reflects the difficulty of integrating different research specializations focusing on two different neurological systems in the brain. However, recently, evidence has begun to accumulate about the joint effects of emotion and cognition. The conclusion seems to be that emotion is an underlying determinant of strength of behaviour pattern memory and cognition (Damasio 1994; Goleman 1995).

Integrating Sociological and Emotional Stress Perspectives

Development of the Demand/Control model

The goal of the Demand/Control model has been to integrate understanding of the social situation with evidence of emotional response, psychosomatic illness symptoms and active behaviour development in major spheres of adult life activity, particularly in the highly socially structured work situation. However, when the model was being developed, one likely platform for this work, sociological research exploring illness in large population studies, often omitted the detailed level of social or personal response data of stress research, and thus much integrating work was needed to develop the model.

The first Demand/Control integrating idea—for social situation and emotional response—involved stress symptoms, and linked two relatively unidimensional sociological and social psychological research traditions. First, the life stress/illness tradition (Holmes and Rahe 1967; Dohrenwend and Dohrenwend 1974) predicted that illness was based on social and psychological demands alone, without mention of control over stressors. Second, the importance of control at the workplace had been clearly recognized in the job satisfaction literature (Kornhauser 1965): task autonomy and skill variety were used to predict job satisfaction, absenteeism or productivity, with limited additions reflecting the workers’ social relationship to the job—but there was little mention of job workloads. Integrating studies helped bridge the gaps in the area of illness and mental strain. Sundbom (1971) observed symptoms of psychological strain in “mentally heavy work”—which was actually measured by questions relating to both heavy mental pressures and monotonous work (presumably also representing restricted control). The combined insight of these two studies and research traditions was that a two-dimensional model was needed to predict illness: the level of psychological demands determined whether low control could lead to two significantly different types of problem: psychological strain, or passive withdrawal.

The second Demand/Control integration predicted behaviour patterns related to work experience. Behavioural outcomes of work activity also appeared to be affected by the same two broad job characteristics—but in a different combination. Kohn and Schooler (1973) had observed that active orientations to the job were the consequence of both high skill and autonomy levels, plus psychologically demanding work. Social class measures were important correlates here. Meissner (1971) had also found that leisure behaviour was positively associated with opportunities both to take decisions on the job and to perform mentally challenging work. The combined insight of these studies was that “challenge” or mental arousal was necessary, on the one hand, for effective learning and, on the other, could contribute to psychological strain. “Control” was the crucial moderating variable that determined whether environmental demands would lead to “positive” learning consequences, or “negative” strain consequences.

The combination of these two integrating hypotheses, predicting both health and behavioural outcomes, is the basis of the Demand/Control model. “Demand” levels are the contingent factor which determines whether low control leads to either passivity or psychological strain; and “control” levels are the contingent factor which determines whether demands lead to either active learning or psychological strain (Karasek 1976; 1979). The model was then tested on a representative national sample of Swedes (Karasek 1976) to predict both illness symptoms and leisure and political behavioural correlates of psychosocial working conditions. The hypotheses were confirmed in both areas, although many confounding factors obviously share in these results. Shortly after these empirical confirmations, two other conceptual formulations, consistent with the Demand/Control model, appeared, which confirmed the robustness of the general hypotheses. Seligman (1976) observed depression and learned helplessness in conditions of intense demand with restricted control. Simultaneously, Csikszentmihalyi (1975) found that an “active experience” (“flow”) resulted from situations which involved both psychological challenges and high levels of competence. Use of this integrated model was able to resolve some paradoxes in job satisfaction and mental strain research (Karasek 1979): for example, that qualitative workloads were often negatively associated with strain (because they also reflected the individual’s control over his or her use of skills). The most extensive acceptance of the model by other researchers came in 1979 after the expansion of empirical prediction to coronary heart disease, with the assistance of colleague Tores Theorell, a physician with significant background in cardiovascular epidemiology.

A second Demand/Control model integration—physiological response

Additional research has allowed a second level of integration linking the Demand/Control model to physiological response.  The main research developments in physiological research had identified two patterns of an organism’s adaptation to its environment. Cannon’s (1914) fight-flight response is most associated with stimulation of the adrenal medulla—and adrenaline secretion. This pattern, occurring in conjunction with sympathetic arousal of the cardiovascular system, is clearly an active and energetic response mode where the human body is able to use maximum metabolic energy to support both mental and physical exertion necessary to escape major threats to its survival. In the second physiological response pattern, the adrenocortical response is a response to defeat or withdrawal in a situation with little possibility of victory. Selye’s research (1936) on stress dealt with the adrenocortical response to animals in a stressed but passive condition (i.e., his animal subjects were restrained while they were stressed, not a fight-flight situation). Henry and Stephens (1977) describe this behaviour as the defeat or loss of social attachments, which leads to a withdrawal and submissiveness in social interactions.

* A major stimulus for the development of the strain hypothesis of the Demand/Control model in 1974 were Dement’s observations (1969) that vital relaxation related to REM dreaming was inhibited if sleep-deprived cats were “constrained” by a treadmill (perhaps like an assembly line) after periods of extreme psychological stressor exposure. The combined actions of both environmental stressors and low environmental control were essential elements in producing these effects. The negative impacts, in terms of mental derangement, were catastrophic and led to inability to coordinate the most basic physiological processes.

In the early 1980s, Frankenhaeuser’s (1986) research demonstrated the congruence of these two patterns of physiological response with the main hypotheses of the Demand/ Control model—allowing linkage to be made between physiological response and social situation, and emotional response patterns. In high-strain situations, cortisol from the adrenal cortex, and adrenaline from the adrenal medulla, secretions are both elevated, whereas in a situation where the subject has a controllable and predictable stressor, adrenaline secretion alone is elevated (Frankenhaeuser, Lundberg and Forsman 1980). This demonstrated a significant differentiation of psychoendocrine response associated with different environmental situations. Frankenhaeuser used a two-dimension model with the same structure as the Demand/Control model, but with dimensions labelling personal emotional response. “Effort” describes adrenal-medullary stimulating activity (demands in the Demand/Control model) and “distress” describes adrenocortical stimulating activity (lack of decision latitude in the Demand/ Control model). Frankenhaeuser’s emotional response categories illuminate a clearer link between emotion and physiological response, but in this form the Demand/Control model fails to illuminate the association between work sociology and physiological response, which has been another strength of the model.

Integrating person-based stress theory: The dynamic version of the Demand/Control model

One of the challenges behind the development of the Demand/ Control model has been to develop an alternative to the socially conservative explanation that the worker’s perception or response orientations are primary responsible for stress—the claim of some person-based stress theories. For example, it is hard to accept the claims, extended by personality-based stress models, that the majority of stress reactions develop because common individual personality types habitually misinterpret real world stresses or are oversensitive to them, and that these types of personality can be identified on the basis of simple tests. Indeed, evidence for such personality effects has been mixed at best with even the most common measures (although a stress denial personality has been identified—alexithymia (Henry and Stephens 1977). The Type A behaviour pattern, for example, was originally interpreted as the individual’s proclivity to select stressful activities, but research in this area has now shifted to the “anger-prone” personality (Williams 1987). Of course, anger response could have a significant environment-response component. A more generalized version of the personality approach is found in the “person-environment fit” model (Harrison 1978), which postulates that a good match between the person and the environment is what reduces stress. Here also it has been difficult to specify the specific personality characteristics to be measured. Nevertheless, personal response/personality-based approaches addressed the obvious fact that: (a) person-based perceptions are an important part of the process in which environments affect individuals; and (b) there are long-term differences in personal responses to environments. Thus, a time dynamic, integrated environment and person-based version of the Demand/Control model was developed.

The dynamic version of the Demand/Control model (figure 2) integrates environment effects with person-based phenomena such as self-esteem development and long-term exhaustion. The dynamic version integrates person-based and environmental factors by building two combined hypotheses on the original strain and learning mechanisms: (a) that stress inhibits learning; and (b) that learning, in the long term, can inhibit stress. The first hypothesis is that high-strain levels may inhibit the normal capacity to accept a challenge, and thus inhibit new learning. These high-strain levels may be the result of long-lasting psychological strain accumulated over time—and reflected in person-based measures (figure 2, diagonal arrow B). The second hypothesis is that new learning may lead to feelings of mastery or confidence—a person-based measure. These feelings of mastery, in turn, can lead to reduced perceptions of events as stressful and increased coping success (figure 3, diagonal arrow A). Thus, environmental factors, over the long term, partly determine personality, and later, environmental effects are moderated by these previously developed personality orientations. This broad model could incorporate the following, more specific measures of personal response: feelings of mastery, denial, alexithymia, trait anxiety, trait anger, vital exhaustion, burnout, culmulative life-stressor implications, and possibly Type A behaviour components.

Figure 2. Dynamic associations linking environmental strain and learning to evolution of personality

The dynamic model yields the possibility of two long-term dynamic “spirals” of behaviour. The positive behavioural dynamic begins with the active job setting, the increased “feeling of mastery”, and the increased ability to cope with inevitable job stressors. These, in turn, reduce accumulated anxiety and thus increase the capacity to accept still more learning challenges —yielding still further positive personality change and improved well-being. The undesirable behavioural dynamic begins with the high-strain job, the high accumulated residual strain and the restricted capacity to accept learning challenges. These, in turn, lead to diminishing self-esteem and increased stress perceptions—yielding still further negative personality change and diminished well-being. Evidence for submechanisms is discussed in Karasek and Theorell (1990), although the complete model has not been tested. Two promising research directions which could easily integrate with Demand/Control research are “vital exhaustion” research integrated with                                                                                                                                     changing responses to life demands (Appels 1990), and                                                                                                                                   Bandura’s (1977) “self-efficacy” methods, which integrate skill                                                                                                                         development and self-esteem development.

The Demand/Control model and the system dynamics of physiological stress

One necessary next step for Demand/Control research is a more comprehensive specification of the physiological pathways of illness causation. Physiological response is increasingly being understood as a complex system response. The physiology of human stress response—to accomplish, for example, a fight or flight behaviour—is a highly integrated combination of changes in cardiovascular output, brain-stem regulation, respiratory interaction, limbic-system control of the endocrine response, general cortical activation and peripheral circulatory system changes. The concept of “stress” is very possibly most relevant for complex systems—which involve multiple, interacting subsystems and complex causality.*  Accompanying this new perspective of systems dynamic principles in physiology, are definitions of many diseases as disorders of system regulation (Henry and Stephens 1977; Weiner 1977), and investigation of the results of time-dependent, multifactoral adjustments to system equilibrium, or alternatively, their absence in “chaos”.

* Instead of a single and unambiguous cause and effect linkage, as in the "hard sciences" (or hard science mythologically), in stress models causal associations are more complex: there may be many causes which "accumulate" to contribute to a single effect; a single cause ("stressor") may have many effects; or effects which occur only after significant time delays.

Interpreting such observations from the perspective of a “generalized” Demand/Control model, we could say that stress refers to a disequilibrium of the system as a whole, even when parts of the system are functioning. All organisms must have control mechanisms to integrate the actions of separate subsystems (i.e., the brain, the heart and the immune systems). Stress (or job strain) would be an overload condition experienced by the organism’s “control system” when it attempts to maintain integrated functioning in the face of too many environmental challenges (“high demands”), and when the system’s capability of integrated control of its submechanisms fails (“high strain”). To impose order on its chaotic environment, the individual’s internal physiological control systems must “do the work” of maintaining a coordinated physiological regularity (i.e., a constant heart rate) in the face of irregular environmental demands. When the organism’s control capacity is exhausted after too much “organizing” (a low entropy condition, by analogy from thermodynamics), further demands lead to excess fatigue or debilitating strain. Furthermore, all organisms must periodically return their control systems to the rest-state—sleep or relaxation periods (a state of relaxed disorder or high entropy)—to be capable of undertaking the next round of coordinating tasks. The system’s coordination processes or its relaxation attempts may be inhibited if it cannot follow its own optimal course of action, i.e., if it has no possibilities to control its situation or find a satisfactory internal equilibrium state. In general, “lack of control” may represent restriction of the organism’s ability to use all of its adaptive mechanisms to maintain physiological equilibrium in the face of demands, leading to increased long-term burdens and disease risk. This is a direction for future Demand/Control physiological research.

One potentially consistent finding is that while the Demand/Control model predicts cardiovascular mortality, no single conventional risk factor or physiological indicator seems to be the primary pathway of this risk. Future research may show whether “systems dynamic failures” are the pathway.

Macro-social implications of Demand/Control model

Models which integrate over several spheres of research allow broader predictions about the health consequences of human social institutions. For example, Henry and Stephens (1977) observe that in the animal world “psychological demands” result from the thoroughly “social” responsibilities of finding family food and shelter, and rearing and defending offspring; situations of enforced demands combined with social isolation would be hard to imagine. However, the human world of work is so organized that demands can occur without any social affiliation at all. Indeed, according to Frederick Taylor’s Principles of Scientific Management (1911 (1967)), increasing workers’ job demands often should be done in isolation, otherwise the workers would revolt against the process—and return to time-wasting socializing! In addition to showing the utility of an integrated model, this example shows the need to expand even further the social understanding of the human stress response (for example, by adding a social support dimension to the Demand/Control model).

An integrated, socially anchored, understanding of human stress response is particularly needed to understand future economic and political development. Less comprehensive models could be misleading. For example, according to the cognitive model which has dominated public dialogues about future social and industrial development (i.e., the direction for worker’s skills, life in the information society, etc.), an individual has freedom to interpret—i.e., reprogramme—his perception of real world events as stressful or non-stressful. The social implication is that, literally, we can design for ourselves any social arrangement—and we should take the responsibility for adapting to any stresses it may cause. However, many of the physiological consequences of stress relate to the “emotional brain” in the limbic system, which has a deterministic structure with clear limitations on overall demands. It is definitely not “infinitely” re-programmable, as studies of post traumatic stress syndrome clearly indicate (Goleman 1995). Overlooking the limbic system’s limits—and the integration of emotional response and social integration—can lead to a very modern set of basic conflicts for human development. We may be developing social systems on the basis of the extraordinary cognitive capabilities of our brain cortex that place impossible demands on the more basic limbic brain functions in terms of overloads: lost social bonds, lack of internal control possibilities, and restricted ability to see the “whole picture”. In short, we appear to be running the risk of developing work organizations for which we are sociobiologically misfit. These results are not just the consequence of scientific incomplete models, they also facilitate the wrong kinds of social process—processes where the interests of some groups with social power are served to the cost to others of previously inexperienced levels of social and personal dysfunction.

Social class and psychosocial job measures

In many cases, individual level stressors can be modelled as the causal outcome of larger-scale social, dynamic and political- economic processes. Thus, theoretical linkages to concepts such as social class are also needed. Assessment of associations between social situation and illness raise the question of the relation between psychosocial Demand/Control factors and broad measures of social circumstance such as social class. Job decision latitude measure is, indeed, clearly correlated with education and other measures of social class. However, social class conventionally measures effects of income and education which operate via different mechanisms than the psychosocial pathways of the Demand/Control model. Importantly, the job strain construct is almost orthogonal to most social class measures in national populations (however, the active/passive dimension is highly correlated with social class among high status workers (only)) (Karasek and Theorell 1990). The low-decision latitude aspects of low status jobs appear to be a more important contributor to psychological strain than the distinction between mental and physical workload, the conventional determinant of white/blue-collar status. Indeed, the physical exertion common in many blue-collar jobs may be protective for psychological strain in some circumstances. While job strain is indeed more common in low status jobs, psychosocial job dimensions define a strain-risk picture which is significantly independent of the conventional social class measures.

Although it has been suggested that the observed Demand/Control job/illness associations merely reflect social class differences (Ganster 1989; Spector 1986), a review of evidence rejects this view (Karasek and Theorell 1990). Most of the Demand/Control research has simultaneously controlled for social class, and Demand/Control associations persist within social class groups. However, blue-collar associations with the model are more consistently confirmed, and the strength of white-collar associations varies (see “Job strain and cardiovascular disease”, below) across studies, with white-collar single occupation studies being somewhat less robust. (Of course, for the very highest status managers and professionals decision making may become a significant demand in itself.)

The fact that conventional “social class” measures often find weaker associations with mental distress and illness outcomes than the Demand/Control model actually makes a case for new social class conceptions. Karasek and Theorell (1990) define a new set of psychosocially advantaged and disadvantaged workers, with job stress “losers” in routinized, commercialized and bureaucratized jobs, and “winners” in highly creative learning-focused intellectual work. Such a definition is consistent with a new, skill-based industrial output in the “information society”, and a new perspective on class politics.

Methodological Issues

Objectivity of psychosocial job measures

Self-report questionnaires administered to workers have been the most common method of gathering data on psychosocial characteristics of work since they are simple to administer and can be easily designed to tap core concepts in work redesign efforts also (Hackman and Oldham’s JDS 1975), Job Content Questionnaire (Karasek 1985), the Swedish Statshalsan questionnaire. While designed to measure the objective job, such questionnaire instruments inevitably measure job characteristics as perceived by the worker. Self-report bias of findings can occur with self-reported dependent variables such as depression, exhaustion and dissatisfaction. One remedy is to aggregate self-report responses by work groups with similar work situations—diluting individual biases (Kristensen 1995). This is the basis of extensively used systems linking psychosocial job characteristics to occupations (Johnson et al. 1996).

There is also evidence assessing the “objective” validity of self-reported psychosocial scales: correlations between self-report and expert observation data are typically 0.70 or higher for decision latitude, and lower (0.35) correlations for work demands (Frese and Zapf 1988). Also supporting objective validity is the high between-occupation variances of (40 to 45%) of decision latitude scales, which compare favourably with 21% for income and 25% for the physical exertion, which are acknowledged to vary dramatically by occupation (Karasek and Theorell 1990). However, only 7% and 4%, of psychological demands and social support scale variance, respectively, is between occupations, leaving the possibility of a large person-based component of self-reports of these measures.

More objective measurement strategies would be desirable. Some well-known objective assessment methods are congruent with the Demand/Control model (for decision latitude: VERA, Volpert et al. (1983)). However, expert observations have problems also: observations are costly, time consuming, and, in assessment of social interactions, obviously do not generate more accurate measures. There are also theoretical biases involved in the very concept of standard “expert” measures: it is much easier to “measure” the easily observed, repetitive quality of the low status assembly-line worker jobs, than the diverse tasks of high status managers or professionals. Thus, objectivity of the psychosocial measures is inversely related to the decision latitude of the subject.

Some reviews of empirical evidence for the Demand/Control model

Job strain and cardiovascular disease (CVD)

Job strain and heart disease associations represent the broadest base of empirical support for the model. Recent comprehensive reviews have been done by Schnall, Landsbergis and Baker (1994), Landsbergis et al. (1993) and Kristensen (1995). Summarizing Schnall, Landsbergis and Baker(1994) (updated by Landsbergis, personal communication, Fall 1995): 16 of 22 studies have confirmed a job strain association with cardiovascular mortality using a wide range of methodologies, including 7 of 11 cohort studies; 2 of 3 cross-sectional studies; 4 of 4 case control studies; and 3 of 3 studies utilizing disease symptom indicators. Most negative studies have been in older populations (mainly over age 55, some with much post-retirement time) and are mainly based upon aggregated occupation scores which, although they minimize self-report bias, are weak in statistical power. The job strain hypothesis appears to be somewhat more consistent when predicting blue-collar than white-collar CVD (Marmot and Theorell 1988). Conventional CVD risk factors such as serum cholesterol, smoking and even blood pressure, when measured in the conventional manner, have so far only shown inconsistent or weak job-strain effects. However, more sophisticated methods (ambulatory blood pressures) show substantial positive results (Theorell and Karasek 1996).

Job strain and psychological distress/behaviour, absenteeism

Psychological disorder findings are reviewed in Karasek and Theorell (1990). The majority of the studies confirm a job strain association and are from broadly representative or nationally representative populations in a number of countries. The common study limitations are cross-section design and the difficult-to-avoid problem of self-reported job and psychological strain questionnaires, although some studies also include objective observer assessment of work situations and there are also supportive longitudinal studies. While some have claimed that a person-based tendency towards negative affect inflates work-mental strain associations (Brief et al. 1988), this could not be true for several strong findings on absenteeism (North et al. 1996; Vahtera Uutela and Pentii 1996). Associations in some studies are very strong and, in a number of studies, are based on a linkage system which minimizes potential self-report bias (at the risk of loss of statistical power). These studies confirm associations for a broad range of psychological strain outcomes: moderately severe forms of depression, exhaustion, drug consumption, and life and job dissatisfaction, but findings also differ by outcome. There is also some differentiation of negative affect by Demand/Control model dimensions. Exhaustion, rushed tempo or simply reports of “feeling stressed” are more strongly related to psychological demands—and are higher for managers and professionals. More serious strain symptoms such as depression, loss of self-esteem, and physical illness seem to be more strongly associated with low decision latitude—a larger problem for low status workers.

Job strain and musculoskeletal disorders and other chronic diseases

Evidence of the utility of the Demand/Control model is accumulating in other areas (see Karasek and Theorell 1990). Prediction of occupational musculoskeletal illness is reviewed for 27 studies by Bongers et al. (1993) and other researchers (Leino and Häøninen 1995; Faucett and Rempel 1994). This work supports the predictive utility of the Demand/ Control/support model, particularly for upper extremity disorders. Recent studies of pregnancy disorders (Fenster et al. 1995; Brandt and Nielsen 1992) also show job strain associations.

Summary and Future Directions

The Demand/Control/support model has stimulated much research during recent years. The model has helped to document more specifically the importance of social and psychological factors in the structure of current occupations as a risk factor for industrial society’s most burdensome diseases and social conditions. Empirically, the model has been successful: a clear relationship between adverse job conditions (particularly low decision latitude) and coronary heart disease has been established.

However, it is still difficult to be precise about which aspects of psychological demands, or decision latitude, are most important in the model, and for what categories of workers. Answers to these questions require more depth of explanation of the physiological and micro-behavioural effects of psychological demands, decision latitude and social support than the model’s original formulation provided, and require simultaneous testing of the dynamic version of the model, including the active/passive hypotheses. Future utility of Demand/Control research could be enhanced by an expanded set of well-structured hypotheses, developed through integration with other intellectual areas, as outlined above (also in Karasek and Theorell 1990). The active/passive hypotheses, in particular, have received too little attention in health outcome research.

Other areas of progress are also needed, particularly new methodological approaches in the psychological demand area. Also, more longitudinal studies are needed, methodological advances are needed to address self-report bias and new physiological monitoring technologies must be introduced. At the macro level, macro social occupational factors, such as worker collective and organizational level decision influence and support, communication limitations and job and income insecurity, need to be more clearly integrated into the model. The linkages to social class concepts need to be further explored, and the strength of the model for women and the structure of work/family linkages need to be further investigated. Population groups in insecure employment arrangements, which have the highest stress levels, must be covered by new types of study designs—especially relevant as the global economy changes the nature of work relationships. As we are more exposed to the strains of the global economy, new measures at macro levels are needed to test the lack of local control and increased intensity of work activity— apparently making the general form of the Demand/Control model relevant in the future.

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Person–environment fit (PE) theory offers a framework for assessing and predicting how characteristics of the employee and the work environment jointly determine worker well-being and, in the light of this knowledge, how a model for identifying points of preventive intervention may be elaborated. Several PE fit formulations have been proposed, the most widely known ones being those of Dawis and Lofquist (1984); French, Rodgers and Cobb (1974); Levi (1972); McGrath (1976); and Pervin (1967). The theory of French and colleagues, illustrated in figure 1, may be used to discuss the conceptual components of PE fit theory and their implications for research and application.

Figure 1. Schematic of French, Rogers and Cobb's theory of person-environment (PE) fit

Poor PE fit can be viewed from the perspectives of the employee’s needs (needs–supplies fit) as well as the job–environment’s demands (demands–abilities fit). The term needs–supplies fit refers to the degree to which employee needs, such as the need to use skills and abilities, are met by the work environment’s supplies and opportunities to satisfy those needs. Demands–abilities fit refers to the degree to which the job’s demands are met by the employee’s skills and abilities. These two types of fit can overlap. For example, work overload may leave the employer’s demands unmet as well as threaten the employee’s need to satisfy others.

Conceptualizing Person (P) and Environment (E)

Characteristics of the person (P) include needs as well as abilities. Characteristics of the environment (E) include supplies and opportunities for meeting the employee’s needs as well as demands which are made on the employee’s abilities. In order to assess the degree to which P equals (or fits), exceeds, or is less than E, the theory requires that P and E be measured along commensurate dimensions. Ideally, P and E should be measured on equal interval scales with true zero points. For example, one could assess PE fit on workload for a data-entry operator in terms of both the number of data-entry keystrokes per minute demanded by the job (E) and the employee’s keystroke speed (P). As a less ideal alternative, investigators often use Likert type scales. For example, one could assess how much the employee wants to control the work pace (P) and how much control is provided by the job’s technology (E) by using a rating scale, where a value of 1 corresponds to no control, or almost no control and a value of 5 corresponds to complete control.

Distinguishing Subjective from Objective Fit

Subjective fit (F_S) refers to the employee’s perceptions of P and E, whereas objective fit (F_O) refers to assessments that are, in theory, free of subjective bias and error. In practice, there is always measurement error, so that it is impossible to construct truly objective measures. Consequently, many researchers prefer to create a working distinction between subjective and objective fit, referring to measures of objective fit as ones which are relatively, rather than absolutely, immune to sources of bias and error. For example, one can assess objective PE fit on keystroke ability by examining the fit between a count of required keystrokes per minute in the actual workload assigned to the employee (E_O) and the employee’s ability as assessed on an objective-type test of keystroke ability (P_O). Subjective PE fit might be assessed by asking the employee to estimate per minute keystroke ability (P_S) and the number of keystrokes per minute demanded by the job (E_S).

Given the challenges of objective measurement, most tests of PE fit theory have used only subjective measures of P and E (for an exception, see Chatman 1991). These measures have tapped a variety of dimensions including fit on responsibility for the work and well-being of other persons, job complexity, quantitative workload and role ambiguity.

Dynamic Properties of the PE Fit Model

Figure 1 depicts objective fit influencing subjective fit which, in turn, has direct effects on well-being. Well-being is broken down into responses called strains, which serve as risk factors for subsequent illness. These strains can involve emotional (e.g., depression, anxiety), physiological (e.g., serum cholesterol, blood pressure), cognitive (e.g., low self-evaluation, attributions of blame to self or others), as well as behavioural responses (e.g., aggression, changes in lifestyle, drug and alcohol use).

According to the model, levels of and changes in objective fit, whether due to planned intervention or otherwise, are not always perceived accurately by the employee, so that discrepancies arise between objective and subjective fit. Thus, employees can perceive good fit as well as poor fit when, objectively, such is not the case.

Inaccurate employee perceptions can arise from two sources. One source is the organization, which, unintentionally or by design (Schlenker 1980), may provide the employee with inadequate information regarding the environment and the employee. The other source is the employee. The employee might fail to access available information or might defensively distort objective information about what the job requires or about his or her abilities and needs — Taylor (1991) cites such an example.

French, Rodgers and Cobb (1974) use the concept of defences to refer to employee processes for distorting the components of subjective fit, P_S and E_S, without changing the commensurate components of objective fit, P_O and E_O. By extension, the organization can also engage in defensive processes—for example, cover-ups, denial or exaggeration—aimed at modifying employee perceptions of subjective fit without concomitantly modifying objective fit.

The concept of coping is, by contrast, reserved for responses and processes that aim to alter and, in particular, improve objective fit. The employee can attempt to cope by improving objective skills (P_O) or by changing objective job demands and resources (E_O) such as through a change of jobs or assigned responsibilities. By extension, the organization can also apply coping strategies to improve objective PE fit. For example, organizations can make changes in selection and promotion strategies, in training and in job design to alter E_O and P_O.

The distinctions between coping and defence on the one hand and objective and subjective fit on the other can lead to an array of practical and scientific questions regarding the consequences of using coping and defence and the methods for distinguishing between effects of coping and effects of defence on PE fit. By derivation from the theory, sound answers to such questions require sound measures of objective as well as subjective PE fit.

Statistical Models

PE fit can have non-linear relations with psychological strain. Figure 2 presents a U-shaped curve as an illustration. The lowest level of psychological strain on the curve occurs when employee and job characteristics fit each other (P = E). Strain increases as the employee’s abilities or needs respectively fall short of the job’s demands or resources (PE). Caplan and colleagues (1980) report a U-shaped relation between PE fit on job complexity and symptoms of depression in a study of employees from 23 occupations.

Figure 2. Hypothetical U-shaped relation of person-environment fit to psychological strain

Efficacy of the Model

A variety of different approaches to the measurement of PE fit demonstrate the model’s potential for predicting well-being and performance. For example, careful statistical modelling found that PE fit explained about 6% more variance in job satisfaction than was explained by measures of P or E alone (Edwards and Harrison 1993). In a series of seven studies of accountants measuring PE fit using a card-sort method, high-performers had higher correlations between P and E (average r = 0.47) than low performers (average r = 0.26; Caldwell and O’Reilly 1990). P was assessed as the employee’s knowledge, skills and abilities (KSAs), and E was assessed as the commensurate KSAs required by the job. Poor PE fit between the accountant’s values and the firm’s also served to predict employee turnover (Chatman 1991).

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Workload and Brain Function

Knowledge about human needs, abilities and constraints provides guidelines for shaping psychosocial work conditions so as to reduce stress and improve occupational health (Frankenhaeuser 1989). Brain research and behavioural research have identified the conditions under which people perform well and the conditions under which performance deteriorates. When the total inflow of impressions from the outside world falls below a critical level and work demands are too low, people tend to become inattentive and bored and to lose their initiative. Under conditions of excessive stimulus flow and too high demands, people lose their ability to integrate messages, thought processes become fragmented and judgement is impaired. This inverted U-relationship between workload and brain function is a fundamental biological principle with wide applications in working life. Stated in terms of efficiency at different workloads, it means that the optimal level of mental functioning is located at the midpoint of a scale ranging from very low to very high work demands. Within this middle zone the degree of challenge is “just right”, and the human brain functions efficiently. The location of the optimal zone varies among different people, but the crucial point is that large groups spend their lives outside the optimal zone that would provide opportunities for them to develop their full potential. Their abilities are constantly either underutilized or overtaxed.

A distinction should be made between quantitative overload, which means too much work within a given time period, and qualitative underload, which means that tasks are too repetitive, lacking variety and challenge (Levi, Frankenhaeuser and Gardell 1986).

Research has identified criteria for “healthy work” (Frankenhaeuser and Johansson 1986; Karasek and Theorell 1990). These criteria emphasize that workers should be given the opportunity to: (a) influence and control their work; (b) understand their contribution in a wider context; (c) experience a sense of togetherness and belonging at their place of work; and (d) develop their own abilities and vocational skill by continuous learning.

Monitoring Bodily Responses at Work

People are challenged by different work demands whose nature and strength are appraised via the brain. The appraisal process involves a weighing, as it were, of the severity of the demands against one’s own coping abilities. Any situation which is perceived as a threat or challenge requiring compensatory effort is accompanied by the transmission of signals from the brain to the adrenal medulla, which responds with an output of the catecholamines epinephrine and norepinephrine. These stress hormones make us mentally alert and physically fit. In the event that the situation induces feelings of uncertainty and helplessness, the brain messages also travel to the adrenal cortex, which secretes cortisol, a hormone which plays an important part in the body’s immune defence (Frankenhaeuser 1986).

With the development of biochemical techniques that permit the determination of exceedingly small amounts of hormones in blood, urine and saliva, stress hormones have come to play an increasingly important role in research on working life. In the short term, a rise in stress hormones is often beneficial and seldom a threat to health. But in the longer term, the picture may include damaging effects (Henry and Stephens 1977; Steptoe 1981). Frequent or long-lasting elevations of stress-hormone levels in the course of daily life may result in structural changes in the blood vessels which, in turn, may lead to cardiovascular disease. In other words, consistently high levels of stress hormones should be regarded as warning signals, telling us that the person may be under excessive pressure.

Biomedical recording techniques permit the monitoring of bodily responses at the workplace without interfering with the worker’s activities. Using such ambulatory-monitoring techniques, one can find out what makes the blood pressure rise, the heart beat faster, the muscles tense up. These are important pieces of information which, together with stress-hormone assays, have helped in identifying both aversive and protective factors related to job content and work organization. Thus, when searching the work environment for harmful and protective factors, one can use the people themselves as “measuring rods”. This is one way in which the study of human stress and coping may contribute to intervention and prevention at the workplace (Frankenhaeuser et al. 1989; Frankenhaeuser 1991).

Personal Control as a “Buffer”

Data from both epidemiological and experimental studies support the notion that personal control and decision latitude are important “buffering” factors which help people to simultaneously work hard, enjoy their jobs and remain healthy (Karasek and Theorell 1990). The chance of exercising control may “buffer” stress in two ways: first, by increasing job satisfaction, thus reducing bodily stress responses, and secondly, by helping people develop an active, participatory work role. A job that allows the worker to use his or her skills to the full will increase self-esteem. Such jobs, while demanding and taxing, may help to develop competencies that aid in coping with heavy workloads.

The pattern of stress hormones varies with the interplay of positive versus negative emotional responses evoked by the situation. When demands are experienced as a positive and manageable challenge, the adrenaline output is typically high, whereas the cortisol-producing system is put to rest. When negative feelings and uncertainty dominate, both cortisol and adrenaline increase. This would imply that the total load on the body, the “cost of achievement”, will be lower during demanding, enjoyable work than during less demanding but tedious work, and it would seem that the fact that cortisol tends to be low in controllable situations could account for the positive health effects of personal control. Such a neuroendocrine mechanism could explain the epidemiological data obtained from national surveys in different countries which show that high job demands and work overload have adverse health consequences mainly when combined with low control over job-related decisions (Frankenhaeuser 1991; Karasek and Theorell 1990; Levi, Frankenhaeuser and Gardell 1986).

Total Workload of Women and Men

In order to assess the relative workloads associated with men’s and women’s different life situations, it is necessary to modify the concept of work so as to include the notion of total workload, that is, the combined load of demands related to paid and unpaid work. This includes all forms of productive activities defined as “all the things that people do that contribute to the goods and services that other people use and value” (Kahn 1991). Thus, a person’s total workload includes regular employment and overtime at work as well as housework, child care, care of elderly and sick relatives and work in voluntary organizations and unions. According to this definition, employed women have a higher workload than men at all ages and all occupational levels (Frankenhaeuser 1993a, 1993b and 1996; Kahn 1991).

The fact that the division of labour between spouses in the home has remained the same, while the employment situation of women has changed radically, has led to a heavy workload for women, with little opportunity for them to relax in the evenings (Frankenhaeuser et al. 1989). Until a better insight has been gained into the causal links between workload, stress and health, it will remain necessary to regard prolonged stress responses, displayed in particular by women at the managerial level, as warning signals of possible long-term health risks (Frankenhaeuser, Lundberg and Chesney 1991).

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