Job Control
The amount of control or autonomy an employee has over his or her ownwork is perhaps one of the most crucial aspect of working life and one which has been extensively researched. It is a key feature of major theoretical approaches to stress (e.g. Karasek, 1979; Payne, 1979; Warr, 1987), and, together with the related concepts of discretion and autonomy, is a central feature of job design theories (Hackman & Oldham, 1980;Wall et al., 1990a). Furthermore, the importance of job control and related concepts is recognised in the management literature, where it is generally seen as important for releasing employee potential and increasing performance. For example, Peters & Waterman’s (1982) analysis of innovative companies intimately links autonomy with entrepreneurship. The related concept of “empowerment” is a central motivation for many organisational changes and total quality approaches. While control has been linked to a wide range of outcomes, including improving performance and motivation, this post focuses on the implications of the construct for health and well-being.
In the psychological literature, “control” can be viewed as both a characteristic of the environment and a characteristic of the individual. For example, machine-paced assembly work is intrinsically lacking in control; however, the employees themselves may nevertheless be viewed as being high in control, in terms of having high mastery or self-efficacy (Bandura, 1977). The individual may further be seen as having greater or lesser need for control (Burger & Cooper, 1979). Typically, models of stress and job design have treated “control” (and the similar concepts of “decision latitude”, “discretion” and “autonomy”) as characteristics attached to a particular work role or job task, and this approach is the focus of this post. However, the fact that individuals vary in terms of their preferences and perceptions of personal control has implications for these models. Hence individual differences are increasingly being incorporated into approaches to stress and job design. This post aims to introduce two key theoretical approaches to the topic of control in the workplace, the demand–control (or job strain) model (Karasek, 1979), and the job characteristics model (Hackman&Oldham, 1976). Both of these approaches were designed to provide practical guidance to practitioners and managers on the design of work. More recent theoretical developments focusing on more specific types of job control will also be discussed. The post provides a brief overview of the evidence relating to the damaging effects of low control for health and well-being. This includes consideration of the nature of the relationship between job control and health and the effects of individual differences on these relationships. The post discusses the implications of this research for job design interventions and the evidence concerning the effectiveness of such interventions. It finally considers job control in the context of new technology and new work designs.
The literature on job control and health is now vast and a number of comprehensive reviews of various aspects of this literature exist (Ganster & Fusilier, 1989; Kristenson, 1996; Schnall et al., 1994; Terry & Jimmieson, 1999; Van der Doef & Maes, 1998, 1999). This post therefore does not aim to duplicate such reviews, but rather to summarise recent key issues and trends in the research literature and their implications for managers and practitioners.
JOB STRESS AND WORK DESIGN THEORIES
The Demand–Control (“Job Strain”) Model
While job control is an important feature of a number of approaches to occupational stress, the most well known approach, which has been responsible for most of the impetus of research in this area, is Karasek’s demand–control model. However, the key feature of the model is that both psychological and physical strain can be predicted from a combination of demands and control. The model has evolved over the years and, perhaps as a result, there is now a certain amount of uncertainty in its specification (Kasl, 1996). In particular, there is a lack of clarity concerning the exact nature of the hypothesised relationship between the two key variables in the model and strain outcomes. One hypothesis examined in many studies focuses on the negative impacts of jobs that are high in demand and low in control, suggesting that these two variables have an additive effect. A further hypothesis, mooted by Karasek (1979), is that the two variables have an interactive effect such that the combination of high demand and low control produces greater strain than the simple additive effect. This is often viewed as a central feature of the model (e.g. Terry & Jimmieson, 1999). However, the implications of the interactive model are clearly not the same as the additive model. If the effect is interactive (and demand is harmful primarily in conditions of low control) strain could, in practice, be reduced by increasing control without reducing workload (Karasek, 1979; Parkes, 1991). This strategy would be less effective in the case of additive effects.
Further lack of clarity exists concerning the actual nature of the interaction. Kasl (1996) points out that some researchers seem to regard decision latitude as buffering the effect of job demand, such that risk due to high demands will only be present at low levels of control. However, others regard the interaction as synergistic, i.e. both low demand and high control are associated with risk but the combination of the two increases the risk beyond the additive effect. These two approaches are usually not clearly distinguished. Kasl suggests that in many studies the data are presented in such a way that it is not even possible to interpret whether the effect is truly additive or interactive. It is often also the case that the variables are combined into a single “job strain” variable so that it is not possible to separate the effects of demand and control.
A further area of ambiguity which has been widely discussed in the literature is the operationalisation of the key variables (e.g. Ganster & Fusilier, 1989; Jones et al., 1998; Smith et al., 1997). In its original version, Karasek’s model measured decision latitude, a construct which was rather wider than the popular meaning of control, by combining a measure of decision authority with a measure of skill discretion (Karasek, 1979). While decision authority assesses the extent to which people have freedom over how they do their work and have a say over what happens, skill discretion is concerned with the level of skill required and the non-repetitive nature of work. While the two concepts have been shown to be related, they are clearly distinct. Over the years a range of different measures of job control has been used; however, in recent years, a key development in the model has been the increased sophistication in the operationalisation of this variable. This will be discussed further below.
The model has been further developed to include social support (Johnson & Hall, 1988). This is sometimes referred to as the “iso-strain model”. Here again two alternative hypotheses have been identified, the additive hypothesis and the interactive hypothesis, suggesting that support acts as a buffer (Van der Doef & Maes, 1999). Karasek & Theorell (1990) have further proposed the addition of job insecurity and physical demands to the model. However, these latter two variables are seldom included.
The job strain or iso-strain models have been tested using a variety of methods and levels of analysis. At one extreme, long-term epidemiological studies have followed individuals over years to predict coronary heart disease and other disease outcomes (Alterman et al., 1994). At the other extreme, researchers have used laboratory tasks varying in degree of demand and control to examine immediate changes in pulse or other physiological responses (Perrewe & Ganster, 1989). However, the most common approach is the cross-sectional study using self-report measures of demands and control to investigate the predictors of psychological well-being (also based on self-reports) or other symptoms (Dollard et al., 2000; Fletcher & Jones, 1993).
The model has been subject to considerable criticism (Ganster & Fusilier, 1989; Jones et al., 1998; Kristenson, 1996; Muntaner & O’Campo, 1993). For example, concerns have been expressed about the nature and subjectivity of measurement, the statistical tests used to test the interaction, the tendency for its core dimensions to be confounded with socioeconomic status and the lack of account it takes of both wider sociocultural issues and individual differences. It has also been criticised for its simplicity and lack of scope. Nevertheless, perhaps because of its clarity and simplicity, it has stimulated a vast amount of research into the effects of job control on health, in addition to research aiming to improve the model itself. While Karasek’s model is probably the most influential approach to job control and health, a substantial strand of work investigating psychological well-being and job satisfaction is based on the similar construct of autonomy contained in the motivation and job design literature, frequently in the context of the job characteristics model.
The Job Characteristics Model
In motivation and job design research, the notion of autonomy is implicit in the earlywork of Maslow (1970) and Herzberg et al., (1959). However, its key place in job design research is ensured by the job characteristics model (JCM) (Hackman&Oldham, 1976) and its accompanying measurement instrument, the job diagnostic survey (JDS) (Hackman & Oldham, 1980; Idasdak&Drasgow, 1987). This model suggests that there are five core job characteristics: skill variety, task identity, task significance, autonomy and feedback. The construct of “autonomy” is similar to Karasek’s notion of decision authority and includes items concerned with freedom to decide how to do the job and opportunity to use your own discretion. It is hypothesised that these dimensions (via the mediation of the critical psychological states of experienced meaningfulness, experienced responsibility and knowledge of results) predict work motivation, job satisfaction and work effectiveness. In calculating the overall motivating potential of a job, autonomy and feedback are particularly important and are each given equal weighting to the other three elements added together. It is hypothesised that the relationship between job characteristics and the above outcomes is moderated by the individual difference variable, “growth need strength”. The model did not initially suggest relationships between the core job characteristics and health, but later researchers added mental health as an outcome variable (Wall et al., 1978, 1986).
The model has also been adapted to look at job enrichment at both an individual and a group level. For example, in semi-autonomous work groups or self-directed teams, the group may have increases in autonomy and other task characteristics, but the individuals’ jobs may not be improved (Langred, 2000; Wall et al., 1986).
As with Karasek’s model, there has been considerable criticism of the research investigating the JCM, particularly in relation to the strong bias towards the use of cross-sectional studies relying on self-reports alone (Roberts & Glick, 1981). The model is based on the premise that the direction of causation is such that job characteristics cause high or low satisfaction and also that self-reports of job characteristics are an accurate reflection of the objective characteristics of a job. As a result, it is assumed that improving the task to afford greater control will lead to people becoming more motivated as they perceive themselves to have more control. However, it is now widely recognised that there are some problems with this assumption and that self-reports may not always closely correspond to more objective ratings (Sanchez & Levine, 2000; Spector & Jex, 1991). Furthermore, perceptions of work characteristics may be quite easily manipulated (Adler et al., 1985) and the direction of causation may be reciprocal (Wong et al., 1998). The relationship may also be influenced by individual difference variables such as positive and negative affectivity (Munz et al., 1996). Nevertheless, despite these limitations, the model has been extremely influential and has been successful in predicting a number of outcomes, but most frequently it has been used to investigate the predictors of job satisfaction (Champoux, 1991; Loher et al., 1985). This research is considered further below.
Theoretical Developments and the Concept of Job Control
More recent theoretical developments in stress and job design have helped to clarify what is meant by “job control” and have improved the measurement of the construct by differentiating between various specific types of control. This idea is not new. Karasek himself, in the original paper introducing the model in 1979, suggested that future work should distinguish between different aspects of decision latitude. A number of researchers have since developed typologies. This is potentially useful both to improve the predictive power of the theories but also to provide clearer guidelines for practitioners.
Breaugh (1985), for example, suggested three specific facets of autonomy. Work method autonomy refers to the degree of discretion concerning the procedures and methods used in conducting the work. Work scheduling autonomy is the extent of control over scheduling, sequencing or timing of activities and work criteria autonomy describes the degree to which workers can determine the criteria for evaluating their performance.
More recently, Jackson et al. (1993) have developed measures of control over how to do the work (method control) and when the work is done (timing control), in addition to more specific demand concepts. These were originally developed in the context of advanced manufacturing technology but norms have subsequently been developed for a wider range of shop-floor and related jobs, including administrative and managerial posts(Wall et al., 1995). While these factors refer essentially to direct control over the task, Mullarkey et al. (1995) have also suggested a measure of individual role breadth, which encompasses influence over and involvement in decisions affecting broader aspects of work that impact upon the employee. Other types of control may also be important in particular contexts. So, for example,Wall et al. (1990b) consider boundary control (that is, control over secondary aspects of the task such as maintenance and servicing of machines) to be crucial in the context of advanced manufacturing technology. Similarly, Soderfeldt et al. (1996) suggest taking into account a wide range of aspects of control in a study of human service organisations. These include administrative control, ideological control and control within and over a situation.
These specific approaches to job control are nowincreasingly being utilised in the context of Karasek’s model and have potential for extending the model (e.g. Sargent & Terry, 1998). There is, as yet, however, little research investigating either the differential effects of these variables on health or the effectiveness of interventions targeting specific types of control.
Tags: Demand Control Model, iso strain models, job characteristics model, Job Control, job design research, job strain, JOB STRESS, Karasek’s demand control model, Karasek’s model measured decision latitude, long term epidemiological studies, models of stress, Physical Health, psychological literature, Psychological Well-Being, WORK DESIGN THEORIES