Research remains divided over the issue of whether job control acts as a buffer or not.Terry& Jimmieson (1999) extensively reviewed this literature and concluded that the majority of both cross-sectional and longitudinal studies found little support for the interaction in predicting employee adjustment (as measured by job satisfaction, for example). They conclude, perhaps surprisingly, that the strongest support for the interaction is based on studies using objective indicators of job features and/or strains (e.g. Dwyer & Ganster, 1991; Fox et al., 1993). Some support has also been found in studies using experimental methods (Perrewe & Ganster, 1989), suggesting that control may buffer the effects of the demands of specific work tasks. Research looking at cardiovascular outcomes has seldom directly tested the interaction effect, but where it does, Terry & Jimmieson conclude that the findings have generally not been significant.
Terry & Jimmieson discuss reasons for these inconsistencies. One suggestion is that the interaction only occurs for some outcomes, i.e. they argue that they may be specific to non-affective outcomes such as absenteeism (Dwyer and Ganster, 1991; Parkes, 1991) and some physiological measures (Fox et al., 1993). Another possibility is that it is highly dependent on the measure of control. This argument is put strongly by Wall et al. (1996), who suggested that Karasek’s predicted interaction effect is seldom demonstrated because the decision latitude measure used lacks specificity. They compared a focused measure combining timing and method control with the conventional decision latitude measure in a study that aimed to predict psychological strain. They found a significant interaction effect with demand for the specific measure but not for the conventional measure. However, Terry & Jimmieson argue that many studies using focused measures of control are not consistent with Wall et al. (e.g. Carayon, 1993; Kushnir & Melamed, 1991).
The use of multidimensional measures assessing different aspects of control shows some promise in clarifying the nature of relationships. For example, Sargent & Terry (1998) suggest that specific types of control that are relevant to the task will buffer the effects of demands, whereas more peripheral forms of control will not.
It has also been suggested that the relationship between work stressors, including job control, is curvilinear, i.e. not only are low levels of job control harmful but very high levels may also be harmful (Warr, 1987). This poses some potential problems for the demand– control model because models which fail to take into account nonlinear relationships may showspurious interactive effects due to nonlinear effects of either of the variables comprising the interaction term (Lubinski&Humphreys, 1990). Fewstudies have examined curvilinear relationships, leaving open the possibility that where interactions were significant these may have been spurious. Warr (1991), in a study of over 1600 employed people, found significant nonlinear components and taking these into account in the final regressions found no evidence for an interactive effect in predicting job related anxiety, depression and job satisfaction.
Furthermore, a study by Fletcher & Jones (1993) examined the effects of demand and control in a heterogeneous sample of over 3000 men and women, and found, for men, that there was some evidence that the two variables interacted to predict job satisfaction and life satisfaction. However, this effect disappeared once the nonlinear relationships were taken into account, suggesting that it was indeed a spurious effect.
A further reason for the inconsistency in the findings in relation to the interactive effects, which is increasingly attracting attention, is that it may be highly dependent on individual differences. These are discussed below.
Personality Variables
Karasek’s model of job control was designed to provide a general model ofwork redesign and hence did not incorporate individual difference variables. However, a range of personality variables have been found to moderate the impact of demands and control on strain outcomes and are now thought to be one possible explanation for the ambiguous findings in relation to the model (Parkes, 1991). Over the past few years the focus on finding such variables has increased. Typically, personality variables examined are those most closely related to perceptions of personal control such as perceptions of Type A personality, locus of control and self-efficacy. There are two possible ways that personality can act as a moderator. It can either be a buffer or resistance factor, decreasing the impact of stressors or strains, or it can act as a vulnerability factor, increasing the impact. For example, Type A behaviour pattern, characterised by high achievement orientation, time urgency and hostility (Friedman & Rosenman, 1974), is seen as a vulnerability factor. Type A personalities have been shown to be more prone to psychological strain than Type Bs under high-demand working conditions with little control (Kushnir & Melamed, 1991).
Locus of control refers to whether an individual generally believes that the causes of events in their lives are substantially within their control (internal locus) or controlled by external factors (Rotter, 1966). This characteristic has been viewed as both a buffer and a vulnerability factor. For example, Parkes (1991), in a study of civil servants, found that external locus of control increased the vulnerability of driving examiners and student teachers to the psychological impacts of job strain. Thus, the interactive demand-discretion model predicted anxiety for subjects with external locus of control but not for those with internal locus. Daniels & Guppy (1994), however, suggest that having an internal locus of control buffers the effect of stressors on psychological well-being.
Belief that the individual has internal control may not always be coupled with confidence that the individual is able to take that control and succeed in taking a particular desired course of action. This kind of belief has been termed “self-efficacy” (Bandura, 1977) and has also been shown to moderate the impact of job strain. For example, Schaubroeck et al. (2000), in a study of American bank tellers, found that perceived job control moderated the impacts of job demands on psychological strain only for those who were high in selfefficacy. Where they had low self-efficacy, having high control exacerbated the effect of demands. Schaubroeck&Merritt (1997) further found that self-efficacy moderates the effect of job strain on blood pressure such that for individuals with high self-efficacy, job control mitigated the effects of job demands.
Related to the concept of self-efficacy is the dispositional trait of proactive personality. Characteristics of proactive people include being unconstrained by situational forces, effecting environmental change, showing initiative and taking action (Bateman & Crant, 1993). Parker & Sprigg (1999) found that this characteristic, like self-efficacy, moderated the effect of job strain. The effect was such that job demands caused psychological strain except in circumstances where employees had opportunities to reduce demand—that is, they had job control, and they had proactive personality, enabling them to take advantage of this opportunity. For passive employees (those lacking a proactive personality), job control did not mitigate the effects of demands, and for such employees interventions to increase control may have little impact.
Proactive people are likely to use coping strategies that involve taking control, such as analysing the problem and taking action. Such strategies have been characterised as active coping (de Rijk et al., 1998). The role of this type of coping in moderating job strain has been examined by de Rijk et al., who found that for nurses high on active coping, job control was a stress buffer, whereas for those low on active coping, it seemed to increase the effects of job demands on emotional exhaustion.
Overall, these studies suggest that only for individuals high in personality traits such as internal locus of control, self-efficacy and with proactive styles of personality and coping are the impacts of demands reduced by job control. For those low in such characteristics then enhancing control will have little benefit and may even make matters worse. Most studies have considered the moderating effects of personality variables on psychological well-being or minor physical symptoms. There is less evidence in relation to coronary heart disease. However, Bosma et al. (1998) examined the impact of several personality variables in the relationship between job control and heart disease in the Whitehall II study of British civil servants. They suggest that psychological characteristics such as hostility, need for control, negative affectivity, angry coping and unassertive coping had little impact on the association. They acknowledge that they have not considered the effects of all possible psychological factors. For example, they excluded self-efficacy (a factor which Schaubroeck & Merritt (1997) suggest moderates the effects of stressors on blood pressure). Nevertheless, they argue that their study suggests that “increasing job control could, in principle, lower risk of heart disease for all employees” . Thus, it seems likely that different mechanisms are implicated depending on the outcome measure considered. One possibility discussed by Bosma et al. (1998) is that work stressors impact on bodily responses without conscious awareness of being under stress, hence personality styles are less important when physical well-being is the outcome. However, in the case of psychological well-being, the individual’s personality may substantially influence appraisals and, ultimately, well-being. In terms of implications, interventions which focus on the individual’s appraisals and coping (for example, by increasing self-efficacy or active coping) may be effective in reducing psychological distress among workers lacking in job control. However, based on current research evidence, this may be less likely to have an impact on physical outcomes such as heart disease.
Individual differences inwork motivation and needs are seldom considered as moderators of the effect of job strain although de Rijk et al. (1998) found that need for control did not have any moderating effect. However, other kinds of needs and motivation may be important moderators. For example, Homer et al. (1990) used the model to predict women’s risk of delivering preterm, low-birth-weight babies. They found that women working in jobs high in demand and low in control were more likely to deliver such babies than women in other jobs, but only where they did not want to remain working.
Unlike Karasek’s model, the moderating effect of needs is built into the job characteristics model in the form of the variable growth need strength (GNS). This variable assesses the need for personal accomplishment and for learning and development. While there have been inconsistent findings (Roberts & Glick, 1981), meta-analyses support the importance of this variable (Loher et al., 1985; Spector, 1985). For example, Loher et al. (1985) found that the relationship between job characteristics and job satisfaction was stronger for those employees higher in GNS. More recently, Champoux (1991) looked in more detail at relationships and found different patterns of relationship dependent on level of GNS. Those with high levels responded positively to enriched jobs, as predicted; however, distinctly negative responses were found in individuals low in GNS.
More recent work by Landeweerd & Boumans (1994) looked at need for autonomy as a moderator (a variable which they consider to be close to GNS) in a study which used the JDS to predict both satisfaction and health in nurses. They found that perceived autonomy was related to job satisfaction and health complaints but not to absenteeism. When the moderating effect of preference for autonomywas added they found that more job autonomy leads to increased absenteeism in nurses with relatively little preference for autonomy. No significant relationship was found for those who have greater preference for autonomy. Overall, therefore, notwithstanding the indications that high levels of control are generally associated with positive outcomes, individual differences do seem to be important, and for some people increasing autonomy may actually be related to negative outcomes.
Gender
Many early studies examining job control focused exclusively on men’s work and health, and although studies have increasingly looked at gender differences, it remains unclear whether effects are the same for women. Schnall et al. (1994), in their review focusing on CVD, found that in eight out of eleven studies in which comparisons between men and women could be made effect sizes were similar for both men and women. While conflicting evidence still exists, a number of more recent studies have suggested that effects of demands and control may be somewhat lower for women than for men. For example, Weidner et al. (1997) found that having a high-demand/low-control jobwas unrelated to standard coronary risk factors in both sexes but that it was related to increased medical symptoms and health damaging behaviour in a sample of men but not women. Unlike Weidner et al., Wamala et al. (2000) found that even after controlling for standard risk factors, women in the lowest occupational class had a heart disease risk more than twice that of executive and professional women. However, while job control did contribute to this risk, they concluded that neither lack of job control nor the combination of low demand and high control made a substantial contribution. They argue that the impact of such factors is much less for women than for men, perhaps because, for women, job control may not “adequately capture all the negative aspects of their jobs”. Furthermore, women may face multiple stressors, including a range of non-work stressors. This point is reinforced by Brisson et al. (1999), who found that a combination of family responsibilities and high-strain jobs had a greater effect on the blood pressure of white-collar women than exposure to either factor alone. Similar patterns emerges for psychological well-being. Studies reviewed by Van der Doef & Maes (1999) also find less support for the effects of low control and high demands for psychological health forwomen. However, not all studies support this view. For example, Mausner-Dorsch & Eaton (2000) found that job strain was more strongly related to major depression in women.
Overall, when looking at redesigning work for women, employers may need to consider a wider range of influences on psychological well-being.
HAS JOB CONTROL RESEARCH HELPED GUIDE INTERVENTIONS AND JOB REDESIGNS?
A startling feature of Karasek’s model is that despite the fact that it was explicitly designed to aid job redesign, as far as can be ascertained from the published literature, it has had minimal impact in this area. Instead, it has had huge impact in terms of enabling dimensions of work to be incorporated in medical and epidemiological studies investigating the effects of work on health. As a result we now have a large literature providing quite convincing evidence about the negative effects of job control for health, but little use of the model to guide job design.
One reason why this may be so is that the construct of control included in psychological theories tends not to be specific enough to guide interventions. For example, Reynolds (1997) argues that the concept of job control is “somewhat diffuse” and that within a single organisation different individuals will have different levels of control over different aspects of work, as well as different preferences. Reynolds further suggests that we do not have sufficiently well-developed methods for bringing about changes in organisations. These factors help explain her findings in a study comparing an organisational change intervention (increasing control) and a counselling scheme. Reynolds found that neither had any influence on people’s perceptions of work stressors. However, the counselling intervention, but not organisational change, led to improvements in psychological well-being.
A further reason that the model may not be used to guide interventions in practice may be due to its emphasis on such limited aspects of work. It may be clear to employers that problems in a particular occupational group are related to a much wider range of variables (Jones et al., 1998).
Intervention studies that do aim to enrich jobs by increasing control have had mixed results. They also highlight difficulties with both implementing these kind of changes and assessing their effectiveness in the context of rapidly changing organisations (Landsbergis & Vivona-Vaughan, 1995; Maes et al., 1998). For example, Landsbergis & Vivona- Vaughan in the USA (1995) used an intervention based on a range of approaches, including Karasek’s model, to reduce stress in a public service agency. Two matched pairs of departments were assigned to either a treatment or a waiting list control group. The intervention involved employees participating in problem solving committees. They identified stressors and developed action plans to reduce them and to encourage and assist management to implement changes. Priority stressors included such factors as uneven or repetitive workload and poor communication. At the end of one year there were mixed results in one department and negative or negligible impact in the other. It seems likely that the failure of the intervention can be attributed to the fact that it was only department wide while workers were also affected by a range of organisational changes. In this case these included a major agency reorganisation without any employee or union involvement. This produced frustration and disappointment. Both departments lost directors who had supported the changes and some planned changes were not completed. This study clearly demonstrates the wide range of impediments to this kind of organisational change.
It is possible, however, that although employers have not explicitly used the demand– control model, they have nevertheless taken on board the concept of control as a necessary part of job design. The frequent rhetoric of empowerment and the incorporation of control concepts in the management literature suggests that this might be the case. For example, Landsbergis et al. (1999) suggest that new working methods such as “lean production” incorporate total quality management approaches and multi-skilling, techniques which are described in texts as involving increased employee control. However, Karasek (2001) considers that such job enriching approaches are often also accompanied by tougher managerial control. While research is limited on the impact of these new methods of working, Landsbergis et al. (1999) reviewed 38 studies which look at the impact of a range of new work systems and conclude that there is little to suggest that they empower employees. They argue that job control typically remains low while pace of work increases—creating highstrain jobs in Karasek’s terms. Overall, a recent report by Merlli´e & Paoli (2001), which draws on surveys spanning Europe over the period from 1990 to 2001, states that while work intensity has grown, work control has not increased significantly. More specifically, they suggest that increases in employee control from 1990 to 1995 were not sustained in the following five years. In fact, some groups, such as plant and machine operators and sales and service workers, report a decline in the control they have over work.
Evidence for interventions based on the JCM is similarly unimpressive. For example, Kelly (1992) reviewed longitudinal studies of 31 field experiments in job redesign, all of which changed one or more of the dimensions of the JCM (i.e. not necessarily autonomy). They found only limited support for the model, with job redesign leading to significant improvements in job satisfaction in only 17 out of 30 instances. However, where employees perceived an improvement in job content they were more likely to experience increased job satisfaction (though not necessarily motivation or performance). Others have also found inconsistent results in predicting other psychological well-being outcomes. For example, Wall et al. (1986) studied the introduction of semi-autonomouswork groups in a longitudinal study and found that while there were increases in extrinsic satisfaction, there were no effects on mental health. Briner & Reynolds (1999) reviewed the evidence for job redesign interventions generally and concluded that there is limited evidence for their effectiveness, and effects are not uniformly positive. They attribute much of this failure to theoretical limitations.
It is both a strength and a limitation of models such as the demand-discretion model and the job characteristics model that they try to provide simple parsimonious models to fit all situations. By necessity they ignore job-specific factors (Jones et al., 1998) and they ignore contextual factors such as social class (Muntaner & O’Campo, 1993) or organisational factors (Cordery & Wall, 1985). Increasingly, there are calls for much more explicit theories to explain particular phenonoma (Briner & Reynolds, 1999) or to apply to particular occupational groups (Sparks & Cooper, 1999). It is becoming clear that simple parsimonious theories which try to explain a broad range of outcomes can only take us so far in indicating the likely impact of stressors. In the applied context, we need to know what particular specific stressors lead to specific outcomes in particular situations. Theoretical developments towards more specific job control constructs and measures are a helpful move in this direction.
Tags: anxiety, Demand Control Model, depression, GUIDE INTERVENTIONS, JOB STRAINS, Job Control, JOB CONTROL AND STRAINS, JOB REDESIGNS, job satisfaction, job specific factors, Karasek’s model of job control, Locus of Control, Personality Variables, psychological impacts of job strain, Psychological Well-Being, self efficacy