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Karasek's (1979) job demands-control model is one of the most widely studied models of occupational stress (de Lange, Taris, Kompier, Houtman, & Bongers, 2003). The key idea behind the job demands-control model is that control buffers the impact of job demands on strain and can help enhance employees’ job satisfaction with the opportunity to engage in challenging tasks and learn new skills (Karasek, 1979). Most research on the job demands-control has been inconsistent (de Lange et al., 2003; Van Der Deof & Maes, 1999), and the main reasons cited for this inconsistency are that different variables have been used to measure demands, control, and strain, not enough longitudinal research has been done, and the model does not take workers’ individual characteristics into account (Van Der Deof & Maes, 1999). To address these concerns, expansions have been made on the model such as integrating resources, self-efficacy, active coping, and social support into the model (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001b; Johnson & Hall, 1988; Demerouti, Bakker, de Jonge, Janssen, & Schaufeli, 2001a; Landsbergis, Schnall, Deitz, Friedman, & Pickering, 1992). However, researchers have only been partially successful, and therefore, to continue reducing inconstencies, we recommend using longitudinal designs, both objective and subjective measures, a higher sample size, and a careful consideration of the types of demands and control that best match each other theoretically.

Nursing comprises interactions with patients which may require emotional labor. This study clarifies the relation of emotional labor with the three burnout dimensions within the context of the Demand Control Support model in nurses. We used the Dutch Questionnaire on Emotional Labor (D-QEL) to measure surface acting, deep acting, suppression, and emotional consonance. In line with other studies, job characteristics were significantly related to emotional exhaustion and surface acting was significantly related to emotional exhaustion and depersonalization. Emotional consonance, the situation where somebody effortlessly feels the emotion that is required, is related to personal accomplishment.

This chapter examines employee learning behavior as a function of work characteristics. Karasek’s Demand-Control (DC) model proposes that high job demands and high job control are conducive to employee learning behavior. A review of 18 studies revealed that whereas most of these supported these predictions, methodological and conceptual shortcomings necessitate further study. Perhaps the most important weakness of the DC-based research on learning is that the conceptual foundations of the DC model regarding employee learning behavior are quite rudimentary, while the role of interpersonal differences in the learning process is largely neglected. The second part of this chapter explores the relationship between work characteristics and learning behavior from the perspective of German Action Theory (AT). AT explicitly discusses how work characteristics affect learning behavior and assigns a role to interpersonal differences. We conclude by presenting a model that integrates action-theoretical insights on learning with DC-based empirical results.

Recent years have seen an explosion in the study of emotions in organizations, and although emotions play a central role in the job stress process, their role is largely neglected in empirical stressor–strain studies. Our chapter aims to build consensus in the literature by showing that discrete emotions provide a mechanism through which stressors exert their impact on well-being. By examining a larger domain of stressors, emotions, and well-being, we begin to develop and expand upon the nomological network of emotions. In an effort to build on the job demands–resources (JD-R) model, which includes both job demands (i.e., negative stimuli such as time pressure) and resources (i.e., positive stimuli such as autonomy), we include both negative and positive discrete emotions with the expectation that negative emotions will generally be linked to demands and positive emotions will be linked to resources. We also propose that there may be circumstances where demands trigger negative discrete emotions and lead to greater experienced strain, and conversely, where resources arouse positive discrete emotions, which would positively affect well-being. The model in our chapter sheds light on how discrete emotions have different antecedents (i.e., job demands and resources) and outcomes (e.g., satisfaction, burnout, performance), and as such, respond to calls for research on this topic. Our findings will be of particular interest to organizations where employees can be trained to manage their emotions to reduce the strain associated with job stressors.

This chapter combines quantitative studies of the connections between stressors and performance in accounting settings and identifies the mediators and moderators of stressors–performance relationships. Using meta-analyses and path analyses, this research compiles 72 studies to investigate the relationships of stressors with accountant and auditor performance. As hypothesized, bivariate meta-analyses results indicate that work-related stressors negatively affect performance, and burnout and stress are negatively related to performance, whereas motivation is positively related to performance. Moreover, a meta-analytical structural equation modeling indicates that role stressors have significant direct and indirect effects (through burnout and stress) on job performance. Accumulation of multiple samples through meta-analysis bolsters statistical power compared to single-sample studies and thus reveals the sign of residual direct effects of role stressors on job performance in accounting settings.

Most research on the work conditions and family responsibilities associated with work-family conflict and other measures of mental health uses the individual employee as the unit of analysis. We argue that work conditions are both individual psychosocial assessments and objective characteristics of the proximal work environment, necessitating multilevel analyses of both individual- and team-level work conditions on mental health.

This study uses multilevel data on 748 high-tech professionals in 120 teams to investigate relationships between team- and individual-level job conditions, work-family conflict, and four mental health outcomes (job satisfaction, emotional exhaustion, perceived stress, and psychological distress).

We find that work-to-family conflict is socially patterned across teams, as are job satisfaction and emotional exhaustion. Team-level job conditions predict team-level outcomes, while individuals’ perceptions of their job conditions are better predictors of individuals’ work-to-family conflict and mental health. Work-to-family conflict operates as a partial mediator between job demands and mental health outcomes.

Our findings suggest that organizational leaders concerned about presenteeism, sickness absences, and productivity would do well to focus on changing job conditions in ways that reduce job demands and work-to-family conflict in order to promote employees’ mental health.

We show that both work-to-family conflict and job conditions can be fruitfully framed as team characteristics, shared appraisals held in common by team members. This challenges the framing of work-to-family conflict as a “private trouble” and provides support for work-to-family conflict as a structural mismatch grounded in the social and temporal organization of work.

The nature of work has changed in the past 30 years but we do not know what these changes have meant for worker job stress. In this chapter we compare data from three surveys of the quality of work life from 1972 to 2002. At the most general level, work today is less stressful than it was in 1972. Workers report fewer job demands, more decision latitude, less job strain, more job security and greater access to job resources and job support. However, these changes have not affected all workers equally. Women, those with less education, non self-employed workers, blue collar workers and workers in manufacturing industries showed the greatest decreases in job stress although levels of job stress remain higher than for comparison groups (men, college educated, white collar, service workers). Changes were not always linear across time suggesting that some aspects of job strain are sensitive to economic cycles.

New developments in concepts and approaches to job stress should incorporate all relevant types of resources that promote well-being and health. The success resource model of job stress conceptualizes subjective success as causal agents for employee well-being and health (Grebner, Elfering, & Semmer, 2008a). So far, very little is known about what kinds of work experiences are perceived as success. The success resource model defines four dimensions of subjective occupational success: goal attainment, pro-social success, positive feedback, and career success. The model assumes that subjective success is a resource because it is valued in its own right, triggers positive affect and emotions (e.g., pleasure, cf., Weiss & Cropanzano, 1996), helps to protect and gain other resources like self-efficacy (Hobfoll, 1998, 2001), has direct positive effects on well-being (e.g., job satisfaction, cf., Locke & Latham, 1990) and health (Carver & Scheier, 1999), facilitates learning (Frese & Zapf, 1994), and has an energizing (Locke & Latham, 1990, 2002) and attention-directing effect (Carver, 2003), which can promote recovery by promoting mental detachment from work tasks in terms of absence of job-related rumination in leisure time (Sonnentag & Bayer, 2005).

The model proposes that success is promoted by other resources like job control (Frese & Zapf, 1994) while job stressors, like hindrance stressors such as performance constraints and role ambiguity (LePine, Podsakoff, & LePine, 2005), can work against success (Frese & Zapf, 1994). The model assumes reciprocal direct effects of subjective success on well-being, health, and recovery (upward spiral), and a moderator effect of success on the stressor–strain relationship. The chapter discusses research evidence, measurement of subjective occupational success, value of the model for job stress interventions, future research requirements, and methodological concerns.

We explore: (1) the effects of work unit pressure on employees’ satisfaction with work–family balance (S-WFB); (2) the effects of individual-level job and family pressures on S-WFB; and (3) the extent to which schedule control moderates the negative influences of work unit pressure and other demands on employee S-WFB – among employees in a large healthcare system.

The data come from employee responses to the baseline survey (n = 3,950) administered in September 2012, and from administrative unit-level data (445 units) showing the extent to which units were “on-budget” (within 5 percent), “over-budget,” or “under-budget.”

Practices associated with cost containment in a healthcare system of 10,000 employees in the United States appear to have a negative impact on employee S-WFB. Working in a unit that is “under-budget” is negatively associated with individual S-WFB. Employees with high job demands, longer hours, responsibilities for children and/or adults, also reported lower S-WFB than employees without these characteristics.

Research is limited by lack of measures specific to healthcare workers, the use of baseline data only, and sample size for some of the analyses.

Schedule control makes a difference even under high work pressure. The lack of interactions among variables that typically moderate relationships between work pressures and S-WFB suggests the need for more support for healthcare workers under the strain of cost containment.

We include an objective indicator of unit-level job pressures on individual employees, thus identifying specific ways that work stress affects S-WFB.