**1. Introduction**

The world of work is undergoing permanent changes, which imply new challenges for organizations and individuals [1]. In globalized markets, organizations need to be more flexible, less hierarchical, and continually reorganizing to maintain competitiveness and prosperity. Furthermore, changes in the world of work are enabled and accelerated by digitization processes [2–4]. On the one hand, new technologies—such as information and communication technologies—are introduced as a strategy for adapting to constant market pressure. On the other hand, new technologies are again the basis for fundamental reorganization within organizations [5]. This results in a cycle of changes and the developments occur at an increased speed [3,4]. Overall, the world of work becomes more flexible, more unpredictable, and changes at an accelerated pace.

All these phenomena involve altered job demands for employees and lead to changes in job quality. Besides an intensification of work effort [6–8], as well as planning and decision-making demands [9–11], increases in cognitive and learning demands at work are discussed as outcomes of change in the working world [2,12,13]. Generating new knowledge, as well as problem solving, has become an integral part of employees' work tasks [14,15]. Furthermore, employees have to acquire new skills constantly in order to adapt to rapidly changing demands at work [12]. Therefore, maintaining one´s skills has become more difficult due to increasing skill variety in recent years [11] and employees are more frequently confronted with tasks they have not learned or they are not familiar with. Coping with the new requirements and tasks is becoming increasingly relevant, not only for everyday working life but also for personal development, regarding competencies and skills learned in order to maintain employability [16–18].

In the past decades, research on the quality of work has often focused on work intensification and autonomy [19], showing that an appropriate balance between work requirements and autonomy is particularly important for a good quality of work, and in turn for employee well-being [20–27]. However, empirical studies on learning and cognitive demands are scarce and so far little is known about how these demands relate to the well-being of employees. The existing studies predominately focus on learning demands and point to an ambivalent picture regarding the relationship between these demands and employee well-being [13,28]. Moreover, the studies are based on non-representative survey data with small sample sizes, rendering it difficult to generalize the findings for the entire working population. There is also no distinct definition between learning or cognitive demands and both terms are largely used interchangeably. While both refer to confrontation with new tasks at work and the requirement to acquire new knowledge, learning demands can be understood as a superordinate term that includes cognitive demands [29]. In general, learning demands can be defined as demands which "require employees to acquire knowledge and skills that are necessary to perform their jobs effectively" [13]. Cognitive demands involve confrontation with new tasks, unpredictable developments, and solving routine problems [28]. Using this definition, it remains unclear whether an individual learning process is achieved or not and which demands contribute to the cognitive development of the employees [30].

In this study, we add to the existing literature and empirically explore the relationship between cognitive demands and employee well-being. The analyses are based on the German BIBB/BAuA Employment Survey 2018, a large representative cross-section providing recent data on the work and health situation of the working population in Germany (approximately 20,000 respondents). In a first step, we explore the determinants of cognitive demands in order to identify groups frequently facing cognitive demands at work. To measure cognitive demands, we considere three different variables: facing new tasks, improving work, and doing unlearned things. Analyzing the status quo is crucial in order to identify groups of workers with an increased need for additional training or assistance to cope with new requirements. This is of particular relevance as cognitive demands will likely become more prominent in the future and will gradually affect the whole working population. In a second step, we analyze the relationship between cognitive demands—also in interaction with other work demands—and employee well-being. We consider indicator variables for fatigue, self-rated health, and job satisfaction to measure employee well-being.

#### **2. Work–Stress Theories and the Role of Cognitive Demands**

Researchers developed different theoretical models to describe the relationship between different working conditions and employee health (e.g., Job Demands Control Model (JDC) [25], Job Demands-Resources Model (JD-R) [31], or Action Regulation Theory (ART) [32]. While these models consider various working conditions, only a few explicitly include cognitive demands. In the context of our study, two models are of particular importance. Firstly, we rely on the integrated model of psychosocial work characteristics and the consequences of job strain introduced by Glaser et al. [28]. Based on various theories and models [33–35] on the impact of working conditions on attitudes and health, the authors [28] developed a model embedding learning demands, work-related resources, and job stressors in order to predict processes of learning, performance, and health impairment. An important assumption of this model—in line with Karasek [25]—is that not all working conditions should be defined as job demands, regardless of their impact on employee well-being. When cognitive demands are predisposed as working conditions that trigger effort-driven processes and are thus associated with physical and psychological costs, the potential positive effects of cognitive demands for skill acquisition and performance are neglected. The absence of cognitive demands at work could also be negatively related to employee well-being and motivation [28]. Therefore, the authors combine the assumptions of different work-stress theories, including the challenge–hindrance framework that distinguishes between challenge and hindrance demands [36]. Hindrance demands are supposed to reduce personal growth and promote strain and health impairments [36,37]. Challenge demands also

trigger strain, but they are also supposed to have a motivating effect and enable employees to learn and to further develop their own personality. The classification of job demands as challenge or hindrance demands depends on the individual assessment of employees. Therefore, the cognitive appraisals (challenge and hindrance appraisal) of individuals are the important explanatory mechanisms behind the positive and negative effects of job demands on a workers well-being [13,38–40]. In line with this framework, Glaser et al. [28] distinguish between beneficial learning (e.g., task variety and cognitive demands), work-related resources (e.g., autonomy and social support), and stressors or adverse conditions (e.g., overload and conflicts). The proposed model predicts a positive effect of learning demands on personality development and a negative effect of stressors or adverse conditions on health. Empirical analyses exploring this model indicate that problem solving and learning requirements are crucial for creativity and motivation. Other studies confirm these results. For instance, Prem et al. [13] find a significant relationship between learning demands and personal development. Personal development was in turn positively associated with vitality in this study. Furthermore, Crawford et al. [41] show that the correlation between work demands and engagement strongly depends on the specific type of work demand. Demands that were appraised by workers as hindrance were negatively associated with engagement and demands that were appraised by workers as challenges were positively associated with engagement. However, the study of Glaser et al. [28] also showed that learning requirements may be detrimental to health if accompanied by work overload. The authors thus demonstrate—in line with other studies [30,42]—the importance of the interaction of cognitive demands with other working conditions for employee well-being. Based on the model of Glaser et al. [28], we assume that cognitive demands might be both positively and negatively related to the personal development of employees, and in turn also to their attitudes and health. Furthermore, we assume that autonomy and work intensification moderate the effect of cognitive demands on employee well-being.

Secondly, person–environment fit theories (P–E fit) are crucial to explain why cognitive demands at work could have different consequences for different groups of employees. All P–E fit theories assume that the extent to which people fit their work environments has significant consequences (e.g., with respect to their satisfaction, performance, stress, productivity, or turnover). A better fit is associated with better outcomes [43–45]. Moreover, Kristof-Brown and Guay [46] showed that stress is a consequence of a poor person–environment fit. The fit of the individual and the environment is determined by the fulfilment of needs resulting in favorable attitudes, such as job satisfaction or organizational commitment [47,48]. In addition, P–E fit is a reciprocal and ongoing process whereby individuals shape their environments and environments shape individuals [49]. Work environments are associated with cognitive demands to varying degrees. Furthermore, individuals also differ in terms of their needs at work and require different conditions in order to achieve favorable attitudes. In line with the P–E fit theories, we suppose that cognitive demands at work do not equally meet the needs of different employment groups. Consequently, we expect that the probability of perceiving cognitive demands at work as stressful varies across different groups of employees (e.g., with respect to different socio-demographic groups, such as gender or educational level).
