Search results

Addressing occupational stress and fostering employee wellness helps meet a host of organizational stakeholder expectations including high quality of work life (employees), reasonable return on investment (investors), increased productivity (management), and competitiveness (owners). Despite being dynamic in nature, stress and wellness are often studied using a static perspective. One reason for the scarcity of dynamic empirical research is the limited knowledge and use of the tools available to assess change over time. To address this limitation, four tools used to assess change and dynamics of occupational stress and well-being are described: growth models, latent change score models, spectral analysis, and computational modeling. First, we begin by discussing growth curve models and then transition to latent change score models. We then expand into spectral analysis, a tool used to determine cycles of ups and downs that repeat regularly. Last, computational modeling is discussed, where computers and simulations are used to understand a dynamic process. For each tool, we give examples of how they have been used, make recommendations for future use, and provide readers with suggestions and references for how to complete analyses in software and programs, most of which are freely available (i.e., R, Vensim).

The preponderance of studies that rely on self-report for both independent (e.g. stressors) and dependent (e.g. well-being) variables is often deplored, as it creates problems of common method variance, which may lead to inflated, or even spurious, correlations and predictions. It is sometimes suggested that alternative measures should yield more “objective” information on the phenomena under investigation. We discuss this issue with regard to: (a) observational measures of working conditions; (b) physiological measures of strain; and (c) event-based “self-observation” on a micro-level. We argue that these methods are not necessarily “objective.” Like self-report, they are influenced by a plethora of factors; and measurement artifacts can easily be produced. All this can make their interpretation quite difficult, and the conclusion that lack of convergence with self-report automatically invalidates self-report is not necessarily warranted. Especially with regard to physiological measures, one has to keep in mind that they refer to a different response level that follows its own laws and is only loosely coupled with psychological responses. Therefore, replacement is not a promising way to get more reliable estimates of stressor-strain relationships. We argue instead that each method contains both substantive and error variance, and that a combination of various methods seems more auspicious. After discussing advantages and pitfalls of observational, physiological, and self-observational measures, respectively, we report empirical examples from our own research on each of these methods, which are meant to illustrate both the advantages and the problems associated with them. They strengthen the overall conclusion that there is no “substitute” for self-report (which often is necessary to be able to interpret data from other methods, most notably physiological ones). They also illustrate that collecting such data is quite cumbersome, and that a number of conditions have to be carefully considered before using them, and we report some problems we encountered in this research. Altogether, we conclude that self-report measures, if carefully constructed, are better than their reputation, but that the optimal way is to complement them with other measures.

Each of the four objectives can be applied within the military training environment. Military training often requires that soldiers achieve specific levels of performance or proficiency in each phase of training. For example, training courses impose entrance and graduation criteria, and awards are given for excellence in military performance. Frequently, training devices, training media, and training evaluators or observers also directly support the need to diagnose performance strengths and weaknesses. Training measures may be used as indices of performance, and to indicate the need for additional or remedial training.

Sales personnel play a key role in the success of organizations. These individuals present services/products to clients, manage accounts, build relationships, maintain existing business relationships, and must be available for frequent interactions with clients. Business operations are linked to external entities through these activities, suggesting sales groups play a critical role in the success of an organization. As a representative to the external market, sales personnel are subject to unique stressors due to role-specific requirements. These stressors can impact the ability of sales professionals to effectively engage with customers and manage the volatility of financial performance, especially in commission-based compensation structures. Thus, organizations can find utility in identifying sales candidates with higher levels of stress tolerance, who can handle negative client interactions, overcome lulls in sales conversions, and avoid the impact of occupational stressors on long-term sales performance. Research suggests that organizations can use personality to predict stress tolerance as a component of sales performance. To provide organizations with insights into sales-specific coping behaviors associated with stress tolerance, the authors (1) discuss stress inducing factors (stressors) associated with sales role performance, (2) review the individual differences associated with stress tolerance, (3) present personality relationships with sales performance and stress tolerance, and (4) present job-analytic support for stress tolerance competencies relevant to sales performance and criterion-related validity evidence linking personality characteristics to those behaviors. The authors conclude with a discussion around the potential for applied uses of personality in identifying sales personnel with greater likelihoods of exhibiting stress tolerant behaviors in the workplace.