Dirty work is socially constructed as physically, morally, or socially tainted, and these perceptions can shape how dirty workers understand and experience their identities. However, the processes through which the perception of taint shapes dirty workers’ identities and associated outcomes (e.g., identity ambivalence, isolation), as well as the effects of the degree of perceived taint, are not fully understood. To better understand these processes, the present study describes the development and validation of a measure that examines the experience of dirty work through workers’ perceptions of occupational taint. First, an initial pool of items was developed, based on the dirty work literature and open-ended responses describing dirty workers’ perceptions of their work. Across subsequent studies, this item pool was reduced through a series of exploratory factor analyses and evaluated the resulting factor structure using confirmatory factor analysis. These analyses provided preliminary support for a 13-item, three-factor model consisting of physical, moral, and social taint. Finally, convergent validity was examined by testing relationships between physical, moral, and social taint and stress, burnout, job satisfaction, job involvement, and intent to quit. The three-factor structure was further supported by its superior fit relative to both a two-factor model and single-factor model.
Our study examines the role of leaders in employee recovery. We hypothesize that supervisor support for recovery (between-person) will buffer the impact of daily workload (within-person) on evening psychological detachment (within-person). We tested this hypothesis with a 7-day experience sampling methodology study using data from 545 employees, 1970 valid end-of-work observations (51
As organizations increasingly adopt artificial intelligence (AI) and other advanced technologies, many workers worry about the potentially negative repercussions on the future viability and nature of one’s occupation. We hypothesize that such occupation insecurity (OCIS) is positively associated with increased moral disengagement (MD) and subsequent counterproductive workplace behaviors (CWBs). Moreover, we expect that industry-level exposure to AI will serve as a distal macro-contextual cue that amplifies worker strain responses among employees in industries whose occupational tasks and job functions are heavily exposed to AI. Using three waves of survey data from workers across 18 industry sectors with varying degrees of AI exposure, we found that OCIS was positively associated with MD, which in turn was positively associated with CWBs. As predicted, the strength of this indirect effect increased as the level of industry exposure to AI increased. By extending OCIS research into the macro domain, our findings highlight the importance of accounting for industry-level context in AI deployment decisions, as failure to do so may amplify fears of OCIS and its downstream effects on MD and CWBs, both of which can harm the organization and its human employees.
The National Institute for Occupational Safety and Health (NIOSH) has performed important functions related to the protection and promotion of the safety and health of the United States workforce for over five decades, including those related to research, education, and consultation with employers and other stakeholders. The present study explores the relationships between the level of federal investment in occupational safety and health infrastructure, operationalized as the annual NIOSH budget, and occupational injury rates, occupational fatality rates, and workforce productivity. Using archival data collected from publicly available sources including federal budget appropriations, the Centers for Disease Control, and the Bureau of Labor Statistics, we applied the autoregressive distributed lag (ARDL) model to examine both concurrent and lagged effects. We found support for a relatively short-term relationship between the annual NIOSH budget and occupational injuries, as increases in budget were associated with reductions in injury rates within around three years’ time. A non-monotonic relationship between annual budget and fatalities paints a more complex picture, with decreases observed initially at one year not being sustained. Finally, there was no relationship between the annual budget and workforce occupational injuries, with reductions in injury rates occurring around two years’ time, bolstering the argument that investments in workforce safety and health do not come at the expense of a productive workforce. Both the history and future of the occupational safety and health authority are discussed in the context of these findings.
Helping colleagues is a behavior that is common in the workplace and highly relevant for organizational effectiveness. The consequences of helping for the helper is an emerging field of research with mixed findings. Taking the potentially differential nature of reactive and proactive help into account, the present study focuses on the social consequences of help for helpers. Drawing on theory that highlights the fundamental human need to belong as central to psychological functioning, we propose that reactive help positively affects individuals’ sense of relatedness and, subsequently, affective organizational commitment, whereas the effect of proactive help depends on a characteristic of the helping exchange. Specifically, we propose that the level of perceived acceptance of the proactive help shapes the extent to which proactive help may contribute to or impair the sense of relatedness. We tested our model with a daily diary study (n = 110; k = 508) with four daily measures (before work, morning, afternoon, end of day). Multilevel path analyses support the proposed positive effect of reactive help on evening organizational commitment, mediated through afternoon experience of relatedness. The effect of proactive help depended on the extent to which helpers perceived that their help was accepted by the recipients of their help. This research underscores the distinct nature of reactive and proactive help, highlighting how helping may either support or hinder individuals to feel connected to their workplace.
