In response to the Coronavirus disease 2019 global health pandemic, many employees transitioned to remote work, which included remote meetings. With this sudden shift, workers and the media began discussing videoconference fatigue, a potentially new phenomenon of feeling tired and exhausted attributed to a videoconference. In the present study, we examine the nature of videoconference fatigue, when this phenomenon occurs, and what videoconference characteristics are associated with fatigue using a mixed-methods approach. Thematic analysis of qualitative responses indicates that videoconference fatigue exists, often in near temporal proximity to the videoconference, and is affected by various videoconference characteristics. Quantitative data were collected each hour during five workdays from 55 employees who were working remotely because of the COVID-19 pandemic. Latent growth modeling results suggest that videoconferences at different times of the day are related to deviations in employee fatigue beyond what is expected based on typical fatigue trajectories. Results from multilevel modeling of 279 videoconference meetings indicate that turning off the microphone and having higher feelings of group belongingness are related to lower postvideoconference fatigue. Additional analyses suggest that higher levels of group belongingness are the most consistent protective factor against videoconference fatigue. Such findings have immediate practical implications for workers and organizations as they continue to navigate the still relatively new terrain of remote work.

[Correction Notice: An Erratum for this article was reported in Vol 101(7) of Journal of Applied Psychology (see record 2016-32115-001). In the article the affiliations for Emily D. Campion and Matthew H. Reider were originally incorrect. All versions of this article have been corrected.] Emerging advancements including the exponentially growing availability of computer-collected data and increasingly sophisticated statistical software have led to a "Big Data Movement" wherein organizations have begun attempting to use large-scale data analysis to improve their effectiveness. Yet, little is known regarding how organizations can leverage these advancements to develop more effective personnel selection procedures, especially when the data are unstructured (text-based). Drawing on literature on natural language processing, we critically examine the possibility of leveraging advances in text mining and predictive modeling computer software programs as a surrogate for human raters in a selection context. We explain how to "train" a computer program to emulate a human rater when scoring accomplishment records. We then examine the reliability of the computer's scores, provide preliminary evidence of their construct validity, demonstrate that this practice does not produce scores that disadvantage minority groups, illustrate the positive financial impact of adopting this practice in an organization (N ∼ 46,000 candidates), and discuss implementation issues. Finally, we discuss the potential implications of using computer scoring to address the adverse impact-validity dilemma. We suggest that it may provide a cost-effective means of using predictors that have comparable validity but have previously been too expensive for large-scale screening. (PsycINFO Database Record

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Despite sizable but varying estimates of multiple jobholding (MJH) and decades of research across disciplines (e.g., management, economics, sociology, health and medicine), our understanding of MJH is rather limited. The purpose of this review is to provide a coherent synthesis of the literature on MJH, or working more than one job. Beginning with a discussion of the motivations and demographic predictors that forecast MJH, we note a distinct divide between the research that predicts MJH and the research that examines outcomes, with few studies exploring how motivations might relate to MJH experiences and outcomes. Another significant observation in this review is the inconsistency of findings across and within disciplines regarding whether MJH is depleting or enriching. Using this framework to organize our review, we attempt to reconcile the generally mixed results by presenting research on mechanisms and boundary conditions of MJH to explain how and when multiple jobholders (MJHers) are depleted or enriched. By integrating findings from the literature, we are able to articulate more clearly the paths of depletion and enrichment and discuss how push versus pull-based motivations to hold multiple jobs likely predict these pathways. Finally, we provide a strategic agenda highlighting areas where additional research is urgently needed to equip scholars with practical knowledge on how to help MJHers manage their multiple work roles and how to help organizations manage MJHers.