Buono Carmela, Farnese Maria Luisa, Spagnoli Paola
Department of Psychology, University of Campania "Luigi Vanvitelli", 81100 Caserta, Italy.
Department of Psychology, Sapienza University of Rome, 00185 Roma, Italy.
Behav Sci (Basel). 2023 Jul 17;13(7):599. doi: 10.3390/bs13070599.
During the pandemic, the occurrence of extreme working conditions (e.g., the sudden shift to remote work, isolation, and the slowdown of the work processes) exacerbated several phenomena, such as increased workaholism and stress due to technological devices; that is, technostress. Literature on the onset of these phenomena during the pandemic highlighted a possible interplay among them; however, there is still a dearth of knowledge about the direction of the relationship between workaholism and technostress. The present study assessed the relationship between workaholism and technostress through a two-wave cross-lagged study using path analysis in SEM (Structural Equation Modeling). The study was conducted in Italy during the pandemic, and a total of 113 Italian employees completed the online survey at each wave. Results showed that workaholism at Time 1 was a significant predictor of technostress at Time 2 (β = 0.25, = 0.049), while the reversed causation was not supported (β = 0.08, = 0.22). These findings may help employees and organizations to better understand the phenomena of technostress and workaholism and develop strategies to prevent the consequences of excessive and compulsive work and to improve the balanced use of technology for their daily activities.
在疫情期间，极端工作条件的出现（例如，突然转向远程工作、隔离以及工作流程放缓）加剧了几种现象，比如因技术设备导致的工作狂行为增加和压力增大，即技术压力。关于疫情期间这些现象发生情况的文献强调了它们之间可能存在相互作用；然而，对于工作狂行为和技术压力之间关系的方向，仍然缺乏相关知识。本研究通过在结构方程模型（SEM）中使用路径分析的两波交叉滞后研究，评估了工作狂行为与技术压力之间的关系。该研究在疫情期间的意大利进行，共有113名意大利员工在每一波次完成了在线调查。结果显示，第1阶段的工作狂行为是第2阶段技术压力的显著预测因素（β = 0.25，p = 0.049），而反向因果关系未得到支持（β = 0.08，p = 0.22）。这些发现可能有助于员工和组织更好地理解技术压力和工作狂行为现象，并制定策略来预防过度和强迫性工作的后果，以及改善在日常活动中对技术的平衡使用。
