Although remote working can involve positive outcomes both for employees and organizations, in the case of the sudden and forced remote working situation that came into place during the COVID-19 crisis there have also been reports of negative aspects, one of which is technostress. In this context of crisis, leadership is crucial in sustainably managing and supporting employees, especially employees with workaholic tendencies who are more prone to developing negative work and health outcomes. However, while research on the role of the positive aspects of leadership during crises does exist, the negative aspects of leadership during the COVID-19 crisis have not yet been studied. The present study aimed to explore the role of authoritarian leadership in a sample of 339 administrative university employees who worked either completely from home or from home and the workplace. The study examined the moderating effect of a manager on this relationship and the connections between workaholism and technostress through conditional process analysis. Results pointed out that high authoritarian leadership had an enhancing effect, whereas low authoritarian leadership had a protective effect on the relationship between workaholism and technostress, only in the group of complete remote workers. Thus, authoritarian leadership should be avoided and training leaders to be aware of its effect appears to be essential. Limitations, future directions for the study, and practical implications are also discussed.

Recent contributions have reported sleep disorders as one of the health impairment outcomes of workaholism. A possible factor affecting the sleep-wake cycle might be the intensive use of smartphones. The current study aimed to explore the role of intensive smartphone use in the relationship between workaholism and the sleep-wake cycle. Two serial multiple mediation models were tested on a sample of 418 employees, who filled self-report questionnaires measuring workaholism, use of smartphones, sleep quality and daytime sleepiness, using conditional process analysis for testing direct and indirect effects. Results supported our hypotheses regarding two serial multiple mediation models—that intensive smartphone use and poor sleep quality mediated the relationship between workaholism and daytime sleepiness, and that smartphone use and daytime sleepiness mediated the relationship between workaholism and poor quality of sleep. Although the use of a cross-sectional design and the snowball technique for collecting data can be considered as possible limitations, the current study is one of the first to document the potential detrimental role of the intensive smartphone use on the workaholism-sleep disorders relationship.

Decision-making autonomy may have played a crucial role in protecting, or on the contrary, intensifying the onset of negative psychological outcomes for workers with roles with responsibilities during the lockdown due to the Covid-19 crisis. The present study analyzed the emotional dimension of workaholism in relation to emotional exhaustion, considering decision-making autonomy as a moderator of this relationship, in a sample of 101 managers and freelancers in the middle of the lockdown in Italy (early April 2020). Results showed that the relationship between negative (workaholic) emotions and emotional exhaustion was moderated by decision-making autonomy and this moderation differed for managers and freelancers. In particular, the results showed that in the target of managers high levels of negative emotional experiences related to workaholism and low decision-making autonomy are associated with higher levels emotional exhaustion, while high levels of emotional experiences linked to workaholism and high decision-making autonomy produced significantly lower levels of emotional exhaustion. On the contrary, low levels of job autonomy were associated to higher level of emotional exhaustion when negative (workaholic) emotions were low for the freelancers. Limitations are related to the limited sample and the cross-sectional nature of the study. Practical implications lie in considering decision-making autonomy as a double-edged sword, such that when low it could be a risk for managers and when high it could be a risk for freelancers.

Summary: Studies on sleep during the Covid‐19 pandemic have mostly been conducted during the first wave of contagion (spring 2020). To follow up on two Italian studies addressing subjective sleep features during the second wave (autumn 2020), here we assess sleep during the third wave (spring 2021) in a sample of healthy adults from Campania (Southern Italy). Actigraphic data (on 2 nights) and the Pittsburgh Sleep Quality Index were collected from 82 participants (40 F, mean age: 32.5 ± 11.5 years) from 11 March to 18 April 2021, when Campania was classified as a “red zone”, i.e. it was subjected to strict restrictions, only slightly looser than those characterizing the first national lockdown (spring 2020). Although objective sleep duration and architecture appeared in the normal range, the presence of disrupted sleep was indexed by a relevant degree of sleep fragmentation (number of awakenings ≥ 1 min: 12.7 ± 6.12; number of awakenings ≥ 5 min: 3.04 ± 1.52), paralleled by poor subjective sleep quality (Pittsburgh Sleep Quality Index global score: 5.77 ± 2.58). These data suggest that the relevant subjective sleep impairments reported during the first wave could have relied on subtle sleep disruptions that were undetected by the few objective sleep studies from the same period. Taken together with sleep data on previous phases of the pandemic, our findings show that the detrimental effects on sleep determined by the initial pandemic outbreak have not abated across the subsequent waves of contagion, and highlight the need for interventions addressing sleep health in global emergencies.

While university students have experienced increased stress, anxiety, and study obsession (studyholism) during the COVID-19 emergency, supportive university environments and academic self-efficacy (ASE) were found to be protective factors. However, the perception of overstudying could have impaired ASE’s protection against studyholism, akin to workaholism. Following the job-demands resource model, this contribution examines the moderating roles of study load and teaching staff support in the relationship between ASE and exhaustion, mediated by studyholism. 6736 students from 11 universities (69.8% females; Mean age 24.67 years) completed a self-report survey concerning various academic and life aspects. Results showed that ASE was partially mediated by studyholism in its negative relationship with exhaustion. Both study load and support moderate this relationship, although the interaction effect between studyholism and ASE is positive. Nonetheless, ASE plays a protective role for all levels of study load and support, while studyholism is confirmed to have a significant impact on exhaustion, both directly and through its mediating role. Considering the high scores of both studyholism and exhaustion in this sample, the enhancement of ASE should be complemented by teacher support centered around opportunities to review study strategies with the students and strong attention to preventive measures, such as in itinerant evaluation, which could enhance both the perception of positive support and strengthen ASE.

The rapid diffusion of Artificial Intelligence (AI) is transforming job characteristics, raising important questions about how to implement these technologies in organizations in ways that support employee well-being and performance. Drawing on the High-Involvement Management framework, this study examined employee-centered Artificial Intelligence implementation (ECAII) practices (defined as transparent communication, consultation, and training initiatives) as strategic levers to foster positive employee outcomes during Artificial Intelligence-driven transformations. Survey data were collected from 168 Italian white-collar employees who actively used Artificial Intelligence in their work. Structural equation modeling was employed to test direct and indirect relationships among employee-centered Artificial Intelligence implementation practices, work meaningfulness, job satisfaction, and job performance, as well as the moderating role of personal attitudes toward AI. Results showed that employee-centered Artificial Intelligence implementation practices had significant direct effects on both job satisfaction and performance, as well as indirect effects through work meaningfulness. Latent moderated mediation analyses further revealed that these indirect effects were stronger among employees with more positive attitudes toward Artificial Intelligence. Overall, the findings highlighted the importance of employee-centered strategies for enhancing meaningfulness and fostering positive outcomes during technological change. This study contributed to Human Resource Management (HRM) and meaningful work research by extending classic theoretical frameworks to Artificial Intelligence-enabled workplaces. Furthermore, from a practical perspective, our findings provided valuable guidance for organizations by highlighting the importance of transparent communication, employee involvement, and targeted training in reducing uncertainty and helping employees perceive their roles as relevant during the implementation of Artificial Intelligence.