No abstract

Leader negative emotional expression (LNE) has been proposed to contribute to follower performance; however, less is known about employees’ work-related affective state and the characteristics of cognitive attribution during the underlying process. Drawing on the emotions as social information model, we explore the mediating effect of work engagement and the moderating effect of internal locus of control (ILC). The data comprises 315 leader–follower dyads. The results reveal that LNE can decrease follower performance and that work engagement mediates this effect. In addition, the direct effect of LNE on follower performance is moderated by ILC. The negative effect is stronger for employees with low levels of ILC than for those employees with high levels of ILC. Our research provides a better understanding of the internal mechanism and boundary condition of the relationship between LNE and follower performance. Implications and limitations are also discussed.

Work-related use of information and communication technologies after hours (W_ICTs) has significant impacts on both organizations and individuals. However, limited research has explored the detrimental effects of W_ICTs behavior on work-family conflict. To fill this gap, based upon the job demands-resources (JD-R) model and daily diary design with a multilevel model method, we collected 76 employees who completed a 5-day investigation, resulting in 380 observations. Our study found that engaging in W_ICTs behavior positively influenced employees’ own work role overload, which led to an increase in work-family conflict. Furthermore, we found that the positive relationship between work role overload and work-family conflict is stronger when employees’ job autonomy is at lower levels. Our findings provide strong support for the proposed moderated mediation model and extend our understanding of W_ICTs behaviors consequences.

Chronic hepatitis B is a stubborn disease afflicting mankind. Interferon alpha treatment is one of available antiviral options of treating chronic hepatitis B at present. However, the expensive treatment costs and side effects greatly hindered its application. It is useful in practice to patients suffering from hepatitis B that giving the analysis before treatment and predicting the possible effect of treatment according to the physiological mechanism and pathological condition of the patients themselves. This research focus on setting a hepatitis B auxiliary treatment model based on data mining technique which exploits the relationship between the treatment results and the characteristic of different patients. The experiment results on real data sets show that our method is effective and practicable.

Too much of a good thing: The challenge and opportunity of the inverted U.