Serving followers or family? A trickle down model of how servant leadership shapes employee work performance

So far, little research attention has been given to the effects of servant leadership displayed by leaders across an organization’s hierarchy. Using a matched sample of employees and their supervisors from three companies in the Dominican Republic, multilevel structural equation modeling results show that manager servant leadership trickles down to inspire supervisor servant leadership, which increases employee prosocial motivation and subsequent work performance. Furthermore, supervisor family motivation buffered the trickle-down mechanism, so that the effect on employee work performance is weaker for supervisors with high levels of family motivation. Our research sheds light on how and when servant leadership tickles down to shape employee work performance

Do you get what you desire? Consequences of (mis) fit of desired versus actual servant leadership, and the role of context across 10 countries

This study explores how (in)congruence of desired and actual behaviors of servant leaders shape the outcomes of followers’ work engagement, well-being and turnover intentions. We underline the significance of cultural context in influencing follower outcomes and, thus, integrate a gender-cultural perspective to highlight the moderating role of gender inequality on a country level. In so doing, we postulate a strong relationship between the effects of actual/desired behaviors of servant leaders upon follower work outcomes, especially in contexts where gender inequality is high. Our results from documenting the perceptions of full-time employees (n = 2,960) across 10 countries using polynomial regression analyses show that followers’ turnover intentions are lower and work engagement is higher when there is a congruence between followers’ perception of servant leadership and desired servant leadership. Moreover, we found that followers’ well-being is higher when actual and desired servant leadership is congruent as opposed to incongruent. In addition, the results show that the beneficial impact of congruence (as opposed to incongruence) is stronger in the cultural context where gender inequality is high. We contribute to the literature by showing the important impacts of (in)congruence between desired and actual servant leadership on followers’ outcomes

Teamwork: Assessment of teamwork competence in higher education

[EN] Teamwork is a competence highly demanded among workers and an academic field with an extensive specialized literature. Based on this knowledge that comes from the study of organizational behavior, this communication presents a model to understand teamwork in higher education settings. The theoretical model considers structural components (i.e., task interdependence and task uncertainty), processes (i.e., team development and team climate for learning) and results (i.e., team effectiveness). Moreover, an assessment tool (and attitude questionnaire with 42 items-Likert scale with a range from 1 to 7) is also presented to measure these critical components that can allow us to distinguish between effective and ineffective teams in higher education. First results of the application of these tools to 18 team students show good consistency values of the tools being able to distinguish among teams. Additionally, we propose a procedure to obtain aggregated measures per group from the members’ responses considering the degree of agreement among members.Navarro, J.; Bosch, JL.; Palacín, M.; Solé, M.; Berger, R.; Leiva, D.; Ceppi, F.... (2017). Teamwork: Assessment of teamwork competence in higher education. En Proceedings of the 3rd International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 1024-1032. https://doi.org/10.4995/HEAD17.2017.55071024103

Antioxidant Roles of SGLT2 Inhibitors in the Kidney

Diabetic kidney disease; Mitochondrial dysfunction; Oxidative stressMalaltia renal diabètica; Disfunció mitocondrial; Estrès oxidatiuEnfermedad renal diabética; Disfunción mitocondrial; Estrés oxidativoThe reduction-oxidation (redox) system consists of the coupling and coordination of various electron gradients that are generated thanks to serial reduction-oxidation enzymatic reactions. These reactions happen in every cell and produce radical oxidants that can be mainly classified into reactive oxygen species (ROS) and reactive nitrogen species (RNS). ROS and RNS modulate cell-signaling pathways and cellular processes fundamental to normal cell function. However, overproduction of oxidative species can lead to oxidative stress (OS) that is pathological. Oxidative stress is a main contributor to diabetic kidney disease (DKD) onset. In the kidney, the proximal tubular cells require a high energy supply to reabsorb proteins, metabolites, ions, and water. In a diabetic milieu, glucose-induced toxicity promotes oxidative stress and mitochondrial dysfunction, impairing tubular function. Increased glucose level in urine and ROS enhance the activity of sodium/glucose co-transporter type 2 (SGLT2), which in turn exacerbates OS. SGLT2 inhibitors have demonstrated clear cardiovascular benefits in DKD which may be in part ascribed to the generation of a beneficial equilibrium between oxidant and antioxidant mechanisms.The authors are current recipients of grants from FONDO DE INVESTIGACIÓN SANITARIA-FEDER, ISCIII (PI17/00257 and RICORS RD21/0005/0016), and Fundació la Marató de TV3 (421/C/2020, 759/U/2020 and 215/C/2021)

A novel approach to learning through categorical variables applicable to the classification of solitary pulmonary nodule malignancy

Background: One of the main drawbacks in constructing a classification model is that some or all of the covariates are categorical variables. Classical methods either assign labels to each output of a categorical variable or are summarised measures (frequencies and percentages), which can be interpreted as probabilities. Methods: We adopted a novel mathematical procedure to construct a classification model from categorical variables based on a non-classical probability approach. More specifically, we codified the variables following the categorical data representation from the Discriminant Correspondence Analysis before constructing a non-classical probability matrix system that represents an entangled system of dependent-independent variables. We then developed a disentangled procedure to obtain an empirical density function for each representative class (minimum of two classes). Finally, we constructed our classification model using the density functions. Results: We applied the proposed procedure to build a classification model of the malignancy of Solitary Pulmonary Nodule (SPN) after five years of follow up using routine clinical data. First, with 2/3 (270) of the sample of 404 patients with SPN, we constructed the classification model, and then validated it with the remaining 1/3(134) we validated it. We tested the procedure’s stability by repeating the analysis randomly 1000 times. We obtained a model accuracy of 0.74, an F1 score of 0.58, a Cohen’s Kappa value of 0.41 and a Matthews Correlation Coefficient of 0.45. Finally, the area under the ROC curve was 0.86. Conclusion: The proposed procedure provides a machine learning classification model with an acceptable performance of a classification model of solitary pulmonary nodule malignancy constructed from routine clinical data and mainly composed of categorical variables. It provides an acceptable performance, which could be used by clinicians as a tool to classify SPN malignancy in routine clinical practice