Every light has its shadow: a longitudinal study of transformational leadership and leaders’ emotional exhaustion

This study investigated the effects of transformational and laissez‐faire leadership on leaders’ own emotional exhaustion over time. Participants were 2,324 subordinates and 76 supervisors of a services company in Germany. Regression analysis revealed direct longitudinal health‐hampering effects of transformational and laissez‐faire leadership on leaders’ emotional exhaustion. Building on Hobfoll's Conservation of Resources theory (1989), our results showed that the longitudinal health‐hampering effects of transformational leadership would be particularly pronounced for leaders with high levels of organization‐based self‐esteem. Our findings extend the research on potential dark sides of transformational and laissez‐faire leadership as well as organization‐based self‐esteem by focusing on leader‐centered outcomes.     

Negativity bias in defeasible reasoning

In defeasible reasoning, initially drawn conclusions can be withdrawn in light of new information. In this paper, we examine how the conclusions drawn from conditionals describing positive or negative situations can be defeated by subsequent negative or positive information, respectively. Participants were confronted with conditionals of the form “If [situation], then I am happy/sad” which were either followed by no additional information or by additional information describing situations of the same or the opposite valence. The participant's task was to decide on a question asking for a possible conclusion (“Am I happy?” vs. “Am I sad?”). We found a negativity bias in defeasible reasoning: negative information defeated positively charged conclusions more strongly than positive information defeated negatively charged conclusions. We discuss our results in relation to the new psychology of reasoning.     

Family play,reading, and other stimulation and early childhood development in five low-and-middle-income countries

This paper used longitudinal data from five studies conducted in Bangladesh, Bhutan, Cambodia, Ethiopia, and Rwanda to examine the links between family stimulation and early childhood development outcomes (N = 4904; M_age = 51.5; 49% girls). Results from random-effects and more conservative child-fixed effects models indicate that across these studies, family stimulation, measured by caregivers’ engagement in nine activities (e.g., reading, playing, singing), predicted increments in children's early numeracy, literacy, social-emotional, motor, and executive function skills (standardized associations ranged from 0.05 to 0.11 SD). Study-specific models showed variability in the estimates, with null associations in two out of the five studies. These findings indicate the need for additional research on culturally specific ways in which caregivers may support early development and highlight the importance of promoting family stimulation to catalyze positive developmental trajectories in global contexts.

Research Highlights

• Research on the links between family stimulation and early childhood development in low-and-middle-income countries (LMICs) is limited.
• We used longitudinal data from studies conducted in five LMICs to examine the links between family stimulation and early childhood development outcomes.
• Results suggest that family stimulation predicted increments in children's numeracy, literacy, social-emotional, motor, and executive function skills.
• We found variability in the observed estimates, with null associations in two out of the five studies, suggesting the need for additional research in LMICs.

     

Can Happiness Apps Generate Nationally Representative Datasets? - a Case Study Collecting Data on People’s Happiness Using the German Socio-Economic Panel

In the last few years, apps have become an important tool to collect data. Especially in the case of data on people’s happiness, two projects have received substantial attention from both the media and the scientific world: “Track your happiness” from Killingsworth and Gilbert (Science, 330, 932-932, 2010), and “Mappiness,” from MacKerron (2012). Both happiness apps used the experience sampling method to ask people a few times per day how they feel, what they do, with whom, and where. The collected data are then displayed for the participants in simple graphs to help them understand what makes them happy and what does not. Both studies have collected considerable data without giving participants any financial rewards. But quantity is not everything that matters with respect to data collection, and thus, understanding whether nationally representative datasets can be collected using such happiness apps is crucial. To address this question, we built a new happiness app and ran a case-study with over 4000 participants of the innovation sample of the German Socio-Economic Panel (Richter and Schupp in Schmollers Jahrbuch, 135(3), 389–399, 2015). Participants were informed that the app collects data on everyday happiness after a household interview and asked whether they would like to use the app. In the first year (2015), participants did not receive any reward, and in the second year (2016), a different group of participants received a 50 Euro Amazon voucher for their participation. The results showed that our happiness app cannot generate nationally representative datasets if it is not controlled that all demographic sub-groups have access to a smartphone, are highly motivated with a sufficient reward and data is collected with quota sampling.