In: Brain sciences, 2021, vol. 11, no. 6, p. 16
When COVID-19 was declared as a pandemic, many countries imposed severe lockdowns that changed families’ routines and negatively impacted on parents’ and children’s mental health. Several studies on families with children with autism spectrum disorder (ASD) revealed that lockdown increased the difficulties faced by individuals with ASD, as well as parental distress. No studies have...
|
In: The Proceedings of the International History of Public Relations Conference, 2015, p. 232-248
The relationship between public relations (PR) and journalism is mostly conceived of as between “interdependent systems” (Grossenbacher, 1986: 730). In this context, Löffelholz mentions evidence of a “co-evolutionary development of journalism and public relations” that “has not to date been systematically pursued” (Löffelholz, 2004: 472; emphasis author's own). To do so would...
|
In: Journal of Rational-Emotive & Cognitive-Behavior Therapy, 2015, vol. 33, no. 2, p. 148-159
|
In: International journal of environmental research and public health, 2021, vol. 18, no. 5, p. 15 p
Background: The pervasiveness of smartphones has raised concerns about an increase in the prevalence of problematic smartphone use (PSU), which depends on a set of psychological and behavioral risk factors. Previous research has yielded mixed results on factors predicting PSU, including social anxiety and trust. In particular, the role of trust remained largely unexplored. In the present study,...
|
In: Journal of Labor Research, 2020, vol. 41, no. 1, p. 1-33
This paper investigates the sensitivity of average wage gap decompositions to methods resting on different assumptions regarding endogeneity of observed characteristics, sample selection into employment, and estimators’ functional form. Applying five distinct decomposition techniques to estimate the gender wage gap in the U.S. using data from the National Longitudinal Survey of Youth 1979,...
|
(Working Papers SES ; 515)
This paper combines causal mediation analysis with double machine learning to control for observed confounders in a data-driven way under a selection-on- observables assumption in a high-dimensional setting. We consider the average indirect effect of a binary treatment operating through an intermediate variable (or mediator) on the causal path between the treatment and the outcome, as well as...
|
In: Journal of business & economic statistics, 2015, vol. 33, no. 2, p. 179-191
The decomposition of gender or ethnic wage gaps into explained and unexplained components (often with the aim to assess labor market discrimination) has been a major research agenda in empirical labor economics. This article demonstrates that conventional decompositions, no matter whether linear or nonparametric, are equivalent to assuming a (probably too) simple model of mediation (aimed at...
|
(Working Papers SES ; 500)
Mediation analysis aims at evaluating the causal mechanisms through which a treatment or intervention affects an outcome of interest. The goal is to disentangle the total treatment effect into an indirect effect operating through one or several observed intermediate variables, the so-called mediators, as well as a direct effect reflecting any impact not captured by the observed mediator(s)....
|
In: Social Justice Research, 2009, vol. 22, no. 2-3, p. 280-297
|
(Working papers SES ; 495)
This paper proposes semi- and nonparametric methods for disentangling the total causal effect of a continuous treatment on an outcome variable into its natural direct effect and the indirect effect that operates through one or several intermediate variables or mediators. Our approach is based on weighting observations by the inverse of two versions of the generalized propensity score (GPS),...
|
