Relationship between the COVID-19 Pandemic and the Well-Being of Adolescents and Their Parents in Switzerland

This study is based on two waves of data collected by the Swiss Household panel, the first one in 2019, before the beginning of the COVID-19 pandemic, and the second one in May–June 2020, just after the end of the partial lockdown that was decided by the Swiss government. We considered “couples” of adolescents (age 14–24, mean = 18.82, 51.96% female) and their parents living together (n = 431). Our main goal was to determine whether the evolution of the well-being among adolescents was similar to the evolution of the well-being among parents. Ten indicators of well-being were measured identically in both waves and for both adolescents and their parents. Results indicate that while almost all indicators of well-being decreased during partial lockdown for both adolescents and their parents, adolescents were more strongly impacted than their parents. Furthermore, the change observed in adolescents was virtually unaffected by the change observed in their parents, and vice versa. This research is a reminder that while different population groups may be affected differently by a sudden and extreme event, it is not only older people who will be most affected. Here, adolescents appear to have been more adversely affected than adults

The Predictive Power of Transition Matrices

When working with Markov chains, especially if they are of order greater than one, it is often necessary to evaluate the respective contribution of each lag of the variable under study on the present. This is particularly true when using the Mixture Transition Distribution model to approximate the true fully parameterized Markov chain. Even if it is possible to evaluate each transition matrix using a standard association measure, these measures do not allow taking into account all the available information. Therefore, in this paper, we introduce a new class of so-called "predictive power" measures for transition matrices. These measures address the shortcomings of traditional association measures, so as to allow better estimation of high-order models

Determinants for Bullying Victimization among 11–16-Year-Olds in 15 Low- and Middle-Income Countries:\ud A Multi-Level Study

Bullying is an issue of public health importance among adolescents worldwide. The present study aimed at explaining differences in bullying rates among adolescents in 15 low- and middle-income countries using globally comparable indicators of social and economic well-being. Using data derived from the Global School-based Health Survey, we performed bivariate analyses to examine differences in bullying rates by country and by bullying type. We then constructed a multi-level model using four fixed variables (age, gender, hunger and truancy) at the individual level, random effects at the classroom and\ud school levels and four fixed variables at the country level (Gini coefficient, per capita Gross Domestic Project, homicide rate and pupil to teacher ratio). Bullying rates differed significantly by classroom, school and by country, with Egypt (34.2%) and Macedonia (3.6%) having the highest and lowest rates, respectively. Eleven-year-olds were the most likely of the studied age groups to report being bullied, as was being a male. Hunger and truancy were found to significantly predict higher rates of bullying. None of the explanatory variables at the country level remained in the final model. While self-reported bullying varied significantly between countries, the variance between classrooms better explained these differences. Our findings suggest that classroom settings should be considered when designing approaches aimed at bullying prevention.\u

Differences of the quality of care experience: the perception of patients with either network or conventional health plans

Background. Various studies have been performed on differences in quality measures between different models of primary care with inconclusive results. In Switzerland, up to a third of the population chooses network health plans including gatekeeping to profit from lower premiums and almost half of GPs work in primary care networks. Objective. To determine differences in the quality of interpersonal care and practice management between patients consulting a physician organized in a GP network or in independent practice. Methods. We analysed data of the European Project on Patient Evaluation of General Practice Care (EUROPEP) questionnaire measuring the quality of the patient-physician interaction and practice management of 473 primary care physicians. From the 25 178 patients who completed the questionnaire, 72.2% (18 174) consulted a physician participating in a network and 27.8% (7004) a physician working in independent practice. Results. The overall answer pattern of EUROPEP questions shows that patients were generally more satisfied with physicians in independent practice. Particularly, questions within the domains ‘relation and communication' and ‘information and support' and to a lesser degree within ‘Medical care' were significantly answered more favourable by patients of independent physicians. Stratification for chronic diseases showed that significant differences favouring independent physicians were less evident in patients with chronic diseases than in the non-chronic group. Conclusions. The results show differences in the quality of interpersonal care and practice management experienced by patients consulting network—or independent physicians. Therefore, we suggest that efforts to reduce health care spending by promoting more integrated care must also focus on monitoring and improving patient perceived qualitie

Using dynamic microsimulation to understand professional trajectories of the active Swiss population

Within the social and economic sciences and of particular interest to demographers are life course events. Looking at life sequences we can better understand which states, or life events, precede or are precursors to vulnerability. A tool that has been used for policy evaluation and recently has been gaining ground in life course sequence simulation is dynamic microsimulation. Within this context dynamic microsimulation consists in generating entire life courses from the observation of portions of the trajectories of individuals of different ages. In this work, we aim to use dynamic microsimulation in order to analyse individual professional trajectories with a focus on vulnerability. The primary goal of this analysis is to deepen upon current literature by providing insight from a longitudinal perspective on the signs of work instability and the process of precarity. The secondary goal of this work which is to show how, by using microsimulation, data collected for one purpose can be analysed under a different scope and used in a meaningful way. The data to be used in this analysis are longitudinal and were collected by NCCR-LIVES IP207 under the supervision of Prof. Christian Maggiori and Dr. Gregoire Bollmann. Individuals aged 25 to 55 residing in the German-speaking and French-speaking regions of Switzerland were followed annually for four years. These individuals were questioned regarding, amongst their personal, professional and overall situations and well-being. At the end of the fourth wave, there were 1131 individuals who had participated in all waves. The sample remained representative of the Swiss population with women and the unemployed slightly over represented. Using the information collected from these surveys, we use simulation to construct various longitudinal data modules where each data module represents a specific life domain. We postulate the relationship between these modules and layout a framework of estimation. Within certain data modules a set of equations are created to model the process therein. For every dynamic (time-variant) data module, such as the labour-market module, the transition probabilities between states (ex. labour market status) are estimated using a Markov model and then the possible outcomes are simulated. The benefit of using dynamic microsimulation is that longitudinal sample observations instead of stylised profiles are used to model population dynamics. This is one of the main reasons large-scale dynamic microsimulation models are employed by many developed nations. There has been limited use, however, of such approaches with Swiss data. This work contributes to the analysis of professional trajectories of the active Swiss population by utilising dynamic microsimulation methods

A discussion on hidden Markov models for life course data

This is an introduction on discrete-time Hidden Markov models (HMM) for longitudinal data analysis in population and life course studies. In the Markovian perspective, life trajectories are considered as the result of a stochastic process in which the probability of occurrence of a particular state or event depends on the sequence of states observed so far. Markovian models are used to analyze the transition process between successive states. Starting from the traditional formulation of a first-order discrete-time Markov chain where each state is liked to the next one, we present the hidden Markov models where the current response is driven by a latent variable that follows a Markov process. The paper presents also a simple way of handling categorical covariates to capture the effect of external factors on the transition probabilities and existing software are briefly overviewed. Empirical illustrations using data on self reported health demonstrate the relevance of the different extensions for life course analysis