Impact of the stringency of lockdown measures on covid-19: A theoretical model of a pandemic

Background How effective have lockdowns been at reducing the covid-19 infection and mortality rates? Lockdowns influence contact among persons within or between populations including restricting travel, closing schools, prohibiting public gatherings, requiring workplace closures, all designed to slow the contagion of the virus. The purpose of the present study was to assess the impact of lockdown measures on the spread of covid-19 and test a theoretical model of the covid-19 pandemic employing structural equation modelling. Methods Lockdown variables, population demographics, mortality rates, infection rates, and health were obtained for eight countries: Austria, Belgium, France, Germany, Italy, Netherlands, Spain, and the United Kingdom. The dataset, owid-covid-data.csv, was downloaded on 06/01/2020 from: https://github.com/owid/covid-19-data/tree/master/public/data. Infection spread and mortality data were depicted as logistic growth and analyzed with stepwise multiple regression. The overall structure of the covid-19 data was explored through factor analyses leading to a theoretical model that was tested using latent variable path analysis. Results Multiple regression indicated that the time from lockdown had a small but significant effect (β = 0.112, p< 0.01) on reducing the number of cases per million. The stringency index produced the most important effect for mortality and infection rates (β = 0.588,β = 0.702, β = 0.518, β = 0.681; p< 0.01). Exploratory and confirmatory analyses resulted in meaningful and cohesive latent variables: 1) Mortality, 2) Infection Spread, 3) Pop Health Risk, and 4) Health Vulnerability (Comparative Fit Index = 0.91; Standardized Root Mean Square Residual = 0.08). Discussion The stringency index had a large impact on the growth of covid-19 infection and mortality rates as did percentage of population aged over 65, median age, per capita GDP, diabetes prevalence, cardiovascular death rates, and ICU hospital beds per 100K. The overall Latent Variable Path Analysis is theoretically meaningful and coherent with acceptable fit indices as a model of the covid-19 pandemic.

School belonging in adolescents: Psychometric properties of the School Belongingness Scale in Iranian students

The purpose of the present study is to investigate the initial psychometric properties and cultural adaptation of the School Belongingness Scale (SBS) in a sample of Iranian adolescents. Participants included 324 students, ranging in age between 12 and 18 years (M = 14.68, SD = 1.39). Confirmatory factor analysis indicated that responses to the Farsi version of the SBS were characterised by a two-factor measurement model, and latent variable path analysis results revealed this measurement model was predictive of adolescents’ responses to measures of social, emotional, and behavioural problems (e.g., emotional problems, conduct problems), academic achievement, and prosocial behaviour. These results provide initial evidence suggesting that the scale is psychometrically adequate to measure Iranian students’ sense of belonging at school.