Utilizing Instagram Data to Identify Usage Patterns Associated With Schizophrenia Spectrum Disorders

Introduction The global burden of disease (GBD) studies have derived detailed and comparable epidemiological and burden of disease estimates for schizophrenia. We report GBD 2016 estimates of schizophrenia prevalence and burden of disease with disaggregation by age, sex, year, and for all countries. Method We conducted a systematic review to identify studies reporting the prevalence, incidence, remission, and/or excess mortality associated with schizophrenia. Reported estimates which met our inclusion criteria were entered into a Bayesian meta-regression tool used in GBD 2016 to derive prevalence for 20 age groups, 7 super-regions, 21 regions, and 195 countries and territories. Burden of disease estimates were derived for acute and residual states of schizophrenia by multiplying the age-, sex-, year-, and location-specific prevalence by 2 disability weights representative of the disability experienced during these states. Findings The systematic review found a total of 129 individual data sources. The global age-standardized point prevalence of schizophrenia in 2016 was estimated to be 0.28% (95% uncertainty interval [UI]: 0.24–0.31). No sex differences were observed in prevalence. Age-standardized point prevalence rates did not vary widely across countries or regions. Globally, prevalent cases rose from 13.1 (95% UI: 11.6–14.8) million in 1990 to 20.9 (95% UI: 18.5–23.4) million cases in 2016. Schizophrenia contributes 13.4 (95% UI: 9.9–16.7) million years of life lived with disability to burden of disease globally. Conclusion Although schizophrenia is a low prevalence disorder, the burden of disease is substantial. Our modeling suggests that significant population growth and aging has led to a large and increasing disease burden attributable to schizophrenia, particularly for middle income countries.

Several studies and meta-analyses have shown that mortality in people with schizophrenia is higher than that in the general population but have used relative measures, such as standardised mortality ratios. We did a systematic review and meta-analysis to estimate years of potential life lost and life expectancy in schizophrenia, which are more direct, absolute measures of increased mortality.

This paper introduces the R package WRS2 that implements various robust statistical methods. It elaborates on the basics of robust statistics by introducing robust location, dispersion, and correlation measures. The location and dispersion measures are then used in robust variants of independent and dependent samples t tests and ANOVA, including between-within subject designs and quantile ANOVA. Further, robust ANCOVA as well as robust mediation models are introduced. The paper targets applied researchers; it is therefore kept rather non-technical and written in a tutorial style. Special emphasis is placed on applications in the social and behavioral sciences and illustrations of how to perform corresponding robust analyses in R. The R code for reproducing the results in the paper is given in the Supplementary Materials.