Effect of nonnormal random components on level and power in group-randomized trials

The use of group-randomized trials is particularly widespread in the evaluation of health care, educational, and screening strategies. Group-randomized trials represent a subset of a larger class of designs often labeled nested, hierarchical, or multilevel and are characterized by the randomization of intact social units or groups, rather than individuals. The application of random effects models to group-randomized trials requires the specification of fixed and random components of the model. The underlying assumption is usually that these random components are normally distributed. This research is intended to determine if the Type I error rate and power are affected when the assumption of normality for the random component representing the group effect is violated. ^ In this study, simulated data are used to examine the Type I error rate, power, bias and mean squared error of the estimates of the fixed effect and the observed intraclass correlation coefficient (ICC) when the random component representing the group effect possess distributions with non-normal characteristics, such as heavy tails or severe skewness. The simulated data are generated with various characteristics (e.g. number of schools per condition, number of students per school, and several within school ICCs) observed in most small, school-based, group-randomized trials. The analysis is carried out using SAS PROC MIXED, Version 6.12, with random effects specified in a random statement and restricted maximum likelihood (REML) estimation specified. The results from the non-normally distributed data are compared to the results obtained from the analysis of data with similar design characteristics but normally distributed random effects. ^ The results suggest that the violation of the normality assumption for the group component by a skewed or heavy-tailed distribution does not appear to influence the estimation of the fixed effect, Type I error, and power. Negative biases were detected when estimating the sample ICC and dramatically increased in magnitude as the true ICC increased. These biases were not as pronounced when the true ICC was within the range observed in most group-randomized trials (i.e. 0.00 to 0.05). The normally distributed group effect also resulted in bias ICC estimates when the true ICC was greater than 0.05. However, this may be a result of higher correlation within the data. ^

Effectiveness of healthcare waste management interventions in developing countries

Inefficiencies during the management of healthcare waste can give rise to undesirable health effects such as transmission of infections and environmental pollution within and beyond the health facilities generating these wastes. Factors such as prevalence of diseases, conflicts, and the efflux of intellectual capacity make low income countries more susceptible to these adverse health effects. The purpose of this systematic review was to describe the effectiveness of interventions geared towards better managing the generation, collection, transport, treatment and disposal of medical waste, as they have been applied in lower and middle income countries.^ Using a systematic search strategy and evaluation of study quality, this study reviewed the literature for published studies on healthcare waste management interventions carried out in developing countries, specifically the low and lower middle income countries from year 2000 to the current year. From an initially identified set of 829 studies, only three studies ultimately met all inclusion, exclusion and high quality criteria. A multi component intervention in Syrian Arab Republic, conducted in 2007 was aimed at improving waste segregation practice in a hospital setting. There was an increased use of segregation boxes and reduced rates of sharps injury among staff as a result of the intervention. Another study, conducted in 2008, trained medical students as monitors of waste segregation practice in an Indian teaching hospital. There was improved practice in wards and laboratories but not in the intensive care units. The third study, performed in 2008 in China, consisted of modification of the components of a medical waste incinerator to improve efficiency and reduce stack emissions. Gaseous pollutants emitted, except polychlorodibenzofurans (PCDF) were below US EPA permissible exposure limits. Heavy metal residues in the fly ash remained unchanged.^ Due to the paucity of well-designed studies, there is insufficient evidence in literature to conclude on the effectiveness of interventions in low income settings. There is suggestive but insufficient evident that multi-component interventions aimed at improving waste segregation through behavior modification, provision of segregation tools and training of monitors are effective in low income settings.^