Critical appraisal of epidemiological study design and variable operationalization

¶ … C-Sections in the United States. While the article itself is not an empirical work, it draws extensively from the work of medical researchers and experts in the field. The phenomenon under consideration was the alarming increase in the rates of C-sections amongst all sectors of the American population. The writer used a bar chart to demonstrate that the numbers of C-sections have increased steadily from 1998 to 2007. The increase was from a low of 21 C-sections per 100 births in 1998, to 32 per 100 births in 2007. Overall, the numbers of C-sections has increased by more than 50% since 1996.

The main hypothesis tested examined the relationship between induction and C-sections. It was hypothesized that there was a direct relationship between the induction of labor in a woman and conducting a C-section. This hypothesis suggests that as the numbers of induced labors increase there will also be an increase in C-sections. While there are multiple reasons why a doctor might induce labor in a woman, one of the companion concerns with induced labor and the apparent rush to conduct a C-section might be the impatience of medical doctors. This latter sub-hypothesis was demonstrated by showing that the dilation width when the decision to conduct a C-section was about the same as what might be observed in the initial phases of labor. This suggests that women were not in the active phase of labor when the decision to have the surgery was taken.

The study from which the data for these conclusions was drawn was conducted using a quasi-experimental design. The quasi-experimental design is similar to the experimental design with the exception that individuals are not randomly assigned to the compared groups. Based on the information provided in the article the lead researcher suggested that the findings from the research could not be considered as having the degree of internal validity desired because the women were not assigned to the induced and non-induced group randomly. This statement appears to be consistent with the quasi-experimental design.

The research used variables measured at the interval level and nominal levels, and used both categorical and non-categorical variables. The induction of labor was a categorical variable measured in the form of a yes no response. Having a C-section was also a categorical variable since it was measured as yes or no, C-section. The width of the cervix at the time the decision was taken to have the surgery was measured in inches. The point of induction was operationalized as the width of the cervix. This variable was measured at the interval level and is discrete variable. The combination of categorical and discrete variables allowed the researcher to engage in different types of data analysis. Descriptive statistics were produced for the categorical data. The findings were generally, in the form of percentages of increase, there was no indication additional testing was done to determine whether the observed difference was significant.

There is no indication in the article about the mechanism used to validate the instruments. However, the researcher did engage in a form of data triangulation by comparing the data from one study with that of a more general study. This comparison occurred for the percentage of women having a vaginal birth after delivering by C-section. The report suggested a 23% difference between the study and the official government figures. This particular discrepancy appears to suggest that there is a need for further study in the area to examine the reasons for the difference or to produce percentages that contain less variance.