2.4 Data analysis
We performed univariate and bivariate analyses of the acquired data. In
univariate analysis, frequency tables, bar graphs, and pie charts were
generated by SPSS, which reflects the distribution of observations based
on several options for a variable. Bivariate analysis was performed to
compare two variables using statistical tests depending on the nature of
the data. The chi-square test was the statistical test of choice in the
comparison of two categorical variables coupled with close inspection of
the p value to the proposed 5% type 1 error to determine the
significance of the variables compared. Several tests were conducted as
part of the statistical inferences to determine the most reasonable
direction of the suggested hypothesis at the start of the research.
Moreover, descriptive statistics were calculated to emphasize the
distribution, location, and spread of the data. The data were found to
be skewed to the right because of outliers. Therefore, the median was
reported as a measure of central tendency. Furthermore, the
interquartile range was delineated to describe the variability of the
data.
When calculating the most common depressive symptoms among our study
participants, the frequencies of symptoms 1-4 were obtained by adding
the “most” and “occasionally” responses, whereas the frequencies of
symptoms 5-6 were calculated by adding the “rarely” and “sometimes”
responses. It is important to note that the total for the occupation
demographic was lower because only employed participants who chose to
specify their occupation were counted, and the total for the openness
about mental health was lower because it is an optional question since
only those who had mental illness could choose to answer this question.