Title 7. CROSS – SECTIONAL STUDIES.pdf ✅

PHARMD GURU Page 3  The prevalence of disease or other health related characteristics are important in public health for assessing the burden of disease in a specified population and in planning and allocating health resources.  Good for descriptive analyses and for generating hypotheses. WEAKNESSES:  Difficult to determine whether the outcome followed exposure in time or exposure resulted from the outcome.  Not suitable for studying rare diseases or diseases with a short duration.  As cross-sectional studies measure prevalent rather than incident cases, the data will always reflect determinants of survival as well as etiology.  Unable to measure incidence.  Associations identified may be difficult to interpret.  Susceptible to bias due to low response and misclassification due to recall bias. EXAMPLES OF CROSS-SECTIONAL STUDY: You've now understood what parameters encompass the cross-sectional research method. To better illustrate this, below are 2 examples: 1) Phone companies rely on advanced and innovative features to drive sales. Research amongst the target demographic market by a phone manufacturer validates the expected adoption rate and potential sales of the phone. In a cross-sectional study, males and females across geographies and ages are enrolled for this research. If the study results show that Asian women would not buy the phone because it is bulky, the mobile phone company can tweak the design before its launch or develop and market a smaller phone for women. 2) Another example of a cross-sectional study would be a medical study looking at the prevalence of cancer amongst a certain population. The researcher can evaluate people from different ages, ethnicities, geographical location and social backgrounds. If a significant amount of men from a particular age are found to be more prone to have the disease, the researcher can conduct further studies to understand the reason behind it — like a longitudinal study.