Cross Sectional Study

Cross Sectional Study

Responses 1

The concept of cross-sectional study has a one-time population coverage and dispels any prevailing assumptions. It shares similarity with cohort studies owing to the fact that the duo starts with population base. Cross sectional concept lays focus on the number of times a disease has been reported. According to Lormeau, Blake, Mons, Lastère, Roche, Vanhomwegen and Vial (2016) cross sections study, which is a form of a study design, identifies a population sample and then marshals data regarding the subjects. Data collection enables individual classification as either positive or negative of the aspects under test.

It permits realization of multifaceted results and exposures, which can be put study. Also, it is affordable, expeditious and simple to undertake (Kotloff, Nataro, Blackwelder, Nasrin, Farag, Panchalingam and Faruque, 2013). Moreover, the design allows one time data collection and quantification of disease commonness for subjects under study. Furthermore, it enables validation of disputing of hypothesis. The study design has several weaknesses. It adopts a small population size and does not quantify the number of reported new cases. In addition, it is not fit for investigating un-common conditions.

Response 2

The form of a study design puts to study causative agents and history of a disease. It validates or disputes infection or its absence. It helps diagnose the root cause of a condition. The presence and result of a condition is identified one time. Researchers investigating multiple study variables can use cross sectional design (Singh, Chang, Richards, Weiner, Clark & Segal, 2013). The approach determines commonness of a disease but fails to show the cause and effect difference.

Cross sectional concept is efficient because it allows data gathering within a short time period. In addition, it is easy to apply and costs less. Also, the strategy upholds concept of ethics. The method does loose its effectiveness within time. The approach is characterised by setbacks such as biasness, inability to show distinction. The method may also show incoherence because of age and time.

Reference

Cao-Lormeau, V. M., Blake, A., Mons, S., Lastère, S., Roche, C., Vanhomwegen, J., & Vial, A. L. (2016). Guillain-Barré Syndrome outbreak associated with Zika virus infection in French Polynesia: a case-control study. The Lancet, 387(10027), 1531-1539.

Kotloff, K. L., Nataro, J. P., Blackwelder, W. C., Nasrin, D., Farag, T. H., Panchalingam, S., … & Faruque, A. S. (2013). Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case-control study. The Lancet, 382(9888), 209-222.

Singh, S., Chang, H. Y., Richards, T. M., Weiner, J. P., Clark, J. M., & Segal, J. B. (2013). Glucagonlike peptide 1–based therapies and risk of hospitalization for acute pancreatitis in type 2 diabetes mellitus: a population-based matched case-control study. JAMA internal medicine, 173(7), 534-539.

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