The appropriate choice in study design is essential for the successful execution of biomedical and public health research. There are many study designs to choose from within two broad categories of observational and interventional studies. Each design has its own strengths and weaknesses, and the need to understand these limitations is necessary to arrive at correct study conclusions.Observational study designs, also called epidemiologic study designs, are often retrospective and are used to assess potential causation in exposure-outcome relationships and therefore influence preventive methods. Observational study designs include ecological designs, cross sectional, case-control, case-crossover, retrospective and prospective cohorts. An important subset of observational studies is diagnostic study designs, which evaluate the accuracy of diagnostic procedures and tests as compared to other diagnostic measures. These include diagnostic accuracy designs, diagnostic cohort designs, and diagnostic randomized controlled trials.Interventional studies are often prospective and are specifically tailored to evaluate direct impacts of treatment or preventive measures on disease. Each study design has specific outcome measures that rely on the type and quality of data utilized. Additionally, each study design has potential limitations that are more severe and need to be addressed in the design phase of the study. This manuscript is meant to provide an overview of study design types, strengths and weaknesses of common observational and interventional study designs.
Objectives Most studies of carpal tunnel syndrome (CTS) incidence and prevalence among workers have been limited by small sample sizes or restricted to a small subset of jobs. We established a common CTS case definition and then pooled CTS prevalence and incidence data across six prospective studies of musculoskeletal outcomes to measure CTS frequency and allow better studies of etiology. Methods Six research groups collected prospective data at >50 workplaces including symptoms characteristic of CTS and electrodiagnostic studies (EDS) of the median and ulnar nerves across the dominant wrist. While study designs and the timing of data collection varied across groups, we were able to create a common CTS case definition incorporating both symptoms and EDS results from data that were collected in all studies. Results At the time of enrollment, 7.8% of 4321 subjects met our case definition and were considered prevalent cases of CTS. During 8833 person-years of follow-up, an additional 204 subjects met the CTS case definition for an overall incidence rate of 2.3 CTS cases per 100 person-years. Conclusions Both prevalent and incident CTS were common in data pooled across multiple studies and sites. The large number of incident cases in this prospective study provides adequate power for future exposure– response analyses to identify work- and non-work-related risk factors for CTS. The prospective nature allows determination of the temporal relations necessary for causal inference.
Application and interpretation of statistical evaluation of relationships is a necessary element in biomedical research. Statistical analyses rely on P value to demonstrate relationships. The traditional level of significance, P<0.05, can be negatively impacted by small sample size, bias, and random error, and has evolved to include interpretation of statistical trends, correction factors for multiple analyses, and acceptance of statistical significance for P>0.05 for complex relationships such as effect modification.
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