How can you differentiate between common epidemiological study types?

1 Observational studies

Observational studies are studies that observe and measure the exposure and outcome of interest in a population without intervening or manipulating any variables. Observational studies can be classified into two main categories: descriptive and analytical. Descriptive studies describe the distribution and frequency of a disease or a risk factor in a population, such as case reports, case series, cross-sectional studies, and ecological studies. Analytical studies compare the exposure and outcome between different groups of individuals, such as cohort studies, case-control studies, and nested case-control studies.

2 Experimental studies

Experimental studies are studies that assign the exposure or intervention to the participants randomly and compare the outcome between the exposed and unexposed groups. Experimental studies can provide stronger evidence of causality than observational studies, as they can control for confounding factors and reduce selection bias. The most common type of experimental study in epidemiology is the randomized controlled trial (RCT), which can test the efficacy and safety of a treatment, prevention, or policy. Other types of experimental studies include quasi-experimental studies, which lack randomization, and cluster randomized trials, which randomize groups of individuals rather than individuals.

4 Diagnostic studies

Diagnostic studies are studies that evaluate the accuracy and performance of a test or a tool to diagnose a disease or a condition. Diagnostic studies can measure the sensitivity, specificity, positive predictive value, negative predictive value, and likelihood ratios of a test, which indicate how well the test can identify true positives, true negatives, false positives, and false negatives. Diagnostic studies can also compare the test with a gold standard or a reference test, which is the most accurate and reliable test available for the disease or condition.

5 Prognostic studies

Prognostic studies are studies that assess the outcome and course of a disease or a condition over time in a population or a subgroup of individuals. Prognostic studies can identify and quantify the factors that influence the risk, severity, duration, or survival of a disease or a condition, such as demographic, clinical, biological, or behavioral variables. Prognostic studies can also evaluate the effectiveness and impact of different treatments, interventions, or strategies on the outcome and course of a disease or a condition. Prognostic studies can be observational or experimental, and can use different methods, such as survival analysis, risk prediction models, or decision analysis.

6 Causal inference studies

Causal inference studies are studies that aim to infer the causal relationship between an exposure and an outcome in a population, using statistical, mathematical, or computational methods. Causal inference studies can address the limitations and challenges of observational and experimental studies, such as confounding, selection bias, measurement error, or ethical issues. Causal inference studies can use different approaches, such as counterfactual theory, potential outcomes framework, causal diagrams, propensity score methods, instrumental variables, or mediation analysis.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?