Non-specificity impacts the design of epidemiological studies in several ways. Researchers must account for multiple potential outcomes when designing studies, which might require larger sample sizes and more complex statistical analyses. Additionally, non-specificity necessitates the use of multifactorial models that can adjust for various confounding variables. This ensures that the observed associations are not falsely attributed to a single factor.
