Inaccurate or unreliable research findings due to multicollinearity can lead to misguided clinical guidelines or treatment protocols. For example, if a study aims to explore the factors influencing patient recovery times, multicollinearity among variables like age, severity of illness, and comorbid conditions can obscure the true impact of each factor, potentially leading to ineffective or suboptimal care strategies.
