According to the study design principles, which approach helps minimize loss to follow-up?

• A. Exclude Patients Unlikely To Remain In Database
• B. Increase Frequency Of Data Collection
• C. Include Only Those Who Move Frequently
• D. Use Cross-Sectional Design

Answer: (A)

In longitudinal study designs, keeping participants over time and obtaining complete follow-up data is essential, because missing information can bias results and reduce statistical power. Excluding patients who are unlikely to stay in the database is a straightforward way to minimize loss to follow-up: by removing individuals prone to dropping out, the dataset stays more complete, and analyses rely on fewer missing observations. This helps preserve the integrity of the follow-up data and the study’s precision.

However, this approach can introduce selection bias and limit how well findings generalize to the broader population, since the study now reflects a subgroup more likely to remain in the database.

Increasing how often you collect data doesn't necessarily prevent loss to follow-up and can increase participant burden, potentially causing more dropouts. Including people who move frequently changes the composition of the cohort in a way that can bias results. A cross-sectional design captures data at one point in time and doesn't involve follow-up, so loss to follow-up isn't a design concern there.