Which approach best protects participant privacy by removing direct identifiers before analysis?

• A. Storing Data on Shared Drives
• B. Collecting Additional Identifiers
• C. De-Identifying Data by Removing Personal Identifiers
• D. Publishing Raw Datasets

Answer: (C)

Protecting participant privacy hinges on removing information that can directly identify someone before any analysis. This de-identification step means you strip out names, exact birth dates, addresses, phone numbers, social security numbers, and other single items that could point to an individual. By substituting codes or removing these identifiers, the data set becomes suitable for analysis without easily linking results back to a person. This practice reduces the risk of re-identification and aligns with ethical and legal privacy protections. Standards like HIPAA’s de-identification guidelines provide clear methods for doing this, and researchers often couple it with reducing quasi-identifiers (like narrow age ranges or specific locations) or aggregating data to further lessen re-identification risk. Conversely, keeping identifiers in the data on shared drives, collecting more identifying information, or publishing raw data would expose individuals and increase privacy risk.