Data Collection & CRF Management Flashcards

A mother in a lactation study reports she stopped breastfeeding between two scheduled visits. How should this be documented in the CRF?

Answer: Record it as a protocol deviation and note the cessation date

Any change in key study behaviors between visits should be captured as a protocol deviation with the relevant date to maintain data integrity.

In a lactation support intervention study, what is the primary purpose of double data entry?

Answer: To reduce transcription errors by comparing two independently entered datasets

Double data entry involves two separate individuals entering the same data, with discrepancies resolved to minimize transcription errors.

Which of the following is an example of a continuous variable in a lactation CRF?

Answer: Volume of expressed breast milk in milliliters

Volume of expressed milk is a continuous variable because it can take any value along a measurable scale.

What does an audit trail in an electronic CRF system document?

Answer: All data entries, modifications, deletions, and the user who made them with timestamps

Audit trails provide a chronological record of all changes to electronic data, ensuring accountability and supporting data integrity.

A CRF asks for the date of the first postpartum lactation consultation. Which date format should be used per ICH E6 GCP guidelines?

Answer: Day, month, year (DD/MMM/YYYY)

ICH E6 GCP recommends the DD/MMM/YYYY format (e.g., 11/JUL/2026) to avoid ambiguity between month and day.

In a lactation study CRF, the 'reason for not breastfeeding' field has multiple checkboxes. A participant reports two reasons. How should this be recorded?

Answer: Check all applicable boxes and document both reasons

When multiple answers apply, all relevant boxes should be checked to capture complete and accurate data.

What is the role of a data manager in a lactation clinical study?

Answer: Overseeing collection, verification, and cleaning of study data to ensure integrity

The data manager is responsible for ensuring all collected data is complete, accurate, and clean before analysis.