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Multiple Choice

Which statement describes the principle of data capture proportionality?

Data capture proportionality means only collect what’s truly needed to answer the trial questions and protect participants, with the amount of data tied to the level of risk and how important the data is to the study’s objectives. This balance ensures you have enough information to assess safety and efficacy and maintain data quality, without overburdening sites or exposing subjects to unnecessary procedures. That’s why the statement that capture should be proportionate to risks and data importance is the best fit. Collecting data extensively regardless of risk over-collects; trying to minimize data to reduce risk could leave important information out; and capturing data in a discretionary, informal way risks inconsistency and non-compliance with approved procedures.

Data capture proportionality means only collect what’s truly needed to answer the trial questions and protect participants, with the amount of data tied to the level of risk and how important the data is to the study’s objectives. This balance ensures you have enough information to assess safety and efficacy and maintain data quality, without overburdening sites or exposing subjects to unnecessary procedures. That’s why the statement that capture should be proportionate to risks and data importance is the best fit. Collecting data extensively regardless of risk over-collects; trying to minimize data to reduce risk could leave important information out; and capturing data in a discretionary, informal way risks inconsistency and non-compliance with approved procedures.