In all types of human research, identifying the variables to collect in your study should be

straightforward after you’ve selected a study design and enumerated all the objectives. In a

clinical trial, you will need to operationalize the measurements you need, meaning you will need

to find a way to measure each concept specified in the objectives. Measurements can fall into

these categories:

Administrative: This information includes data related to recruitment, consent, and enrollment, as

well as contact information for each participant. You need to keep track of study eligibility

documentation, as well as the date of each visit, which study activities took place, and final status

at end of study (such as whether participants completed the study, dropped out of the study, or any

other outcome).

Intervention-related: This includes data related to the intervention for each participant, such as

group assignment, dosing level, compliance, and adherence measures. If you plan to assign a

participant to a particular group but they end up in another group, you need to keep track of both

group assignments.

Outcome-related: This includes ensuring you are measuring both efficacy and safety outcomes on

a regular schedule that is documented. You may be asking the participant to keep records, or they

may need to be measured in person (to obtain laboratory values, X-rays, and other scans, ECGs,

and so on).

Potential confounding variables: These variables are determined by way of what is known about

participants’ relationship with the intervention, outcome, and study eligibility criteria. Typically,

potential confounding variables include basic demographic information such as date of birth,

gender, and ethnicity. Confounders could also be measured with questions posed to the participant

about health behaviors such as tobacco use, exercise patterns, and diet. There are also questions

about medical history, including current conditions, past hospitalizations, family medical history,

and current and past medication use. Measurements such as height and weight as well as other

physical measurements can also be included.

Values that do not change over time, such as birth date and medical history, only need to be

recorded at the beginning of the study. In designs including follow-up visits, values that change

over time are measured multiple times over the duration of data collection for the study.

Depending on the research objectives, these could include weight, medication use, and test

results. Most of this data collection is scheduled as part of study visits, and but some may be

recorded only at unpredictable times, if at all (such as adverse events, and withdrawing from the

study before it is completed).

Deciding who is eligible for the study

Because you can’t examine the entire population for whom the intervention you’re studying is intended,

you must select a sample from that population. How you filter in the right sample for your study is by