High-quality data entry depends on trained users. Even a well-designed REDCap database can produce poor data if users do not understand the protocol, forms, source documents, validation warnings, access rules, or query workflow. Training should be treated as a required study activity, not an optional orientation.
Training should begin with the study protocol and data collection purpose. Users should understand why data are being collected and how their work affects participant safety, study validity, and public trust. They should then learn the CRFs or eCRFs, including field definitions, units, coded options, required fields, and completion guidelines. Training should include practical demonstrations and hands-on practice using test records.
Users should also be trained on confidentiality and access control. They should understand why accounts must not be shared, how to protect passwords, what data they are allowed to view, how to handle printed documents, and how to report suspected breaches. In multisite studies, users should understand site-level access restrictions and the importance of not attempting to view records outside their role.
Competency assessment helps confirm that training was effective. This may involve completing practice records, responding to validation warnings, entering an adverse event, resolving a query, or demonstrating correct handling of source documents.

Competency should be documented before production access is granted. Refresher training should occur after major protocol amendments, database changes, repeated data quality problems, staff turnover, or monitoring findings.
Training materials should be version controlled. If CRFs change, training slides, completion guidelines, and practice scenarios may also need updates. Sites should receive current materials, and outdated materials should be retired. Training logs should record who was trained, when, on what version of materials, and by whom.