Classification schemes for knowledge translation interventions: a practical resource for researchers.

Area of Science:

• Implementation Science
• Healthcare Research
• Knowledge Translation Interventions

Background:

• Growing number of knowledge translation (KT) interventions to integrate evidence into healthcare.
• Emergence of classification schemes for KT interventions.
• Need for quality evaluation and guidance in selecting KT classification schemes.

Purpose of the Study:

• To examine and assess the quality of 51 identified classification schemes for KT interventions.
• To provide information to aid researchers in selecting appropriate KT classification schemes for their research context and purpose.

Main Methods:

• Abstracted data on objectives, scope, socioecologic level, adaptability, target group, intent, and purpose from 51 classification schemes.
• Evaluated methodological quality of scheme development using an adapted AGREE II tool.
• Reached consensus on recommending schemes for researcher use.

Main Results:

• Evaluated 44 classification schemes, recommending 35.
• Ten recommended schemes focused on behavior change, six on population health.
• Most schemes targeted practice (29), broadly applicable (25), and intended for implementation (most).

Conclusions:

• Thirty-five knowledge translation (KT) intervention classification schemes are recommended for use in healthcare research.
• The study's categorization and quality analysis assist researchers in selecting suitable KT schemes for implementation science.