A lean method for selecting determinants when developing behavior change interventions

Area of Science:

• Behavioral Science
• Health Psychology
• Intervention Development

Background:

• Systematic behavior change intervention development necessitates understanding determinant structures and distributions.
• Resource constraints often limit data collection for behavior change institutions.
• Identifying relevant determinants is crucial for effective intervention design.

Purpose of the Study:

• Introduce CIBERlite, an approach for assessing determinant relevance with limited resources.
• Validate short measurements of determinants against full measurements.
• Demonstrate the utility of the CIBERlite plot for visualizing determinant data.

Main Methods:

• Convergent validity of short and full determinant measurements (N=401).
• Proof-of-concept for the CIBERlite plot using short measurements (N=415).
• Expert estimation study to assess prediction accuracy of determinant scores (N=45).

Main Results:

• Short measurements showed convergent validity with full measurements.
• The CIBERlite plot efficiently visualizes determinant structures and distributions for eight behaviors.
• Experts struggled to accurately predict determinant scores, highlighting the need for empirical data.

Conclusions:

• CIBERlite provides a valuable, resource-efficient alternative for conducting determinant studies.
• The CIBERlite plot aids in selecting relevant determinants for behavior change interventions.
• Empirical data collection is essential, even with limited resources, for effective intervention planning.