Values Clarification Methods in Decision Support Tools for Lung Cancer Screening: A Systematic Review and Content...

Area of Science:

• Medical Informatics
• Public Health
• Decision Science

Background:

• Values clarification is crucial for shared decision-making, especially in lung cancer screening (LCS) due to complex benefit-harm trade-offs.
• Explicit, theory-based values clarification methods are hypothesized to best support patient decision-making.

Purpose of the Study:

• To characterize values clarification methods in patient-facing LCS decision support tools.
• To explore associations between these methods and behavioral/decisional outcomes.

Main Methods:

• Systematic review of 48 studies evaluating 32 unique LCS decision support tools.
• Data extraction on study characteristics and values clarification methods (explicit, implicit, none).
• Meta-analysis of randomized controlled trials (RCTs) to assess tool impact on LCS uptake.

Main Results:

• Over 80% of LCS decision support tools included values clarification (50% explicit, 50% implicit).
• RCTs showed decision support tools doubled LCS odds (OR 1.98), driven by explicit or no values clarification.
• Tools lacking values clarification were of lower quality; theory-based explicit methods were rarely used.

Conclusions:

• LCS decision support tools frequently incorporate values clarification and enhance screening uptake.
• Underutilization of theory-based explicit values clarification methods limits potential improvements in decision support quality.