In the meta-analysis, what were the correct classification rates for truthful statements and lies?

In the meta-analysis, what were the correct classification rates for truthful statements and lies?

• A. 54% truthful and 50% lies
• B. 61% truthful as non-deceptive and 47% lies as deceptive
• C. 70% truthful and 60% lies
• D. 45% truthful and 30% lies

Answer: (B)

Focus on how well people classify statements as truthful versus deceptive across many studies. The meta-analysis shows about 61% accuracy for labeling truthful (non-deceptive) statements correctly and about 47% accuracy for labeling lies (deceptive statements) correctly. This pattern reveals a truth bias: people tend to label statements as truthful more often, which helps explain the higher accuracy for truthful statements but lower accuracy for lies. The overall ability to detect deception is modest at best, since even lies are only correctly identified less than half the time. The other options propose higher or more balanced rates that don’t align with typical meta-analytic findings, where accuracy is modest and lies are harder to detect than truths.

Focus on how well people classify statements as truthful versus deceptive across many studies. The meta-analysis shows about 61% accuracy for labeling truthful (non-deceptive) statements correctly and about 47% accuracy for labeling lies (deceptive statements) correctly. This pattern reveals a truth bias: people tend to label statements as truthful more often, which helps explain the higher accuracy for truthful statements but lower accuracy for lies. The overall ability to detect deception is modest at best, since even lies are only correctly identified less than half the time.

The other options propose higher or more balanced rates that don’t align with typical meta-analytic findings, where accuracy is modest and lies are harder to detect than truths.