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<p>The study examined how well the Scientific Content Analysis Technique (SCAN) could differentiate between genuine and false statements related to negative experiences. SCAN, employed as a lie detection tool, was applied by trained, independent, and blind assessors who evaluated 151 truthful and 156 fabricated statements based on eleven SCAN criteria. Participants were divided into “Truth” and “Lie” groups, with the former describing genuine negative personal experiences and the latter instructed to describe fictional negative experiences. Inter-rater reliability was generally low, with only two criteria showing substantial agreement. Although criteria “Time” and “Change in language” were identified as significant predictors of veracity, their reliability was questioned due to low inter-rater agreement. Discriminant analysis confirmed their importance in distinguishing truthful and fabricated accounts, explaining 10.5% of the variability. Loadings of all other SCAN criteria were small or negligible. Additionally, truth-tellers were correctly classified in 71% of cases, a result that may have been influenced by a truth-bias effect, whereas liars were correctly classified in only 58% of cases, a rate that is close to chance level. In conclusion, SCAN was found to be ineffective for lie detection, consistent with prior independent research, and its use is discouraged due to potential harm and lack of efficacy.</p>

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Inefficacy of the SCAN Technique in Discriminating Between Truthful and Fabricated Statements

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月8日

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  • Igor Areh,
  • Marija Umolac

摘要

The study examined how well the Scientific Content Analysis Technique (SCAN) could differentiate between genuine and false statements related to negative experiences. SCAN, employed as a lie detection tool, was applied by trained, independent, and blind assessors who evaluated 151 truthful and 156 fabricated statements based on eleven SCAN criteria. Participants were divided into “Truth” and “Lie” groups, with the former describing genuine negative personal experiences and the latter instructed to describe fictional negative experiences. Inter-rater reliability was generally low, with only two criteria showing substantial agreement. Although criteria “Time” and “Change in language” were identified as significant predictors of veracity, their reliability was questioned due to low inter-rater agreement. Discriminant analysis confirmed their importance in distinguishing truthful and fabricated accounts, explaining 10.5% of the variability. Loadings of all other SCAN criteria were small or negligible. Additionally, truth-tellers were correctly classified in 71% of cases, a result that may have been influenced by a truth-bias effect, whereas liars were correctly classified in only 58% of cases, a rate that is close to chance level. In conclusion, SCAN was found to be ineffective for lie detection, consistent with prior independent research, and its use is discouraged due to potential harm and lack of efficacy.