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Reliable and valid measure of lying
- The scale was also assessed for interitem consistency (Cronbach’s α) and test-retest reliability. We found that the LiES scale was a reliable and valid measure of lying. The LiES scale may be a useful tool for assessing the general tendency to lie across various contexts.
scholarlypublishingcollective.org/uip/ajp/article/132/3/343/257567/Development-of-the-Lying-in-Everyday-Situations
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Sep 1, 2019 · We found that the LiES scale was a reliable and valid measure of lying. The LiES scale may be a useful tool for assessing the general tendency to lie across various contexts.
Oct 1, 2019 · The scale was also assessed for interitem consistency (Cronbach’s α) and test-retest reliability. We found that the LiES scale was a reliable and valid measure of lying. The LiES scale may be a useful tool for assessing the general tendency to lie across various contexts.
Jun 28, 2023 · The LiES scale can be used by researchers to study lying broadly, but it might also be used to assess mendacity in contexts such as the workplace, romantic relationships, and other contexts in which everyday lies are common.
Aug 12, 2023 · The LiES Scale (Hart et al., 2019) is a 14-item questionnaire that measures an individual’s inclination to lie in everyday life (e.g. ‘I lie to stay out of arguments with people’) on a seven-point Likert-type scale from strongly disagree (1) to strongly agree (7).
in Everyday Situations (LiES) Scale (28) is a 14‐item scale designed to assess the propensity to lie. The LiES scale has demonstrated high internal consistency, test‐retest reliability, and concurrent validity and displayed high internal consis-tency reliability in the current study (Cronbach's α¼0.88). The
Oct 16, 2020 · The LiES scale has demonstrated high internal consistency, test-retest reliability, and concurrent validity and displayed high internal consistency reliability in the current study (Cronbach's α=0.88).
Lie scales play a crucial role in ensuring the accuracy and reliability of psychological assessments. By detecting and accounting for response distortions, researchers and clinicians can obtain more valid and representative data, leading to better-informed decisions and appropriate interventions.