Translation Symmetry and Familiarity of End-Point Anchor Points in Likert Scales
Authors
Abstract
Likert scales are widely used to measure agreement levels, typically on a structurally and linguistically symmetrical scale. In non-English settings, literal translations of scale anchors often produce awkward or asymmetrical phrases that deviate from everyday language, potentially affecting data validity. This study examines the impact of translations through an online experiment with 532 Slovenian smartphone users, randomly assigned to two groups. One group used structurally symmetrical translations (GroupSA), while the other used more natural but asymmetrical translations (GroupCA) to measure constructs related to information security within Protection Motivation Theory. GroupCA showed significant correlations with the dependent variable for all predictors, consistently higher Composite Reliability and Average Variance Extracted, slightly higher means, and lower skewness and kurtosis. Additionally, “Completely agree” was chosen more often than the less familiar “Strongly agree.” These results highlight the influence of translation choices on survey outcomes, emphasizing the need for careful linguistic adaptation in cross-cultural research.