Qianqian Pan1, Stephen Westland2, Roger Ellwood3. 1. School of Design, University of Leeds, Leeds, LS2 9JT, United Kingdom. Electronic address: q.pan@leeds.ac.uk. 2. School of Design, University of Leeds, Leeds, LS2 9JT, United Kingdom. Electronic address: s.westland@leeds.ac.uk. 3. Colgate Palmolive Dental Health Unit, Williams House, Manchester Science Park, Manchester, M15 6SE, United Kingdom. Electronic address: roger.ellwood@manchester.ac.uk.
Abstract
OBJECTIVES: To evaluate the performance of existing equations that measure perceptual whiteness of teeth. METHODS: Three new psychophysical experiments were conducted and combined with two previously published experiments to form a large set of data to test performance of whiteness indices. Three whiteness indices (WIC, WIO, WID,) were compared with regard to their ability to measure perceived whiteness. Coefficient of determination (r2) and '% wrong decisions' were used as measures of performance. One of the new experiments involved 500 participants across five different countries to explore the effect of gender, age and culture on whiteness perception. RESULTS: Equations (WIO and WID) that have been optimized for use with tooth whiteness better correlated with visual perceptions of changes in tooth whiteness than the more general CIE whiteness index (WIC). The best performance was given by WIO (in terms of both r2 and % wrong decisions). No effect of age, gender or culture was found on whiteness perception. CONCLUSIONS: WIO is a robust method for assessing whiteness of human teeth.
OBJECTIVES: To evaluate the performance of existing equations that measure perceptual whiteness of teeth. METHODS: Three new psychophysical experiments were conducted and combined with two previously published experiments to form a large set of data to test performance of whiteness indices. Three whiteness indices (WIC, WIO, WID,) were compared with regard to their ability to measure perceived whiteness. Coefficient of determination (r2) and '% wrong decisions' were used as measures of performance. One of the new experiments involved 500 participants across five different countries to explore the effect of gender, age and culture on whiteness perception. RESULTS: Equations (WIO and WID) that have been optimized for use with tooth whiteness better correlated with visual perceptions of changes in tooth whiteness than the more general CIE whiteness index (WIC). The best performance was given by WIO (in terms of both r2 and % wrong decisions). No effect of age, gender or culture was found on whiteness perception. CONCLUSIONS: WIO is a robust method for assessing whiteness of human teeth.