Purpose:<\/b> Clinical ordinal rating scales of movements, e.g., the Expanded Disability Status Scale, have poor intra- and interrater reliability, are insensitive to subtle differences and result in coarse-grained ratings compared to relative comparative rating methods. We therefore established video-based setwise comparison as a fine-grained, reliable and efficient rating method of motor dysfunction using algorithmic support.<\/p>\n
Materials and methods:<\/b> Eight neurologists rated a set of 40 multiple sclerosis patient videos of the Finger-to-Nose-Test using both the newly developed setwise comparison and the established pairwise comparison techniques, which result in a continuous rating scale. Reliability was assessed by the intra-class correlation coefficient. Construct validity was estimated as Pearson\u2019s correlation between the continuous scale and severity ratings according to the Neurostatus scale for upper-extremity tremor\/dysmetria and the Nine-hole-peg-test. Comparing the time needed for ratings assessed efficiency.<\/p>\n
Results:<\/b> Intra-class correlation coefficient was 0.83 for setwise and 0.7 for pairwise comparison. Correlation to the tremor\/dysmetria score of the Neurostatus was 0.86 for both rating procedures and correlation to the Nine-hole-peg-test was 0.64 (setwise) and 0.66 (pairwise). The time needed to rate 40 videos was 22.9\u2009\u00b1\u20096.9\u2009minutes (setwise) and 77.8\u2009\u00b1\u200914.5\u2009minutes (pairwise).<\/p>\n
Conclusions:<\/b> Setwise comparison is an efficient, valid and reliable method for fine-grained rating of motor dysfunction that can be applied to larger datasets. It is substantially more efficient than pairwise comparison.<\/p>\n","protected":false},"excerpt":{"rendered":"
Purpose: Clinical ordinal rating scales of movements, e.g., the Expanded Disability Status Scale, have poor intra- and interrater reliability, are insensitive to subtle differences and result in coarse-grained ratings compared to relative comparative rating methods. We therefore established video-based setwise comparison as a fine-grained, reliable and efficient rating method of motor dysfunction using algorithmic support. 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