Tzu-I Lee, Tsu-Hsin Howe, Hao-Ling Chen, Tien-Ni Wang; Predicting Handwriting Legibility in Taiwanese Elementary School Children. Am J Occup Ther 2016;70(6):7006220020. https://doi.org/10.5014/ajot.2016.016865
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© 2021 American Occupational Therapy Association
This study investigates handwriting characteristics and potential predictors of handwriting legibility among typically developing elementary school children in Taiwan. Predictors of handwriting legibility included visual–motor integration (VMI), visual perception (VP), eye–hand coordination (EHC), and biomechanical characteristics of handwriting. A total of 118 children were recruited from an elementary school in Taipei, Taiwan. A computerized program then assessed their handwriting legibility. The biomechanics of handwriting were assessed using a digitizing writing tablet. The children’s VMI, VP, and EHC were assessed using the Beery–Buktenica Developmental Test of Visual–Motor Integration. Results indicated that predictive factors of handwriting legibility varied in different age groups. VMI predicted handwriting legibility for first-grade students, and EHC and stroke force predicted handwriting legibility for second-grade students. Kinematic factors such as stroke velocity were the only predictor for children in fifth and sixth grades.
Task completion time, which was calculated in seconds from the first stroke to the last. A writing stroke was defined as the movement occurring between two zero crossings of the velocity function.
Stroke velocity, which was obtained by dividing the stroke length by the on-paper time during one stroke. The magnitude of stroke velocity indicates the speed of writing per stroke. The mean stroke velocity was derived from the average of all strokes in all of the writing tasks.
Stroke force, which was calculated by dividing the sum of the axial pen tip force by the number of sampling points of each stroke. A larger magnitude of stroke force indicates that the child put more pressure on the paper. The mean stroke force was calculated. In this study, we only recorded the axial pen force in the middle four-fifths of a stroke to avoid the large variations found in the starting and ending force of a stroke (Chang & Yu, 2013).
Pause time per stroke, which was derived by dividing the cumulative pause time period by the total stroke number.
Predictors of handwriting legibility vary among different age groups in elementary school children (e.g., integrating visual–perceptual processing, eye–hand coordination, and stroke force predicted legibility in first- and second-grade participants and biomechanical factors were the best predictors of legibility in fifth- and sixth-grade participants).
Because predictors vary, when clinicians evaluate a child’s handwriting performance, they must consider the influential factors for legibility for the child’s age.
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