The Role of Demographic and Symbolic Features in Clinical Arabic Graphesthesia Testing

Autor: Maan J. Al-Herbish, Lujain M. Al-Yousef, Mohammed Al-Nafisah, Mohammed H. Alanazy, Taim Muayqil, Lubna M. Halawani, Bandar N. Aljafen, Sakhar S. Albader
Rok vydání: 2018
Předmět:
Zdroj: European Neurology. 80:19-27
ISSN: 1421-9913
0014-3022
Popis: Objective: Graphesthesia is the ability to identify a symbol traced on the skin. Agraphesthesia is the impairment in this ability and is encountered in various disorders of the somatosensory pathways. We aimed to describe the demographic and symbolic features that influence correct recognition of Arabic graphesthesia stimuli in healthy Arabic individuals. Methods: Participants were community dwelling healthy Arabian individuals of 18 years of age or older. Demographic information collected included age, gender, years of education, and hand dominance. Assessment was conducted using a list of 15 symbols drawn in a single stroke while the hands were obscured from vision. Symbols were current letters and numbers from Arabic script. Each participant was exposed to 60 attempts in total in a random order and correct responses were counted. Results: A total of 126 male and female participants were included. On average, men scored less than women (p < 0.0001), older subjects scored less than those below 30 years of age (p = 0.03), and higher years of education resulted in higher scores (p = 0.047) while handedness did not significantly associate with performance. More correct responses were seen for numerical symbols than letters (p < 0.0001). Symbols with unique script were more likely to be correctly identified. Conclusions: Number and letter symbols traced on the palm are identified with varying levels of accuracy when conducted according to our method. Female gender, younger age, and higher education are associated with higher scores. Among the many potential symbolic properties that contribute to recognition, a numeric symbol with a unique script is most likely to be correctly identified.
Databáze: OpenAIRE