The relationship between working memory and processing speed: The influence of demographic factors in the South African sample.

Abstract

Abstract Working memory (WM) and processing speed (PS) seem to be related cognitive functions, as both play a role in learning and task management; however, demographic factors are often linked to cognitive performance and subject to cultural differences, which can potentially alter the relationship between these variables. This study aimed to explore the relationship between PS and WM, and to investigate whether PS moderates the relationship between demographic variables (age, years of education, language experience, socioeconomic status [SES], and gender) and WM. A total of 97 healthy multilingual adults (mean age = 32.4 and SD = 10, and mean years of education = 12.5 and SD = 1.8) participated in a battery of cognitive tests, which included the Symbol Digit Modality Test (SDMT), the Digit Span (DS) task, and the Letter Number Sequencing (LNS) test. The study employed a non-experimental, cross-sectional, correlational design. The findings from a correlation analysis indicated a significant association between WM measures and SDMT-Oral. A General Linear Model (GLM) analysis results demonstrated that age, years of education, and English as a first language (EFL) had significant correlations with the majority of cognitive measures, while number of known languages (NL) correlated solely with DS sequencing, and gender exclusively with DS forward. Also, PS, as measured by SDMT-Oral, predicted WM on selected demographic variables. Furthermore, the results confirmed the moderation of PS on the relationship between age and EFL on Long Digit Span Backward (LDSB). Additionally, age interacted with LNS; also, age and Living Standard Measure (LSM) category interacted with LLNS. There was an effect of years of education on SDMT-Oral and LLNS, while no significant interaction between SDMT-Oral, years of education, and WM measures. Overall, this study indicated that PS and demographic variables influence WM performance. Keywords: cognitive assessment, processing speed, working memory, multilingualism, socioeconomic status, education