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Motor cognitive processing speed estimation among the primary schoolchildren by deriving prediction formula: A
Vencita Priyanka Aranha1, Monika Moitra2, Shikha Saxena3
1Department of Pediatric Physiotherapy, Maharishi Markandeshwar Institute of Physiotherapy and Rehabilitation, Mullana, Haryana, India.
Insights
A new formula estimates motor cognitive processing speed (MCPS) in children using the ruler drop method. This simple tool can help identify children with slowed processing, aiding early intervention.
Area of Science:
- Pediatric Neurodevelopment
- Cognitive Psychology
- Motor Skill Assessment
Background:
- Motor cognitive processing speed (MCPS) is crucial for function and performance but underutilized clinically.
- Lack of convenient methods hinders MCPS assessment in children.
- This study addresses the need for a practical MCPS estimation tool for primary schoolchildren.
Purpose of the Study:
- To estimate motor cognitive processing speed (MCPS) in primary schoolchildren.
- To develop a convenient formula for MCPS assessment in children.
- To establish the predictability of age on MCPS in this population.
Main Methods:
- Cross-sectional study involving 204 primary schoolchildren (aged 6-12 years).
- Motor cognitive processing speed (MCPS) measured using the ruler drop method (RDM).
- Multiple regression analysis used to derive a predictive equation for MCPS.
Main Results:
- The mean MCPS was 230.01 ms ± 26.5 ms.
- A regression equation was derived: MCPS (ms) = 279.625 - 5.495 × age.
- The equation demonstrated 41.3% predictability (R=0.413) and 17.1% variability (R²=0.171).
Conclusions:
- A practical formula for predicting motor cognitive processing speed (MCPS) in primary schoolchildren using the ruler drop method (RDM) has been established.
- This formula can aid in identifying children with slowed processing speeds.
- The findings support the use of RDM for accessible MCPS assessment in pediatric populations.
Objectives:
Motor cognitive processing speed (MCPS) is often reported in terms of reaction time. In spite of being a significant indicator of function, behavior, and performance, MCPS is rarely used in clinics and schools to identify kids with slowed motor cognitive processing. The reason behind this is the lack of availability of convenient formula to estimate MCPS. Thereby, the aim of this study is to estimate the MCPS in the primary schoolchildren.
Materials And Methods:
Two hundred and four primary schoolchildren, aged 6-12 years, were recruited by the cluster sampling method for this cross-sectional study. MCPS was estimated by the ruler drop method (RDM). By this method, a metallic stainless steel ruler was suspended vertically such that 5 cm graduation of the lower was aligned between the web space of the child's hand, and the child was asked to catch the moving ruler as quickly as possible, once released from the examiner's hand. Distance the ruler traveled was recorded and converted into time, which is the MCPS. Multiple regression analysis of variables was performed to determine the influence of independent variables on MCPS.
Results:
Mean MCPS of the entire sample of 204 primary schoolchildren is 230.01 ms ± 26.5 standard deviation (95% confidence interval; 226.4-233.7 ms) that ranged from 162.9 to 321.6 ms. By stepwise regression analysis, we derived the regression equation, MCPS (ms) = 279.625-5.495 × age, with 41.3% (R = 0.413) predictability and 17.1% (R2 = 0.171 and adjusted R2 = 0.166) variability.
Conclusion:
MCPS prediction formula through RDM in the primary schoolchildren has been established.
