Open Access Journal

ISSN : 2456-1304 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Science Engineering and Management (IJSEM)

Monthly Journal for Science Engineering and Management

ISSN : 2456-1304 (Online)

Development and Validation of Predictive Model for Post-Cerebral Palsy Recovery

Author : Dr.chinmayee Patel, Dr.Anilkumar Mishr

Date of Publication :8th August 2024

Abstract: Background: It is found that 10% of the global population has some form of disability from different causes; in India, it is 3.8% of the population. Nearly 15-20% of physically disabled children are affected by Cerebral Palsy. In India, the estimated incidence is around 3/1000 live births. Cerebral palsy is the most common motor disability in childhood. Predictive modelling: is a procedure that utilizes data and statistics to predict outcomes through the use of data models. Most commonly it is used to identify the event one wants to forecast or predict in the future. Predictive modeling can be exercised for this type of unknown future event. Early specific forecasting of recovery may be helpful to set realistic goals, to plan proper discharge policy, and requirement of home adjustment and also social support. For the same, there is a need to develop a new scale for the assessment of sensory and motor disability among children with cerebral palsy. Participant Information and Method: Self-developed 30 questionnaire “Cerebral Palsy Recovery Predictor – GFMS Model Score” was developed by the researcher which included questions regarding the sensory and motor function among cerebral palsy patients. Gross Motor Function Classification System (Assessed by physical examination) was matched with Gross Motor Function Classification System Model Score (Predicted by model). By matching actual & model scores Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value and overall accuracy was calculated. The model was verified by 6 paediatric physiotherapy out of which 3 were Clinical therapist and 3 were academicians with post graduate degree in masters in paediatric physiotherapy with minimum of 5 years of experience out of which 3 were Clinical therapist and 3 were academicians. Once the suggestion was received from all the physiotherapist, modification in the scale were made as per the suggestions and the scale was resent for the validation and final scale was produced for use. Result: Predictive Model for the Assessment of Sensory and Motor Functions is a newly developed with good validity to assess the sensory and motor functions among children with cerebral palsy. Conclusion: Predictive Model for the Assessment of Sensory and Motor Functions is a set of questionnaires with good validity to assess the sensory and motor functions among children with cerebral palsy and can be used to assess the sensory and motor dysfunctions among children with disabilities following cerebral palsy.

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