Development and validation of an algorithm-based choice of outcome measures for assessing motor developmental delay – A study protocol

Evidence-Based Practice (EBP) links the use of standardized outcome measures in the clinical decision-making process. Despite the availability of numerous evidence-based outcome measures in pediatric rehabilitation, their effective utilization in clinical practice is limited, thus affecting the knowledge translation process. In a clinical care setting, therapists face cognitive load and often employ heuristics to choose appropriate outcome measures due to a lack of knowledge or time constraints. The present study aims to minimize the cognitive load and bias on the therapist by introducing a machine learning-based algorithm to choose appropriate outcome measures for motor developmental delay. The investigators will review the existing literature to identify the relevant outcome measures and categorize them under key criteria to develop an algorithm. Subsequently, the algorithm will be subjected to expert and machine validation. Such an algorithm will improve the accuracy and consistency in choosing appropriate outcome measures for assessing motor developmental delay.