Peer-reviewed article
Estimating indicator weights for the motor health of pre-school-aged children: an integrated-methods approach.
Du D, Chai L, Fu Q, Yang G, Huang Y et al. ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study develops a weighted indicator system to evaluate motor health in pre-school children by combining expert judgment and data-driven methods. Researchers used the Delphi method and entropy weighting to create weights for six primary indicators and 26 secondary indicators of motor development. The final weighting system integrates both expert opinion and patterns in data to provide a more credible assessment tool. The study does not test an intervention but rather creates a measurement framework for evaluating children's motor development.
Key points
- Six primary indicators have combined weight of 1.0, with individual weights ranging from 0.109 to 0.213
- 26 secondary indicators have weights ranging from 0.014 to 0.215
- For second-level indicators, the integrated method showed strong correlation with Delphi method (r = 0.917, P < 0.001) and entropy method (r = 0.558, P = 0.003)
- The integrated subjective-objective approach combines expert experience with intrinsic data patterns
- Motor health assessment during pre-school years is identified as a pressing issue requiring urgent attention
Limitations
The document provides no information about how the indicator system was validated against actual child outcomes or whether it can predict later development. The study does not test whether using these weights actually improves assessment quality compared to other approaches.
Abstract
Introduction Motor health and long-term development of pre-school children is a pressing issue that requires urgent attention. While motor health is critically important for the early growth stage of pre-school children, establishing a multi-dimensional health evaluation indicator weighting system using an integrated subjective-objective weighting method remains a cutting-edge challenge in current research. Methods WPS Office 6.4 and IBM® SPSS® Statistics 26.0 were used to analyze the data, with the significance threshold set at P-value < 0.05. The integrated subjective-objective weighting method mainly consists of four steps: (i) the Delphi subjective weighting method, including A i , A s , A a , W i , Wi' ω; (ii) the entropy objective weighting method, including X ij , P ij , E j , d j , and W j ; (iii) the comprehensive weighting method, including relevant parameters Wj* , among others; (iv) IBM® SPSS® Amos (TM) 24.0 was used to conduct further data analysis. Results The total combined weight of the six primary indicators is 1.0, with individual weights ranging from 0.109 to 0.213. The corresponding weights of the 26 secondary indicators range from 0.014 to 0.215. Regarding the weighting of first-level indicators, no significant correlation was found between the comprehensive weighting method and the Delphi method (r = 0.771, P = 0.072), nor between the comprehensive weighting method and the entropy weight method (r = 0.600, P = 0.208). Similarly, no significant correlation was observed between the Delphi method and the entropy weight method (r = 0.143, P = 0.787). In contrast, for second-level indicators, the comprehensive weighting method demonstrated a strong correlation with both the Delphi method (r = 0.917, P < 0.001) and the entropy weight method (r = 0.558, P = 0.003). However, no significant correlation was detected between the Delphi method and the entropy weight method (r = 0.268, P = 0.185). Conclusion By adopting an integrated subjective-objective weighting method, this study establishes evaluation indicator weights based on two foundations: the intrinsic patterns within the data and expert experience. The weights derived through this dual-foundation approach therefore exhibit improved rationality and credibility, providing important reference value for the comprehensive assessment of pre-school children's motor health.