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Journal Article

Citation

Gong H, Wang Y, Li Y, Ye P, Xie L, Lu G, Liu J, Song J, Zhai X, Xu H, Duan L. Front. Pediatr. 2023; 11: e970867.

Copyright

(Copyright © 2023, Frontiers Media)

DOI

10.3389/fped.2023.970867

PMID

37187581

PMCID

PMC10175816

Abstract

BACKGROUND: Understanding the occurrence and severity of child injuries is the cornerstone of preventing child injuries. Currently, there is no standardized child injury surveillance dataset in China.

METHODS: Multistage consultation by a panel of Chinese experts in child injury to determine items to include in the core dataset (CDS) was performed. The experts participated in two rounds of the modified Delphi method comprising a consultation questionnaire investigation (Round 1) and a face-to-face panel discussion (Round 2). Final consensus was established based on the opinions of the experts regarding the modified CDS information collection items. Enthusiasm and authority exhibited by the experts were evaluated by the response rate and using the expert authority coefficient, respectively.

RESULTS: The expert panel included 16 experts in Round 1 and 15 experts in Round 2. The experts during both rounds had a high degree of authority, with an average authority coefficient of 0.86. The enthusiasm of the experts was 94.12%, and the proportion of suggestions reached 81.25% in Round 1 of the modified Delphi method. The draft CDS evaluated in Round 1 included 24 items, and expert panelists could submit recommendations to add items. Based on findings in Round 1, four additional items, including nationality, residence, type of family residence, and primary caregiver were added to the draft of the CDS for Round 2. After Round 2, consensus was reached on 32 items arranged into four domains-general demographic information, injury characteristics, clinical diagnosis and treatment, and injury outcome-to include in the final CDS.

CONCLUSION: The development of a child injury surveillance CDS could contribute to standardized data collection, collation, and analysis. The CDS developed here could be used to identify actionable characteristics of child injury to assist health policymakers in designing evidence-based injury prevention interventions.


Language: en

Keywords

child injury; core dataset; injury surveillance; modified Delphi method; surveillance tool

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