Evidence map›Paper›PMID 37187581›Full record

ArticleFrontiers in pediatrics2023

Development of a core dataset for child injury surveillance: a modified Delphi study in China.

Hairong Gong, Yuan Wang, Yongzhen Li, Pengpeng Ye, Li Xie, Guoping Lu, Jing Liu, Jun Song, Xiaowen Zhai, Hong Xu and 1 more

Abstract read
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Article in Frontiers in pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Hairong Gong *Emergency Department Children's Hospital of Fudan University, Shanghai, China.
Yuan Wang *National Center for Chronic and Non-Communicable Diseases Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yongzhen LiDepartment of Clinical Nutrition New Hong Qiao Campus for Children's Hospital of Fudan University, Shanghai China.
Pengpeng YeNational Center for Chronic and Non-Communicable Diseases Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Li XieClinical Research Institute School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Guoping LuEmergency Department Children's Hospital of Fudan University, Shanghai, China.
Jing LiuEmergency Department Children's Hospital of Fudan University, Shanghai, China.
Jun SongEmergency Department Children's Hospital of Fudan University, Shanghai, China.
Xiaowen ZhaiEmergency Department Children's Hospital of Fudan University, Shanghai, China.
Hong XuEmergency Department Children's Hospital of Fudan University, Shanghai, China.
Leilei DuanNational Center for Chronic and Non-Communicable Diseases Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

child injurycore datasetinjury surveillancemodified Delphi methodsurveillance tool

Identifiers

PMID37187581
PMCPMC10175816

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