Development, contributions, and future directions of a multicenter child abuse research network

被引:1
|
作者
Henry, M. Katherine [1 ,2 ,3 ]
Lindberg, Daniel M. [4 ]
Campbell, Kristine A. [5 ]
Wood, Joanne N. [6 ]
机构
[1] Univ Pennslvania, Perelman Sch Med, Div Gen Pediat Clin Futures, Philadelphia, PA 19104 USA
[2] Univ Pennslvania, Perelman Sch Med, Childrens Hopsital Philadelphia, Dept Radiol, Philadelphia, PA 19104 USA
[3] Univ Pennslvania, Perelman Sch Med, Dept Pediat, Philadelphia, PA 19104 USA
[4] Univ Colorado, Kempe Ctr Prevent & Treatment Child Abuse & Neglec, Sch Med, Dept Emergency Med, 12631 E 17 th Ave Mailstop C326, Aurora, CO 80045 USA
[5] Univ Utah, Primary Childrens Hosp, Ctr Safe & Hlth Families, Dept Pediat, Salt Lake City, UT USA
[6] Univ Penn, Childrens Hosp Philadelphia, Perelman Sch Med, Div Gen Pediat,PolicyLab & Clin Futures, Philadelphia, PA 19104 USA
基金
美国医疗保健研究与质量局;
关键词
CAPNET; Multicenter studies; Child abuse; OCCULT HEAD-INJURY; RESEARCH PRIORITIES; PEDIATRICS; TRAUMA;
D O I
10.1016/j.cppeds.2024.101573
中图分类号
R72 [儿科学];
学科分类号
100202 ;
摘要
CAPNET is a multicenter child abuse pediatrics research network developed to support research that will make the medical care of potentially abused children more effective, safe, and fair. CAPNET currently collects detailed clinical data from child physical abuse evaluations from 11 leading pediatric centers across the U.S. From its inception, the goal of CAPNET was to support multiple research studies addressing the care of children undergoing evaluations for physical abuse and to create a flexible data collection and quality assurance system to be a resource for the wider community of child maltreatment l researchers. Annually, CAPNET collects rich clinical data on over 4000 children evaluated due to concerns for physical abuse. CAPNET's data are well-suited to studies improving the standardization, equity, and accuracy of evaluations in the medical setting when child physical abuse is suspected. Here we describe CAPNET's development, content, lessons learned, and potential future directions of the network.
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页数:5
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