Suppr超能文献

儿童中风知识的社区层面衡量指标:来自嘻哈中风项目的研究结果

Community-Level Measures of Stroke Knowledge among Children: Findings from Hip Hop Stroke.

作者信息

Simmons Cailey, Noble James M, Leighton-Herrmann Ellyn, Hecht Mindy F, Williams Olajide

机构信息

Albany Medical College, Albany, New York.

Department of Neurology, Columbia University Medical Center, New York, New York; Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York; G.H. Sergievsky Center, Columbia University, New York, New York.

出版信息

J Stroke Cerebrovasc Dis. 2017 Jan;26(1):139-142. doi: 10.1016/j.jstrokecerebrovasdis.2016.08.045. Epub 2016 Oct 14.

Abstract

BACKGROUND

Community-level determinants of stroke knowledge among children are unknown but could meaningfully impact public stroke education campaigns. We explored for associations between community- and school-level quality measures relative to baseline stroke knowledge among children participating in the Hip Hop Stroke program.

METHODS

Baseline stroke knowledge assessments were performed in 2839 fourth-, fifth-, and sixth-grade students (ages 9-11 years) from November 2005 to April 2014. Knowledge was assessed relative to school performance grade (SPG, graded A-F; a school-level measure determined by the New York City [NYC] Department of Education) and economic need index (ENI, range: 0-2; a community-level, within-school measure of subsidized housing and meals with higher scores indicating more socioeconomic distress).

RESULTS

Schools studied included those with SPG = B (n = 196), SPG = C (n = 1590), and SPG = D (n = 1053) and mean ENI = .85 (standard deviation: .23). A composite assessment of knowledge, including 4 stroke symptoms (blurred vision, facial droop, sudden headache, and slurred speech), was conducted consistently since 2006. Overall, students correctly identified a mean of 1.74 stroke symptoms (95% confidence interval: 1.70-1.79; possible range: 0-4, expected value of chance response alone or no knowledge = 2). For quartiles of ENI, mean knowledge scores are as follows: ENI = 2.00, ENI = 2.09, ENI = 1.46, and ENI = 1.56 (ENI and ENI versus ENI, P < .001). For SPG, SPG = B schools: 2.09, SPG = C: 1.83, and SPG = D: 1.56 (SPG = C and SPG = D versus SPG = B schools, P ≤ .05).

CONCLUSIONS

Children's stroke knowledge was lowest in NYC communities with greater economic need and lower school performance. These findings could guide stroke education campaign implementation strategies.

摘要

背景

儿童中风知识的社区层面决定因素尚不清楚,但可能对公共中风教育活动产生重大影响。我们探讨了参与嘻哈中风项目的儿童社区和学校层面质量指标与基线中风知识之间的关联。

方法

2005年11月至2014年4月,对2839名四、五、六年级学生(9 - 11岁)进行了基线中风知识评估。根据学校表现等级(SPG,评分A - F;由纽约市[NYC]教育部确定的学校层面指标)和经济需求指数(ENI,范围:0 - 2;社区层面、校内补贴住房和膳食的指标,分数越高表明社会经济困境越大)对知识进行评估。

结果

研究的学校包括SPG = B(n = 196)、SPG = C(n = 1590)和SPG = D(n = 1053)的学校,平均ENI = 0.85(标准差:0.23)。自2006年以来,对包括4种中风症状(视力模糊、面部下垂、突发头痛和言语不清)的知识进行了综合评估。总体而言,学生正确识别的中风症状平均为1.74种(95%置信区间:1.70 - 1.79;可能范围:0 - 4,仅随机回答或无知识的预期值 = 2)。对于ENI的四分位数,平均知识得分如下:ENI = 2.00、ENI = 2.09、ENI = 1.46和ENI = 1.56(ENI与ENI对比,P < 0.001)。对于SPG,SPG = B的学校:2.09,SPG = C的学校:1.83,SPG = D的学校:1.56(SPG = C和SPG = D的学校与SPG = B的学校对比,P≤0.05)。

结论

在经济需求更大且学校表现较低的纽约市社区,儿童的中风知识水平最低。这些发现可为中风教育活动的实施策略提供指导。

相似文献

4
Stroke education program of act FAST for junior high school students and their parents.初中学生及其家长的 FAST 行动中风教育计划。
J Stroke Cerebrovasc Dis. 2014 May-Jun;23(5):1040-5. doi: 10.1016/j.jstrokecerebrovasdis.2013.08.021. Epub 2013 Oct 2.
6
Long-term learning of stroke knowledge among children in a high-risk community.高危社区儿童中风知识的长期学习。
Neurology. 2012 Aug 21;79(8):802-6. doi: 10.1212/WNL.0b013e3182661f08. Epub 2012 Aug 8.

本文引用的文献

4
Long-term learning of stroke knowledge among children in a high-risk community.高危社区儿童中风知识的长期学习。
Neurology. 2012 Aug 21;79(8):802-6. doi: 10.1212/WNL.0b013e3182661f08. Epub 2012 Aug 8.
7
Stroke literacy in Central Harlem: a high-risk stroke population.哈莱姆中部的中风知识水平:高危中风人群。
Neurology. 2009 Dec 8;73(23):1950-6. doi: 10.1212/WNL.0b013e3181c51a7d. Epub 2009 Nov 4.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验