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口腔健康素养与在大学综合牙科诊所就诊的成年人预约失约之间的关系。

The association between oral health literacy and failed appointments in adults attending a university-based general dental clinic.

机构信息

Division of Public Health and Community Dentistry, University of California, Los Angeles, School of Dentistry, Los Angeles, CA, USA.

出版信息

Community Dent Oral Epidemiol. 2014 Jun;42(3):263-70. doi: 10.1111/cdoe.12089. Epub 2013 Dec 24.

Abstract

OBJECTIVES

The purpose of this study is to determine the association between personal characteristics, a person's oral health literacy, and failing to show for dental appointments at a university dental clinic.

METHODS

A secondary data analysis was conducted on data collected from 200 adults at a university dental clinic between January 2005 and December 2006. In the original study, an oral health literacy instrument, the Rapid Estimate of Adult Literacy in Medicine and Dentistry (REALM-D), was administered, sociodemographic and health information seeking behavior was gathered, and electronic records were reviewed.

RESULTS

Descriptive and bivariate analyses and a classification and regression tree (CART) analysis were conducted. Seeking health information through fewer sources vs. multiple sources was the strongest predictor of failing to show. The subjects' oral health literacy, as measured by the REALM-D List 3 score, was the next most significant variable. Classification and regression tree analyses also selected gender, chief complaint, age, and payment type as predictor variables.

CONCLUSIONS

Multiple factors contribute to failing to show for dental appointments. However, individuals who use fewer sources of oral health information, a subset of health literacy skills, are more likely to fail to show for dental appointments.

摘要

目的

本研究旨在确定个人特征、口腔健康素养与大学牙科诊所预约失约之间的关联。

方法

对 200 名 2005 年 1 月至 2006 年 12 月在大学牙科诊所就诊的成年人的数据进行二次数据分析。在最初的研究中,使用了口腔健康素养工具——医学和牙科成人快速估计阅读能力(REALM-D)进行评估,收集了社会人口统计学和健康信息寻求行为,并审查了电子记录。

结果

进行了描述性和双变量分析以及分类回归树(CART)分析。与通过多种来源相比,通过较少来源寻求健康信息是失约的最强预测因素。REALM-D 列表 3 分数衡量的口腔健康素养是下一个最重要的变量。分类回归树分析还选择了性别、主要诉求、年龄和支付类型作为预测变量。

结论

多种因素导致预约失约。然而,使用较少口腔健康信息来源的个体,即健康素养技能的一个子集,更有可能失约。

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