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本文引用的文献

1
Frequency format diagram and probability chart for breast cancer risk communication: a prospective, randomized trial.用于乳腺癌风险沟通的频率格式图表和概率图:一项前瞻性随机试验。
BMC Womens Health. 2008 Oct 20;8:18. doi: 10.1186/1472-6874-8-18.
2
Presenting health risk information in different formats: the effect on participants' cognitive and emotional evaluation and decisions.以不同形式呈现健康风险信息:对参与者认知、情感评估及决策的影响。
Patient Educ Couns. 2008 Dec;73(3):443-7. doi: 10.1016/j.pec.2008.07.013. Epub 2008 Aug 21.
3
Clinical implications of numeracy: theory and practice.数字素养的临床意义:理论与实践。
Ann Behav Med. 2008 Jun;35(3):261-74. doi: 10.1007/s12160-008-9037-8. Epub 2008 Aug 2.
4
Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations.传达健康风险的数字、文字和视觉形式:建议的最佳实践及未来建议。
Med Decis Making. 2007 Sep-Oct;27(5):696-713. doi: 10.1177/0272989X07307271. Epub 2007 Sep 14.
5
Validation of the Subjective Numeracy Scale: effects of low numeracy on comprehension of risk communications and utility elicitations.主观算术能力量表的验证:低算术能力对风险沟通理解和效用引出的影响。
Med Decis Making. 2007 Sep-Oct;27(5):663-71. doi: 10.1177/0272989X07303824. Epub 2007 Jul 24.
6
The influence of graphic format on breast cancer risk communication.图形格式对乳腺癌风险沟通的影响。
J Health Commun. 2006 Sep;11(6):569-82. doi: 10.1080/10810730600829916.
7
Design features of graphs in health risk communication: a systematic review.健康风险沟通中图表的设计特点:一项系统综述
J Am Med Inform Assoc. 2006 Nov-Dec;13(6):608-18. doi: 10.1197/jamia.M2115. Epub 2006 Aug 23.
8
How health care systems can begin to address the challenge of limited literacy.医疗保健系统如何开始应对识字率有限的挑战。
J Gen Intern Med. 2006 Aug;21(8):884-7. doi: 10.1111/j.1525-1497.2006.00544.x.
9
Numeracy and decision making.算术能力与决策制定。
Psychol Sci. 2006 May;17(5):407-13. doi: 10.1111/j.1467-9280.2006.01720.x.
10
Formats for improving risk communication in medical tradeoff decisions.改善医疗权衡决策中风险沟通的形式。
J Health Commun. 2006 Mar;11(2):167-82. doi: 10.1080/10810730500526695.

健康素养、计算能力与图形化乳腺癌风险估计的解读。

Health literacy, numeracy, and interpretation of graphical breast cancer risk estimates.

机构信息

Saddleback Memorial Medical Center, USA.

出版信息

Patient Educ Couns. 2011 Apr;83(1):92-8. doi: 10.1016/j.pec.2010.04.027.

DOI:10.1016/j.pec.2010.04.027
PMID:20554149
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4041683/
Abstract

OBJECTIVE

Health literacy and numeracy are necessary to understand health information and to make informed medical decisions. This study explored the relationships among health literacy, numeracy, and ability to accurately interpret graphical representations of breast cancer risk.

METHODS

Participants (N=120) were recruited from the Facing Our Risk of Cancer Empowered (FORCE) membership. Health literacy and numeracy were assessed. Participants interpreted graphs depicting breast cancer risk, made hypothetical treatment decisions, and rated preference of graphs.

RESULTS

Most participants were Caucasian (98%) and had completed at least one year of college (93%). Fifty-two percent had breast cancer, 86% had a family history of breast cancer, and 57% had a deleterious BRCA gene mutation. Mean health literacy score was 65/66; mean numeracy score was 4/6; and mean graphicacy score was 9/12. Education and numeracy were significantly associated with accurate graph interpretation (r=0.42, p<0.001 and r=0.65, p<0.001, respectively). However, after adjusting for numeracy in multivariate linear regression, education added little to the prediction of graphicacy (r(2)=0.41 versus 0.42, respectively).

CONCLUSION

In our highly health-literate population, numeracy was predictive of graphicacy.

PRACTICE IMPLICATIONS

Effective risk communication strategies should consider the impact of numeracy on graphicacy and patient understanding.

摘要

目的

健康素养和计算能力对于理解健康信息和做出明智的医疗决策是必要的。本研究探讨了健康素养、计算能力与准确解读乳腺癌风险图形表示之间的关系。

方法

参与者(N=120)从 Facing Our Risk of Cancer Empowered(FORCE)会员中招募。评估健康素养和计算能力。参与者解读了描述乳腺癌风险的图形,做出了假设的治疗决策,并对图形的偏好进行了评分。

结果

大多数参与者为白种人(98%),至少完成了一年的大学学业(93%)。52%的参与者患有乳腺癌,86%的参与者有乳腺癌家族史,57%的参与者有有害的 BRCA 基因突变。平均健康素养得分为 65/66;平均计算能力得分为 4/6;平均图形能力得分为 9/12。教育程度和计算能力与准确解读图形显著相关(r=0.42,p<0.001 和 r=0.65,p<0.001)。然而,在多元线性回归中调整计算能力后,教育对图形能力的预测作用不大(r(2)=0.41 与 0.42 相比,分别)。

结论

在我们这个健康素养较高的人群中,计算能力可以预测图形能力。

实践意义

有效的风险沟通策略应考虑计算能力对图形能力和患者理解的影响。