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评估关于骨质疏松症和骨质疏松症药物治疗的在线患者信息的质量和可读性,并提出改进建议。

Evaluation of quality and readability of online patient information on osteoporosis and osteoporosis drug treatment and recommendations for improvement.

机构信息

School of Medicine, Keele University & Haywood Academic Rheumatology Centre, Stoke-on-Trent, UK.

School of Medicine, Keele University, Newcastle-under-Lyme, Staffordshire, UK.

出版信息

Osteoporos Int. 2021 Aug;32(8):1567-1584. doi: 10.1007/s00198-020-05800-7. Epub 2021 Jan 27.

DOI:10.1007/s00198-020-05800-7
PMID:33501570
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8376728/
Abstract

UNLABELLED

Patient information is important to help patients fully participate in their healthcare. Commonly accessed osteoporosis patient information resources were identified and assessed for readability, quality, accuracy and consistency. Resources contained inconsistencies and scored low when assessed for quality and readability. We recommend optimal language and identify information gaps to address.

INTRODUCTION

The purpose of this paper is to identify commonly accessed patient information resources about osteoporosis and osteoporosis drug treatment, appraise the quality and make recommendations for improvement.

METHODS

Patient information resources were purposively sampled and text extracted. Data extracts underwent assessment of readability (Flesch Reading Ease and Flesch-Kincaid Grade Level) and quality (modified International Patient Decision Aid Standards (m-IPDAS)). A thematic analysis was conducted, and keywords and phrases were used to describe osteoporosis and its treatment identified. Findings were presented to a stakeholder group who identified inaccuracies and contradictions and discussed optimal language.

RESULTS

Nine patient information resources were selected, including webpages, a video and booklets (available online), from government, charity and private healthcare providers. No resource met acceptable readability scores for both measures of osteoporosis information and drug information. Quality scores from the modified IPDAS ranged from 21 to 64% (7-21/33). Thematic analysis was informed by Leventhal's Common-Sense Model of Disease. Thirteen subthemes relating to the identity, causes, timeline, consequences and controllability of osteoporosis were identified. Phrases and words from 9 subthemes were presented to the stakeholder group who identified a predominance of medical technical language, misleading terms about osteoporotic bone and treatment benefits, and contradictions about symptoms. They recommended key descriptors for providers to use to describe osteoporosis and treatment benefits.

CONCLUSIONS

This study found that commonly accessed patient information resources about osteoporosis have highly variable quality, scored poorly on readability assessments and contained inconsistencies and inaccuracies. We produced practical recommendations for information providers to support improvements in understanding, relevance, balance and bias, and to address information gaps.

摘要

未加标签

患者信息对于帮助患者充分参与他们的医疗保健至关重要。确定并评估了常用的骨质疏松症患者信息资源的可及性、可读性、质量、准确性和一致性。资源存在不一致性,并且在质量和可读性评估方面得分较低。我们建议使用最佳语言并确定需要解决的信息差距。

引言

本文的目的是确定常用的骨质疏松症和骨质疏松症药物治疗患者信息资源,并评估其质量,提出改进建议。

方法

有针对性地采样患者信息资源并提取文本。对数据提取内容进行了可读性(Flesch 阅读容易度和 Flesch-Kincaid 年级水平)和质量(改良的国际患者决策辅助标准(m-IPDAS))评估。进行了主题分析,并使用关键词和短语来描述骨质疏松症及其治疗。研究结果提交给利益相关者小组,他们确定了不准确和矛盾之处,并讨论了最佳语言。

结果

共选择了 9 种患者信息资源,包括政府、慈善和私人医疗保健提供者提供的网页、视频和小册子(在线提供)。没有一种资源在骨质疏松症信息和药物信息的两种测量方法中都达到可接受的可读性分数。改良 IPDAS 的质量分数范围为 21%至 64%(7-21/33)。主题分析受 Leventhal 的疾病常识模型的启发。确定了与骨质疏松症的身份、原因、时间线、后果和可控性相关的 13 个子主题。将 9 个子主题的短语和单词提交给利益相关者小组,他们确定了医学专业术语的主导地位、关于骨质疏松性骨骼和治疗益处的误导性术语以及关于症状的矛盾。他们建议提供者使用关键描述符来描述骨质疏松症和治疗益处。

结论

本研究发现,常用的骨质疏松症患者信息资源质量差异很大,可读性评估得分较低,且存在不一致性和不准确之处。我们为信息提供者提供了切实可行的建议,以支持提高理解、相关性、平衡和偏见,并解决信息差距。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af83/8376728/acd508b7e27b/198_2020_5800_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af83/8376728/2e6f3dea2c33/198_2020_5800_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af83/8376728/acd508b7e27b/198_2020_5800_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af83/8376728/2e6f3dea2c33/198_2020_5800_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af83/8376728/acd508b7e27b/198_2020_5800_Fig2_HTML.jpg

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