基于微信公众号的神经系统罕见病相关治疗信息质量评价

  目的  评价基于微信公众号的神经系统罕见病相关治疗信息的质量。  方法  查询7种神经系统罕见疾病的微信公众号，筛选后等比例随机抽取其中的治疗类文章，使用DISCERN量表双人独立评估，以二者平均分作为最终质量评价指标，并进一步探索文章质量影响因素。  结果  共纳入来自28个公众号的173篇文章，公众号运营主体中医疗团体数量最多(50.29%)，文章涉及的疾病以肌萎缩侧索硬化为主(82.66%)，而涉及的治疗形式集中在常规护理支持(49.71%)。治疗类文章的整体信息质量较差，DISCERN评价分值为(30.27±7.20)分，“差”与“极差”占比达到86.70%，而“良”仅有3篇(1.73%)，无“优”等级文章，大部分文章未提供完整赞助方及引用信息、不治疗后果以及共同决策等信息。  结论  我国基于微信公众号的神经系统罕见病相关治疗信息在可信度和详尽度方面质量均较低，未来应重点加强对引用信息、不同治疗方法比较等关键点的把控，以确保信息完整。

Quality assessment of the therapeutic health information of rare neurological diseases on WeChat official account

  Objective  To assess the quality of online health information about rare neurological diseases on the WeChat official account in China.  Methods  We screened the WeChat official accounts about seven rare neurological diseases, and all existing articles in them were selected. The articles related to the treatment were then included using proportional random sampling. The quality was assessed independently by two well-trained reviewers using the DISCERN. The mean scores of the two observers were used as the final score to assess quality and to further explore the influencing factors for quality.  Results  A total of 28 WeChat official accounts and 173 articles were included for analysis. Medical groups posted most of the articles (50.29%), amyotrophic lateral sclerosis was the most frequently discussed disease (82.66%), and the treatment type of articles mainly focused on the nursing support (49.71%). The whole quality was poor, with a low average score of 30.27±7.20. Most of the articles (86.70%) were graded in the "poor" and the "worst", only 3 (1.73%) articles were in the "good", and no "excellent" articles existed. Most articles did not provide complete sponsor and citation resources, the consequence without treatment, and the co-determination information.  Conclusions  For rare neurological diseases, the quality of health information on the WeChat official account in China was poor based on the credibility and circumstantiality. Future work should strengthen the quality management of key information, such as citation resources and the comparison information between advantages and disadvantages of different treatments, to further ensure the accuracy of therapeutic health information.