Egenis-ESRC Centre for Genomics in Society, University of Exeter, Exeter, UK.
J Am Med Inform Assoc. 2012 May-Jun;19(3):479-88. doi: 10.1136/amiajnl-2011-000243. Epub 2011 Aug 16.
Healthcare debates and policy developments are increasingly concerned with a broad range of values-related areas. These include not only ethical, moral, religious, and other types of values 'proper', but also beliefs, preferences, experiences, choices, satisfaction, quality of life, etc. Research on such issues may be difficult to retrieve. This study used word frequency analysis to generate a broad pool of search terms and a brief filter to facilitate relevant searches in bibliographic databases.
Word frequency analysis for 'values terms' was performed on citations on diabetes, obesity, dementia, and schizophrenia (Medline; 2004-2006; 4440 citations; 1,110,291 words). Concordance® and SPSS 14.0 were used. Text words and MeSH terms of high frequency and precision were compiled into a search filter. It was validated on datasets of citations on dentistry and food hypersensitivity.
144 unique text words and 124 unique MeSH terms of moderate and high frequency (≥ 20) and very high precision (≥ 90%) were identified. Of these, 19 text words and seven MeSH terms were compiled into a 'brief values filter'. In the derivation dataset, it had a sensitivity of 76.8% and precision of 86.8%. In the validation datasets, its sensitivity and precision were, respectively, 70.1% and 63.6% (food hypersensitivity) and 47.1% and 82.6% (dentistry).
This study provided a varied pool of search terms and a simple and highly effective tool for retrieving publications on health-related values. Further work is required to facilitate access to such research and enhance its chances of being translated into practice, policy, and service improvements.
医疗保健的辩论和政策发展越来越关注广泛的与价值观相关的领域。这些不仅包括伦理、道德、宗教和其他类型的“适当”价值观,还包括信念、偏好、经验、选择、满意度、生活质量等。研究此类问题可能具有一定难度。本研究使用词频分析生成广泛的检索词,并使用简短的过滤器来促进书目数据库中相关检索。
对糖尿病、肥胖症、痴呆症和精神分裂症的文献(Medline;2004-2006;4440 条引文;1110291 个单词)进行了“价值观术语”的词频分析。使用 Concordance® 和 SPSS 14.0。将高频率和高精度的文本词和 MeSH 术语汇编成一个搜索过滤器。并在牙科学和食物过敏的引文数据集上进行了验证。
确定了 144 个独特的文本词和 124 个中等和高频率(≥20)和非常高精度(≥90%)的独特 MeSH 术语。其中,19 个文本词和 7 个 MeSH 术语被汇编成一个“简短的价值观过滤器”。在推导数据集,其敏感性为 76.8%,精度为 86.8%。在验证数据集,其敏感性和精度分别为 70.1%和 63.6%(食物过敏)和 47.1%和 82.6%(牙科学)。
本研究提供了一个多样化的检索词池和一个简单而高效的工具,用于检索与健康相关价值观的文献。需要进一步的工作来促进对这类研究的访问,并提高将其转化为实践、政策和服务改进的机会。