Research Department, Clinical Locomotion Science Network, Spine Centre of Southern Denmark, Hospital Lillebaelt, Middelfart, Denmark.
Spine (Phila Pa 1976). 2011 Oct 15;36(22):1878-84. doi: 10.1097/BRS.0b013e3181ffe53f.
Analysis of Roland Morris Disability Questionnaire (RMDQ) and Oswestry Disability Index (Oswestry) responses.
To determine the prevalence of unanswered questions on the RMDQ23 (23-item RMDQ version) and Oswestry questionnaires. To determine whether managing RMDQ23 missing data using proportional recalculation is more accurate than simply ignoring missing data.
It is likely that the most common method for calculating an RMDQ sum score is to simply ignore any unanswered questions. In contrast, the raw sum score on the Oswestry is converted to a 0 to 100 scale, with the advantage of allowing missing data to be accommodated by proportional recalculation.
The prevalence of unanswered RMDQ23 questions was measured in a research project and a routine care setting. The accuracy of the RMDQ23 proportional recalculation method was measured using 311 fully completed RMDQ23 and matching Oswestry questionnaire sets. Raw sum scores were calculated, and questions systematically dropped. At each stage, sum scores were converted to a score on a 0 to 100 scale and the error calculated. Wilcoxon Tests were used to compare the magnitude of the error scores.
The prevalence of people who did not answer one or more questions was 29.5% (RMDQ23) in routine care, and 13.9% (Oswestry) and 20.3% (RMDQ23) in a research project. Proportional recalculation was a more accurate method to calculate RMDQ sum scores than simply ignoring missing data, when two or more questions were unanswered.
Because of less error when missing data are present, the most accurate method for expressing RMDQ sum scores collected using Yes/No answers is conversion to a 0 to 100 scale. This conversion method is (a) if all questions are answered or only one question is unanswered, multiply the raw sum score by 100 divided by the total number of questions, and (b) if two or more questions are unanswered, multiply the raw sum score by 100 divided by the number of answered questions.
对 Roland Morris 残疾问卷（RMDQ）和 Oswestry 残疾指数（Oswestry）的回答进行分析。
确定 Roland Morris 残疾问卷 23 项（RMDQ23）和 Oswestry 问卷中未回答问题的比例。确定使用比例重新计算来处理 RMDQ23 缺失数据是否比简单地忽略缺失数据更准确。
最常见的计算 RMDQ 总分的方法可能是简单地忽略任何未回答的问题。相比之下，Oswestry 的原始总分转换为 0 到 100 的比例，通过比例重新计算可以容纳缺失数据的优点。
在研究项目和常规护理环境中测量未回答的 RMDQ23 问题的比例。使用 311 份完整的 RMDQ23 和匹配的 Oswestry 问卷，测量 RMDQ23 比例重新计算方法的准确性。计算原始总分，并系统地删除问题。在每个阶段，将总分转换为 0 到 100 的分数，并计算误差。使用 Wilcoxon 检验比较误差分数的大小。
在常规护理中，有 29.5%（RMDQ23）的人未回答一个或多个问题，在研究项目中，有 13.9%（Oswestry）和 20.3%（RMDQ23）的人未回答一个或多个问题。当有两个或更多问题未回答时，比例重新计算是一种比简单忽略缺失数据更准确的计算 RMDQ 总分的方法。
由于存在缺失数据时的误差较小，对于使用是/否回答收集的 RMDQ 总分，最准确的表示方法是转换为 0 到 100 的比例。这种转换方法是（a）如果所有问题都回答了，或者只有一个问题未回答，则将原始总分乘以 100 除以问题总数；（b）如果有两个或更多问题未回答，则将原始总分乘以 100 除以回答的问题数。
