为转换qDASH和PRWHE分数创建一个共同的比例表
Mary R Harvey1,2, Jeremy Rodrigues3, Jane E McEachan4
1Oxford University Hospitals NHS Trust, Oxford, UK.
The Journal of hand surgery, European volume
|April 12, 2025
概括
这项研究通过开发一个统一的疼痛和运动功能的尺度来验证两种常见的手术结果,即手臂,肩膀和手的快速残疾问卷 (DASH) 和患者额定手腕和手的评估 (PRWHE). 一个查找表使得这些患者报告的结果措施之间的得分可以进行比较.
科学领域:
- 整形外科 整形外科 整形外科
- 手术手术手术手术手术
- 健康 结果 研究 研究 结果
- 心理测量 心理测量 心理测量
背景情况:
- 手臂,肩膀和手的快速残疾问卷 (DASH) 和患者额定手腕和手评估 (PRWHE) 是手术中广泛使用的患者报告的结果指标 (PROM).
- 评估这些工具的结构有效性和可比性对于强大的临床研究和实践至关重要.
- 目前在直接比较DASH和PRWHE之间的分数方面存在限制.
研究的目的:
- 使用项目响应理论评估DASH和PRWHE的结构有效性.
- 开发一个共同的,统一的尺度来绘制DASH和PRWHE的分数.
- 为了促进这两种经常使用的仪器之间的患者结果的直接比较.
主要方法:
- 用物品响应理论 (IRT) 和因子分析来评估DASH和PRWHE的基础结构.
- 为了确定健康构造,开发了共同的尺度:"疼痛"和"运动功能".
- 使用频率密度图和布兰德-阿尔特曼分析来评估这两项措施之间的分数的可比性.
主要成果:
- 因子分析证实,DASH和PRWHE都测量了相同的两个主要健康结构:"疼痛"和"运动功能".
- 成功开发了两个不同的常用尺度,一个是"疼痛"和一个是"运动功能".
- 统计分析表明,开发的尺度允许可靠地比较DASH和PRWHE之间的分数.
结论:
- DASH和PRWHE在"疼痛"和"运动功能"方面展示了共同的结构有效性.
- 新开发的共同秤和附带的查询表为比较这些仪器测量的结果提供了有价值的工具.
- 这有助于在手术研究和临床实践中更一致和可比的结果报告.
关键词:
一个共同的度量标准.在这种情况下,Prom是Prom.患者指定的手腕和手的评估.快速残疾的手臂的手臂.肩膀和手的调查问卷计算机化适应性测试是计算机化的适应性测试.患者报告的结果措施.心理测量是指心理测量.更多相关视频
04:54Author Spotlight: IntelliSleepScorer — A High-Accuracy, Accessible GUI Software for Automated Sleep Stage Scoring in Mice and its Application in Psychiatric Research
Published on: November 8, 2024
406
08:25Polar Histogram Visualization of Acute Stress Disorder Scale Scores for Comprehensive Clinical Assessment
Published on: December 6, 2024
262
相关概念视频
Introduction to z Scores
310
A z score (or standardized value) is measured in units of the standard deviation. It indicates how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores...
z scores...
310
z Scores and Area Under the Curve
10.3K
z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
10.3K
Ratio Level of Measurement
17.1K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
17.1K
z Scores and Unusual Values
9.2K
The z score is one of the three measures of relative standing. It describes the location of a value in a dataset relative to the mean. z scores are obtained after the standardization of the values in a dataset. The z score for the mean is 0.
This score indicates how far a value is from the mean in terms of standard deviation. For example, if a data value has a z score of +1, the researcher can infer that the particular data value is one standard deviation above the mean. If another data...
This score indicates how far a value is from the mean in terms of standard deviation. For example, if a data value has a z score of +1, the researcher can infer that the particular data value is one standard deviation above the mean. If another data...
9.2K
Dimensional Analysis
44.2K
Dimensional analysis, also known as the factor label method, is a versatile approach for mathematical operations. The main principle behind this approach is: the units of quantities must be subjected to the same mathematical operations as their associated numbers. This method can be applied to computations ranging from simple unit conversions to more complex and multi-step calculations involving several different quantities and their units.
Conversion Factors and Dimensional Analysis
The unit...
Conversion Factors and Dimensional Analysis
The unit...
44.2K
Testing a Claim about Standard Deviation
2.4K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.4K
