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Related Concept Videos

Ordinal Level of Measurement00:55

Ordinal Level of Measurement

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.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the...

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Related Experiment Video

Updated: Jun 2, 2026

The Mouse Stroke Unit Protocol with Standardized Neurological Scoring for Translational Mouse Stroke Studies
10:45

The Mouse Stroke Unit Protocol with Standardized Neurological Scoring for Translational Mouse Stroke Studies

Published on: February 7, 2025

Outcome measurement in stroke: a scale selection strategy.

Karen Baker1, Stefan J Cano, E Diane Playford

  • 1Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK.

Stroke
|May 14, 2011
PubMed
Summary

Selecting appropriate outcome measures for stroke rehabilitation is crucial. This review proposes a three-stage strategy to identify reliable and valid scales, aiding healthcare professionals in evidence-based tool selection.

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Computerized Adaptive Testing System of Functional Assessment of Stroke
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Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

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Last Updated: Jun 2, 2026

The Mouse Stroke Unit Protocol with Standardized Neurological Scoring for Translational Mouse Stroke Studies
10:45

The Mouse Stroke Unit Protocol with Standardized Neurological Scoring for Translational Mouse Stroke Studies

Published on: February 7, 2025

Computerized Adaptive Testing System of Functional Assessment of Stroke
05:21

Computerized Adaptive Testing System of Functional Assessment of Stroke

Published on: January 7, 2019

Area of Science:

  • Rehabilitation Medicine
  • Clinical Measurement
  • Psychometrics

Background:

  • Selecting reliable and valid outcome measures is essential for evaluating new stroke rehabilitation treatments.
  • Healthcare professionals face challenges in choosing the most appropriate measurement tools from a wide array of available instruments.

Purpose of the Study:

  • To propose a structured approach for selecting appropriate outcome measurement scales in stroke rehabilitation research.
  • To guide healthcare professionals in identifying reliable, valid, and responsive instruments for clinical studies.

Main Methods:

  • Developed a three-stage scale selection strategy for a robotic device stroke rehabilitation study.
  • Reviewed guidance documents (Medical Outcome Trust, FDA PRO Guidance) for key assessment criteria.
  • Conducted a literature search and appraised identified scales based on psychometric properties and clinical relevance in collaboration with experts.

Main Results:

  • Initially identified and appraised 45 measures.
  • No single measure fully captured all essential outcome domains.
  • Identified Stroke Rehabilitation Assessment of Movement, Chedoke Arm and Hand Inventory, and ABILHAND as best meeting criteria.
  • Included Fugl-Meyer and Action Research Arm Test based on clinical content and study design.

Conclusions:

  • The proposed three-stage review process offers a potentially valuable method for evidence-based scale selection in stroke rehabilitation.
  • This systematic approach can enhance the rigor and reliability of outcome measurement in clinical trials.