You are here

Article Text

Article menu
Download PDFPDF
Rating scales for neurologists
  1. J Hobart
  1. Correspondence to:
 Dr Jeremy Hobart
 Department of Clinical Neurosciences, Peninsula Medical School, Derriford Hospital, Plymouth PL6 8DH, UK; Jeremy.Hobartphnt.swest.nhs.uk

https://doi.org/10.1136/jnnp.74.suppl_4.iv22

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    A neurologist once told me that he found the subject of rating scales “exceedingly dull”, while another found the area “abstruse”. I have therefore attempted to produce an overview that is helpful and conveys some of the basic principals underlying outcomes measurement and rating scales. Clinicians must realise that because this is an alien and somewhat “dry” area, they may need to invest some time to appreciate the issues. Instead of discussing specific scales or rating scales for rehabilitation, which will only be relevant to a limited audience, I have chosen to discuss the importance of rating scales and how to achieve high quality measurement. I hope this makes the text more widely applicable to the neurological community.

    The take home message is simple; neurologists need to take their rating scales very seriously.

    WHY ARE RATING SCALES IMPORTANT?

    Rating scales are important because they are a method of measurement. Measurement is important because inferences are based on it.1 For example, in clinical trials we measure variables (for example, disability), perform statistical tests on the numbers generated by scales, and base conclusions on the results. These conclusions influence patient care, prescribing, policy making, and the expenditure of public funds. Thus, the validity of inferences from clinical trials is directly dependent on the quality of the measurement instruments used. Some measurements are clear cut—for example, mortality rates. However, measurement becomes complex for more abstract, ill defined, “soft” outcomes such as patient’s perspectives of the impact of disease and their quality of life. If we are serious about using these abstract variables to evaluate clinical practice we must be serious about our attempts to measure them as rigorously as possible.

    Consider clinical trials of interferons and glatiramer acetate in multiple sclerosis (MS). These trials have produced interesting results: an incontrovertible reduction in relapse rate and accumulation of …

    View Full Text

    Linked Articles