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Quality of Life Research

, Volume 24, Issue 3, pp 575–589 | Cite as

Creating meaningful cut-scores for Neuro-QOL measures of fatigue, physical functioning, and sleep disturbance using standard setting with patients and providers

  • Karon F. Cook
  • David E. Victorson
  • David Cella
  • Benjamin D. Schalet
  • Deborah Miller
Article

Abstract

Purpose

To establish clinically relevant classifications of health outcome scores for four Neuro-QOL measures (lower extremity function, upper extremity function, fatigue, and sleep disturbance).

Methods

We employed a modified educational standard-setting methodology to identify cut-scores for symptom severity. Clinical vignettes were developed to represent graduated levels of symptom severity. A clinician panel and a panel of persons with multiple sclerosis (PwMS) were recruited, and, in separate, 1-day meetings, the panelists identified adjacent vignettes they judged to represent the threshold between two levels of severity for a given domain (e.g., threshold between a vignette that indicated “no problems” with sleep and the adjacent one that represented “mild problems” with sleep). Working independently, each panel (PwMS and clinicians) reached consensus on its recommended thresholds for each of the four targeted measures. Cut-scores were defined as the mean location for each pair of threshold vignettes.

Results

PwMS and clinician panels derived identical thresholds for severity levels of lower extremity function and sleep disturbance, but slightly different ones for upper extremity function and fatigue. In every case of divergence, PwMS set higher thresholds for more severe classifications of symptoms (by 0.5 SDs) than did clinicians.

Conclusions

The modified bookmarking method is effective for defining thresholds for symptom severity based on self-reported outcome scores and consensus judgments. Derived cut-scores and severity levels provide an interpretative context for Neuro-QOL scores. Future studies should explore whether these findings can be replicated and evaluate the validity of the classifications compared to external criteria.

Keywords

Interpretation of HRQOL data Item response theory (IRT) Psychometric methods/scaling Neurology Multiple sclerosis 

Notes

Acknowledgments

This research was supported by The National Multiple Sclerosis Society. The contents represent original work and have not been published elsewhere. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the author or upon any organization with which the author(s) is/are associated.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Karon F. Cook
    • 1
  • David E. Victorson
    • 1
  • David Cella
    • 1
  • Benjamin D. Schalet
    • 1
  • Deborah Miller
    • 2
  1. 1.Department of Medical Social SciencesNorthwestern University Feinberg School of MedicineChicagoUSA
  2. 2.Mellen CenterCleveland Clinic FoundationClevelandUSA

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