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01-03-2015 | Uitgave 3/2015

Quality of Life Research 3/2015

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

Tijdschrift:
Quality of Life Research > Uitgave 3/2015
Auteurs:
Karon F. Cook, David E. Victorson, David Cella, Benjamin D. Schalet, Deborah Miller

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.

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