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- Title
Measuring Pain Impact Versus Pain Severity Using a Numeric Rating Scale.
- Authors
Fraenkel, Liana; Falzer, Paul; Fried, Terri; Kohler, Minna; Peters, Ellen; Kerns, Robert; Leventhal, Howard
- Abstract
Background: Routine assessments of pain using an intensity numeric rating scale (NRS) have improved documentation, but have not improved clinical outcomes. This may be, in part, due to the failure of the NRS to adequately predict patients' preferences for additional treatment. Objective: To examine whether patients' illness perceptions have a stronger association with patient treatment preferences than the pain intensity NRS. Design: Single face-to-face interview. Participants: Outpatients with chronic, noncancer, musculoskeletal pain. Main Measures: Experience of pain was measured using 18 illness perception items. Factor analysis of these items found that five factors accounted for 67.1% of the variance; 38% of the variance was accounted for by a single factor labeled 'pain impact.' Generalized linear models were used to examine how NRS scores and physical function compare with pain impact in predicting preferences for highly effective/high-risk treatment. Key Results: Two hundred forty-nine subjects agreed to participate. Neither NRS nor functioning predicted patient preference (NRS: χ2 = 1.92, df = 1, p = 0.16, physical functioning: χ2 = 2.48, df = 1, p = 0.11). In contrast, pain impact was significantly associated with the preference for a riskier/more effective treatment after adjusting for age, comorbidity, efficacy of current medications and numeracy (χ2 = 4.40, df = 1, p = 0.04). Conclusions: Tools that measure the impact of pain may be a more valuable screening instrument than the NRS. Further research is now needed to determine if measuring the impact of pain in clinical practice is more effective at triggering appropriate management than more restricted measures of pain such as the NRS.
- Subjects
PAIN management; OUTPATIENT medical care; CHRONIC diseases; CLINICAL medicine; LINEAR statistical models; MATHEMATICAL models
- Publication
JGIM: Journal of General Internal Medicine, 2012, Vol 27, Issue 5, p555
- ISSN
0884-8734
- Publication type
Article
- DOI
10.1007/s11606-011-1926-z