Hospitalized patients quantify verbal pain intensity descriptors: methodological issues and values for 26 descriptors. Issue 2 (February 2020)

• Record Type: Journal Article
• Authors: Schlaeger, Judith M.; Cain, Kevin C.; Myklebust, Erin K.; Powell-Roach, Keesha L.; Dyal, Brenda W.; Wilkie, Diana J.
• Is Part Of: Pain. Volume 161:Issue 2(2020)
• Publication Date: 2020-02
• Subjects: Pain language -- Verbal descriptors -- Pain intensity -- Pain measurement; Pain -- Periodicals; Douleur -- Périodiques; Anesthésie -- Périodiques; Pain; Electronic journals; Periodicals; Electronic journals; 616.0472
• DOI: 10.1097/j.pain.0000000000001716
• Languages: English
• ISSNs: 0304-3959

Abstract

Abstract : Abstract: Patients often tell others about their pain using their own verbal descriptors of pain intensity, but the meaning of this pain language is not universally evident, which could contribute to misinterpretation about pain severity. The study purpose was to discover the intensity values of verbal pain intensity descriptors. The 248 randomly selected inpatients used a visual analogue scale to assign a value to each of 26 pain intensity descriptors. Each participant completed 36 randomly ordered visual analogue scales, 10 of which were replications. Except for descriptors with medians close to 0 or 100 mm, there was large, across-person variability for the descriptors. For example, medians ± SD for some exemplar descriptors were no pain 0.7 ± 2.4; mild 16.2 ± 12.2; discomforting 31.3 ± 22.2; distressing 55.3 ± 24; horrible 87.8 ± 13.6; and excruciating 94.6 ± 9.3. Test–retest reliability indicated small within-person variability on scores assigned to each descriptor. Thirteen descriptors showed some statistically significant but rather small effects of presentation order. Findings contribute estimates for the magnitude of pain represented by each of the 26 descriptors. Clinicians, text data miners, and researchers should consider these values as they interpret the meaning of the descriptors that they hear in daily practice or research settings or that they find in electronic health records, email messages, or social media posts. Despite the wide variability in the magnitude of each descriptor, findings provide insights about the intensity of pain when individuals use verbal pain intensity descriptors in conversations, social media, or clinical encounters. Abstract : Numerical estimates for 26 pain intensity descriptors inform interpretation of verbal reports in clinical practice and for electronic health records or social media text–based research.