Measurement properties of painDETECT: Rasch analysis of responses from community-dwelling adults with neuropathic pain

Tara L Packham, Joseph C Cappelleri, Alesia Sadosky, Joy C MacDermid, Florian Brunner, Tara L Packham, Joseph C Cappelleri, Alesia Sadosky, Joy C MacDermid, Florian Brunner

Abstract

Background: painDETECT (PD-Q) is a self-reported assessment of pain qualities developed as a screening tool for pain of neuropathic origin. Rasch analysis is a strategy for examining the measurement characteristics of a scale using a form of item response theory. We conducted a Rasch analysis to consider if the scoring and measurement properties of PD-Q would support its use as an outcome measure.

Methods: Rasch analysis was conducted on PD-Q scores drawn from a cross-sectional study of the burden and costs of NeP. The analysis followed an iterative process based on recommendations in the literature, including examination of sequential scoring categories, unidimensionality, reliability and differential item function. Data from 624 persons with a diagnosis of painful diabetic polyneuropathy, small fibre neuropathy, and neuropathic pain associated with chronic low back pain, spinal cord injury, HIV-related pain, or chronic post-surgical pain was used for this analysis.

Results: PD-Q demonstrated fit to the Rasch model after adjustments of scoring categories for four items, and omission of the time course and radiating questions. The resulting seven-item scale of pain qualities demonstrated good reliability with a person-separation index of 0.79. No scoring bias (differential item functioning) was found for this version.

Conclusions: Rasch modelling suggests the seven pain-qualities items from PD-Q may be used as an outcome measure. Further research is required to confirm validity and responsiveness in a clinical setting.

Keywords: Neuropathic pain; Outcome measurement; PainDETECT; Rasch analysis.

Figures

Fig. 1
Fig. 1
Category probability curves for the burning item. a before rescoring (b) after rescoring
Fig. 2
Fig. 2
Person-Item Map grouped by sex. Key for Fig. 2: These dual histograms illustrated the relationship of the severity of NeP in the respondents (top) to the difficulty of the items (bottom). The logits scale on the x-axes of the graphs represents a standardized score where the mean severity or difficulty is set to 0, and one logit = one SD. The y-axis of the top histogram shows the probability of attaining the standardized score if you are a male vs. female; while the lower histogram shows the probability of endorsing a given score for a particular item
Fig. 3
Fig. 3
Person-Item threshold map. Key for Fig. 3: These dual histograms illustrated the relationship of the severity of NeP in the respondents (top) to the difficulty of the items (bottom). The logits scale on the x-axes of the graphs represents a standardized score where the mean severity or difficulty is set to 0, and one logit = one SD. The y-axis of the top histogram shows the distribution of standardized scores while the lower histogram shows the probability of endorsing a given score for a particular item

References

    1. Melzack R, Katz J. Pain. Wiley Interdiscip Rev Cogn Sci. 2013;4(1):1–15. doi: 10.1002/wcs.1201.
    1. Woolf CJ. Review series introduction what is this thing called pain ? J Clin Invest. 2010;120(11):10–12. doi: 10.1172/JCI45178.
    1. Woolf CJ, Mannion RJ. Neuropathic pain: aetiology, symptoms, mechanisms, and management. Lancet. 1999;353(9168):1959–1964. doi: 10.1016/S0140-6736(99)01307-0.
    1. Freynhagen R, Baron R, Gockel U, Tölle TR. painDETECT: a new screening questionnaire to identify neuropathic components in patients with back pain. Curr Med Res Opin. 2006;22(10):1911–1920. doi: 10.1185/030079906X132488.
    1. Moreton BJ, Tew V, das Nair R, Wheeler M, Walsh D, Lincoln NB. Pain phenotype in patients with knee osteoarthritis: classification and measurement properties of painDETECT and self-report Leeds assessment of neuropathic symptoms and signs scale in a cross-sectional study. Arthritis Care Res. 2015;67(4):519–528. doi: 10.1002/acr.22431.
    1. Gudbergsen H, Bartels EM, Krusager P, et al. Test-retest of computerized health status questionnaires frequently used in the monitoring of knee osteoarthritis: a randomized crossover trial. BMC Musculoskelet Disord. 2011;12:190. doi: 10.1186/1471-2474-12-190.
    1. Ahmed S, Magan T, Vargas M, Harrison A, Sofat N. Use of the painDETECT tool in rheumatoid arthritis suggests neuropathic and sensitization components in pain reporting. J Pain Res. 2014;7:579–588.
    1. Koop SMW, ten Klooster PM, Vonkeman HE, Steunebrink LMM, van de Laar MAFJ. Neuropathic-like pain features and cross-sectional associations in rheumatoid arthritis. Arthritis Res Ther. 2015. doi:10.1186/s13075-015-0761-8.
    1. Wallace VCJ, Ellis CM, Burman R, Knights C, Shaw CE, Al-Chalabi A. The evaluation of pain in amyotrophic lateral sclerosis: a case controlled observational study. Amyotroph Lateral Scler Front Degener. 2014;15(7-8):520–527. doi: 10.3109/21678421.2014.951944.
    1. Tampin B, Briffa NK, Goucke R, Slater H. Identification of neuropathic pain in patients with neck/upper limb pain: application of a grading system and screening tools. Pain. 2013;154:2813–2822. doi: 10.1016/j.pain.2013.08.018.
    1. Cappelleri JC, Bienen EJ, Koduru V, Sadosky A. Measurement properties of painDETECT by average pain severity. Clinicoecon Outcomes Res. 2014;6:497–504.
    1. Cappelleri JC, Koduru V, Bienen EJ, Sadosky A. A cross-sectional study examining the psychometric properties of the painDETECT measure in neuropathic pain. J Pain Res. 2015;8:159–167.
    1. Luigi T. Measuring behaviours and perceptions:rash analysis as a tool for rehabilitation research. J Rehabil Med. 2003;35:105–115. doi: 10.1080/16501970310010448.
    1. Horton M, Tennant A. Patient reported outcomes: misinference from ordinal scales? Trials. 2011;12(Suppl 1):A65. doi: 10.1186/1745-6215-12-S1-A65.
    1. Streiner DL. Measure for measure: new developments in measurement and item response theory. Can J Psychiatry. 2010;55(3):180–186. doi: 10.1177/070674371005500310.
    1. Hagquist C, Bruce M, Gustavsson JP. Using the rasch model in nursing research: an introduction and illustrative example. Int J Nurs Stud. 2009;46:380–393. doi: 10.1016/j.ijnurstu.2008.10.007.
    1. Bond TG, Fox CM. Applying the rasch model: fundamental measurement in the human sciences. 3. Mahwah, New Jersey: Lawrence Erlbaum Associates; 2015.
    1. Cappelleri JC, Zou K, Bushmakin A, et al. Patient-reported outcomes: measurement, implementation and interpretation. Boca Raton, Fla: Chapman & Hall/CRC Press; 2013.
    1. Tennant A, Horton M, Pallant JF. Introductory rasch analysis: a workbook. Leeds, UK: Department of Rehabilitation Medicine, University of Leeds; 2011.
    1. Streiner DL, Norman GR. Health measurement scales: a practical guide to their development and use. 4. Oxford, UK: Oxford University Press; 2008.
    1. Schaefer C, Sadosky A, Mann R, et al. Pain severity and the economic burden of neuropathic pain in the United States: BEAT neuropathic pain observational study. Clinicoecon Outcomes Res. 2014;6:483–496.
    1. Schaefer C, Mann R, Sadosky A, et al. Burden of illness associated with peripheral and central neuropathic pain among adults seeking treatment in the united states: a patient-centered evaluation. Pain Med (US) 2014;15(12):2105–2119. doi: 10.1111/pme.12502.
    1. Ware J, Kosinski M, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34(3):220–233. doi: 10.1097/00005650-199603000-00003.
    1. Cleeland CS, Ryan KM. Pain assessment: global use of the brief pain inventory. Ann Acad Med Singapore. 1994;23(2):129–138.
    1. Tan G, Jensen MP, Thornby JI, Shanti BF. Validation of the brief pain inventory for chronic nonmalignant pain. J Pain. 2004;5(2):133–137. doi: 10.1016/j.jpain.2003.12.005.
    1. Grieve S, Perez RSGM, Birklein F, Brunner F, Bruehl S, Harden RN, Packham T, Gobeil F, Haigh R, Holly J, Terkelsen A, Davies L, Lewis J, Thomassen I, Connett R, Worth T, Vatine JJ, McCabe CS. Core Outcome Measures for complex regional PAin syndrome Clinical sTudies (COMPACT): Presenting a core measurement set. PAIN. 2017. Accepted manuscript in press.
    1. Lundgren Nilsson A, Tennant A. Past and present issues in rasch analysis: the functional independence measure (FIMTM) revisited. J Rehabil Med. 2011;43:884–891. doi: 10.2340/16501977-0871.
    1. Packham T, Macdermid JC. Measurement properties of the patient-rated wrist and hand evaluation: rasch analysis of responses from a traumatic hand injury population. J Hand Ther. 2013;26(3):216–224. doi: 10.1016/j.jht.2012.12.006.
    1. Linacre J. Sample size and item calibration stability. Rasch Meas Trans. 1994;7:328.
    1. Smith EV. Detecting and evaluating the impact of multidimensionality using item Fit statistics and principal component analysis of residuals. J Appl Meas. 2002;3:205–231.
    1. Fischer W., Jr Reliability, separation, strata statistics. Rasch Meas Trans. 1992;6(3):238.
    1. Persson CU, Sunnerhagen KS, Lundgren-Nilsson Å. Rasch analysis of the modified version of the postural assessment scale for stroke patients: postural stroke study in Gothenburg (POSTGOT) BMC Neurol. 2014;14(1):134. doi: 10.1186/1471-2377-14-134.
    1. Racine M, Dion D, Dupuis G, et al. The Canadian STOP-PAIN Project: The Burden of Chronic Pain-Does Sex Really Matter? Clin J Pain. 2013;0(0):1-10. doi:10.1097/AJP.0b013e3182a0de5e.
    1. Racine M, Tousignant-Laflamme Y, Kloda LA, Dion D, Dupuis G, Choinière M. A systematic literature review of 10 years of research on sex/gender and experimental pain perception – part 1: Are there really differences between women and men? Pain. 2012;153(3):602–618. doi: 10.1016/j.pain.2011.11.025.
    1. Tennant A, McKenna SP, Hagell P. Application of rasch analysis in the development and application of quality of life instruments. Value Health. 2004;7(Suppl 1):S22–S26. doi: 10.1111/j.1524-4733.2004.7s106.x.
    1. Assembly WM. Declaration of Helsinki. Adopted by the 18th World Medical Assembly (WMA) General Assembly H, Finland, 1964; amended in Tokyo, Japan (1975), in Venice, Italy (1983), in Hong Kong (1989), in W.Somerset, South Africa (1996), and by the 52nd WMA General Asse. World Medical Association Declaration of Helsinki. . Published 2000. Accessed April 19, 2016.

Source: PubMed

Sponsor e collaboratori

Condizioni mediche

Interventi farmacologici

3
Sottoscrivi