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Development and evaluation of the PI-G: a three-scale measure based on the German translation of the PROMIS® pain interference item bank

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Abstract

Objective

Study aim was to translate the PROMIS® pain interference (PI) item bank (41 items) into German, test its psychometric properties in patients with chronic low back pain and develop static subforms.

Methods

We surveyed N = 262 patients undergoing rehabilitation who were asked to fill out questionnaires at the beginning and 2 weeks after the end of rehabilitation, applying the Oswestry Disability Index (ODI) and Pain Disability Index (PDI) in addition to the PROMIS® PI items. For psychometric testing, a 1-parameter item response theory (IRT) model was used. Exploratory and confirmatory factor analyses as well as reliability and construct validity analyses were conducted.

Results

The assumptions regarding IRT scaling of the translated PROMIS® PI item bank as a whole were not confirmed. However, we succeeded in devising three static subforms (PI-G scales: PI mental 13 items, PI functional 11 items, PI physical 4 items), revealing good psychometric properties.

Conclusion

The PI-G scales in their static form can be recommended for use in German-speaking countries. Their strengths versus the ODI and PDI are that pain interference is assessed in a differentiated manner and that several psychometric values are somewhat better than those associated with the ODI and PDI (distribution properties, IRT model fit, reliability). To develop an IRT-scaled item bank of the German translations of the PROMIS® PI items, it would be useful to have additional studies (e.g., with larger sample sizes and using a 2-parameter IRT model).

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References

  1. Cella, D., Riley, W., Stone, A., et al. (2010). The patient-reported outcomes measurement information system (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194.

    Article  PubMed Central  PubMed  Google Scholar 

  2. Cella, D., Yount, S., Rothrock, N., et al. (2007). The patient-reported outcomes measurement information system (PROMIS): Progress of an NIH roadmap cooperative group during its first two years. Medical Care, 45(5 Suppl 1), 3–11.

    Article  Google Scholar 

  3. Lai, J. S., Cella, D., Choi, S., et al. (2011). How item banks and their application can influence measurement practice in rehabilitation medicine: A PROMIS fatigue item bank example. Archives of Physical Medicine and Rehabilitation, 92(10 Suppl), S20–S27.

    Article  PubMed Central  PubMed  Google Scholar 

  4. Fries, J., Rose, M., & Krishnan, E. (2011). The PROMIS of better outcome assessment: Responsiveness, floor and ceiling effects, and Internet administration. Journal of Rheumatology, 38(8), 1759–1764.

    Article  PubMed  Google Scholar 

  5. Paz, S., Spritzer, K., Morales, L., & Hays, R. (2013). Evaluation of the patient-reported outcomes information system (PROMIS®) Spanish-language physical functioning items. Quality of Life Research, 22(7), 1819–1830.

    Article  PubMed  Google Scholar 

  6. Turk, D. C., & Melzack, R. (2011). Handbook of pain assessment (3rd ed.). New York: Guilford Press.

    Google Scholar 

  7. Riley, W. T., Rothrock, N., Bruce, B., et al. (2010). Patient-reported outcomes measurement information system (PROMIS) domain names and definitions revisions: Further evaluation of content validity in IRT-derived item banks. Quality of Life Research, 19(9), 1311–1321.

    Article  PubMed Central  PubMed  Google Scholar 

  8. Fayers, P. M., Hjermstad, M. J., Klepstad, P., et al. (2011). The dimensionality of pain: Palliative care and chronic pain patients differ in their reports of pain intensity and pain interference. Pain, 152(7), 1608–1620.

    Article  PubMed  Google Scholar 

  9. Jensen, M. P., Gould, E. M., Victor, T. W., Gammaitoni, A. R., White, R. E., & Galer, B. S. (2010). The relationship of changes in pain quality to pain interference and sleep quality. Journal of Pain, 11(8), 782–788.

    Article  PubMed  Google Scholar 

  10. Ware, J. E., Snow, K. K., Kosinski, M., & Gandek, B. (2000). SF-36 health survey: Manual and interpretation guide. Lincoln, RI: QualityMetric Inc.

    Google Scholar 

  11. Aaronson, N. K., Ahmedzai, S., Bergman, B., et al. (1993). The European organization for research and treatment of cancer QLQ-C30: A quality-of-life instrument for use in international clinical trials in oncology. Journal of the National Cancer Institute, 85(5), 365–376.

    Article  PubMed  CAS  Google Scholar 

  12. Eremenco, S. L., Cella, D., & Arnold, B. J. (2005). A comprehensive method for the translation and cross-cultural validation of health status questionnaires. Evaluation and the Health Professions, 28(2), 212–232.

    Article  PubMed  Google Scholar 

  13. Fairbank, J. C., & Pynsent, P. B. (2000). The Oswestry disability index. Spine, 25(22), 2940–2952.

    Article  PubMed  CAS  Google Scholar 

  14. Mannion, A. F., Junge, A., Fairbank, C. T., Dvorak, J., & Grob, D. (2006). Development of a German version of the Oswestry Disability Index. Part 1: cross-cultural adaptation, reliability, and validity. European Spine Journal, 15(1), 55–65.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  15. Tait, R. C., Chibnall, J. T., & Krause, S. (1990). The pain disability index: Psychometric properties. Pain, 40(2), 171–182.

    Article  PubMed  CAS  Google Scholar 

  16. Dillmann, U., Nilges, P., Saile, H., & Gerbershagen, H. (1994). Behinderungseinschätzung bei chronischen Schmerzpatienten [Assessing disability in chronic pain patients]. Der Schmerz, 8(2), 100–110.

    Article  PubMed  CAS  Google Scholar 

  17. Zigmond, A. S., & Snaith, R. P. (1983). The hospital anxiety and depression scale. Acta Psychiatrica Scand., 67, 361–370.

    Article  CAS  Google Scholar 

  18. Herrmann-Lingen, C., Buss, U., & Snaith, R. P. (2005). HADS-D: Hospital anxiety and depression scale–deutsche version: Deutsche Adaptation der Hospital Anxiety and Depression Scale. Bern: Huber.

    Google Scholar 

  19. Ware JE (1993) SF-36 health survey manual and interpretation guide. Boston, MA: The Health Institute, New England Medical Center.

  20. Bullinger, M., & Kirchberger, I. (1998). SF-36 Fragebogen zum Gesundheitszustand. Göttingen: Hogrefe.

    Google Scholar 

  21. Amtmann, D., Cook, K. F., Jensen, M. P., et al. (2010). Development of a PROMIS item bank to measure pain interference. Pain, 150(1), 173–182.

    Article  PubMed Central  PubMed  Google Scholar 

  22. Hu, L. T., & Bentler, P. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equal Mode, 6, 1–55.

    Article  Google Scholar 

  23. Tucker, L., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38, 1–10.

    Article  Google Scholar 

  24. Farin, E., Ullrich, A., & Hauer, J. (2013). Participation and social functioning in patients with fibromyalgia: Development and testing of a new questionnaire. Health Qual Life Outcomes, 11(1), 135.

    Article  PubMed Central  PubMed  Google Scholar 

  25. Reeve, B. B., Hays, R. D., Bjorner, J. B., et al. (2007). Psychometric evaluation and calibration of health-related quality of life banks. Plans for the patient-reported outcome measurement information system (PROMIS). Medical Care, 45, S22–S31.

    Article  PubMed  Google Scholar 

  26. Cook, K., Teal, C., Bjorner, J., et al. (2007). IRT health outcomes data analysis project: An overview and summary. Quality of Life Research, 16, 121–132.

    Article  PubMed  Google Scholar 

  27. Kaiser, H. F., & Rice, J. (1974). Little Jiffy, Mark IV. Educational and Psychological Measurement, 34, 111–117.

    Article  Google Scholar 

  28. Coster, W. J., Haley, S. M., Andres, P. L., Ludlow, L. H., Bond, T. L. Y., & Peng-sheng, N. (2004). Refining the conceptual basis for rehabilitation outcome measurement. Personal care and instrumental activities domain. Medical Care, 42, I62–I72.

    Article  PubMed  Google Scholar 

  29. Conrad, K. J., & Smith, E. V. (2004). International conference on objective measurement. Applications of Rasch analysis in health care. Medical Care, 41(1), I1–I6.

    Google Scholar 

  30. Bjorner, J. B., Kosinski, M., & Ware, J. E. (2005). Computerized adaptive testing and item banking. In P. Fayers & R. Hays (Eds.), Assessing quality of life in clinical trials (pp. 95–112). Los Angeles: Oxford University Press.

    Google Scholar 

  31. Bond, T. G., & Fox, C. M. (2001). Applying the Rasch model: Fundamental measurement in the human sciences. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  32. Prieto, L., Alonso, J., & Lamarca, R. (2003). Classical test theory versus Rasch analysis for quality of life questionnaire reduction. Health Qual Life Outcomes, 1, 27.

    Article  PubMed Central  PubMed  Google Scholar 

  33. Mokkink, L., Terwee, C., Patrick, D., et al. (2010). The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Quality of Life Research, 19(4), 539–549.

    Article  PubMed Central  PubMed  Google Scholar 

  34. Mokkink, L., Terwee, C., Knol, D., et al. (2010). The COSMIN checklist for evaluating the methodological quality of studies on measurement properties: A clarification of its content. BMC Medical Research Methodology, 10(1), 22.

    Article  PubMed Central  PubMed  Google Scholar 

  35. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). New York: Academic Press.

    Google Scholar 

  36. Miller, T. B., & Kane, M. (2001). The precision of change scores under absolute and relative interpretations. Appl Meas Educ, 14(4), 307–327.

    Article  Google Scholar 

  37. Rosenthal, R., & Rosnow, R. L. (2000). Contrasts and effect sizes in behavioral research. A correlational approach. Cambridge: Cambridge University Press.

    Google Scholar 

  38. Huijnen, I. P. J., Kindermans, H. P. J., Seelen, H. A. M., et al. (2011). Effects of self-discrepancies on activity-related behaviour: Explaining disability and quality of life in patients with chronic low back pain. Pain, 152(9), 2165–2172.

    Article  PubMed  Google Scholar 

  39. Blyth, F. M., Macfarlane, G. J., & Nicholas, M. K. (2007). The contribution of psychosocial factors to the development of chronic pain: The key to better outcomes for patients? Pain, 129(1–2), 8–11.

    Article  PubMed  Google Scholar 

  40. Farin, E., Gramm, L., & Schmidt, E. (2013). The patient-physician relationship in patients with chronic low back pain as a predictor of outcomes after rehabilitation. Journal of Behavioral Medicine, 36(3), 246–258.

    Article  PubMed  Google Scholar 

  41. Wang, P., Zhang, J., Liao, W., et al. (2012). Content comparison of questionnaires and scales used in low back pain based on the international classification of functioning, disability and health: A systematic review. Disability and Rehabilitation, 34(14), 1167–1177.

    Article  PubMed  Google Scholar 

  42. Cook, K., Kallen, M., & Amtmann, D. (2009). Having a fit: Impact of number of items and distribution of data on traditional criteria for assessing IRT‘s unidimensionality assumption. Quality of Life Research, 18(4), 447–460.

    Article  PubMed Central  PubMed  Google Scholar 

  43. Reise, S. P., Scheines, R., Widaman, K. F., & Haviland, M. G. (2013). Multidimensionality and structural coefficient bias in structural equation modeling: A bifactor perspective. Educ Psychol Meas, 73(1), 5–26.

    Article  Google Scholar 

  44. DeWalt, D. A. M., Rothrock, N. P., & Yount, S. P. (2007). Stone AAP, on behalf of the PROMIS Cooperative Group. Evaluation of item candidates: The PROMIS qualitative item review. Medical Care, 45(5), S12–S21.

    Article  PubMed Central  PubMed  Google Scholar 

  45. Yamashiro, K., Arimura, T., Iwaki, R., Jensen, M. P., Kubo, C., & Hosoi, M. (2011). A multidimensional measure of pain interference: reliability and validity of the pain disability assessment scale. Clinical Journal of Pain, 27(4), 338–343.

    Article  PubMed  Google Scholar 

  46. Holroyd, K. A., Malinoski, P., Davis, M. K., & Lipchik, G. L. (1999). The three dimensions of headache impact: Pain, disability and affective distress. Pain, 83(3), 571–578.

    Article  PubMed Central  PubMed  CAS  Google Scholar 

  47. Cleeland, C. S., Nakamura, Y., Mendoza, T. R., Edwards, K. R., Douglas, J., & Serlin, R. C. (1996). Dimensions of the impact of cancer pain in a four country sample: New information from multidimensional scaling. Pain, 67(2–3), 267–273.

    Article  PubMed  CAS  Google Scholar 

  48. Klepstad, P., Loge, J. H., Borchgrevink, P. C., Mendoza, T. R., Cleeland, C. S., & Kaasa, S. (2002). The Norwegian brief pain inventory questionnaire: Translation and validation in cancer pain patients. Journal of Pain and Symptom Management, 24(5), 517–525.

    Article  PubMed  Google Scholar 

  49. Saxena, A., Mendoza, T., & Cleeland, C. S. (1999). The assessment of cancer pain in North India: The validation of the Hindi brief pain inventory–BPI-H. Journal of Pain and Symptom Management, 17(1), 27–41.

    Article  PubMed  CAS  Google Scholar 

  50. Jensen, M. P., Smith, D. G., Ehde, D. M., & Robinsin, L. R. (2001). Pain site and the effects of amputation pain: Further clarification of the meaning of mild, moderate, and severe pain. Pain, 91(3), 317–322.

    Article  PubMed  CAS  Google Scholar 

  51. McHorney, C. A., & Tarlov, A. R. (1995). Individual-patient monitoring in clinical practice: Are available health status surveys adequate? Quality of Life Research, 4(4), 293–307.

    Article  PubMed  CAS  Google Scholar 

  52. Osborne, T. L., Raichle, K. A., Jensen, M. P., Ehde, D. M., & Kraft, G. (2006). The reliability and validity of pain interference measures in persons with multiple sclerosis. Journal of Pain and Symptom Management, 32(3), 217–229.

    Article  PubMed  Google Scholar 

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Acknowledgments

We thank the anonymous reviewers as well as the editor for their careful reading of our manuscript and their many insightful comments and suggestions. We thank the PROMIS® network for reviewing our translation and for their technical support during the project. We also thank Ms Desiree Kosiol and Ms Milena Meder for their support during the translation process and data acquisition. Finally, we thank the participating rehabilitation centers, their staff and all participating patients: Klinik am Brunnenberg, Bad Elster; Thermalbad Wiesenbad, Wiesa/OT Wiesenbad; Ziegelfeld-Klinik St. Blasien; m&I Fachklinik Hohenurach, Bad Urach; Marcus-Klinik, Bad Driburg; RehaKlinikum Bad Säckingen GmbH, Bad Säckingen; Weserland-Klinik Bad Seebruch, Vlotho; Klinik Dr. Muschinsky, Bad Lauterberg.

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Authors and Affiliations

  1. Department of Quality Management and Social Medicine, University Medical Center Freiburg, Engelbergerstr. 21, 79106, Freiburg, Germany

    Erik Farin, Michaela Nagl, Lukas Gramm, Katja Heyduck & Manuela Glattacker

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  1. Erik Farin
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Correspondence to Erik Farin.

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Farin, E., Nagl, M., Gramm, L. et al. Development and evaluation of the PI-G: a three-scale measure based on the German translation of the PROMIS® pain interference item bank. Qual Life Res 23, 1255–1265 (2014). https://doi.org/10.1007/s11136-013-0575-6

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