Archives of Physical Medicine and Rehabilitation
Volume 90, Issue 9 , Pages 1499-1505 , September 2009

Predictors of Nonresponse in a Questionnaire-Based Outcome Study of Vocational Rehabilitation Patients

  • Cyrille Burrus, MD

      Affiliations

    • Clinique romande de réadaptation suvaCare, Sion, Switzerland
    • ,
  • Pierluigi Ballabeni, PhD

      Affiliations

    • Clinique romande de réadaptation suvaCare, Sion, Switzerland
    • Institute of Social and Preventive Medicine, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
    • Corresponding Author InformationReprint requests to Pierluigi Ballabeni, PhD, Clinique romande de réadaptation, Case postale 352, Avenue Grand-Champsec 90, CH-1951 Sion, Switzerland
    • ,
  • Olivier Deriaz, MD, PhD

      Affiliations

    • Clinique romande de réadaptation suvaCare, Sion, Switzerland
    • ,
  • Charles Gobelet, MD

      Affiliations

    • Clinique romande de réadaptation suvaCare, Sion, Switzerland
    • ,
  • François Luthi, MD

      Affiliations

    • Clinique romande de réadaptation suvaCare, Sion, Switzerland

References 

  1. Stang A. Nonresponse research–an underdeveloped field in epidemiology. Eur J Epidemiol. 2003;18:929–931
  2. Vestbo J, Rasmussen FV. Baseline characteristics are not sufficient indicators of non-response bias in follow-up studies. J Epidemiol Community Health. 1992;46:617–619
  3. Jacomb PA, Jorm AF, Korten AE, Christensen H, Henderson AS. Predictors of refusal to participate: a longitudinal health survey of the elderly in Australia. BMC Public Health. 2002;2:4
  4. Johnson TP, Holbrook AL, Cho YI, Bossarte RM. Nonresponse error in injury-risk surveys. Am J Prev Med. 2006;31:427–436
  5. Butcher JL, MacKenzie EJ, Cushing B, et al. Long-term outcomes after lower extremity trauma. J Trauma. 1996;41:4–9
  6. Michaels AJ, Michaels CE, Moon CH, Zimmerman MA, Peterson C, Rodriguez JL. Psychosocial factors limit outcomes after trauma. J Trauma. 1998;44:644–648
  7. Michaels AJ, Michaels CE, Smith JS, Moon CH, Peterson C, Long WB. Outcome from injury: general health, work status, and satisfaction 12 months after trauma. J Trauma. 2000;48:841–848discussion 8-50
  8. Harris IA, Young JM, Rae H, Jalaludin BB, Solomon MJ. Predictors of general health after major trauma. J Trauma. 2008;64:969–974
  9. Ponsford J, Hill B, Karamitsios M, Bahar-Fuchs A. Factors influencing outcome after orthopedic trauma. J Trauma. 2008;64:1001–1009
  10. Groves RM. Nonresponse rates and nonresponse bias in household survey. Public Opin Q. 2006;646–675
  11. Stang A, Jöckel KH. Studies with low response proportions may be less biased than studies with high response proportions. Am J Epidemiol. 2004;159:204–210
  12. Rupp I, Triemstra M, Boshuizen HC, Jacobi CE, Dinant HJ, van den Bos GA. Selection bias due to non-response in a health survey among patients with rheumatoid arthritis. Eur J Public Health. 2002;12:131–135
  13. Fejer R, Hartvigsen J, Kyvik KO, Jordan A, Christensen HW, Hoilund-Carlsen PF. The Funen Neck and Chest Pain study: analysing non-response bias by using national vital statistic data. Eur J Epidemiol. 2006;21:171–180
  14. Heilbrun LK, Ross PD, Wasnich RD, Yano K, Vogel JM. Characteristics of respondents and nonrespondents in a prospective study of osteoporosis. J Clin Epidemiol. 1991;44:233–239
  15. Huyse FJ, Lyons JS, Stiefel FC, et al. “INTERMED”: a method to assess health service needs, I: development and reliability. Gen Hosp Psychiatry. 1999;21:39–48
  16. Stiefel FC, de Jonge P, Huyse FJ, et al. “INTERMED”: a method to assess health service needs, II: results on its validity and clinical use. Gen Hosp Psychiatry. 1999;21:49–56
  17. Stiefel FC, Huyse FJ, Sollner W, et al. Operationalizing integrated care on a clinical level: the INTERMED project. Med Clin North Am. 2006;90:713–758
  18. Ponzer S, Bergman B, Brismar B, Johansson LM. A study of patient-related characteristics and outcome after moderate injury. Injury. 1996;27:549–555
  19. Engel GL. The need for a new medical model: a challenge for bio-medicine. Science. 1977;196:129–136
  20. Engel GL. The clinical application of the biopsychosocial model. Am J Psychiatry. 1980;137:535–544
  21. de Jonge P, Bauer I, Huyse FJ, Latour CH. Medical inpatients at risk of extended hospital stay and poor discharge health status: detection with COMPRI and INTERMED. Psychosom Med. 2003;65:534–541
  22. de Jonge P, Hoogervorst EL, Huyse FJ, Polman CH. INTERMED: a measure of biopsychosocial case complexity: one year stability in multiple sclerosis patients. Gen Hosp Psychiatry. 2004;26:147–152
  23. de Jonge P, Ruinemans GM, Huyse FJ, ter Wee PM. A simple risk score predicts poor quality of life and non-survival at 1 year follow-up in dialysis patients. Nephrol Dial Transplant. 2003;18:2622–2628
  24. Di Gangi Herms AM, Pinggera GM, de Jonge P, Strasser H, Sollner W. Assessing health care needs and clinical outcome with urological case complexity: a study using INTERMED. Psychosomatics. 2003;44:196–203
  25. Koch N, Stiefel F, de Jonge P, et al. Identification of case complexity and increased health care utilization in patients with rheumatoid arthritis. Arthritis Rheum. 2001;45:216–221
  26. de Jonge P, Latour C, Huyse FJ. Interrater reliability of the INTERMED in a heterogeneous somatic population. J Psychosom Res. 2002;52:25–27
  27. Stiefel FC, de Jonge P, Huyse FJ, et al. INTERMED: an assessment and classification system for case complexity: results in patients with low back pain. Spine. 1999;24:378–384discussion 85
  28. Fischer CJ, Stiefel FC, de Jonge P, et al. Case complexity and clinical outcome in diabetes mellitus: a prospective study using the INTERMED. Diabetes Metab. 2000;26:295–302
  29. Hoogervorst EL, de Jonge P, Jelles B, et al. The INTERMED: a screening instrument to identify multiple sclerosis patients in need of multidisciplinary treatment. J Neurol Neurosurg Psychiatry. 2003;74:20–24
  30. Hosmer DW, Lemeshow S. Applied logistic regression. 2nd ed.. New York: John Wiley and Sons; 2000;
  31. Long JS, Freese J. Regression models for categorical variables using Stata. 2nd ed.. College Station: Stata Pr; 2006;
  32. Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–387
  33. Steyerberg EW, Harrell FE, Borsboom GJ, Eijkemans MJ, Vergouwe Y, Habbema JD. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001;54:774–781
  34. Scerri M, de Goumoens P, Fritsch C, Van Melle G, Stiefel F, So A. The INTERMED questionnaire for predicting return to work after a multidisciplinary rehabilitation program for chronic low back pain. Joint Bone Spine. 2006;73:736–741
  35. Dickinson H, Parkinson K, McManus V, et al. Assessment of data quality in a multi-centre cross-sectional study of participation and quality of life of children with cerebral palsy. BMC Public Health. 2006;6:273
  36. Oremus M, Wolfson C. Female specialists were more likely to respond to a postal questionnaire about drug treatments for Alzheimer disease. J Clin Epidemiol. 2004;57:620–623
  37. Stang A, Moebus S, Dragano N, et al. Baseline recruitment and analyses of nonresponse of the Heinz Nixdorf Recall Study: identifiability of phone numbers as the major determinant of response. Eur J Epidemiol. 2005;20:489–496
  38. Wanner P. Recensement fédéral de la population 2000: migration et intégration. Neuchâtel: Office fédéral de la statistique; 2004;
  39. Census 2000 summary file 3 (Technical documentation). Washington (DC): US Census Bureau; 2002;
  40. Weech-Maldonado R, Elliott MN, Morales LS, Spritzer K, Marshall GN, Hays RD. Health plan effects on patient assessments of Medicaid managed care among racial/ethnic minorities. J Gen Intern Med. 2004;19:136–145
  41. de Moerloose P, Mazzolai L, Bounameaux H. Patient education and illiteracy in Switzerland. Rev Med Suisse. 2008;4:323–324
  42. Angus VC, Entwistle VA, Emslie MJ, Walker KA, Andrew JE. The requirement for prior consent to participate on survey response rates: a population-based survey in Grampian. BMC Health Services Research. 2003;3:21
  43. Lundberg I, Damström-Thakker K, Hällström T, Forsell Y. Determinants of non-participation, and the effects of non-participation on potential cause-effect relationships, in the PART study on mental disorders. Soc Psychiatry Psychiatr Epidemiol. 2005;40:475–483
  44. Sogaard AJ, Selmer R, Bjertness E, Thelle D. The Oslo Health Study: the impact of self-selection in a large, population-based survey. Int J Equity Health. 2004;3:3
  45. Barton J, Bain C, Hennekens CH, et al. Characteristics of respondents and non-respondents to a mailed questionnaire. Am J Public Health. 1980;70:823–825
  46. O'Neill TW, Marsden D, Silman AJ. Differences in the characteristics of responders and non-responders in a prevalence survey of vertebral osteoporosis (European Vertebral Osteoporosis Study Group). Osteoporos Int. 1995;5:327–334
  47. Reijneveld SA, Stronks K. The impact of response bias on estimates of health care utilization in a metropolitan area: the use of administrative data. Int J Epidemiol. 1999;28:1134–1140
  48. Rothman KJ, Greenland S, Lash TL. Modern epidemiology. 3rd ed.. Philadelphia: Lippincott, Williams and Wilkins; 2008;
  49. MacKenzie EJ, Morris JA, Jurkovich GJ, et al. Return to work following injury: the role of economic, social, and job-related factors. Am J Public Health. 1998;88:1630–1637
  50. Seland K, Cherry N, Beach J. A study of factors influencing return to work after wrist or ankle fractures. Am J Ind Med. 2006;49:197–203

 Supported by Schweizerische Unfallversicherungsanstalt (SUVA) (grant no. 100204).

 A commercial party having a direct financial interest in the results of the research supporting this article has conferred or will confer a financial benefit on 1 or more of the authors. The Clinique romande de réadaptation belongs to SUVA, the Swiss national accident insurance.

PII: S0003-9993(09)00356-6

doi: 10.1016/j.apmr.2009.03.014

Archives of Physical Medicine and Rehabilitation
Volume 90, Issue 9 , Pages 1499-1505 , September 2009

Article Tools