Prevalence of malingering in patients with chronic pain referred for psychologic evaluation in a medico-legal context

Arch Phys Med Rehabil. 2009 Jul;90(7):1117-26. doi: 10.1016/j.apmr.2009.01.018.

Abstract

Objective: To provide an empirical estimate of the prevalence of malingered disability in patients with chronic pain who have financial incentive to appear disabled.

Design: Retrospective review of cases.

Setting: A private neuropsychologic clinic in a southeastern metropolitan area.

Participants: Consecutive patients (N=508) referred for psychologic evaluation related to chronic pain over a 10-year period (1995-2005).

Interventions: Not applicable.

Main outcome measures: Prevalence of malingering was examined using 2 published clinical diagnostic systems (Malingered Pain-Related Disability and Malingered Neurocognitive Dysfunction) as well as statistical estimates based on well validated indicators of malingering.

Results: The prevalence of malingering in patients with chronic pain with financial incentive is between 20% and 50% depending on the diagnostic system used and the statistical model's underlying assumptions. Some factors associated with the medico-legal context such as the jurisdiction of a workers' compensation claim or attorney representation were associated with slightly higher malingering rates.

Conclusions: Malingering is present in a sizable minority of patients with pain seen for potentially compensable injuries. However, not all excess pain-related disability is a result of malingering. It is important not to diagnose malingering reflexively on the basis of limited or unreliable findings. A diagnosis of malingering should be explicitly based on a formal diagnostic system.

MeSH terms

  • Adult
  • Chronic Disease
  • Compensation and Redress
  • Educational Status
  • Female
  • Humans
  • Male
  • Malingering / epidemiology*
  • Malingering / psychology*
  • Pain / psychology*
  • Prevalence
  • Psychometrics
  • Racial Groups
  • Retrospective Studies
  • Workers' Compensation / statistics & numerical data