title: Research on injury compensation and health outcomes: ignoring the problem of reverse causality led to a biased conclusion.
abstract: OBJECTIVE
  This study highlights the serious consequences of ignoring reverse causality bias in studies on compensation-related factors and health outcomes and demonstrates a technique for resolving this problem of observational data.
  
  
  METHODS
  Data from an English longitudinal study on factors, including claims for compensation, associated with recovery from neck pain (whiplash) after rear-end collisions are used to demonstrate the potential for reverse causality bias. Although it is commonly believed that claiming compensation leads to worse recovery, it is also possible that poor recovery may lead to compensation claims--a point that is seldom considered and never addressed empirically. This pedagogical study compares the association between compensation claiming and recovery when reverse causality bias is ignored and when it is addressed, controlling for the same observable factors.
  
  
  RESULTS
  When reverse causality is ignored, claimants appear to have a worse recovery than nonclaimants; however, when reverse causality bias is addressed, claiming compensation appears to have a beneficial effect on recovery, ceteris paribus.
  
  
  CONCLUSIONS
  To avert biased policy and judicial decisions that might inadvertently disadvantage people with compensable injuries, there is an urgent need for researchers to address reverse causality bias in studies on compensation-related factors and health.
authors.affiliation: Australian Centre for Economic Research on Health, The University of Queensland, Herston, Queensland 4029, Australia. nataliespearing@hotmail.com
authors.forename: Natalie M
authors.initials: NM
authors.lastname: Spearing
authors.forename: Luke B
authors.initials: LB
authors.lastname: Connelly
authors.forename: Hong S
authors.initials: HS
authors.lastname: Nghiem
authors.forename: Louis
authors.initials: L
authors.lastname: Pobereskin
mesh_terms: D000063:Accidents, Traffic; D000328:Adult; D015982:Bias; D015984:Causality; D035881:Compensation and Redress; D003627:Data Interpretation, Statistical; D004739:England / Q000453:epidemiology; D005260:Female; D006304:Health Status; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D019547:Neck Pain / Q000191:economics / Q000453:epidemiology / Q000534:rehabilitation; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data; D012044:Regression Analysis; D012107:Research Design; D014911:Whiplash Injuries / Q000191:economics / Q000453:epidemiology* / Q000534:rehabilitation