There has been very little discussion in the literature or scientific examination of the validity of post‐injury self‐reported estimates of pre‐injury health status for the purpose of evaluating post‐injury losses. This can only be determined through a large prospective population‐based cohort study (with injury as one of the outcomes), where baseline pre‐injury health states and utility can be assessed both prospectively (pre‐injury) and retrospectively (post‐injury). This is a virtually insurmountable methodologic challenge because of the sample size required to ensure the necessary numbers of injuries.2
This study uses empirical data to attempt to discuss this issue.
The results show that retrospectively measured pre‐injury health status and HRQL scores of participants who completely recovered were similar to scores at 12 months after injury and that the mean baseline scores of the injured cohort, irrespective of outcome, were consistently higher than the Australian norms. This suggests that either bias was operating or this cohort was healthier and fitter than the general population. In this study, recall bias was not expected to be a significant problem, as participants were interviewed, on average, 1 week after injury, with half completing baseline interviews within 3 days after injury.
The findings suggest that the injured population may not be representative of the general population. This is supported by several studies.1,2,24,25
However, the evidence seems mixed as to whether the injured population is more physically healthy and fitter than the general population or less so. The results of the current study are consistent with the observation that rates of sports‐related injury in the older population are increasing.24
Greenspan and Kellerman1
also found that pre‐injury physical and general health subscores were better among adults injured by gunshot than established population norms.
However, these findings seem to contradict those reported recently in the only population‐based research to compare pre‐existing morbidity in a large cohort of injured people (n
032) and a matched sample from the general population.25
In that study, the injured cohort had higher comorbidity scores and almost twice the hospital admissions and physician claims in the previous 12 months than the non‐injured cohort. Although HRQL was not explicitly measured, this finding casts doubt on the explanation that higher baseline health status and HRQL scores in our study were because of better health in this group compared with the general population. However, it may simply reflect the fact that disease status (as measured by comorbidity and health service usage) may not correlate well with everyday functioning (as measured by self‐reported health status and HQRL).26
In either case, the findings suggest that the injured population may not be representative of the general population.
An alternative explanation for these findings is response shift. Evidence exists that people may not maintain a consistent internal scale for their responses over time and this may be exaggerated by an intervening traumatic event,27
such as injury, leading an individual to re‐evaluate their prior health state in light of their current experience. This change in internal standards, in values or in the conceptualization of quality of life is known as response shift.28
Response shift occurs in self‐report assessments “whenever the standards for making judgments change between pretest and posttest, resulting in a change in the meaning and understanding of the construct under study”.29
In this case, retrospectively measuring pre‐injury health during the acute post‐injury phase may result in a higher relative assessment of the pre‐injury state than if the measure was taken before the injury. This would explain the significantly higher scores in the cohort compared with the population norms. However, without prospective baseline pre‐injury measures for comparison with retrospective baseline measures, it is not possible to assess the role of response shift.
- The prospective measurement of pre‐injury baseline health status and health‐related quality of life (HRQL) is rarely an option in injury outcome studies.
- Alternative methods such as the use of retrospective pre‐injury measurement or population norms, as the baseline against which to assess post‐injury losses, have received little methodologic attention.
- Although retrospectively measured pre‐injury health status and HRQL were consistently higher than population norms, in an injured cohort, these were consistent with 12‐month post‐injury scores for participants who made a full recovery.
- Response shift may operate such that the retrospective measurement of baseline health status and HRQL may be more appropriate than the use of population norms for evaluating post‐injury losses.
In contrast with the view that recall bias could invalidate a retrospective measure of pre‐injury health, there is a strong assumption, in the literature on response shift, that assessments of HRQL derived from a retrospective baseline administration are more valid than prospective assessments,30
for comparison with post‐test (post‐injury) measures. This is because they are presumed to be completed with the same internal standard of measurement,31
the assessment of the retrospective pre‐injury baseline state, and that of subsequent post‐injury states, being made with reference to the same information (ie, experience of injury). Response shift could explain why no significant difference was found between the retrospective pre‐injury and 12‐month post‐injury scores on most measures for the completely recovered group and why baseline scores were generally higher than population norms.
Although factors such as severity of injury, pre‐injury health and compensable status have been shown to influence recovery from injury, the extent to which these factors influence response shift is unknown. Differences in injury severity, for example, may result in the differential effect of response shift between groups. However, because the retrospective pre‐injury and post‐injury measures are presumed to be completed with the same internal standard of measurement, this should not affect the evaluation of post‐injury losses (ie, the difference between the two values) or the generalizability of our findings.
Furthermore, given the evidence that injured populations differ from the general population, retrospectively measured pre‐injury health status and HRQL seem preferable to population norms in evaluating post‐injury losses. In this study, using age‐based population norms as baseline measures would have resulted in participants who completely recovered being assigned considerable health and HRQL gains as a result of their injury, and much reduced losses (and in some cases gains) for participants who did not recover.