Eur J Pediatr (2011) 170:65–73 group seemed to be divided into two subgroups: one ‘larger’ group that had but minimal residual problems after 12 months and one ‘smaller’ subgroup with important, long-lasting problems in a wide range of health items for patient and caregivers. More restrictive inclusion criteria might have generated a more homogeneous sample but since health problems are not necessarily or solely related to, e.g. injury severity, it might as well have given significant information loss. A certain degree of observer variability is unavoidable (because of among others' cognitive and memory effects). In our sample, parent–parent differences did not reach significance except in two items. If there were differences, then these were most often situated around the cut-off mild vs. moderate. In line with existing literature, parent–child differences were more pronounced [9, 13, 36]. In the trauma group, children tended to underscore compared to their parents. This might be related to more adaptation and satisficing by the child. For the controls, on the contrary, existing differences were most often related to higher severity scores by the child. Overall in relation to their medical consumption, we found these youngsters to report a higher level of problems and show a higher level of item interdependence (‘halo bias’). Although child reporting might provide important additional information, obtaining a proxy-reported questionnaire in every patient is probably the most consistent and reliable option for among others trauma registries [17, 25]. First of all, for a lot of patients, only a proxy report will be available (selection bias) [25, 36]. Second, while parents might be underestimating certain non-observable problems and are themselves influenced by their child’s health state, they are more accessible and less influenced by knowledge or short-time memory effects, response shift or satisficing [5, 9, 23, 34]. Most often, it is them who decide about health care resource use [30]. Item properties and the effect of covariates The IROS instrument primarily provides information from medium to high health burden levels. In line with this, effective factor scores (z01) ranged from 0.41 to 0.967. This implies that IROS items distinguish less well between patients from optimal health to mild or moderate health problems, but are very appropriate in distinguishing patients with more severe health states. This is not surprisingly given the asymmetric severity scaling and the inherent skewed distribution. However, where left-sided sensitivity might be important for individual counselling, the primary focus of any health measurement tool should be on the above median burden patients and for this IROS performance is great. To further identify the characteristics of the ‘worse outcome’ subgroup, we evaluated the effect of several 71 covariates, based on the factor scores from the IRT model. Significant impact could only be proven for the patient state at discharge as scored by the POPC. Demographic parameters, trauma circumstances, injury diagnosis or length of stay all failed to reach significance. However, children that were older, had a higher ISS or after traffic injury tended to have worse factor scores. Most likely, these children represent a distinct subgroup. The fact that the ISS on its own, although it describes severity of injuries, is not strongly related with long-term outcome is not that surprising. Similar observations have been made by other authors and especially in children the usefulness of the ISS to predict outcome remains unproven, if not doubtful [12]. Current limitations and future directions Although not matched for a priori health state, evaluating the trauma children vs. a control group, matched for age, gender and proxy characteristics, is probably the closest we can get to ‘attributable burden’—more so than with normative data. One well-acknowledged host factor in childhood injury is the existence of attention deficit hyperactivity disorder or other conduct disorders [4]. However, in our population, no difference between both groups in methylphenidate use was observed. We evaluated outcome at 12 months post-injury, as this is a point of presumed steady state. Ideally, we would have had intermittent points of evaluation, to also evaluate recovery patterns, but for this we lacked the logistics. We are planning a second evaluation 5 years after the initial trauma. We evaluated the effect of selected covariates on the outcome of these severely injured children and could only identify a significant impact of health state at discharge. However, other covariates are known to be of possible influence on long-term outcome after trauma and were not available here: social support, a priori mental health, etc. [20, 32]. Further, exploring these covariates is imperative, as they might provide us with clues to help patient and surroundings: better outcome, less unmet needs.... As for the IRT model itself, the distinction between causal and effect indicators is of course arbitrary. From a theoretical point of view however, this allows for a more realistic approach to the measurement of health status and acknowledges the importance of each of the items considered. Still, accounting for causal effects did not change factor scores considerably and thus, for future samples, only using the effect indicators to calculate factor scores might be an acceptable alternative. Importantly, since the estimated factor scores value (the burden of) an individual person’s health between 0 and 1, they can be used to compare individuals and groups, for instance in randomised controlled trials, economical evaluations, etc.