Longitudinal studies of development are good – but what are they good for?

Abstract

This commentary is on the original article by Nordstrand et al. on pages 1042-1048 of this issue. Commentaries 997 2. Rosenbaum PL, Walter SD, Hanna SE, et al. Prognosis for gross motor function in cerebral palsy: creation of motor development curves. JAMA 2002; 288: 1357-63. 3. Palisano RJ, Hanna SE, Rosenbaum PL, et al. Validation of a model of gross motor function for children with cerebral palsy. Phys Ther 2000; 80: 974-85.

Upper‐limb contracture development in children with cerebral palsy: a population‐based study

“…) showed regular sloped lines indicating that the passive ROM development was captured satisfactorily. For longitudinal studies, mixed models have been recommended to study change over time …”

“…For longitudinal studies, mixed models have been recommended to study change over time. 20,21 Another possible limitation of this study is the use of registry data only. As time goes by other variables seem important, but cannot be analysed because they are not included in the registry data.…”

Hand Function in Young Children with Cerebral Palsy: Current Practice and Parent-Reported Benefits

“…Together with the statistical methods of mixed-models analysis, this is a recommended design to study the development of heterogeneous populations like children with CP. 226 There are, however, some limitations to the longitudinal analysis in paper III. A larger number of children, a more even distribution of children in the different groups, and a higher number of assessments for each child would have strengthened the study.…”

Infant hand development in unilateral cerebral palsy: filling the knowledge gap

“…Another strong point of longitudinal studies is that they can be used to identify predictors of development. Interestingly, Sakzewski et al . found no significant associations between development and other factors, not even whether the child had early intervention or not.…”

“…However, there are downsides to the reporting of this analysis, in that the information given on variability within each group is limited. As Hanna points out, one of the strengths of development curves is when they show how much the development varies between children, 3 which is important information for end-users.…”