Rhodes and colleagues’ decision to investigate working memory profiles in children with ADHD, ODD, and a combined diagnosis (see preceding article in this issue: Rhodes, Park, Seth and Coghill, 2012), is certainly timely, as there is an increasing awareness of the role of working memory capacity in educational achievement and classroom behaviour. Indeed, it is often suggested that poor working memory capacity might underpin apparent problems of inattention in the classroom, and it may well be the case that the working memory profiles of these two conditions are different from one another. It is therefore undoubtedly important to understand the pattern of deficits in children with ADHD and ODD, and where they arise, in order to direct educational support to these individuals in an appropriate way. In addition, the approach taken by Rhodes et al. is much more theoretically motivated than one often sees in studies of this kind. It makes excellent sense to decompose working memory performance into its executive control and non-executive storage aspects, the latter of which appears to have distinct verbal and spatial components. There is a growing consensus in the literature that long-term memory plays a role in constraining working memory performance, so the inclusion of long-term memory measures in this battery is very welcome. Determining the factor structure that emerges from these tasks, and using this to drive most of the analysis of group differences, is also a very sensible analytic strategy. We therefore fully support the principle of using factor analysis in work of this kind. However, we know from our own experience that it is all too easy to generate an inappropriate factor structure from a dataset, and, from that, questionable estimates of latent variables, and we would argue that aspects of Rhodes et al.’s confirmatory factor analysis may be open to question. In any working memory battery one would expect to see higher correlations between tasks tapping the same storage domain, for example, between two spatial storage tasks or between two verbal storage tasks, than between tasks tapping different domains. In this data set, there are a number of relatively small correlations between tasks tapping verbal storage only in contrast to somewhat higher correlations between verbal and spatial storage only measures (e.g., r = .30 for the correlation between e-prime verbal storage and verbal recognition free recall, r = .40 for the correlation between e-prime spatial storage and verbal recognition free recall, Table 3). This suggests that the tasks may not be as pure indicators of verbal and spatial skills as one might like. Although the confirmatory factor analysis supports a model that includes separable domains for visual and verbal material (p. 132), the model itself arguably does not give an entirely parsimonious account of the data because it also includes a general short-term memory latent variable (Figure 1: Rhodes at al., 2012). One might argue that it makes sense to dissociate domain-specific short-term memory content from the domain-general processes that support the ordering of that content (Majerus et al., 2010), and if so then there may be a theoretical rationale for this type of model. However, it is also likely that the fit indices in a model such as this will show a good fit to the data, as it encompasses all possible relations between variables, in a sense holding two potentially separate theoretical positions simultaneously. Some form of nested model in which verbal and spatial functioning latent variables were partialled out of the working memory storage latent variable might be a more theoretically coherent way of modeling these data. A further issue with the factor analysis employed in this paper is the use of a single solution for four apparently distinct groups. If the authors are correct in assuming that children in the different subgroups show different patterns of impairment, one would presumably not expect the intercorrelations between factors to be consistent across subgroups; a selective impairment in verbal ability will clearly alter the relative relationships between factors in comparison to a global delay. Latent variable modelling is a powerful technique for showing independence of domains and correlations between latent variables, but it is not clear to us whether it is entirely appropriate to aggregate all the individuals in this study for the purposes of this analysis. Certainly some evidence of a similar pattern of correlations in the Journal of Child Psychology and Psychiatry 53:2 (2012), pp 138–140 doi:10.1111/j.1469-7610.2011.02507.x
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Jun 29, 2017
Steffie Van Der Steen + 2
