Optimising the ingredients for evaluation of the effects of intervention

Lyndsey Nickels*, Wendy Best, David Howard

*Corresponding author for this work

Research output: Contribution to journalArticle

7 Citations (Scopus)


Background: In Howard, Best, and Nickels (2015, Optimising the design of intervention studies: Critiques and ways forward. Aphasiology, 2015.), we presented a set of ideas relevant to the design of single-case studies for evaluation of the effects of intervention. These were based on our experience with intervention research and methodology, and a set of simulations. Our discussion and conclusions were not intended as guidelines (of which there are several in the field) but rather had the aim of stimulating debate and optimising designs in the future. Our paper achieved the first aim—it received a set of varied commentaries, not all of which felt we were optimising designs, and which raised further points for debate. Aims: This paper responds to the commentaries and in the context of recent guidelines for evaluation of the design of single-case studies. We aim to further the discussion our target article has started and extend the scope of the discussion more broadly to issues that were not raised in our target article (e.g., replication). Main Contributions and Conclusions: It is clear that there is a strong consensus that adequately designed single-case studies of intervention are an appropriate and important tool in our quest for effective interventions with people with cognitive disorders. It is also the case that many agree that there is no single design that is appropriate for every intervention, every participant or every question. However, whichever design is used it must be able to discriminate between the true effect of an intervention on behaviour, and other potential reasons for change (e.g., practice effects, spontaneous recovery, Hawthorne effects, and placebo effects). We have suggested that, depending on the conditions and question to be addressed, this can be achieved using a combination of design features. These may include: multiple pre-treatment baselines, treated and untreated (or subsequently treated) items/processes/tasks, control tasks (not predicted to be affected by treatment even when generalisation is expected), and a cross-over phase (replication across items/tasks). In addition, the outcome of treatment should be evaluated statistically. We note that generalisation, which is clinically desirable, can lead to particular difficulties in attributing change to intervention unless appropriate controls have been included, and that when items are selected on the basis of poor pre-treatment performance, apparent treatment-related gains may in fact be due to regression to the mean and discuss the implications of this for future research.

Original languageEnglish
Pages (from-to)619-643
Number of pages25
Issue number5
Publication statusPublished - 4 May 2015


  • effectiveness
  • intervention
  • single-case experimental design
  • therapy study design
  • treatment effectiveness

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