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Multiple Baseline Single-Case Experimental Design Using Statistical Analysis: Piloting a Mindfulness-Based Intervention for Obsessive–Compulsive Disorder

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By: Published: 2018 | Product: SAGE Research Methods Cases Part 2
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Abstract

Single-case experimental designs provide an ideal research method for the initial stages of testing new interventions. As part of my Doctorate in Clinical Psychology, I sought to test a mindfulness-based approach to intrusive thoughts associated with obsessive–compulsive disorder. At this time, the evidence for mindfulness-based interventions was growing but a purely mindfulness-based approach to psychological therapy had not been trialed in obsessive–compulsive disorder despite there being theoretical reasons to believe that it might be helpful for this often debilitating mental health problem. Single-case experimental designs allow you to gather rich detail about the therapy process, providing a deeper understanding about how an intervention works for individuals when little is known about the treatment. Repeatedly demonstrating the effect of moving from a baseline (no intervention) to a treatment phase in a multiple baseline design helps increase confidence that any effect found is produced by the intervention rather than a co-occurring factor. In this case study, I appraise the use of a multiple baseline design in which three participants moved from baseline monitoring of obsessive–compulsive disorder symptoms, to a control intervention (relaxation training), and to a mindfulness-based intervention for obsessive–compulsive disorder. I discuss the advantages of using both standardized and individually tailored (idiographic) measures of outcomes. I also consider the arguments for and against the use of statistical analysis with the type of data collected in single-case experimental designs and discuss the challenges encountered in undertaking this type of analysis.

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Experimental design

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