Component analyses using single-subject experimental designs: a review.

Ward-Horner et al. (2010) read 30 single-case papers that pulled apart multi-part treatments. They wanted to see how researchers decide which pieces matter.

Each paper used a component analysis. That means they tested parts of a package to find the active ingredients.

Most studies only asked, 'Is this piece needed?' Almost none asked, 'Is this piece enough on its own?'

The team built a simple notation to fix the gap. It shows when a study checks both necessity and sufficiency.

Kasari (2002) had already warned that autism programs are black boxes. John et al. answered by mapping how to open those boxes.

Omino et al. (1993) showed a quick clinic method: start with the full package, then drop parts. The new notation formalizes that strip-down idea.

Gaily et al. (1998) praised PND meta-analysis for single-case work. John’s review includes those PND papers, but pushes past numbers to better design.

Next time you run a treatment package, use the notation. First prove each part is needed. Then test if the smallest set still works. You will avoid wasting time on fluff and give clients only what truly helps.