Orthogonal Factorial Designs for Trials of Therapist-Delivered Interventions: Randomizing Intervention-Therapist Combinations to Patients.
- 1University of Leeds, Leeds, UK.
- 2University of St Andrews, St Andrews, UK.
- 3King's College London, London, UK.
Abstract
It is recognized that treatment-related clustering should be allowed for in the sample size and analyses of individually-randomized parallel-arm trials that evaluate therapist-delivered interventions such as psychotherapy. Here, interventions are a treatment factor, but therapists are not. If the aim of a trial is to separate effects of therapists from those of interventions, we propose that interventions and therapists should be regarded as two potentially interacting treatment factors (one fixed and one random) with a factorial structure. We consider the specific design where each therapist delivers each intervention (crossed therapist-intervention design), and the resulting therapist-intervention combinations are randomized to patients. We adopt a classical Design of Experiments (DoE) approach to propose a family of orthogonal factorial designs and their associated data analyses, which allow for therapist learning and center too. We set out the associated data analyses using ANOVA and regression and report the results of a small simulation study conducted to explore the performance of the proposed randomization methods in estimating the intervention effect and its standard error, the between-therapist variance and the between-therapist variance in the intervention effect. We conclude that more purposeful trial design has the potential to lead to better evidence on a range of complex interventions and outline areas for further methodological research.
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BibTeX
@article{walwyn2026orthogonal,
title = {{Orthogonal Factorial Designs for Trials of Therapist-Delivered Interventions: Randomizing Intervention-Therapist Combinations to Patients.}},
author = {R E A Walwyn and R A Bailey and A Singh and N Corrigan and S G Gilmour},
journal = {Statistics in medicine},
year = {2026},
month = nov,
doi = {10.1002/sim.70813},
url = {https://europepmc.org/article/MED/43006738},
note = {CC BY},
}
RIS
TY - JOUR
TI - Orthogonal Factorial Designs for Trials of Therapist-Delivered Interventions: Randomizing Intervention-Therapist Combinations to Patients.
AU - R E A Walwyn
AU - R A Bailey
AU - A Singh
AU - N Corrigan
AU - S G Gilmour
PY - 2026
DA - 2026/11/01
JO - Statistics in medicine
DO - 10.1002/sim.70813
UR - https://europepmc.org/article/MED/43006738
AB - It is recognized that treatment-related clustering should be allowed for in the sample size and analyses of individually-randomized parallel-arm trials that evaluate therapist-delivered interventions such as psychotherapy. Here, interventions are a treatment factor, but therapists are not. If the aim of a trial is to separate effects of therapists from those of interventions, we propose that interventions and therapists should be regarded as two potentially interacting treatment factors (one fixed and one random) with a factorial structure. We consider the specific design where each therapist delivers each intervention (crossed therapist-intervention design), and the resulting therapist-intervention combinations are randomized to patients. We adopt a classical Design of Experiments (DoE) approach to propose a family of orthogonal factorial designs and their associated data analyses, which allow for therapist learning and center too. We set out the associated data analyses using ANOVA and regression and report the results of a small simulation study conducted to explore the performance of the proposed randomization methods in estimating the intervention effect and its standard error, the between-therapist variance and the between-therapist variance in the intervention effect. We conclude that more purposeful trial design has the potential to lead to better evidence on a range of complex interventions and outline areas for further methodological research.
SN - 0277-6715
SN - 1097-0258
ER -