Orthogonal factorial designs for trials of therapist-delivered interventions: Randomising intervention-therapist combinations to patients

TL;DR

This paper proposes a novel factorial design for trials of therapist-delivered interventions, allowing for better separation of intervention and therapist effects through orthogonal randomisation of therapist-intervention combinations.

Contribution

It introduces a family of orthogonal factorial designs with associated analysis methods for therapist and intervention effects in clinical trials.

Findings

Simulation shows improved estimation of intervention effects.

Design allows for therapist learning and centre effects.

Potential for more accurate evidence on complex interventions.

Abstract

It is recognised that treatment-related clustering should be allowed for in the sample size and analyses of individually-randomised parallel-group 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, 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 randomised 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 centre 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 randomisation 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.