Persistent carry-over in a two-period randomised crossover design for behavioural
interventions without the expectation of return to baseline after intervention
cessation
#MMPMID41345689
Kulnik ST
; Carrozzo AE
; Crutzen R
Trials
2025[Dec]; 26
(1
): 561
PMID41345689
show ga
BACKGROUND: The two-period randomised crossover design can be advantageous over
the parallel-group randomised controlled design with two study arms, yielding
greater statistical power and requiring smaller sample sizes. However, a general
assumption of the crossover design is that study participants return to their
stable baseline state after the experimental treatment has been withdrawn, either
immediately or following a wash-out period. MAIN BODY: In this article, we
describe an alternative paradigm for the crossover design, which assumes that
participants do not return to their baseline after the experimental treatment has
discontinued-in other words, a paradigm under which a persistent carry-over
effect is anticipated and even desired after intervention cessation. Such a
paradigm is suitable, for example, when investigating behaviour change
interventions that aim to establish long-lasting health behaviours through, for
example, patient education or counselling. We present sample size calculations
and statistical simulations to illustrate that under this alternative paradigm,
the randomised crossover design can still maintain greater power than the
parallel-group randomised controlled design. Statistical simulations show that,
under realistic assumptions of partial or full carry-over, the crossover design
can maintain equal or greater power than the parallel-group design, particularly
when between-subject heterogeneity is non-negligible. CONCLUSION: Trialists may
consider this approach when the nature or intention of the experimental treatment
is contrary to the assumption of return to baseline.
|*Behavior Therapy/methods
[MESH]
|*Health Behavior
[MESH]
|*Randomized Controlled Trials as Topic/methods/statistics & numerical data
[MESH]
|*Research Design/statistics & numerical data
[MESH]
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