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The unresolved problem is that adherence switching is typically modelled as a binary choice between biomedical and traditional care, whereas patients in practice hold both options simultaneously and respond to the perceived credibility of each. The paper specifies a random-utility model in which the probability of adherence switching depends on the relative credibility of the herbalist, the probability of disclosure to the clinical team, and the retention cost of switching. Because no primary data are available, the analysis is framed as a design and power study for a discrete-choice experiment (DCE) to be fielded in Botswana. Using a before-after-control-impact (BACI) design with a declared variance structure (between-cluster SD = 6.0, residual SD = 4.5, intraclass correlation = 0.64), the paper characterises the operating characteristics of the proposed estimator across 8, 16, 24 and 32 clusters and effect sizes of 3, 5 and 8 percentage points, with 2000 replications per cell. Power reaches 80% at 54 clusters for a 5-percentage-point effect. The contribution is a design template that makes dual-therapy disclosure an explicit estimand rather than an unmeasured confounder, and that specifies the cluster counts and effect sizes at which a Botswana DCE can credibly detect adherence switching.
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Mothibi et al. (2026) studied this question.
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