The frequency of community health worker home visits required to reduce early childhood caries in Ghanaian preschoolers remains unspecified, and the cluster-randomised designs used to evaluate such programmes are rarely powered to detect the small incidence differences that matter at population scale. No observational data were used or claimed. Under a declared variance structure with between-cluster standard deviation 6.0, residual standard deviation 4.5 and intraclass correlation 0.64, power was estimated across 2000 replications per design cell for cluster counts of 8, 16, 24 and 32 and effect sizes of 3, 5 and 8 percentage points. The analysis indicates that 52 clusters are required to detect a 5 percentage point reduction at 80% power, and that the minimum detectable effect at 80% power falls steeply as cluster count rises from 8 to 32. The BACIP interaction estimator is shown to be sensitive to the intraclass correlation of 0.64, which inflates the cluster-level variance and makes small cluster counts unreliable for threshold detection. The contribution is a design specification for target-trial emulations of counselling dose, not an estimate of programme effect.
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Mumbere et al. (2026) studied this question.
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