Effectiveness of BHATIN (Behavior-Tailored Intervention) for Self-Care Management and Clinical Biomarkers Among Patients with Hypertension: A Quasi-Experimental Study [Letter]

We read with interest the article by Usman et al, which evaluated the BHATIN model for improving self-care management and clinical biomarkers among adults with hypertension. 1 The topic is clinically important because sustainable behavioral support is central to community hypertension care.Our main reason for responding is to highlight several methodological and analytical limitations that may compromise internal validity and lead to overestimation of the intervention effect.We also offer practical suggestions that may strengthen interpretation of the findings and guide future evaluations of similar nurse-led interventions.The first concern relates to the unit of allocation.Participants were recruited from two different villages, with one village designated as the intervention site and the other as the control site. 1 This means that treatment assignment was completely confounded with village.Therefore, observed post-intervention differences may reflect the BHATIN intervention, pre-existing village-level differences, or both.This concern is not only theoretical.As reported in Table 2 by Usman et al, there were statistically significant baseline differences in weight, height, total cholesterol, uric acid, and salt preference, and large numerical differences in attitude, subjective norm, and behavioral intention. 1These imbalances could plausibly reflect differences in village-level health behaviors, habitual diet and salt exposure, medication-use patterns, community health-worker engagement, or routine primary-care implementation before the intervention began.Guidance for cluster trials has emphasized that studies with one cluster per arm should be avoided because the intervention effect cannot be validly separated from the cluster effect. 2At minimum, this limitation should be stated more explicitly and causal language should be softened.Future evaluations could use individual randomization within villages when contamination is manageable, or multiple villages per arm, a cluster-randomized design, or a steppedwedge approach when contamination is a major concern.A second issue concerns baseline comparability and the analytical strategy used to estimate treatment effects.The paper states that the groups were generally comparable at baseline, yet several variables differed materially. 1 In nonrandomized studies, reliance on baseline significance testing to establish comparability is problematic because it may obscure clinically relevant imbalance and may misguide confounder handling. 3More importantly, the authors analyzed within-group change using paired t-tests and post-intervention between-group differences using independent t-tests. 1 For pre-post comparative studies, this approach is weaker than regression-based analyses that adjust for baseline