<p>This study estimates the prevalence of depression among college students at two distinct college campuses—one in New Delhi (India) and the other in Lahore (Pakistan). The survey was performed using a complex but theoretically more accurate Mixture Binary Randomized Response Technique (RRT) Model published in 2024. In addition to estimating the prevalence of depression, the study also examined whether the application of a complex theoretical model in a field survey is prone to measurement errors. Results indicate that RRT estimates align closely with the non-RRT anonymous “drop -in—the—box” method at one site where the trust level in the RRT methodology was high validating the theoretical model's practical utility in contrast to the other site where the trust level in RRT was low. The lower respondent trust yielded a negative estimate for measurement error which complicated the interpretation. It is observed that the model produces robust estimates even in lower-trust environments. These findings highlight the importance of transparent reporting in field surveys using complex models, underscoring that mixture RRT methodologies can produce reliable prevalence estimates under realistic conditions. Our study emphasizes the critical role of respondent comprehension and trust in survey validity and advocates for thoughtful application of RRT techniques in diverse cultural contexts.</p>