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This article addresses the pervasive issue of missing data in biomedical research and the potential solutions to prevent it. The focus is on proactive strategies for prevention at various stages of the research process. Advocating for a comprehensive study design, clear communication through information sheets during consent, and the use of well-designed data collection tools are key to preventing missing data issues in health research. In addition, the training and supervision for data collectors, especially in the context of potential biases arising from sensitive questions, are critical. Electronic data collection has the advantages of validation and checks to prevent missing data. Hence, adequate planning is a must to reduce missing values and improve the validity of the study outcome.

Missing data can introduce biases and affect the generalizability of research findings, undermining the scientific rigor of studies and impeding the development of evidence-based practices. To overcome these challenges, health-care providers and researchers must adopt robust strategies to identify, prevent, and handle missing data effectively. This includes implementing standardized data collection procedures, utilizing advanced statistical techniques to account for missingness, and embracing emerging technologies that facilitate comprehensive and timely data capture. By prioritizing the management of missing data, health-care professionals and researchers can enhance patient care, improve research quality, and ultimately contribute to better health outcomes for individuals and populations.

Background: Self-care practices in diabetes are deemed as one of the mainstays of management, but often poorly practiced by people with diabetes. Aim: The study describes self-care practices among adult diabetics registered with a primary health-care setup. Methods: This was a community-based cross-sectional study based out of the Ramaiahguda primary health center in Vikarabad town of Telangana. Informed consent was taken from all participants before the commencement of the study. All eligible candidates were approached for the study. The seven domains of the “American Association of Diabetes Educators measures of outcome” were taken as the base for assessment of self-care practices among the participants. Results: The mean (standard deviation [SD]) age of the 155 study participants was 50.8 years (SD 12.4 years). Among the various components of self-care, drug adherence, glucose monitoring, and diet modifications were regular as per the advice. Comparatively, healthy coping, risk reduction, and problem solving are the areas where the participants had a major scope to improve. The median self-care score of the participants was 15.25 (interquartile range 14.5–16.25) ranging from 0.25 to 18.0. 86 (55.5%) participants had good self-care scores, and 69 (44.5%) participants had moderate self-care scores. Conclusions: The observations from our study point toward a lack of understanding and in-depth evaluation of the effectiveness of diabetic self-care practices, which may in turn be one of the factors affecting compliance to such practices among the diseased population.