Systematic Sampling in Conducting Nursing and Health Sciences Research: Approach for Efficient and Representative Data Collection

Systematic sampling is one of the most widely used probability sampling techniques in health and social science research because of its simplicity, efficiency, and ability to generate representative samples from large populations. This paper aims to present a comprehensive discussion of systematic sampling, including its concepts, procedures, applications, strengths, and limitations in nursing and health sciences. Using an integrative review approach organized through the IMRAD format, the study synthesized literature from methodological references and scholarly sources related to systematic sampling. Findings show that systematic sampling involves selecting participants at regular intervals from an ordered population list after identifying a random starting point. It is especially useful in hospital-based studies, community surveys, patient satisfaction research, and public health investigations where complete population lists are available. The method reduces time and operational burden compared with simple random sampling while maintaining objectivity in participant selection. However, potential weaknesses such as periodicity, hidden patterns in sampling frames, and dependence on accurate population lists must be carefully considered. The discussion highlights that when properly implemented, systematic sampling can provide reliable and practical data for evidence-based nursing and healthcare decision-making. The paper concludes that systematic sampling remains a valuable method for researchers who need a structured and manageable sampling strategy without compromising scientific rigor. It is recommended that nursing and health researchers use systematic sampling when population frames are accessible and when careful planning can minimize possible bias.