In nursing research, a population refers to the entire aggregate of cases that meet a designated set of criteria. Unlike everyday usage where population means all people living in a country like Nigeria, a research population can consist of patients, pregnant women, practicing nurses, or even hospital records. Defining this group clearly is the very first step before planning any data collection in a community or clinical ward.
A target population is the entire aggregate of cases about which the researcher would like to generalize findings. For instance, all diabetic patients in Nigeria form a target population. However, studying every single one of them is practically impossible due to financial and geographical constraints.
An accessible population is the portion of the target population that is actually available to the researcher. If a nurse researcher in Lagos studies diabetic patients attending clinics at Lagos University Teaching Hospital, that specific clinic group is the accessible population.
Researchers set boundaries using specific criteria to ensure participant safety and study validity.
A sampling frame is the actual list of all elements or members in the accessible population from which the sample is drawn, such as an institutional register of nursing students. From this list, researchers apply various sampling techniques.
Choosing how many participants to recruit is a critical decision in nursing research. If a sample is too small, the study may lack statistical power to detect real differences in patient outcomes. Conversely, an excessively large sample wastes scarce resources and time. Researchers rely on power analysis formulas, anticipated effect sizes, and acceptable margin of error to calculate the optimal sample size.
Sampling bias occurs when the chosen participants do not accurately represent the wider accessible population, often due to poor recruitment methods like reliance solely on volunteers. When bias is minimized, generalizability (external validity) increases, allowing the researcher to safely apply study findings from a sample of patients to broader clinical populations across different healthcare settings.