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Selecting the sample
  1. Allison Shorten1,
  2. Calvin Moorley2
  1. 1Yale University School of Nursing, West Haven, Connecticut, USA
  2. 2University of East London, School of Health, Sport and Bioscience, Stratford, London, UK
  1. Correspondence to: Dr Allison Shorten
    , Yale University School of Nursing, PO Box 27399, West Haven, CT 06516-7399, USA; allison.shorten{at}

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Sample selection is a key factor in research design and can determine whether research questions will be answered before the study has even begun. Good sample selection and appropriate sample size strengthen a study, protecting valuable time, money and resources. In the context of healthcare research, poor design could lead to use of harmful practices, delays in new treatment and lost opportunities for high quality care. Not every study can achieve design perfection and researchers often seek a balance between the ideal sample and one that is feasible or convenient, acknowledging the limitations of their design decisions. Sample selection is far from simple but here are some of the techniques to think about as you read research and make the most out of your research endeavours.

Sampling the population

It is critical to take the time to clearly identify the population of interest for the specific research question. Nursing researchers are usually interested in answering questions about very specific patient populations which can span an incredible array of possibilities applying to international, national, local and organisational contexts. Research populations closely reflect nursing specialties, some of which are gender (eg, pregnant women) and age specific (eg, adolescent diabetes). It is rarely feasible to conduct a study that reaches every patient in the population of interest, therefore a subset or sample of that population is selected for study.

Different sampling methods are used depending on the aim of the study and whether the research question seeks a confident answer about the population of interest. If it does then the sample/s should represent the population for inferences to be made. Not all research questions depend on making inferences and there are many examples in qualitative research where the aim is theory development or exploration of patient experiences and inferences are not the focus.

Sampling methods: quantitative research

Probability (representative) sampling …

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  • Competing interests None.

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