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How many is enough? Justifying sample size in descriptive quantitative research

  • Ruth Alison Mursa
  • , Christopher Patterson
  • , Gemma McErlean
  • , Elizabeth Halcomb
  • University of Wollongong

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

BACKGROUND: Descriptive quantitative researchers often use surveys to collect data about a group or phenomenon. Determining the required sample size in descriptive surveys can pose a challenge as there is no simple 'formula' by which to calculate an appropriate sample. However, when a sample is too small the study may fail to answer the research question and too many responses can create resource implications. AIM: To explore considerations regarding the justification of adequate sample size in descriptive quantitative research. DISCUSSION: Several considerations may assist quantitative descriptive researchers in examining the appropriateness and justification of sample size. Response rates can guide decision-making around the proportion of the target population who respond. Additionally, consideration of any validated tools, the spread or responses and types of analysis can guide sampling decisions. CONCLUSION: The strategies in this article provide a considered approach to justifying sample size in descriptive quantitative research. Factors such as response rates and analytical considerations provide a transparent means of justifying an adequate sample. IMPLICATIONS FOR PRACTICE: Providing clear justification for the sample size within descriptive quantitative research demonstrates a robust research approach and optimises resource use.

Original languageEnglish
Pages (from-to)35-40
Number of pages6
JournalNurse Researcher
Volume33
Issue number2
DOIs
Publication statusPublished - 11 Jun 2025
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2025 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.

Keywords

  • data analysis
  • data collection
  • online research
  • quantitative research
  • research
  • research methodology
  • research methods
  • study design
  • surveys

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