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

Mursa, RA; Patterson, C; McErlean, G; Halcomb, E

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

Mursa, RA Patterson, C McErlean, G

Halcomb, E

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Publisher:: RCNI
Publication Type:: Journal Article
Citation:: Nurse Res, 2025, 33, (2), pp. 35-40
Issue Date:: 2025-06-11

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Field	Value	Language
dc.contributor.author	Mursa, RA
dc.contributor.author	Patterson, C
dc.contributor.author	McErlean, G https://orcid.org/0000-0001-6496-5678
dc.contributor.author	Halcomb, E
dc.date.accessioned	2026-07-29T05:30:20Z
dc.date.available	2024-10-16
dc.date.available	2026-07-29T05:30:20Z
dc.date.issued	2025-06-11
dc.identifier.citation	Nurse Res, 2025, 33, (2), pp. 35-40
dc.identifier.issn	1351-5578
dc.identifier.issn	2047-8992
dc.identifier.uri	http://hdl.handle.net/10453/195823
dc.description.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.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	RCNI
dc.relation.ispartof	Nurse Res
dc.relation.isbasedon	10.7748/nr.2025.e1958
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	1110 Nursing
dc.subject.classification	4204 Midwifery
dc.subject.classification	4205 Nursing
dc.subject.mesh	Sample Size
dc.subject.mesh	Humans
dc.subject.mesh	Research Design
dc.subject.mesh	Nursing Research
dc.subject.mesh	Data Collection
dc.subject.mesh	Humans
dc.subject.mesh	Data Collection
dc.subject.mesh	Sample Size
dc.subject.mesh	Nursing Research
dc.subject.mesh	Research Design
dc.subject.mesh	Sample Size
dc.subject.mesh	Humans
dc.subject.mesh	Research Design
dc.subject.mesh	Nursing Research
dc.subject.mesh	Data Collection
dc.title	How many is enough? Justifying sample size in descriptive quantitative research.
dc.type	Journal Article
utslib.citation.volume	33
utslib.location.activity	England
utslib.for	1110 Nursing
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Health
pubs.organisational-group	University of Technology Sydney/Faculty of Health/School of Nursing and Midwifery
pubs.organisational-group	University of Technology Sydney/Faculty of Health/School of Nursing and Midwifery/Discipline of Nursing
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/
dc.date.updated	2026-07-29T05:30:19Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	33
utslib.citation.issue	2

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.

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http://hdl.handle.net/10453/195823