Is the CVI an acceptable indicator of content validity? Appraisal and recommendations
Abstract
Nurse researchers typically provide evidence of content validity for instruments by computing a content validity index (CVI), based on experts' ratings of item relevance. We compared the CVI to alternative indexes and concluded that the widely-used CVI has advantages with regard to ease of computation, understandability, focus on agreement of relevance rather than agreement per se, focus on consensus rather than consistency, and provision of both item and scale information. One weakness is its failure to adjust for chance agreement. We solved this by translating item-level CVIs (I-CVIs) into values of a modified kappa statistic. Our translation suggests that items with an I-CVI of .78 or higher for three or more experts could be considered evidence of good content validity.
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For at least six experts, the acceptable CVI value is at least 0.83.
“| At least six experts | At least 0.83 | Polit & Beck (2006), Polit et al., (2007) |”
From ABC of content validation and content validity index calculation (2019) · cites this paper as Polit et al., (2007)
For three to five experts, the acceptable CVI value should be 1.
“| Three to five experts | Should be 1 | Polit & Beck (2006), Polit et al., (2007) |”
From ABC of content validation and content validity index calculation (2019) · cites this paper as Polit et al., (2007)
Most recommendations propose a minimum of six experts for content validation.
“It can be concurred that for content validation, the minimum acceptable expert number is two, however most of recommendations propose a minimum of six experts.”
From ABC of content validation and content validity index calculation (2019) · cites this paper as Polit et al., (2007)
The relevance of an assessment tool has been frequently used to measure content validity.
“Despite the two aspects of content validity (i.e., relevant and representativeness of an assessment tool), the relevant of an assessment tool that was advocated by Davis (5) has been frequently used to measure the content validity (6, 7).”
From ABC of content validation and content validity index calculation (2019) · cites this paper as [7]
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- Authors
- Polit, D. F., Beck, C. T., & Owen, S. V.
- Affiliations
- Griffith University (AU)
- University of Connecticut (US)
- The University of Texas at San Antonio Health Science Center (US)
- Corresponding author
- Polit, Denise F.
- ORCID
- Beck, Cheryl Tatano
- Venue
- Research in Nursing & Health
- Publisher
- Wiley
- Published
- 2007-07-24
- Volume
- 30
- Issue
- 4
- Pages
- 459-467
- ISSN
- 0160-6891 (ISSN-L)
- 1098-240X
- OpenAlex
- W2078199993
- Cited by
- 5,273
- References
- 5
- Citations by year
- 2026: 854 · 2025: 709 · 2024: 654 · 2023: 553 · 2022: 554 · 2021: 423 · 2020: 363 · 2019: 240 · 2018: 201 · 2017: 181 · 2016: 140 · 2015: 106 · 2014: 85 · 2013: 71 · 2012: 55
- FWCI
- 58.82
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Research in Nursing & Health (publishedVersion)
- PubMed (publishedVersion)
- Griffith Research Online (submittedVersion)
- Topics
- Social Sciences › Education › Health Education and Validation
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Keywords
- content validity index, content validity, content validity ratio, kappa statistic, chance-corrected agreement, expert ratings, instrument development, nursing research instruments
- MeSH terms
- Data Interpretation, Statistical, Humans, Psychometrics, Sensitivity and Specificity, Reproducibility of Results, Nursing Research, Observer Variation, Guidelines as Topic, Consensus
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