A QUANTITATIVE APPROACH TO CONTENT VALIDITY1
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The minimum acceptable content validity ratio (CVR) threshold was 0.37 for the first Delphi round (N = 29) and 0.42 for the second round (N = 24).
“Based on Lawshe’s critical values, the minimum acceptable CVR threshold was determined according to panel size, with a cutoff value of 0.37 for the first Delphi round (N = 29) and 0.42 for the second round (N = 24) (49).”
From Identifying social media professionalism competencies in Vietnamese medical students: a modified Delphi method (2026) · cites this paper as [49]
Content validity will be quantitatively and qualitatively assessed by a panel of 10 specialists using CVR and CVI.
“Content validity will be quantitatively and qualitatively assessed by a panel of 10 specialists. The qualitative assessment will evaluate phrasing, wording, item relevance and placement. Quantitatively, the content validity ratio (CVR) and content validity index (CVI) will be calculated based on expert ratings.49”
From Determinants of the choice of delivery mode in pregnant women: a convergent parallel mixed-methods study protocol (2026) · cites this paper as [49]
The final integrated framework comprised 24 consensus components organized into seven domains, plus the AHP priority architecture.
“The final integrated framework-comprising 24 consensus components organized into seven domains, plus the AHP priority architecture-was subjected to expert content validity verification using Lawshe's [35] CVR.”
From Toward Sustainable AI Literacy in Higher Education: A Delphi–AHP Approach to Identifying Key Components of AI/Data Extracurricular Programs (2026) · cites this paper as [35]
Consensus was determined using three indicators: content validity ratio (CVR) with a minimum threshold of 0.62 for a panel of 10, coefficient of variation (CV ≤ 0.5), and degree of consensus (≥0.75 based on the interquartile range to upper quartile ratio).
“Consensus was determined using three indicators: (a) content validity ratio (CVR) [35] with a minimum threshold of 0.62 for a panel of 10 (i.e., at least nine panel members rating the item ≥ 4); (b) coefficient of variation (CV ≤ 0.5); and (c) degree of consensus (≥0.75 based on the interquartile range to upper quartile ratio).”
From Toward Sustainable AI Literacy in Higher Education: A Delphi–AHP Approach to Identifying Key Components of AI/Data Extracurricular Programs (2026) · cites this paper as [35]
Content validity was assessed by consulting five field experts on 11 items using the Lawshe technique.
“After assessing the linguistic validity of the tool, ensuring its content validity involved consulting five field experts on 11 items. These experts used the Lawshe [31] technique to rate each item as (1) removed/not relevant, (2) relevant but needing correction, or (3) very relevant/approved.”
From Turkish adaptation of the clinical reasoning evaluation simulation tool (CREST-TR): a validity and reliability study (2025) · cites this paper as [31]
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- Authors
- LAWSHE, C. H.
- Affiliations
- Purdue University West Lafayette (US)
- Corresponding author
- LAWSHE, C. H.
- Venue
- Personnel Psychology
- Publisher
- Wiley
- Published
- 1975-12
- Volume
- 28
- Issue
- 4
- Pages
- 563-575
- ISSN
- 0031-5826 (ISSN-L)
- 1744-6570
- OpenAlex
- W1998623504
- Cited by
- 7,313
- References
- 2
- Citations by year
- 2026: 996 · 2025: 1009 · 2024: 792 · 2023: 730 · 2022: 641 · 2021: 576 · 2020: 485 · 2019: 350 · 2018: 287 · 2017: 223 · 2016: 236 · 2015: 204 · 2014: 174 · 2013: 139 · 2012: 79
- FWCI
- 3.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Personnel Psychology (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Education › Health Education and Validation
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Keywords
- content validity, test development, job analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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