Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 659

The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.

How Should the Internal Structure of Personality Inventories Be Evaluated?

Open access
Hopwood, Christopher J., Donnellan, M. Brent·2010·Personality and Social Psychology Review

Abstract

Personality trait inventories often perform poorly when their structure is evaluated with confirmatory factor analysis (CFA). The authors demonstrate poor CFA fit for several widely used personality measures with documented evidence of criterion-related validity but also show that some measures perform well from an exploratory factor analytic perspective. In light of these results, the authors suggest that the failure of these measures to fit CFA models is because of the inherent complexity of personality, issues related to its measurement, and issues related to the application and interpretation of CFA models. This leads to three recommendations for researchers interested in the structure and assessment of personality traits: (a) utilize and report on a range of factor analytic methods, (b) avoid global evaluations regarding the internal validity of multiscale personality measures based on model fit according to conventional CFA cutoffs, and (c) consider the substantive and practical implications of model modifications designed to improve fit.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1177/1088868310361240

Cites

76 of 76 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 76 references

Cited by

See all 659

Metadata

Authors
Hopwood, C. J., & Donnellan, M. B.
Venue
Personality and Social Psychology Review
Published
2010-04-30
Volume
14
Issue
3
Pages
332-346
ISSN
  • 1088-8683 (ISSN-L)
  • 1532-7957
OpenAlex
W2159230122
Cited by
659
References
76
FWCI
44.91
Type
journal article
Language
en
Open access
green

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 ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: How Should the Internal Structure of Personality Inventories Be Evaluated? https://app.cochat.ai/papers/10.1177/1088868310361240
The paper
Hopwood, C. J., & Donnellan, M. B. (2010). How Should the Internal Structure of Personality Inventories Be Evaluated? Personality and Social Psychology Review. https://doi.org/10.1177/1088868310361240

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.