Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 259

The DOI matches its Crossref record; 160 of the 160 references it cites were found in a registry or an index.

Construct Development and Validation in Three Practical Steps: Recommendations for Reviewers, Editors, and Authors

Lambert, Lisa Schurer, Newman, Daniel A.·2023·Organizational Research Methods

Abstract

We review contemporary best practice for developing and validating measures of constructs in the organizational sciences. The three basic steps in scale development are: (a) construct definition, (b) choosing operationalizations that match the construct definition, and (c) obtaining empirical evidence to confirm construct validity. While summarizing this 3-step process [i.e., Define-Operationalize-Confirm], we address many issues in establishing construct validity and provide a checklist for journal reviewers and authors when evaluating the validity of measures used in organizational research. Among other points, we pay special attention to construct conceptualization, acknowledging existing constructs, improving existing measures, multidimensional constructs, macro-level constructs, and the need for independent samples to confirm construct validity and measurement equivalence across subpopulations.

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 · 10.1177/10944281221115374

Cites

160 of 160 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 160 references

Cited by

See all 259

Metadata

Authors
Lambert, L. S., & Newman, D. A.
Venue
Organizational Research Methods
Published
2022-08-15
Volume
26
Issue
4
Pages
574-607
ISSN
  • 1094-4281 (ISSN-L)
  • 1552-7425
OpenAlex
W4291824852
Cited by
259
References
160
FWCI
23.99
Type
journal article
Language
en
Open access
closed

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: Construct Development and Validation in Three Practical Steps: Recommendations for Reviewers, Editors, and Authors. https://app.cochat.ai/papers/10.1177/10944281221115374
The paper
Lambert, L. S., & Newman, D. A. (2023). Construct Development and Validation in Three Practical Steps: Recommendations for Reviewers, Editors, and Authors. Organizational Research Methods. https://doi.org/10.1177/10944281221115374

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.