Evidence map›Paper›PMID 41048536›Full record

ArticleInformation systems research : ISR2025

The ITEM Ontology: A Tool to Elucidate the Anatomy of Psychometric Indicators.

Kai R Larsen, Roland M Mueller, Dario Bonaretti, Diana Fischer-Preßler, James Jim Burleson, Nimisha Singh, Jeffrey Parsons, Jean-Charles Pillet, Lan Sang, Zhu Drew Zhang

Abstract read
In one paragraph

Article in Information systems research : ISR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Kai R LarsenUniversity of Colorado Boulder.
Roland M MuellerBerlin School of Economics and Law.
Dario BonarettiNEOMA Business School.
Diana Fischer-PreßlerUniversity of Applied Sciences Frankfurt.
James Jim BurlesonCalifornia Polytechnic State University.
Nimisha SinghBennett University, India.
Jeffrey ParsonsMemorial University of Newfoundland.
Jean-Charles PilletToulouse Business School.
Lan SangUniversity of Colorado Boulder.
Zhu Drew ZhangUniversity of Rhode Island.

Funding

Columbia University Science of Behavior Change Resource and Coordinating Center renewal -Ontology Administrative SupplementU24AG052175 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI EDMONDSON, DONALD · 2015 to 2024
$14.5M
NIA NIH HHS U24 AG052175
6 · The paper itself

Abstract

Survey-based research in information systems requires valid scales to advance theory, and the discipline has developed rigorous procedures to assess scale validity. In principle, these procedures ensure that scales consist of clear indicators and faithfully represent the focal construct. However, the focus on the psychometric properties of scales has overshadowed the role of lexical and semantic elements in the validation process, leading to invalid scales. This overemphasis on psychometric properties will persist unless researchers have a systematic approach to analyzing the properties of indicators and share the outcome of such analyses in formats that can be peer-reviewed, critiqued, or corroborated by other researchers. Thus, the psychometric community needs a shared language and method to uncover the properties of indicators and identify validity problems that psychometric analysis fails to detect. Drawing on ontology development methods, we propose the Indicator Terminology for Explanation and Measurement (ITEM) Ontology, consisting of four high-level hierarchies of entities: objects, measurables, qualifiers, and response sets, each almost always found within an individual indicator. We develop an approach, a codebook, and a website for applying ITEM to psychometric indicators. Common approaches to ontology evaluation are then used to evaluate its expressiveness, utility, importance, accessibility, suitability, and external validity. We find that the ITEM Ontology is highly generative in that it can be used to address several previously unsolvable problems in survey science, polling, and theory testing.

Indexed as

indicator evaluationinformation systemsITEM Ontologypsychometricsscale developmentvalidity

Identifiers

PMID41048536
PMCPMC12490787

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.