Evidence map›Paper›PMID 41635505›Full record

ArticleFrontiers in psychology2026

Improving olfactory assessment: an item response theory analysis of the American English version of the Sniffin' sticks identification subtest.

Eva Tolomeo, Leognano Ceraudo, Ryann Kolb, Pamela H Dalton, Marco Tullio Liuzza, Valentina Parma

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Eva TolomeoDepartment of Health Sciences, University "Magna Graecia", Catanzaro, Italy.
Leognano CeraudoDepartment of Health Sciences, University "Magna Graecia", Catanzaro, Italy.
Ryann KolbMonell Chemical Senses Center, Philadelphia, PA, United States.
Pamela H DaltonMonell Chemical Senses Center, Philadelphia, PA, United States.
Marco Tullio LiuzzaDepartment of Developmental Psychology and Socialization, University of Padova, Padova, Italy.
Valentina ParmaMonell Chemical Senses Center, Philadelphia, PA, United States.

Funding

SCENTinel: A Rapid Smell Test for COVID-19 SurveillanceU01DC019578 · NIDCD · MONELL CHEMICAL SENSES CENTER · PI DALTON, PAMELA HELEN, PARMA, VALENTINA · 2021 to 2023
$1.2M
NIDCD NIH HHS U01 DC019578
6 · The paper itself

Abstract

Introduction: The Sniffin' Sticks Extended Test (SSET) is one of the most widely used tools for assessing olfactory function in research and clinical settings. Despite its broad application, a detailed psychometric evaluation of its items, including those within the identification subtest, remains limited. This study aimed to evaluate the reliability, validity, and item-level functioning of the SSET identification subtest using Item Response Theory (IRT), to identify potential weaknesses and propose possible areas for improvement. Methods: The study included 397 US-based participants (60.5% female; mean age 44.61 ± SD = 18.17 [45 ± 18]) who completed the American English version of the identification subtest of the SSET. IRT analyses were conducted using both a one-parameter (1PL) and a two-parameter (2PL) logistic model to estimate item difficulty and discrimination. A Differential Item Functioning (DIF) analysis was also performed to investigate potential sex-related biases in item responses. Results: Model comparison indicated that the 2PL model provided a better fit than the 1PL model. The 2PL analysis revealed that three items (i.e., Discussion: These findings support the use of IRT to identify poorly performing items, enabling the refinement of the SSET, to enhance its precision and reliability across populations. Future research should explore item revisions and extend psychometric evaluations to other subtests and samples.

Indexed as

differential item functioningitem response theoryodor identificationolfactory assessmentSniffin’ sticks

Identifiers

PMID41635505
PMCPMC12863060

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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.