Evidence map›Paper›PMID 38127205›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2024

Unsupervised item response theory models for assessing sample heterogeneity in patient-reported outcomes measures.

Tolulope T Sajobi, Ridwan A Sanusi, Nancy E Mayo, Richard Sawatzky, Lene Kongsgaard Nielsen, Veronique Sebille, Juxin Liu, Eric Bohm, Oluwagbohunmi Awosoga, Colleen M Norris and 3 more

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In one paragraph

Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 16% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Internal validation methods to detect patient characteristics associated with differential item functioning in patient-reported outcome measures.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Article
  2. Tree-based item-response theory model for evaluating differential item functioning in patient-reported outcome measures: a web-based R Shiny implementation.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Article
  3. Article
  4. Tree-based latent variable model for assessing differential item functioning in patient-reported outcome measures: a simulation study.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Article
  5. Enhancing Measurement Precision of Patient-Reported Outcomes Using Item Response Theory.Inquiry : a journal of medical care organization, provision and financing
    Article
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

13 authors at 9 institutions in 3 countries.

Tolulope T SajobiDepartment of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, T2N 4Z6, Canada. ttsajobi@ucalgary.ca.ORCID http://orcid.org/0000-0002-5696-5552
Ridwan A SanusiDepartment of Community Health Sciences, University of Manitoba, Winnipeg, Canada.
Nancy E MayoCenter for Outcomes Research and Evaluation (CORE), Research Institute of the McGill University Health Center, McGill University, Montreal, Canada.
Richard SawatzkySchool of Nursing, Trinity Western University, Langley, British Columbia, Canada.
Lene Kongsgaard NielsenQuality of Life Research Center, Odense University Hospital, Odense, Denmark.
Veronique SebilleNantes Université, Université de Tours, CHU Nantes, INSERM, methodS in Patient-Centered Outcomes and HEalth ResEarch, SPHERE, 44000, Nantes, France.
Juxin LiuDepartment of Mathematics & Statistics, University of Saskatchewan, Saskatoon, Canada.
Eric BohmDepartment of Surgery, University of Manitoba, Winnipeg, Canada.
Oluwagbohunmi AwosogaFaculty of Health Sciences, University of Lethbridge, Lethbridge, Canada.
Colleen M NorrisFaculty of Nursing, University of Alberta, Edmonton, Canada.
Stephen B WiltonDepartment of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, T2N 4Z6, Canada.
Matthew T JamesDepartment of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, Calgary, T2N 4Z6, Canada.
Lisa M LixDepartment of Community Health Sciences, University of Manitoba, Winnipeg, Canada.
University of Calgary · CAUniversity of Manitoba · CAMcGill University · CAOdense University Hospital · DKUniversité de Tours · FRUniversity of Alberta · CAUniversity of Lethbridge · CAUniversity of Saskatchewan · CAWestern University · CA

Funding

CIHR 438908
6 · The paper itself

Abstract

purposeUnsupervised item-response theory (IRT) models such as polytomous IRT based on recursive partitioning (IRTrees) and mixture IRT (MixIRT) models can be used to assess differential item functioning (DIF) in patient-reported outcome measures (PROMs) when the covariates associated with DIF are unknown a priori. This study examines the consistency of results for IRTrees and MixIRT models.

methodsData were from 4478 individuals in the Alberta Provincial Project on Outcome Assessment in Coronary Heart Disease registry who received cardiac angiography in Alberta, Canada, and completed the Hospital Anxiety and Depression Scale (HADS) depression subscale items. The partial credit model (PCM) based on recursive partitioning (PCTree) and mixture PCM (MixPCM) were used to identify covariates associated with differential response patterns to HADS depression subscale items. Model covariates included demographic and clinical characteristics.

resultsThe median (interquartile range) age was 64.5(15.7) years, and 3522(78.5%) patients were male. The PCTree identified 4 terminal nodes (subgroups) defined by smoking status, age, and body mass index. A 3-class PCM fits the data well. The MixPCM latent classes were defined by age, disease indication, smoking status, comorbid diabetes, congestive heart failure, and chronic obstructive pulmonary disease.

conclusionPCTree and MixPCM were not consistent in detecting covariates associated with differential interpretations of PROM items. Future research will use computer simulations to assess these models' Type I error and statistical power for identifying covariates associated with DIF.

Indexed as

Patient Reported Outcome MeasuresQuality of LifeAlbertaFemaleHumansMaleMiddle AgedPsychometricsClassification and regression treesCoronary artery diseaseDifferential item functioningHospital anxiety and depression scaleItem response theoryPatient-reported outcomes

Identifiers

PMID38127205
PMCPMC10894181
OpenAlexW4390048276

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.