Evidence map›Paper›PMID 34590202›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2022

Efficient and precise Ultra-QuickDASH scale measuring lymphedema impact developed using computerized adaptive testing.

Cai Xu, Mark V Schaverien, Joani M Christensen, Chris J Sidey-Gibbons

Abstract read
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Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Development of a PROMIS multidimensional cancer-related fatigue (mCRF) form using modern psychometric techniques.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Article
  3. Article
  4. Suitability of the animated activity questionnaire for use as computer adaptive test: establishing the AAQ-CAT.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2023
    Article
  5. Article
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Cai XuMD Anderson Center for INSPiRED Cancer Care (Integrated Systems for Patient-Reported Data), The University of Texas MD Anderson Cancer Center, Houston, USA.
Mark V SchaverienDepartment of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, USA.
Joani M ChristensenDepartment of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, USA.
Chris J Sidey-GibbonsDepartment of Symptom Research, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd. Unit 1055, Houston, TX, 77030-4009, USA. cgibbons@mdanderson.org.ORCID http://orcid.org/0000-0002-4732-7305

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to evaluate and improve the accuracy and efficiency of the QuickDASH for use in assessment of limb function in patients with upper extremity lymphedema using modern psychometric techniques.

methodWe conducted confirmative factor analysis (CFA) and Mokken analysis to examine the assumption of unidimensionality for IRT model on data from 285 patients who completed the QuickDASH, and then fit the data to Samejima's graded response model (GRM) and assessed the assumption of local independence of items and calibrated the item responses for CAT simulation.

resultsInitial CFA and Mokken analyses demonstrated good scalability of items and unidimensionality. However, the local independence of items assumption was violated between items 9 (severity of pain) and 11 (sleeping difficulty due to pain) (Yen's Q3 = 0.46) and disordered thresholds were evident for item 5 (cutting food). After addressing these breaches of assumptions, the re-analyzed GRM with the remaining 10 items achieved an improved fit. Simulation of CAT administration demonstrated a high correlation between scores on the CAT and the QuickDash (r = 0.98). Items 2 (doing heavy chores) and 8 (limiting work or daily activities) were the most frequently used. The correlation among factor scores derived from the QuickDASH version with 11 items and the Ultra-QuickDASH version with items 2 and 8 was as high as 0.91.

conclusionBy administering just these two best performing QuickDash items we can obtain estimates that are very similar to those obtained from the full-length QuickDash without the need for CAT technology.

Indexed as

Computerized Adaptive TestingLymphedemaHumansPsychometricsQuality of LifeSurveys and QuestionnairesComputerized adaptive testingItem response theoryLymphedemaPatient reported outcome measureQuickDASH measureUltra-QuickDASH

Identifiers

PMID34590202
PMCPMC8921172

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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.