Evidence map›Paper›PMID 31955391›Full record

ArticleNeurology and therapy2020

Psychometric Properties of the SymptoMScreen Questionnaire in a Mild Disability Population of Patients with Relapsing-Remitting Multiple Sclerosis: Quantifying the Patient's Perspective.

José Meca-Lallana, Jorge Maurino, Miguel Ángel Hernández-Pérez, Ángel P Sempere, Luis Brieva, Elena García-Arcelay, María Terzaghi, Gustavo Saposnik, Javier Ballesteros

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Article in Neurology and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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

10 citing papers in PubMed.

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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

9 authors.

José Meca-LallanaClinical Neuroimmunology Unit and Multiple Sclerosis CSUR, Department of Neurology, Hospital Universitario "Virgen de la Arrixaca", Biomedical Research Institute of Murcia (IMIB-Arrixaca), Universidad Católica San Antonio (UCAM), Murcia, Spain.
Jorge MaurinoMedical Department, Roche Farma, Madrid, Spain. jorge.maurino@roche.com.ORCID http://orcid.org/0000-0001-9858-3555
Miguel Ángel Hernández-PérezDepartment of Neurology, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain.
Ángel P SempereDepartment of Neurology, Hospital General Universitario de Alicante, Alicante, Spain.
Luis BrievaDepartment of Neurology, Hospital Universitari Arnau de Vilanova, Biomedical Research Institute of Lleida (IRBLleida), Lleida, Spain.
Elena García-ArcelayMedical Department, Roche Farma, Madrid, Spain.
María TerzaghiDecision Neuroscience Unit, Li Ka Shing Institute, University of Toronto, Toronto, Canada.
Gustavo SaposnikDecision Neuroscience Unit, Li Ka Shing Institute, University of Toronto, Toronto, Canada.
Javier BallesterosDepartment of Neurosciences and CIBERSAM, University of Basque Country (UPV/EHU), Leioa, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Crucial elements for achieving optimal long-term outcomes in multiple sclerosis (MS) are patient confidence and effective physician-patient communication. Patient-reported instruments may provide the means to fill the gap in currently available clinician-rated measures. The SymptoMScreen (SMSS) is a brief self-assessment tool for measuring symptom severity in 12 neurologic domains commonly affected by MS. We conducted a non-interventional study to assess the dimensional structure and item characteristics of the SMSS. A total of 218 patients with relapsing-remitting MS and mild disability (median Expanded Disability Status Scale score 2.0) were studied. Symptom severity was low (SMSS score 13.5, interquartile range 4.2-27), fatigue being the domain with the highest impact. A non-parametric item response theory, i.e., Mokken analysis, found that the SMSS is a robust one-dimensional scale (overall scalability index H  0.60) with high reliability (Cronbach's alpha  0.94). The confirmatory factor analysis model confirmed the unidimensional structure (comparative fit index 1.0, root-mean-square error of approximation  0.001). Samejima's model fitted well an unconstrained model with different item difficulties. The SMSS shows appropriate psychometric characteristics and may constitute a valuable and easy-to-implement addition to measure the symptom severity in clinical practice.

Indexed as

Multiple sclerosisPatient-reported outcomePsychometric methodsSymptom severity

Identifiers

PMID31955391
PMCPMC7229098

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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.