Evidence map›Paper›PMID 35901070›Full record

SynthesisPloS one2022

Spatial and temporal distribution of the prevalence of unemployment and early retirement in people with multiple sclerosis: A systematic review with meta-analysis.

Bruno Kusznir Vitturi, Alborz Rahmani, Guglielmo Dini, Alfredo Montecucco, Nicoletta Debarbieri, Paolo Bandiera, Mario Alberto Battaglia, Tommaso Manacorda, Benedetta Persechino, Giuliana Buresti and 3 more

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 5 pooled it
3.4field-weighted citation impact, top 7% 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

15 citing papers in PubMed, 5 syntheses or guidelines pooled it, 25 citations in OpenAlex.

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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

13 authors at 5 institutions in 1 country.

Bruno Kusznir VitturiDepartment of Health Sciences, University of Genoa, Genoa, Italy.ORCID 0000-0002-2821-9042
Alborz RahmaniDepartment of Health Sciences, University of Genoa, Genoa, Italy.
Guglielmo DiniDepartment of Health Sciences, University of Genoa, Genoa, Italy.
Alfredo MontecuccoDepartment of Health Sciences, University of Genoa, Genoa, Italy.
Nicoletta DebarbieriIRCCS Ospedale Policlinico San Martino, Occupational Medicine Unit, Genoa, Italy.
Paolo BandieraItalian Multiple Sclerosis Association (AISM), Genoa, Italy.
Mario Alberto BattagliaScientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy.
Tommaso ManacordaScientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy.
Benedetta PersechinoItalian Workers' Compensation Authority (INAIL), Genoa, Italy.
Giuliana BurestiItalian Workers' Compensation Authority (INAIL), Genoa, Italy.
Michela PonzioScientific Research Area, Italian Multiple Sclerosis Foundation (FISM), Genoa, Italy.
Matilde IngleseDepartment of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DiNOGMI) and Center of Excellence for Biomedical Research (CEBR), University of Genoa, Genoa, Italy.
Paolo DurandoDepartment of Health Sciences, University of Genoa, Genoa, Italy.
Ospedale Policlinico San Martino · ITAssociazione Italiana Sclerosi Multipla · ITIstituto Nazionale per l'Assicurazione Contro gli Infortuni sul Lavoro · ITUniversity of Genoa · ITUniversity of Siena · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aimed to summarise the prevalence of unemployment and early retirement among people with MS and analyze data according to a spatio-temporal perspective.

methodsWe undertook a systematic search of PubMed/MEDLINE, Scopus, SciVerse ScienceDirect, and Web of Science. We included any peer-reviewed original article reporting the prevalence of unemployment and early retirement in the working-age population with MS. We excluded articles off-topic, with other study designs, whose study sample were unlikely to be representative of the MS population and in case of unavailability of the full text or essential information. A random-effects meta-analysis was used to measure overall prevalence estimates of unemployment and early retirement. We used meta-regression and subgroup analysis to evaluate potential moderators of prevalence estimates and the leave-one-out method for sensitivity analyses.

resultsOur research identified 153 studies across 29 countries encompassing 188436 subjects with MS. The pooled overall effect size for unemployment and early retirement was 35.6% (95% CI 32.8-38.4; I2 = 99.31) and 17.2% (95% CI 14.6-20.2; I2 = 99.13), respectively. The prevalence of unemployment varied according to the year of publication (p < 0.001) and there was a statistically significant decrease in the prevalence of unemployment over time (p = 0.042). Regarding early retirement, only seven (31.8%) estimates obtained from studies that were published before 2010 were below the overall effect size in comparison to 27 (60.0%) estimates extracted from data published between 2010 and 2021 (p = 0.039). There was a significant difference in prevalence according to countries (p < 0.001). Psychiatric illness was an important clinical feature responsible for patients leaving the workforce in regions with a high MS prevalence.

conclusionsUnemployment and early retirement due to MS remain highly prevalent, despite a slight decline in the last decade. The prevalence of unemployment and early retirement varies globally.

Indexed as

Multiple SclerosisRetirementEmploymentHumansPrevalenceUnemployment

Identifiers

PMID35901070
PMCPMC9333213
OpenAlexW4288432569

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.