Evidence map›Paper›PMID 35608742›Full record

ArticleInternational journal of health economics and management2023

Disability specific equivalence scales: a case-control approach applied to the cost of acquired brain injuries.

Eleftherios Giovanis, Martina Menon, Federico Perali

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Article in International journal of health economics and management, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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

1 citing paper in PubMed.

  1. 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

3 authors.

Eleftherios GiovanisFaculty of Economics and Administrative Sciences, Department of International Trade and Business, İzmir Bakırçay University, Menemen, 35665, Izmir, Turkey. giovanis95@gmail.com.ORCID http://orcid.org/0000-0002-7492-7461
Martina MenonDepartment of Economics, University of Verona, Via Cantarane 24, 37129, Verona, Italy.
Federico PeraliDepartment of Economics, University of Verona, Via Cantarane 24, 37129, Verona, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study estimates the household costs resulting from acquired brain injuries in terms of a reduction in the standard of living. The application uses primary data collected in the Verona and Florence provinces of Italy integrating highly detailed health information with information about consumption, income, wealth, time-use and relational well-being describing the standard of living. In general, the estimates of disability costs in previous studies are obtained from survey data without a specific focus on individuals with disabilities but collect information on the general health status. In contrast, this study exploits highly detailed information on a sample of "cases" with a disability, whose intensity is measured by the highly precise European quality of life measure-5 domain-5 (EQ-5D) instrument, to be compared with a sample of "control" formed by households without disabled members. The disability scales have been estimated using a Structural Equation Modelling (SEM) based procedure. We then implement interpersonal comparisons on the health income dimension in a theoretically plausible way, testing the independence hypothesis of equivalence scales. Our study finds that on average disabled households need an additional amount of about €1800 per month to reach the same standard of livings as the non-disabled households corresponding to a scale of 1.78.

Indexed as

Persons with DisabilitiesQuality of LifeCase-Control StudiesFamily CharacteristicsHumansIncomeAcquired brain injuryDisability costsEquivalence scalesInterpersonal comparisonStandard of livingStructural equation modelling

Identifiers

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Registered trials

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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.