Evidence map›Paper›PMID 42070182›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2026

Factors associated with health state valuations: a secondary analysis of an EQ-5D-3L valuation study from Jordan.

Abeer Al Rabayah, Fatima Al Sayah, Marjan Arvandi, Uwe Siebert

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Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Abeer Al RabayahInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research, and Health Technology Assessment, UMIT TIROL - University for Health Sciences and Technology, Hall in Tirol, Austria. Abeer-Ahmad-Hamdan.Al-Rabayah@umit-tirol.at.ORCID http://orcid.org/0000-0003-2952-9103
Fatima Al SayahAlberta PROMs & EQ-5D Research & Support Unit (APERSU), School of Public Health, University of Alberta, Edmonton, AB, Canada.
Marjan ArvandiInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research, and Health Technology Assessment, UMIT TIROL - University for Health Sciences and Technology, Hall in Tirol, Austria.
Uwe SiebertInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research, and Health Technology Assessment, UMIT TIROL - University for Health Sciences and Technology, Hall in Tirol, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeElicitation of EQ-5D value sets using time trade-off (TTO) is based on the general population’s degree of preference for specific health states. This study aimed to identify factors associated with health state valuations among the Jordanian population, conducted as part of the EQ-5D-3L valuation study.

methodsA cross-sectional study using EQ-5D-3L valuation data from Jordanian participants was used to identify factors associated with health state valuation. The valuation study followed the latest EuroQol Group valuation protocol (EQ-VT v2.1). Participants aged ≥ 18 years were interviewed via videoconferencing. Sociodemographic, geographic regions, and health indicators data were collected. We applied a quota sampling based on region, gender, and age. Univariate and multivariable (multilevel mixed effects model, Tobit random, and random intercept) regression models were applied to identify associations. Statistical analysis was conducted using STATA version 17.

resultsFrom September 2021 to April 2022, 301 participants were included in the study, covering all Jordanian governorates from the north, middle, and south. A representative sample was achieved. 51% of the participants were females with a mean age of 41 (± 15 (SD)) years. Overall, 69% were married, 50% of the respondents had a higher education degree, and 77% were insured. The mean EQ VAS score was 81(± 14). The multilevel mixed effects model was the best-fit model. Unemployment status and having more than one comorbidity were identified as statistically significant factors associated with cTTO health state valuation in Jordan.

conclusionSocioeconomic characteristics have limited ability to explain how Jordanians value cTTO health states. Future research should explore cultural dimensions and personality traits to understand health state valuations better.

Indexed as

Health StatusQuality of LifeAdolescentAdultAgedCross-Sectional StudiesFemaleHumansJordanMaleMiddle AgedSocioeconomic FactorsSurveys and QuestionnairesYoung AdultcTTOEQ-5D-3LJordanPredictorsValuation

Identifiers

PMID42070182
PMCPMC13136213

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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.