The Use of EQ-5D in the Middle East and North Africa Region: A Systematic Literature Review
Bibliographic record
Abstract
INTRODUCTION: The EQ-5D is the most commonly used preference-based measure of health-related quality of life. There is limited evidence about the use of the EQ-5D in the Middle East and North Africa (MENA) region. This study aimed to systematically identify, review, summarize, and synthesize the published literature on using the EQ-5D in this region. METHODS: A systematic literature review was conducted, according to the PRISMA 2020 guidelines, using PubMed, Cochrane, PsycINFO, and CINAHL and covering the period up to 30 August 2024. Studies using any version of the EQ-5D in adults or youth in the MENA region were included. Pilot studies, guidelines, study protocols, and reviews were excluded. Key study characteristics and outcomes assessed included study design, clinical area, population, type of EQ-5D data reported, reference value set used, and mode of administration. Title/abstract screening was conducted independently by two reviewers to assess eligibility for inclusion. Two researchers completed full-text screening and extracted data using a standardized form. Disagreements were referred to a third reviewer if not resolved by discussion. Results were summarized in systematic evidence tables. RESULTS: After removing duplicates, 18,034 references were considered for title/abstract screening. In total, 184 studies were included with a total sample size of 128,164 subjects. Of the included single-country studies, 42% were reported in Iran, 20% in Saudi Arabia, and 11% in Jordan. Patient populations were investigated in 86% of the studies, 23% of which targeted endocrine diseases. Study design was observational in 57% and experimental in 14% of the studies. Only 10% of the included studies applied the EQ-5D in an economic evaluation. The EQ-5D-3L version was used in 40% of the studies. However, the trend is towards a greater use of the 5L version in more recent years. Twenty percent of the studies reported EQ-5D results using the index score, frequencies of severity levels per dimension, and visual analog scale scores. EQ-5D modes of administration and funding sources were not reported in 16% and 20% of the studies, respectively. CONCLUSION: There is an increased use of the EQ-5D in the MENA region, especially since 2020. In the region, the use of the EQ-5D is more prevalent in clinical studies than in economic evaluation studies. The reporting heterogeneity indicates the need for guidance in reporting EQ-5D study results in this region.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".