Psychometric Properties of EQ-5D-3L and EQ-5D-5L in Cognitively Impaired Patients Living with Dementia
Bibliographic record
Abstract
BACKGROUND: Assessing health-related quality of life in dementia poses challenges due to patients' cognitive impairment. It is unknown if the newly introduced EQ-5D five-level version (EQ-5D-5L) is superior to the 3-level version (EQ-5D-3L) in this cognitively impaired population group. OBJECTIVE: To assess the psychometric properties of the EQ-5D-5L in comparison to the EQ-5D-3L in patients living with dementia (PwD). METHODS: The EQ-5D-3L and EQ-5D-5L were assessed via interviews with n = 78 PwD at baseline and three and six months after, resulting in 131 assessments. The EQ-5D-3L and EQ-5D-5L were evaluated in terms of acceptability, agreement, ceiling effects, redistribution properties and inconsistency, informativity as well as convergent and discriminative validity. RESULTS: Mean index scores were higher for the EQ-5D-5L than the EQ-5D-3L (0.70 versus 0.64). Missing values occurred more frequently in the EQ-5D-5L than the EQ-5D-3L (8%versus 3%). Agreement between both measures was acceptable but poor in PwD with moderate to severe cognitive impairment. The index value's relative ceiling effect decreased from EQ-5D-3L to EQ-5D-5L by 17%. Inconsistency was moderate to high (13%). Absolute and relative informativity increased in the EQ-5D-5L compared to the 3L. The EQ-5D-5L demonstrated a lower discriminative ability and convergent validity, especially in PwD with moderate to severe cognitive deficits. CONCLUSION: The EQ-5D-5L was not superior as a self-rating instrument due to a lower acceptability and discriminative ability and a high inconsistency, especially in moderate to severe dementia. The EQ-5D-3L had slightly better psychometric properties and should preferably be used as a self-rating instrument in economic evaluations in dementia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".