Measurement of health-related quality of life for people with dementia: development of a new instrument (DEMQOL) and an evaluation of current methodology
Bibliographic record
Abstract
OBJECTIVES: To develop and validate a psychometrically rigorous measure of health-related quality of life (HRQoL) for people with dementia: DEMQOL. DATA SOURCES: Literature review. Expert opinion. Interviews and questionnaires. REVIEW METHODS: Gold standard psychometric techniques were used to develop DEMQOL and DEMQOL-Proxy. A conceptual framework was generated from a review of the literature, qualitative interviews with people with dementia and their carers, expert opinion and team discussion. Items for each component of the conceptual framework were drafted and piloted to produce questionnaires for the person with dementia (DEMQOL) and carer (DEMQOL-Proxy). An extensive two-stage field-testing was then undertaken of both measures in large samples of people with dementia (n = 130) and their carers (n = 126) representing a range of severity and care arrangements. In the first field test, items with poor psychometric performance were eliminated separately for DEMQOL and DEMQOL-Proxy to produce two shorter, more scientifically robust instruments. In the second field test, the item-reduced questionnaires were evaluated along with other validating measures (n = 101 people with dementia, n = 99 carers) to assess acceptability, reliability and validity. RESULTS: Rigorous evaluation in two-stage field testing with 241 people with dementia and 225 carers demonstrated that in psychometric terms: (1) DEMQOL is comparable to the best available dementia-specific HRQoL measures in mild to moderate dementia, but is not appropriate for use in severe dementia [Mini Mental State Examination (MMSE) <10]; and (2) DEMQOL-Proxy is comparable to the best available proxy measure in mild to moderate dementia, and shows promise in severe dementia. In addition, the DEMQOL system has been validated in the UK in a large sample of people with dementia and their carers, and it provides separate measures for self-report and proxy report, which allows outcomes assessment across a wide range of severity in dementia. CONCLUSIONS: The 28-item DEMQOL and 31-item DEMQOL-Proxy provide a method for evaluating HRQoL in dementia. The new measures show comparable psychometric properties to the best available dementia-specific measures, provide both self- and proxy-report versions for people with dementia and their carers, are appropriate for use in mild/moderate dementia (MMSE >/= 10) and are suitable for use in the UK. DEMQOL-Proxy also shows promise in severe dementia. As DEMQOL and DEMQOL-Proxy give different but complementary perspectives on quality of life in dementia, the use of both measures together is recommended. In severe dementia, only DEMQOL-Proxy should be used. Further research with DEMQOL is needed to confirm these findings in an independent sample, evaluate responsiveness, investigate the feasibility of use in specific subgroups and in economic evaluation, and develop population norms. Additional research is needed to address the psychometric challenges of self-report in dementia and validating new dementia-specific HRQoL measures.
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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 | 0.242 | 0.192 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".