Factors associated with self- and informant ratings of quality of life, well-being and life satisfaction in people with mild-to-moderate dementia: results from the Improving the experience of Dementia and Enhancing Active Life programme
Bibliographic record
Abstract
BACKGROUND: a large number of studies have explored factors related to self- and informant ratings of quality of life in people with dementia, but many studies have had relatively small sample sizes and mainly focused on health conditions and dementia symptoms. The aim of this study is to compare self- and informant-rated quality of life, life satisfaction and well-being, and investigate the relationships of the two different rating methods with various social, psychological and health factors, using a large cohort study of community-dwelling people with dementia and carers in Great Britain. METHODS: this study included 1,283 dyads of people with mild-to-moderate dementia and their primary carers in the Improving the experience of Dementia and Enhancing Active Life study. Multivariate modelling was used to investigate associations of self- and informant-rated quality of life, life satisfaction and well-being with factors in five domains: psychological characteristics and health; social location; capitals, assets and resources; physical fitness and health; and managing everyday life with dementia. RESULTS: people with dementia rated their quality of life, life satisfaction and well-being more highly than did the informants. Despite these differences, the two approaches had similar relationships with social, psychological and physical health factors in the five domains. CONCLUSION: although self- and informant ratings differ, they display similar results when focusing on factors associated with quality of life, life satisfaction and well-being. Either self- or informant ratings may offer a reasonable source of information about people with dementia in terms of understanding associated factors.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".