Dementia and Its Profound Impact on Family Members and Partners
Bibliographic record
Abstract
INTRODUCTION: Dementia can adversely affect the quality of life (QoL) of family members/partners of those affected. Measuring this often-neglected burden is critical to planning and providing appropriate support services. This study measures this impact using the Family-Reported Outcome Measure (FROM-16). METHODS: A large UK cross-sectional online study through patient research platforms, recruited family members/partners of people with dementia, to complete the FROM-16. RESULTS: Totally, 711 family members/partners (mean age=58.7 y, SD=12.5; females=81.3%) of patients (mean age=81.6, SD=9.6; females=66.9) with dementia completed the FROM-16. The FROM-16 mean total score was 17.5 (SD=6.8), meaning "a very large effect" on QoL of family members, with females being more adversely impacted. CONCLUSIONS: Dementia profoundly impacts the QoL of family members/partners of patients. Routine use of FROM-16 could signpost provision of care support, reducing family members' burnout. Such routine data could be used in economic analysis of the burden of dementia as well as in predicting institutionalization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".