A longitudinal study of care‐recipient relationship type on the quality of life in community‐dwelling older adults with dementia
Bibliographic record
Abstract
Abstract Background With the prolongation of the human lifespan, dementia has become a significant public health issue. In 2050, the number of people living with dementia (PLWD) globally is projected to increase from 50 million in 2018 to 152 million ‐ a 204% increase1. Without a cure or effective treatment for these diseases, maintaining the quality of life (QoL) of PLWD has been identified as the primary goal of care services. In the current study, we used five rounds of National Health and Aging Trends Study (NHATS) data (Round 5 to Round 9) to evaluate how the care‐recipient relationship type influences changes in QoL of PLWD over time. Method This was a secondary analysis of longitudinal data. Older adults were categorized into different groups by the type of relationship: (1) spouse/partner; (2) adult child; (3) informal caregiver other than spouse/partner and adult child, such as child‐in‐law, sibling, friend, etc.; (4) If older adults indicated having multiple caregivers, they were assigned to the group of “multiple caregivers.” QoL was assessed in 4 domains: mental health (assessed by Patient Health Questionnaire for Depression and Anxiety, PHQ‐4), self‐reported physical health, pain (Yes/No) and functional limitations (i.e. number of ADLs assistance). Backward and forward stepwise regressions were used to determine the prediction of older adults’ socio‐demographics (age, sex, race, income, education, marital status, living arrangement) and dementia status (probable dementia, possible dementia, and no dementia) on their QoL over 4 years; the generalized estimating equation (GEE) approach was used to examine the prediction of relationship type on QoL across the 4 years. Result Older adults cared for by an adult‐child or multiple caregivers predicted increased risk for functional limitations after adjustment for their socio‐demographic and dementia status. The interaction between the type of relationship and education was significant, indicating that the effect of relationship types on functional limitations is not uniform across education levels. Conclusion The relationship type between care recipients and caregivers is linked to QoL changes, particularly with functional limitations in PLWD. Socio‐demographics such as education attainment might shape the influence of care‐recipient relationship type on changes in functional limitations over time.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".