The Course of Quality of Life and Its Predictors in Nursing Home Residents With Young-Onset Dementia
Bibliographic record
Abstract
OBJECTIVE: To explore the course of quality of life (QoL) and possible resident-related predictors associated with this course in institutionalized people with young-onset dementia (YOD). DESIGN: An observational longitudinal study. SETTING AND PARTICIPANTS: A total of 278 residents with YOD were recruited from 13 YOD special care units in the Netherlands. METHODS: Secondary analyses were conducted with longitudinal data from the Behavior and Evolution in Young-ONset Dementia (BEYOND)-II study. QoL was assessed with proxy ratings, using the Quality of Life in Dementia (QUALIDEM) questionnaire at 4 assessment points over 18 months. Predictors included age, gender, dementia subtype, length of stay, dementia severity, neuropsychiatric symptoms, and psychotropic drug use at baseline. Multilevel modeling was used to adjust for the correlation of measurements within residents and clustering of residents within nursing homes. RESULTS: The total QUALIDEM score (range: 0-111) decreased over 18 months with a small change of 0.65 (95% confidence interval -1.27, -0.04) points per 6 months. An increase in several domains of QoL regarding care relationship, positive self-image, and feeling at home was seen over time, whereas a decline was observed in the subscales positive affect, social relations, and having something to do. Residents with higher levels of QoL and more advanced dementia at baseline showed a more progressive decline in QoL over time. Sensitivity analyses indicated a more progressive decline in QoL for residents who died during the follow-up. CONCLUSION AND IMPLICATIONS: This study shows that although overall QoL in nursing home residents with YOD was relatively stable over 18 months, there were multidirectional changes in the QoL subscales that could be clinically relevant. Higher levels of QoL and more advanced stages of dementia at baseline predicted a more progressive decline in QoL over time. More longitudinal studies are needed to verify factors influencing QoL in YOD.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".