A LONGITUDINAL STUDY ON THE EFFECTS OF PHYSICAL ENVIRONMENT ON BEHAVIORS OF RESIDENTS WITH DEMENTIA
Bibliographic record
Abstract
The challenges in investigating the effects of the physical environment on residents with dementia include having a sample of comparable study groups and a lack of long-term follow-up evaluation. This study attempted to address these two challenges by carefully matching residents between groups in sample selection and including three points of time of evaluation in the study design. The main aim of the study is to examine whether residents with dementia living in different physical environment, focusing on large-scale institutional design and small-scale homelike environment exhibit a difference in health and behavioral outcomes. Physical environmental assessment of the two care facilities was conducted using the Therapeutic Environment Screening Survey for Nursing Homes. Behavior assessments of residents were performed using three tools at three assessments over a period of 1 year: (a) Multidimensional Observation Scale for Elderly Subjects, (b) Minimum Data Set, and (c) Dementia Care Mapping. The longitudinal results suggest that older adults with early to moderate stage dementia can be supported to become socially active and engaged with others in an optimal environment. It is possible that a small-scale, home-like unit makes it easier to socially relate with others, as fewer people in the setting are not as overwhelming or over-stimulating. A smaller home-like environment may also offer a sense of comfort, security, and belonging.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".