DOES PERSON-ENVIRONMENT FIT PLAY A ROLE ON APATHY IN LONG-TERM CARE RESIDENTS WITH DEMENTIA?
Bibliographic record
Abstract
Approximately 25–84% of nursing home residents with dementia experience apathy. Apathy is characterized by lack of motivation, lack of initiative, decreased responsiveness to environmental stimulation, and a flat mood. Apathy is associated with rapid cognitive decline, poor quality of life, and higher mortality. Lawton’s competence and environmental press model suggests that an individual’s behavior and affect are influenced by the fit of their functional abilities with the environmental demands. Yet, the relationship between environment and apathy is understudied. Therefore, this study examined the relationship between functional person-environment fit and apathy in dementia. This is a cross-sectional study using the baseline data from two trials of Function Focused Care for residents with moderate to severe cognitive impairment. The sample included 199 residents with dementia recruited from four nursing homes and four assisted living facilities. Functional person-environment fit was measured using the Enabler scale. Apathy was measured using the Apathy Evaluation Scale. Multilevel linear models were used for analysis. Participants were 84 years old on average and the majority were Caucasian female. Findings revealed that greater person-environment fit was associated with lower apathy (β=.017, P=.025). The association was not significant after controlling for age, gender, type of care setting, cognitive function, depression, agitation, and physical function. In conclusion, findings are insufficient to support the association between functional person-environment fit and apathy. Future research may further examine the impact of individual characteristics on the relationship between environment and apathy and explore the impact of social environment on apathy in dementia.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".