The Use of a Simulated Environment (Easy Street) to Retrain Independent Living Skills in Elderly Persons: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Older adults who receive training for functional skills in contextually appropriate environments may show greater functional improvement than persons trained in a traditional environment. Functionally limited older adults receiving training in contextually appropriate environments (simulated home and community settings) may show greater improvement in activities of daily living (ADL) than persons trained in a traditional manner. METHODS: Eighty-eight patients from a day hospital, aged 65 years or older, were randomized to either receive rehabilitation in a simulated environment (Easy Street) or in a gymnasium setting. Rehabilitation focused on retraining functional skills in a contextually appropriate environment (Easy Street) or in a traditional setting (gymnasium) using motor learning principles for a period of 16 weeks. Outcome measures included the Structured Assessment of Instrumental Living Skills (SAILS), a performance measure with criterion and timed components; a self-report health status questionnaire, the Short Form-36 (SF-36); and the patient-orientated goal-directed Canadian Occupational Performance Measure (COPM). RESULTS: There were no group differences on any of the outcome measures: SAILS (p = .3); the SF-36 physical (p = .83) and mental (p = .51); and the COPM performance scale (p = .94) and satisfaction scale (p = .40). CONCLUSIONS: Although we have not excluded benefits of contextually appropriate rehabilitation environments with different intervention approaches, at different stages of rehabilitation or with patients at higher functional levels, our results suggest the appropriateness of a moratorium on these expensive interventions pending demonstration of clear positive effects determined from further study.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| 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 | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".