A STUDY OF EVIDENCE-BASED COGNITIVE REHABILITATION PROGRAMS FOR ALZHEIMER’S DISEASE AND DEMENTIA
Bibliographic record
Abstract
The Principal Investigators of the 2017 Study, comparing the effectiveness of two cognitive rehabilitation therapies, will report the outcome of the Study. The national study examined the effectiveness of two cognitive rehabilitation therapies -- SAIDO Learning and a Language and Social Stimulation Activity -- the goal, to improve psychological symptoms (apathy and depressed mood), quality of life, and cognitive and physical functioning in persons with mild-moderate dementia. To achieve this, Eliza Jennings collaborated with the Medical Director for the Center for Rehabilitation for the internationally renowned Cleveland Clinic and a Ph.D professor of nursing and research from Case Western Reserve University to serve as Principal Investigators for the Trial. The yearlong Study was designed to study a maximum of 60 residents of long-term care and assisted living communities from nine aging services organizations across the country, with Subjects each participating in the study for a maximum of six months. The following Assessment tools were administered to Study Subjects: Mini Mental State Examination (MMSE); Montreal Cognitive Assessment (MoCA-B); Frontal Assessment Battery at Bedside (FAB); Person-Environment Apathy rating (PEAR); Dementia Quality of Life Instrument (DQoL); Geriatric Depression Scale (GDS); Activity Measure for Post-Acute Care (AMPAC); and Apathy Evaluation Scale (AES).
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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 | 0.021 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".