P1‐545: INCREASED POSITIVE AFFECT AND LIFE ENGAGEMENT AS A RESULT OF MONTESSORI PROGRAMMING
Bibliographic record
Abstract
Montessori for Aging and Dementia, extends the tenets of person-centered care by focusing on the abilities, needs, and interests of persons with dementia in a supportive environment. The steps of staff education, implementation and evaluation of a Montessori program that focused on engaging elders with dementia in previous life roles, while providing environmental supports according to the Montessori philosophy will be described. The purpose of this study was to evaluate the impact of Montessori programming in one care area and document the process for replication throughout the care community. A pre-post quasi experimental descriptive study was conducted with 29 elders in the intervention community. The mean age of participants was 89.52 years (SD = 7.17); participants scored M = 9.86 ( SD = 5.71, range = 2 – 25) on the Montreal Cognitive Assessment. The Montessori program was implemented over the course of 1 year via online and in-person didactic sessions, environmental modifications and weekly coaching calls. Outcome measures included number of responsive behaviors, falls, medications and hospitalizations; attitude and attention according to the Observational Measure of Engagement; the Observed Emotion Rating Scale; the Cohen-Mansfield Agitation Inventory; and the Dementia Quality of Life Scale. A treatment fidelity measure was developed to record the frequency of the program standards in place before and after the program was implemented. Three standards areas were assessed: Leadership (7 features), Staff (9 features) and Prepared Environment (6 features), for a total of 88 required components of a fully implemented program. At pre-test the community demonstrated 30% of the required features across the 3 standards areas. At the 1 year post-assessment, the community demonstrated a significant improvement in the required components of the program, 69%. At pretest, participants had no roles in caring for the community. As a result of Montessori implementation, more than half of the participants were engaging in one to two roles a day. Participants displayed significantly more positive emotions from pre-implementation (M=3.35, SD =1.04) to post-implementation (M=3.97, SD=.76); t(28)=-2.83, p = .009. No other statistically significant relationships were noted.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".