Using the Montessori Approach for a Clientele with Cognitive Impairments: A Quasi-Experimental Study Design
Bibliographic record
Abstract
BACKGROUND: The choice of activities responding to the needs of people with moderate to severe dementia is a growing concern for care providers trying to target the need for a feeling of self-accomplishment by adapting activities to the abilities of elderly patients. The activities created by Maria Montessori seem to be adaptable to this clientele. This study evaluates the short-term effects, as compared to regular activities offered in the milieu. METHODS: This is a quasi-experimental study where each of the 14 participants was observed and filmed in two conditions: during Montessori activities, during regular activities, and one control condition (no activity). RESULTS: The results show that Montessori activities have a significant effect on affect and on participation in the activity. They support the hypothesis that when activities correspond to the needs and abilities of a person with dementia, these positive effects are also observed on behaviours. CONCLUSIONS: This study enabled its authors to corroborate the findings presented in the literature and to contribute additional elements on the positive effects of the use of Montessori activities and philosophy. Used with people with moderate to severe dementia these allow the satisfaction of their basic psychological needs, their well being, and hence, on their quality of life.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".