Effects of language stimulation on cognition of institutionalized aged people: a preliminary case series study
Bibliographic record
Abstract
ABSTRACT. Cognitive stimulation programs for institutionalized elderly people show positive results, however few studies have investigated the effectiveness of language stimulation programs for the health of this population. Objectives: To characterize the cognitive-linguistic profile of institutionalized elderly and to compare their performance before and after a language stimulation program (LSP). Methods: An exploratory case series study was conducted with nine residents of a Home for the Aged. Elderly people aged 60 or over, of both sexes, without neurological or neuropsychiatric diseases, communication disorders, intellectual impairment or severe visual or hearing impairment were included. The participants were submitted to an initial assessment through the Montreal Cognitive Assessment (MoCA) and Montreal Toulouse Battery Language Assessment – Brazil to characterize the cognitive-linguistic profile of the studied group. Five elderly were selected to participate in the LSP, of wich only two participated effectively in the program, but all were reassessed after the program was completed. Results: on the initial assessment, of the nine participants, only one had adequate cognitive performance and all presented changes in macro and/or microlinguistics aspects of oral discourse, with oral comprehension preserved. On the reassessment carried out with five participants, only two participants who adhered effectively to the program obtained improvements in MoCa scores. In regarding language, three participants performed better in the oral emission measures. The performance of the participants in oral comprehension remained or declined. Conclusion: The speech-language therapy intervention through a LSP contributes to improving the cognitive-linguistic performance of institutionalized elderly.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".