Case Report: Outcomes of Feldenkrais Movements on Self-reported Cognitive Decline in Older Adults.
Bibliographic record
Abstract
UNLABELLED: Context • A lack of cognitive health can limit a person's well-being and may compromise independent living. The potential for cognitive decline is a major concern for aging individuals. Regular physical activity has been shown to improve cognitive processes. However, functional limitations frequently prevent older adults from participating in conventional exercise programs. Given the gentle nature of mind-body exercises, interventions such as the Feldenkrais may provide an alternative. Objective • The study intended to investigate whether Feldenkrais lessons can offset cognitive decline among older adults. DESIGN: The study was a case series with 2 participants. Setting • The study took place in the wellness center of a retirement community. Participants • Participants were 2 female residents in the community, with self-reported cognitive challenges. Intervention • The Feldenkrais method awareness through movement (ATM) was used. The lessons were based on common Feldenkrais themes, such as the relationship between eye organization and body movement, coordination of muscles, breathing, and an exploration of the participants' habits. Outcome Measures • The Trail Making Test A (TMT-A) and Trail Making Tests B (TMT-B) were used to measure cognitive function at baseline and after the Feldenkrais intervention. Results • Both participants improved their performance on the TMT-A and TMT-B after completing the Feldenkrais intervention. Neither of the 2 participants reported any adverse events related to the lessons. Conclusion • The beneficial results warrant further research into the efficacy of Feldenkrais as complementary, alternative therapy for preserving cognitive function on a larger scale and in populations with diagnosed cognitive impairments.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".