Aging, the Central Nervous System, and Mobility in Older Adults: Interventions
Bibliographic record
Abstract
BACKGROUND: Research suggests that the central nervous system (CNS) and mobility are closely linked. CNS-mediated mobility impairment may represent a potentially new and prevalent syndrome within the older adult populations. Interventions targeting this group may have the potential to improve mobility and cognition and prevent disability. METHODS: In 2012, the Gerontological Society of America (GSA) and the National Institute on Aging (NIA) sponsored a 3-year conference workshop series, "Aging, the CNS, and Mobility." The goal of this third and final conference was to (i) report on the state of the science of interventions targeting CNS-mediated mobility impairment among community-dwelling older adults and (ii) partnering with the NIA, explore the future of research and intervention design focused on a potentially novel aging syndrome. RESULTS: Evidence was presented in five main intervention areas: (i) pharmacology and diet; (ii) exercise; (iii) electrical stimulation; (iv) sensory stimulation/deprivation; and (v) a combined category of multimodal interventions. Workshop participants identified important gaps in knowledge and key recommendations for future interventions related to recruitment and sample selection, intervention design, and methods to measure effectiveness. CONCLUSIONS: In order to develop effective preventive interventions for this prevalent syndrome, multidisciplinary teams are essential particularly because of the complex nature of the syndrome. Additionally, integrating innovative methods into the design of interventions may help researchers better measure complex mechanisms, and finally, the value of understanding the link between the CNS and mobility should be conveyed to researchers across disciplines in order to incorporate cognitive and mobility measurements into study protocols.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".