Mental Flexibility Influences the Association Between Poor Balance and Falls in Older People – A Secondary Analysis
Bibliographic record
Abstract
Impairments of balance predispose older people to falls. Some cognitive functions, especially executive functioning have been shown to affect balance and discriminate fallers from non-fallers. Mental flexibility is a component of the executive function and comprises multiple cognitive processes that work together to adjust the course of thoughts or actions according to the changing demands of a situation without the use of explicit instructions. However, the role of mental flexibility in balance in older people remains unclear. Mental flexibility comprises complementary cognitive functions required for dealing with unpredictable environmental demands. The study aim was to examine the relationship between mental flexibility and falls in a cohort of 212 older people (80.6 ±4.9 years; 62% female). We hypothesized that: (i) participants with impaired balance would have worse mental flexibility compared to those with good balance; and (ii) poor mental flexibility would predict falls in the sub-group with impaired balance. Balance performance was assessed by measuring postural sway while standing on a medium density foam mat with eyes open for 30 seconds. Mental flexibility was assessed using a computerized short-form of the Wisconsin Card Sorting Test (WCST; 64 cards) with its sub-components comprising general performance, perseveration, failure-to-maintain set and conceptual ability. Falls were measured prospectively for 12-months using monthly calendars. MANCOVA revealed that WCST performance was associated with balance (Wilks’ Lambda = 0.883, F=2.168; p=0.013, partial eta squared (η2p) =.061) due primarily to reduced concept formation ability (F2,207=5.787, p=0.004, η2p =.053). Negative binomial regression analysis adjusting for age, education, contrast sensitivity, proprioception, inhibition and inhibitory choice stepping reaction time revealed that lower concept formation ability was predictive for falls (Incidence Rate Ratio 1.0648 (95% confidence interval 1.0316-1.08199)). Further, lower concept formation ability partly explained the association between balance and falls: i.e. fallers in the upper balance tertile had reduced concept formation performance whereas non-fallers had similar concept formation performance across the three balance tertiles. These findings suggest that poor mental flexibility affects the ability to maintain steady balance contributing to increased risk of falls in older people.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".