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Record W2897526455 · doi:10.1016/j.jalz.2018.06.1339

P2‐643: ACTION SENIORS! PROMOTING EXECUTIVE FUNCTIONS WITH EXERCISE TO PREVENT FALLS IN AT‐RISK OLDER ADULTS

2018· article· en· W2897526455 on OpenAlexaff
Teresa Liu‐Ambrose, Jennifer Davis, John R. Best, Wency Chan, Winnie Cheung, Chun Liang Hsu, K Veselý, Larry Dian, Karim Miran-Khan

Bibliographic record

VenueAlzheimer s & Dementia · 2018
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsPositive Living Society of British ColumbiaOkanagan University CollegeVancouver Coastal HealthUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaBritish Columbia Centre of Excellence for Women's Health
Fundersnot available
KeywordsDigit symbol substitution testMedicineRandomized controlled trialPhysical therapyFalls in older adultsPoison controlGrip strengthGerontologyInjury preventionInternal medicineEmergency medicinePlacebo

Abstract

fetched live from OpenAlex

Impaired executive function is an established risk factor for falls. We tested whether exercise-induced improvements in executive function mediate the efficacy of exercise on falls reduction in older adults. A 12-month randomized controlled trial of 344 adults, aged 70 years and older, with ≥ 1 fall resulting in medical attention in the previous 12 months. Participants were randomized to Exercise (EX) or Guideline Care (CON). Falls were tracked prospectively. Participants in the EX group received the Otago Exercise Program, a home-based exercise program. All participants received American Geriatric Society Guideline Care for falls prevention provided by a geriatrician. Differences in falls incidence was tested with a negative binomial regression model and the effects on changes in digit symbol substitution test (DSST) were tested using a linear mixed model. Formal mediation – whether changes in DSST mediated the association between EX and falls – was tested using robust standard errors and 1000 draws to construct the 95% confidence intervals. We included 331 of 344 participants in this preliminary analysis (CON: n = 166; EX: n = 165). Groups were well balanced on age (81.9 [SD = 6.0] versus 81.3 [6.1], respectively) and sex (69% female versus 64% male, respectively). Individuals in the EX group experienced 33% fewer falls than the CON group (incident rate ratio = 0.67, 95% CI: 0.50, 0.91, p = .01; Figure 1). The EX group also improved in DSST scores at trial completion compared with the CON group (between-group difference = 1.11, 95% CI: 0.05, 2.18, p = .04; Figure 2). We observed evidence that EX-induced reductions in falls were mediated by changes in DSST. Specifically, improvements in DSST predicted fewer number of falls (estimate = -3.25, 95% CI: -5.64, -0.85, p = .008), and accounting for changes in DSST performance reduced the effect of EX on number of falls from -0.66 (total effect) to -0.59 (direct effect). This indicates that 10% of the effect of EX on falls reduction can be explained by improvements in DSST. Falls Observed over 12 Months. Change in DSST by Experimental Group. Improved executive function is a mechanism by which exercise reduces falls among at-risk older adults.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0450.003

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.

Opus teacher head0.013
GPT teacher head0.274
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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