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Record W3048708351 · doi:10.4018/ijeach.2020070102

Impact of Attentional Loading and Task Constraints on Postural Control of Healthy Older Adults

2020· article· en· W3048708351 on OpenAlexaff
Eryk Przysucha, Brontë A. Vollebregt, Carlos Zerpa

Bibliographic record

VenueInternational Journal of Extreme Automation and Connectivity in Healthcare · 2020
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsLakehead University
Fundersnot available
KeywordsTask (project management)CognitionPsychologyBalance (ability)Cognitive psychologyPhysical medicine and rehabilitationElementary cognitive taskAttentional controlDevelopmental psychologyMedicineEngineeringPsychiatry

Abstract

fetched live from OpenAlex

Postural control is attention demanding, and it may be jeopardized when a secondary cognitive task is involved, particularly for older adults. The magnitude of this interference depends on different individual (perceptuo-motor status), task (single vs. dual tasking), and environmental constraints (support surface). The purpose of this research was to examine if older adults may be affected by various types of secondary cognitive tasks, while maintaining quiet standing on different support surfaces. In line with conceptual models, the results indicated that postural control of older adults was compromised when they were required to dual-task, especially when the support surface was challenging. This was a robust finding across all the measures of COP. In regards to the degree to which different attentional tasks affected postural control, the results remained equivocal. From a practical standpoint, the results indicated that older adults should exhibit caution when simultaneously performing a balance and a cognitive task involved particularly when the surface is unsteady.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.378
Teacher spread0.338 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2020
Admission routes1
Has abstractyes

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