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Record W4387818152 · doi:10.1186/s12883-023-03405-1

At-home computerized executive-function training to improve cognition and mobility in normal-hearing adults and older hearing aid users: a multi-centre, single-blinded randomized controlled trial

2023· article· en· W4387818152 on OpenAlexafffundabout
Rachel Downey, Nathan Gagné, Niroshica Mohanathas, Jennifer L. Campos, Kathleen M. Pichora-Fuller, Louis Bherer, Maxime Lussier, Natalie A. Phillips, Walter Wittich, Nancy St-Onge, Jean‐Pierre Gagné, Karen Li

Bibliographic record

VenueBMC Neurology · 2023
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversité de MontréalInstitut universitaire de cardiologie et de pneumologie de QuébecInstitut Universitaire de Gériatrie de MontréalMontreal Heart InstituteToronto Rehabilitation InstituteUniversity of TorontoUniversity Health NetworkConcordia University
FundersCanadian Institutes of Health Research
KeywordsCognitive trainingCognitionHearing aidHearing lossActive listeningAudiologyRandomized controlled trialMedicinePopulationPhysical medicine and rehabilitationCognitive declineExecutive functionsCognitive skillPsychologyPsychiatryDementia

Abstract

fetched live from OpenAlex

BACKGROUND: Hearing loss predicts cognitive decline and falls risk. It has been argued that degraded hearing makes listening effortful, causing competition for higher-level cognitive resources needed for secondary cognitive or motor tasks. Therefore, executive function training has the potential to improve cognitive performance, in turn improving mobility, especially when older adults with hearing loss are engaged in effortful listening. Moreover, research using mobile neuroimaging and ecologically valid measures of cognition and mobility in this population is limited. The objective of this research is to examine the effect of at-home cognitive training on dual-task performance using laboratory and simulated real-world conditions in normal-hearing adults and older hearing aid users. We hypothesize that executive function training will lead to greater improvements in cognitive-motor dual-task performance compared to a wait-list control group. We also hypothesize that executive function training will lead to the largest dual-task improvements in older hearing aid users, followed by normal-hearing older adults, and then middle-aged adults. METHODS: A multi-site (Concordia University and KITE-Toronto Rehabilitation Institute, University Health Network) single-blinded randomized controlled trial will be conducted whereby participants are randomized to either 12 weeks of at-home computerized executive function training or a wait-list control. Participants will consist of normal-hearing middle-aged adults (45-60 years old) and older adults (65-80 years old), as well as older hearing aid users (65-80 years old, ≥ 6 months hearing aid experience). Separate samples will undergo the same training protocol and the same pre- and post-evaluations of cognition, hearing, and mobility across sites. The primary dual-task outcome measures will involve either static balance (KITE site) or treadmill walking (Concordia site) with a secondary auditory-cognitive task. Dual-task performance will be assessed in an immersive virtual reality environment in KITE's StreetLab and brain activity will be measured using functional near infrared spectroscopy at Concordia's PERFORM Centre. DISCUSSION: This research will establish the efficacy of an at-home cognitive training program on complex auditory and motor functioning under laboratory and simulated real-world conditions. This will contribute to rehabilitation strategies in order to mitigate or prevent physical and cognitive decline in older adults with hearing loss. TRIAL REGISTRATION: Identifier: NCT05418998. https://clinicaltrials.gov/ct2/show/NCT05418998.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.067
GPT teacher head0.291
Teacher spread0.224 · 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 designRandomized 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

Citations7
Published2023
Admission routes3
Has abstractyes

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