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Record W4390191838 · doi:10.1002/alz.082985

Hearing loss moderates cognitive‐motor dual‐tasking before and after combined exercise and cognitive training in older adults with mild cognitive impairment: Findings from the SYNERGIC and COMPASS‐ND studies

2023· article· en· W4390191838 on OpenAlexaffabout
Rachel Downey, Berkley Petersen, Niroshica Mohanathas, Jennifer L. Campos, Manuel Montero‐Odasso, Louis Bherer, M. Kathleen Pichora‐Fuller, Natalie A. Phillips, Karen Li

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsSimon Fraser UniversityConcordia UniversityWestern UniversityToronto Rehabilitation InstituteUniversity Health NetworkUniversité de Montréal
Fundersnot available
KeywordsHearing lossAudiologyCognitionCognitive trainingPsychomotor learningVerbal fluency testPsychologyDementiaFluencyEffects of sleep deprivation on cognitive performanceCognitive declineGaitPhysical medicine and rehabilitationMedicineNeuropsychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Age‐related hearing loss is associated with poor cognitive‐motor dual‐task performance and is a risk factor for dementia and mild cognitive impairment (MCI). Although different interventions have shown to improve dual‐task performance in older adults, it is currently unclear whether hearing ability affects training efficacy in individuals with MCI. Methods Secondary data analyses of 75 participants with MCI (Mage = 73.66 ± 6.67) who completed the Canadian Consortium on Neurodegeneration and Aging SYNERGIC and COMPASS‐ND studies. We investigated how hearing ability (normal hearing (n = 56), hearing loss (n = 19)) moderated the efficacy of a 20‐week intervention (combined exercise and cognitive training (n = 32), exercise training alone (n = 31), control (n = 12)) on single‐ and dual‐task working memory performance (serial one or seven subtractions, semantic fluency) and spatio‐temporal gait characteristics. Results At baseline, participants with hearing loss had slower gait speed and higher step time variability while concurrently completing the semantic fluency task, compared to participants with normal hearing. Participants with hearing loss also had higher accuracy on the semantic fluency and serial seven subtractions tasks while dual‐tasking, compared to participants with normal hearing. Single‐ and dual‐task gait speed increased significantly following combined exercise and cognitive training, with greater improvements observed in participants with hearing loss compared to those with normal hearing. However, older adults with hearing loss showed a significant decrease in dual‐task serial seven subtractions and semantic fluency following combined exercise and cognitive training. Conclusion These findings help clarify the relationship between hearing loss, cognition, and mobility in old age and inform training recommendations for persons with MCI based on hearing ability. Combined exercise and cognitive training appears to have increased attentional and physical resources, allowing participants with hearing loss to shift postural prioritization strategies while dual‐tasking from a posture‐second strategy to a posture‐first strategy. Thus, combined exercise and cognitive training may be particularly beneficial for older adults with both MCI and hearing loss, in order to improve safe walking behaviours while multi‐tasking and mitigate further decline.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.282
Teacher spread0.248 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

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