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Record W4404162857 · doi:10.1016/j.exger.2024.112628

Effects of home-based exercise alone or combined with cognitive training on cognition in community-dwelling older adults: A randomized clinical trial

2024· article· en· W4404162857 on OpenAlexafffund
Emma Gabrielle Dupuy, Florent Besnier, Christine Gagnon, Thomas Vincent, Tudor Vrinceanu, Caroll‐Ann Blanchette, Juliana Breton, Kathia Saillant, Josep Iglésies, Sylvie Belleville, Martin Juneau, Paolo Vitali, Anil Nigam, Mathieu Gayda, Louis Bherer

Bibliographic record

VenueExperimental Gerontology · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsDouglas Mental Health University InstituteInstitut Universitaire de Gériatrie de MontréalUniversité du Québec à MontréalMontreal Heart Institute
FundersFondation Mirella et Lino SaputoFondation Institut de Cardiologie de MontréalUniversité de Montréal
KeywordsCognitionRandomized controlled trialCognitive trainingPhysical medicine and rehabilitationGerontologyPhysical therapyMedicineTraining (meteorology)PsychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Structured and supervised physical exercise and cognitive training are two efficient ways to enhance cognition in older adults. Performing both within a combined intervention could maximize their effect on cognition due to their potential synergy on brain functions. During the COVID-19 pandemic, these interventions were particularly relevant due to the collateral impact of social restrictions regarding physical activity and the level of cognitive stimulation. However, the benefits of remotely monitored intervention combining physical exercise and cognitive training for older adult cognition remain to be demonstrated. 127 older adults (age: 65.20 ± 7.95) were randomized in two arms, encouraging self-engagement in six months of home-based physical exercise alone or combined with cognitive training, monitored by phone once a week. Neuropsychological assessment was performed under videoconference supervision at baseline and after three and six months. Composite Z -scores were calculated for processing speed, executive functioning, working, and episodic memory to assess changes after three and six months of training. The weekly metabolic expenditure of self-reported activities was estimated using the compendium of physical activity to distinguish participants performing higher and lower doses of exercise (median split). 106 participants (83.46 %) completed the 6-month training. Results showed a greater Z -score change in executive functioning for participants in the combined arm than those who only exercised (F = 4.127, p = 0.046, η p 2 = 0.050). Group x Exercise dose interaction was observed for episodic memory Z-score change (F = 6.736, p = 0.011, η p 2 = 0.070), with a greater improvement for participants performing higher doses of exercise compared to those who performed a lower dose, only in exercise alone arm. Performing a higher dose of exercise increased the working memory Z -score change in both intervention arms compared to a lower dose (F = 7.391, p = 0.008, η p 2 = 0.076). Remote combined training may lead to larger improvement in executive functioning than exercise alone. Physical exercise showed a dose-related improvement in working and episodic memory performances. The combination of cognitive interventions mitigated the effects of exercise on episodic memory. These results suggest that home-based exercise and cognitive training may help improve older adults' cognition. COVEPIC was retrospectively registered on December 03, 2020. Clinical trials Identifier: NCT04635462 - https://clinicaltrials.gov/ct2/show/record/NCT04635462?term=NCT04635462&draw=2&rank=1 • Combining cognitive training with exercise may improve executive functioning and episodic memory in older adults • A higher dose of exercise is associated with increased benefits in working and episodic memory for older adults • Home-based intervention, including exercise and cognitive training remotely monitored once a week, is likely to support older adults cognition

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)0.001
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 score0.098
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.401
Teacher spread0.347 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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