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Record W4387667297 · doi:10.1186/s12877-023-04390-3

Dual task measures in older adults with and without cognitive impairment: response to simultaneous cognitive-exercise training and minimal clinically important difference estimates

2023· article· en· W4387667297 on OpenAlexaboutno aff
I‐Chen Chen, I‐Ching Chuang, Ku‐Chou Chang, Chih-Hung Chang, Ching‐Yi Wu

Bibliographic record

VenueBMC Geriatrics · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersMinistry of Science and Technology, TaiwanChang Gung Medical FoundationHealthy Aging Research CenterChang Gung UniversityChang Gung Memorial Hospital
KeywordsMinimal clinically important differenceCognitionMontreal Cognitive AssessmentMedicineEffects of sleep deprivation on cognitive performanceCognitive testAudiologyPhysical therapyPhysical medicine and rehabilitationRandomized controlled trialCognitive impairmentPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Responsiveness and minimal clinically important difference (MCID) are critical indices to understand whether observed improvement represents a meaningful improvement after intervention. Although simultaneous cognitive-exercise training (SCET; e.g., performing memory tasks while cycling) has been suggested to enhance the cognitive function of older adults, responsiveness and MCID have not been established. Hence, we aimed to estimate responsiveness and MCIDs of two dual task performance involving cognition and hand function in older adults with and without cognitive impairment and to compare the differences in responsiveness and MCIDs of the two dual task performance between older adults with and without cognitive impairment. METHODS: A total of 106 older adults completed the Montreal Cognitive Assessment and two dual tasks before and after SCET. One dual task was a combination of Serial Sevens Test and Box and Block Test (BBT), and the other included frequency discrimination and BBT. We used effect size and standardized response mean to indicate responsiveness and used anchor- and distribution-based approaches to estimating MCID ranges. When conducting data analysis, all participants were classified into two cognitive groups, cognitively healthy (Montreal Cognitive Assessment ≥ 26) and cognitively impaired (Montreal Cognitive Assessment < 26) groups, based on the scores of the Montreal Cognitive Assessment before SCET. RESULTS: In the cognitively healthy group, Serial Seven Test performance when tasked with BBT and BBT performance when tasked with Serial Seven Test were responsive to SCET (effect size = 0.18-0.29; standardized response mean = 0.25-0.37). MCIDs of Serial Seven Test performance when tasked with BBT ranged 2.09-2.36, and MCIDs of BBT performance when tasked with Serial Seven Test ranged 3.77-5.85. In the cognitively impaired group, only frequency discrimination performance when tasked with BBT was responsive to SCET (effect size = 0.37; standardized response mean = 0.47). MCIDs of frequency discrimination performance when tasked with BBT ranged 1.47-2.18, and MCIDs of BBT performance when tasked with frequency discrimination ranged 1.13-7.62. CONCLUSIONS: Current findings suggest that a change in Serial Seven Test performance when tasked with BBT between 2.09 and 2.36 corrected number (correct responses - incorrect responses) should be considered a meaningful change for older adults who are cognitively healthy, and a change in frequency discrimination performance when tasked with BBT between 1.47 and 2.18 corrected number (correct responses - incorrect responses) should be considered a meaningful change for older adults who are cognitively impaired. Clinical practitioners may use these established MCIDs of dual tasks involving cognition and hand function to interpret changes following SCET for older adults with and without cognitive impairment. TRIAL REGISTRATION: NCT04689776, 30/12/2020.

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)0.003
metaresearch head score (Gemma)0.014
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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.327
Teacher spread0.299 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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