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Record W7000114949

The effects of a multimodal exercise program plus brain games apps in cognitive parameters of nursing home residents

2019· article· en· W7000114949 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology Use by Older Adults
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionIntervention (counseling)Psychological interventionPerceptionNursing homesCognitive trainingExecutive functionsCognitive decline
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION The aging process leads to inevitable life changes and is characterized by a progressive loss of psychological and physiological functions (1). Often, these changes lead to institutionalization, where cognition and physical fitness tends to decline (2). Some studies have shown that multimodal exercise programs can have a broad impact in older adults, improving a number of cognitive and physical functions, including executive functioning, speed of behavior and balance (3). Also, in recent years there has been a growing interest in the use of digital technological devices for promoting specific competencies in the elderly. For instance, video games improve perceptual speed measures (4), memory, executive function, visuospatial abilities, vigilance, and reasoning abilities (5). Several studies used video games, but studies with tablet computers are not common. Moreover, to the best of our knowledge, few studies on the effects of multimodal exercise interventions have focused on nursing home residents. Therefore, the main objective of this pilot study is to examine the effects of an intervention designed for nursing home residents that include both a multimodal exercise component and a videogame component (brain games apps). METHODS Twelve older women and men were selected by convenience among a nursing home residence. Participants served as their own controls. During the first 4 weeks (control period), the participants continued with their normal daily life activities. After the control period, the group engaged in an intervention program for 6 weeks. The intervention program consisted of a multimodal exercise program (2 times per week) plus selected brain games played on a tablet computer (2 times per week). The 4 exercise sessions per week were alternated between multimodal exercise program and brain games performed on the tablet computer. Assessment of cognition was collected at three different times: prior to the control period (T0), after the control period (T1), and at the end of the intervention (T2). The 8 ft up-and-go test of the senior fitness test (6) was performed with and without a cognitive dual task (counting backward from 30). This type of assessment has been shown to be reliable and valid to establish the fall risk of healthy elderly people (7). A clinical psychologist administered the Mini-Mental State Examination (MMS) as well as the Montreal Cognitive Assessment (MOCA) questionnaire to analyze the effects of the program on immediate and short-term memory. RESULTS The intervention (multimodal exercise plus brain games apps) did not affect the ability to perform the 8 ft up-and-go test under single- and dual-task conditions (p=0.250 and p=0.375 respectively). Regarding immediate and short-term memory ability (measured by questions from the MMS and MOCA questionnaires), we found an improvement in one of the items related to short-term memory on MOCA. In this case, an increase in memory capacity was observed between T0 and T2 (p=0.033) CONCLUSIONS In this pilot study, we found a few positive changes in related cognitive variables as the result of the planned intervention. Nevertheless, the gains observed in short-term memory are encouraging. It is important that future studies test the effectiveness of engaging older adults in similar interventions using a large sample and a longer duration. This could confirm the tendencies found in the current research and prompt practitioners to use new digital technological devices for promoting specific competencies in the elderly.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.047
GPT teacher head0.409
Teacher spread0.362 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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