The effects of a multimodal exercise program plus brain games apps in cognitive parameters of nursing home residents
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".