scholarly journals The impact of cognitive training and mental stimulation on cognitive and everyday functioning of healthy older adults: A systematic review and meta-analysis

2014 ◽  
Vol 15 ◽  
pp. 28-43 ◽  
Author(s):  
Michelle E. Kelly ◽  
David Loughrey ◽  
Brian A. Lawlor ◽  
Ian H. Robertson ◽  
Cathal Walsh ◽  
...  
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Cognitive Training ◽  
Meta Analysis ◽  
Everyday Functioning ◽  
Healthy Older Adults ◽  
Mental Stimulation ◽  
The Impact

scholarly journals The Impact of Protein Supplementation on Appetite and Energy Intake in Healthy Older Adults: A Systematic Review with Meta-Analysis

2020 ◽  
Author(s):  
Sana Ben-Harchache ◽  
Helen M Roche ◽  
Clare A Corish ◽  
Katy M Horner
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Longitudinal Studies ◽  
Energy Intake ◽  
Energy Content ◽  
Meta Analysis ◽  
Protein Supplementation ◽  
Cochrane Library ◽  
Healthy Older Adults ◽  
The Impact

ABSTRACT Protein supplementation is an attractive strategy to prevent loss of muscle mass in older adults. However, it could be counterproductive due to adverse effects on appetite. This systematic review and meta-analysis aimed to determine the effects of protein supplementation on appetite and/or energy intake (EI) in healthy older adults. MEDLINE, The Cochrane Library, CINAHL, and Web of Science were searched up to June 2020. Acute and longitudinal studies in healthy adults ≥60 y of age that reported effects of protein supplementation (through supplements or whole foods) compared with control and/or preintervention (for longitudinal studies) on appetite ratings, appetite-related peptides, and/or EI were included. Random-effects model meta-analysis was performed on EI, with other outcomes qualitatively reviewed. Twenty-two studies (9 acute, 13 longitudinal) were included, involving 857 participants (331 males, 526 females). In acute studies (n = 8), appetite ratings were suppressed in 7 out of 24 protein arms. For acute studies reporting EI (n = 7, n = 22 protein arms), test meal EI was reduced following protein preload compared with control [mean difference (MD): −164 kJ; 95% CI: −299, −29 kJ; P  = 0.02]. However, when energy content of the supplement was accounted for, total EI was greater with protein compared with control (MD: 649 kJ; 95% CI: 438, 861 kJ; P < 0.00001). Longitudinal studies (n = 12 protein arms) showed a higher protein intake (MD: 0.29 g ⋅ kg−1 ⋅ d−1; 95% CI: 0.14, 0.45 g ⋅ kg−1 ⋅ d−1; P < 0.001) and no difference in daily EI between protein and control groups at the end of trials (MD: −54 kJ/d; 95% CI: −300, 193 kJ/d; P  = 0.67). While appetite ratings may be suppressed with acute protein supplementation, there is either a positive effect or no effect on total EI in acute and longitudinal studies, respectively. Therefore, protein supplementation may represent an effective solution to increase protein intakes in healthy older adults without compromising EI through appetite suppression. This trial was registered at PROSPERO as https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019125771 (CRD42019125771).

The impact of exercise on the cognitive functioning of healthy older adults: A systematic review and meta-analysis

2014 ◽  
Vol 16 ◽  
pp. 12-31 ◽  
Author(s):  
Michelle E. Kelly ◽  
David Loughrey ◽  
Brian A. Lawlor ◽  
Ian H. Robertson ◽  
Cathal Walsh ◽  
...  
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Cognitive Functioning ◽  
Meta Analysis ◽  
Healthy Older Adults ◽  
The Impact

The impact of memory-strategy training interventions on participant-reported outcomes in healthy older adults: A systematic review and meta-analysis.

2019 ◽  
Vol 34 (4) ◽  
pp. 587-597 ◽  
Author(s):  
Rebecca Hudes ◽  
Jill B. Rich ◽  
Angela K. Troyer ◽  
Iris Yusupov ◽  
Susan Vandermorris
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Meta Analysis ◽  
Strategy Training ◽  
Healthy Older Adults ◽  
Training Interventions ◽  
Memory Strategy ◽  
The Impact

scholarly journals Repetition Priming in Individuals with Amnestic Mild Cognitive Impairment and Alzheimer’s Dementia: a Systematic Review and Meta-Analysis

2021 ◽  
Author(s):  
Liselotte De Wit ◽  
Vitoria Piai ◽  
Pilar Thangwaritorn ◽  
Brynn Johnson ◽  
Deirdre O’Shea ◽  
...  
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Repetition Priming ◽  
Meta Analysis ◽  
Healthy Older Adults ◽  
Amnestic Mci ◽  
Standard Mean Difference ◽  
Priming Paradigm

AbstractThe literature on repetition priming in Alzheimer’s disease (AD) is inconsistent, with some findings supporting spared priming while others do not. Several factors may explain these inconsistencies, including AD severity (e.g., dementia vs. Mild Cognitive Impairment; MCI) and priming paradigm-related characteristics. This systematic review and meta-analysis provides a quantitative summary of repetition priming in AD. We examined the between-group standard mean difference comparing repetition priming in AD dementia or amnestic MCI (aMCI; presumably due to AD) to controls. Thirty-two studies were selected, including 590 individuals with AD dementia, 267 individuals with amnestic MCI, and 703 controls. Our results indicated that both individuals with aMCI and AD dementia perform worse on repetition priming tasks than cognitively older adults. Paradigm-related moderators suggested that the effect size between studies comparing the combined aMCI or AD dementia group to cognitively healthy older adults was the highest for paradigms that required participants to produce, rather than identify, primes during the test phase. Our results further suggested that priming in AD is impaired for both conceptual and perceptual priming tasks. Lastly, while our results suggested that priming in AD is impaired for priming tasks that require deep processing, we were unable to draw firm conclusions about whether priming is less impaired in aMCI or AD dementia for paradigms that require shallow processing.

Influential Factors for Older Users’ Acceptance of eHealth Services: an Integrated Acceptance Framework (IAF) (Preprint)

2021 ◽  
Author(s):  
Jiyeon Yu ◽  
Angelica de Antonio ◽  
Elena Villalba-Mora
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
New Technologies ◽  
Meta Analysis ◽  
Health Condition ◽  
Influential Factors ◽  
Current Status ◽  
Five Dimensions ◽  
The Impact ◽  
Acceptance Factors

BACKGROUND eHealth and Telehealth play a crucial role in assisting older adults who visit hospitals frequently or who live in nursing homes and can benefit from staying at home while being cared for. Adapting to new technologies can be difficult for older people. Thus, to better apply these technologies to older adults’ lives, many studies have analyzed acceptance factors for this particular population. However, there is not yet a consensual framework to be used in further development and the search for solutions. OBJECTIVE This paper presents an Integrated Acceptance Framework (IAF) for the older user’s acceptance of eHealth, based on 43 studies selected through a systematic review. METHODS We conducted a four-step study. First, through a systematic review from 2010 to 2020 in the field of eHealth, the acceptance factors and basic data for analysis were extracted. Second, we carried out a thematic analysis to group the factors into themes to propose and integrated framework for acceptance. Third, we defined a metric to evaluate the impact of the factors addressed in the studies. Last, the differences amongst the important IAF factors were analyzed, according to the participants’ health conditions, verification time, and year. RESULTS Through the systematic review, 731 studies were founded in 5 major databases, resulting in 43 selected studies using the PRISMA methodology. First, the research methods and the acceptance factors for eHealth were compared and analyzed, extracting a total of 105 acceptance factors, which were grouped later, resulting in the Integrated Acceptance Framework. Five dimensions (i.e., personal, user-technology relational, technological, service-related, environmental) emerged with a total of 23 factors. Also, we assessed the quality of the evidence. And then, we conducted a stratification analysis to reveal the more appropriate factors depending on the health condition and the assessment time. Finally, we assess which are the factors and dimensions that are recently becoming more important. CONCLUSIONS The result of this investigation is a framework for conducting research on eHealth acceptance. To elaborately analyze the impact of the factors of the proposed framework, the criteria for evaluating the evidence from the studies that have extracted factors are presented. Through this process, the impact of each factor in the IAF has been presented, in addition to the framework proposal. Moreover, a meta-analysis of the current status of research is presented, highlighting the areas where specific measures are needed to facilitate e-Health acceptance.

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