scholarly journals Letter to the Editor: Relations between subjective well-being and Alzheimer's disease: a systematic review

2020 ◽  
Vol 14 (4) ◽  
pp. 440-441
Author(s):  
Vitor Maia Arca ◽  
Laiza de Oliveira Lucena ◽  
Breno José Alencar Pires Barbosa ◽  
Fernanda Panage Moura ◽  
Amer Cavalheiro Hamdan
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Well Being ◽  
Subjective Well Being ◽  
Letter To The Editor

scholarly journals Relations between subjective well-being and Alzheimer’s disease: A systematic review

2020 ◽  
Vol 14 (2) ◽  
pp. 153-158 ◽  
Author(s):  
Fernanda Panage Moura ◽  
Amer Cavalheiro Hamdan
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Methodological Quality ◽  
Positive Emotions ◽  
Well Being ◽  
The Elderly ◽  
Quality Level ◽  
Subjective Well Being

ABSTRACT. Subjective Well-Being (SWB) is determined by the degree of satisfaction with one's own life and the intensity/frequency with which we experience negative and positive emotions. Current studies indicate that SWB is beneficial for health. Objective: The aim of this systematic review was to analyze the methodological quality of published articles on SWB in people with Alzheimer’s disease (AD). Methods: The keywords “Well-Being” and “Alzheimer” were used. Inclusion criteria were a) articles with a sample of the elderly population; b) empirical articles; c) articles published between 2014 and 2019. Analysis of the selected articles was performed using the Downs and Black Checklist. Results: 13 articles were selected for further analysis. The results showed that only one of the articles reached a high methodological quality level. The other articles had an average level, ranging from 46% to 67%, of total protocol compliance. Conclusion: The studies analyzed had a medium level of methodological quality. It is important to improve the methodological quality of studies on SWB in people with AD.

scholarly journals Effects of Aerobic Exercise on Cognition and Activities of Daily Living in Alzheimer’s Disease: A Systematic Review

2021 ◽  
Author(s):  
Vívian Maria Gomes de Oliveira ◽  
Cíntia Gonçalves Nogueira ◽  
Gabriela Ferreira Paticcié ◽  
Leonardo Oliveira Silva ◽  
Igor Jacomedes de Oliveira ◽  
...  
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Activities Of Daily Living ◽  
Daily Living ◽  
Functional Neuroimaging ◽  
Neuropsychiatric Symptoms ◽  
Well Being ◽  
Response To Treatment ◽  
Alzheimer Dementia

Background: Alzheimer’s disease (AD) represents one of the main causes of cognitive and functional decline in the world. Concomitant with pharmacological treatment, the practice of aerobic exercises (AE) can help in the symptomatic control of the disease. Objectives: To evaluate the effects of AE on activities of daily living and cognition in patients with AD. Methods: A systematic review was undertaken. EMBASE, Pubmed and BVS databases were searched using the terms “Alzheimer disease”, “Alzheimer syndrome” and “Alzheimer dementia”; “aerobic” and “exercise”. The inclusion criteria were: randomized controlled trials from 2016 to 2021, English language studies and human studies. Among 854 studies found, six were included in the review. Results: The potential benefits of AE training in AD patients are: improvement of functioning, quality of life and cognitive performance; better control of neuropsychiatric symptoms and possible reduction of systemic inflammation. Conclusions: AEs are associated with cognitive and functional performance gain in AD, probably related to synaptic plasticity optimization and improvement of the feeling of well-being. Although AEs may improve cognitive and neuropsychiatric symptoms, the response to treatment is individual. Future longitudinal studies with larger cohorts and functional neuroimaging studies are required for a better understanding of the real benefit of AE in AD.

scholarly journals Exercise interventions for older adults with Alzheimer’s disease: a systematic review and meta-analysis protocol

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Julie M. Faieta ◽  
Hannes Devos ◽  
Prasanna Vaduvathiriyan ◽  
Michele K. York ◽  
Kirk I. Erickson ◽  
...  
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Older Adults ◽  
Alzheimer's Disease ◽  
Financial Burden ◽  
Meta Analysis ◽  
Well Being ◽  
Pharmacological Intervention ◽  
Exercise Interventions ◽  
Ovid Medline

Abstract Background The growing societal and economic impact of Alzheimer’s disease (AD) is further compounded by the present lack of disease-modifying interventions. Non-pharmacological intervention approaches, such as exercise, have the potential to be powerful approaches to improve or mitigate the symptoms of AD without added side effects or financial burden associated with drug therapies. Various forms and regiments of exercise (i.e., strength, aerobic, multicomponent) have been reported in the literature; however, conflicting evidence obscures clear interpretation of the value and impact of exercise as an intervention for older adults with AD. The primary objective of this review will be to evaluate the effects of exercise interventions for older adults with AD. In addition, this review will evaluate the evidence quality and synthesize the exercise training prescriptions for proper clinical practice guidelines and recommendations. Methods This systematic review and meta-analysis will be carried out by an interdisciplinary collective representing clinical and research stakeholders with diverse expertise related to neurodegenerative diseases and rehabilitation medicine. Literature sources will include the following: Embase, PsychINFO, OVID Medline, and Ovid MEDLINE(R) and Epub Ahead of Print, In-Process & Other Non-Indexed Citations and Daily. Inclusion criteria are participants with late onset AD and structured exercise interventions with prescribed duration, frequency, and intensity. The primary outcome of this study will center on improved or sustained cognitive functioning. Secondary outcomes will include institutionalization-related outcomes, ability in activities of daily living, mood and emotional well-being, quality of life, morbidity, and mortality. Analysis procedures to include measurement of bias, data synthesis, sensitivity analysis, and assessment of heterogeneity are described in this protocol. Discussion This review is anticipated to yield clinically meaningful insight on the specific value of exercise for older adults with AD. Improved understanding of diverse exercise intervention approaches and their specific impact on various health- and function-related outcomes is expected to guide clinicians to more frequently and accurately prescribe meaningful interventions for those affected by AD. Systematic review registration PROSPERO CRD42020175016.

P2-338: Subjective well-being among caregivers of elderly with Alzheimer's disease

2012 ◽  
Vol 8 (4S_Part_10) ◽  
pp. P379-P380
Author(s):  
Lais Lopes ◽  
Orestes Forlenza ◽  
Paula Nunes ◽  
Glenda Santos ◽  
Meire Cachioni
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Well Being ◽  
Subjective Well Being

Leveraging Technology in Detection of Alzheimer’s Disease: A Systematic Review (Preprint)

2019 ◽  
Author(s):  
Clemens Kruse ◽  
Britney Larson ◽  
Reagan Wilkinson ◽  
Roger Samson ◽  
Taylor Castillo
Keyword(s):  
Magnetic Resonance Imaging ◽  
United States ◽  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
The United States ◽  
Diagnostic Process ◽  
Resonance Imaging ◽  
Common Cause ◽  
Key Terms

BACKGROUND Incidence of AD continues to increase, making it the most common cause of dementia and the sixth-leading cause of death in the United States. 2018 numbers are expected to double by 2030. OBJECTIVE We examined the benefits of utilizing technology to identify and detect Alzheimer’s disease in the diagnostic process. METHODS We searched PubMed and CINAHL using key terms and filters to identify 30 articles for review. We analyzed these articles and reported them in accordance with the PRISMA guidelines. RESULTS We identified 11 technologies used in the detection of Alzheimer’s disease: 66% of which used some form of MIR. Functional, structural, and 7T magnetic resonance imaging were all used with structural being the most prevalent. CONCLUSIONS MRI is the best form of current technology being used in the detection of Alzheimer’s disease. MRI is a noninvasive approach that provides highly accurate results in the diagnostic process of Alzheimer’s disease.

scholarly journals Machine Learning for the Classification of Alzheimer’s Disease and Its Prodromal Stage Using Brain Diffusion Tensor Imaging Data: A Systematic Review

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1071
Author(s):  
Lucia Billeci ◽  
Asia Badolato ◽  
Lorenzo Bachi ◽  
Alessandro Tonacci
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Classification Problem ◽  
Computer Algorithms ◽  
Imaging Data

Alzheimer’s disease is notoriously the most common cause of dementia in the elderly, affecting an increasing number of people. Although widespread, its causes and progression modalities are complex and still not fully understood. Through neuroimaging techniques, such as diffusion Magnetic Resonance (MR), more sophisticated and specific studies of the disease can be performed, offering a valuable tool for both its diagnosis and early detection. However, processing large quantities of medical images is not an easy task, and researchers have turned their attention towards machine learning, a set of computer algorithms that automatically adapt their output towards the intended goal. In this paper, a systematic review of recent machine learning applications on diffusion tensor imaging studies of Alzheimer’s disease is presented, highlighting the fundamental aspects of each work and reporting their performance score. A few examined studies also include mild cognitive impairment in the classification problem, while others combine diffusion data with other sources, like structural magnetic resonance imaging (MRI) (multimodal analysis). The findings of the retrieved works suggest a promising role for machine learning in evaluating effective classification features, like fractional anisotropy, and in possibly performing on different image modalities with higher accuracy.

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