A Systematic Review of Non‐pharmacological Treatments for Apathy in Dementia

Christos Theleritis,Kostas Siarkos,Anastasios A. Politis,Everina Katirtzoglou,Antonios Politis

International Journal of Geriatric Psychiatry（2017）

Cited 60|Views15

Abstract

ObjectiveApathy is one of the most frequent neuropsychiatric symptoms encountered in dementia. Early diagnosis and timely treatment of apathy in dementia are crucial because apathy has been associated with poor disease outcome, reduced daily functioning, and caregiver distress. DesignExtensive electronic search from the databases included in the National Library of Medicine as well as PsychInfo and Google Scholar for studies which have investigated the effect of non-pharmacological treatments of apathy in dementia. Quality of the studies was appraised. ResultsA total of 1303 records were identified and 120 full-texts assessed. Forty-three unique studies were reviewed. A variety of interventions were found to be effective in reducing apathy in demented patients, particularly when provided in a multidisciplinary manner. However, quantification of the effect was limited by the marked methodological heterogeneity of the studies and the small number of studies where apathy was the primary outcome measure. ConclusionsTreatment of apathy in dementia is a complex and underexplored field. Certain studies suggest promise for a variety of non-pharmacological interventions. Standardized and systematic efforts primarily focusing on apathy may establish a benefit from individualized treatments for specific disease groups.

Translated text

Key words

apathy,dementia,non-pharmacological,systematic review,treatment

求助PDF

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper