WeChat Mini Program
Old Version Features

上海市闵行区居家老年人身体功能状况调查及养老服务需求分析

Chinese Primary Health Care(2019)

Cited 2|Views29
Abstract
目的 调查上海市闵行区居家老年人的身体功能状况和生存质量,分析居家老年人养老服务需求,为满足居家老年人的照护和健康需求提出建议.方法 采用ADL量表、SF-12量表和自行设计的问卷,对闵行区902名60岁以上居家老年人的身体功能、生存质量和养老需求进行面对面调查.结果 902名居家老年人中,86.6%的老年人日常生活活动能力良好,11.7%的老年人有轻度功能障碍,1.6%的老年人有中度以上功能障碍.年龄、婚姻状况、是否患高血压和是否患糖尿病是居家老年人生理健康和心理健康的共同影响因素;居家养老的老年人目前获取社区养老服务的比例相对较低,环境打扫在居家老年人最希望获取服务中选择的比例最高.结论 闵行区居家老年人面临社区养老资源发掘不足、缺乏专业化的养老服务供给等问题,应通过完善市场机制,激活社区资本的参与,发展嵌入式养老模式,改善居家养老服务的社会环境,提升居家老年人的健康服务水平,推动健康老龄化.
More
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
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined