在老年人中使用大语言模型的接受:基于TAM的研究
Aoqi Wang1, Meihua Piao1, You Zhou1
1School of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, No 33 Ba Da Chu Road, Shijingshan District, Beijing, 100144, China.
Studies in health technology and informatics
|July 25, 2024
概括
年龄较大的成年人.
科学领域:
- 老年学,人与计算机的交互,人工智能
背景情况:
- 老年人是日益增长的人口,数字互动需求日益增加.
- 了解技术接受对于公平获得数字工具至关重要.
研究的目的:
- 调查老年人接受大型语言模型 (LLM) 的情况.
- 根据技术接受模型 (TAM) 检查影响他们使用LLM意图的因素.
主要方法:
- 横截面调查设计. 横截面调查设计.
- 使用了技术接受模型 (TAM) 框架.
- 对调查数据进行统计分析,以确定重要因素.
主要成果:
- 主观规范,形象,职位相关性,输出质量,结果可证明性和感知到的易用性显著积极影响感知到的有用性.
- 感知到的易用性和感知到的有用性显著积极影响使用LLMs的意图.
- 所有测试的因素都显示出统计学上显著的正相关性 (P<0.05).
结论:
- 感知到的易用性和实用性是LLM在老年人中采用的关键驱动因素.
- 推量身定制的聊天机器人开发,以加强对这一群体的技术整合.
- 调查结果为开发人员和决策者提供了洞察力,以改善数字包容性.
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