与泰国中年人和老年人使用移动医疗相关的因素:横断面研究

IF 2.6 Q2 HEALTH CARE SCIENCES & SERVICES
JMIR Human Factors Pub Date : 2025-03-07 DOI:10.2196/63607
Nida Buawangpong, Wachiranun Sirikul, Penprapa Siviroj
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引用次数: 0

摘要

背景:移动医疗(mHealth)应用程序作为互联网医疗保健的重要组成部分正在全球兴起,但存在问题,特别是在老年人中。目的:我们的目的是调查影响使用(ITU)移动健康应用程序意向的因素,重点关注那些有和没有移动健康经验的人。方法:一项横断面研究于2022年8月至2023年7月进行,包括45岁或以上的泰国公民。自我报告的问卷收集了社会人口统计信息、健康状况、智能手机或平板电脑拥有量以及移动健康使用体验等数据。泰国移动医疗高级技术接受模型问卷采用10分李克特量表评估移动医疗接受度。对2个亚组进行多变量logistic回归分析,对年龄、性别、教育程度、收入和居住面积进行调整:使用ITU移动健康应用程序的和未使用移动健康应用程序的。结果:在1100名参与者中,537人(48.8%)打算使用移动健康应用程序,而563人(51.2%)不打算使用。与那些不打算使用移动健康应用程序的人相比,国际电信联盟的人群平均年龄更年轻,受教育程度更高,收入更高,潜在疾病更少。对于那些从未使用过移动健康应用程序的人来说,拥有智能手机与ITU(调整优势比2.81,95% CI 1.6至4.93;结论:在经验不足的用户中,对移动健康的积极态度显著提高了ITU。相反,患有潜在疾病的人减少了ITU,这表明需要量身定制的移动健康应用程序。对于经验丰富的用户来说,在易用性和老年技术焦虑等方面的接受程度至关重要。未来的研究应该探索具体的移动健康应用程序,以获得更有针对性的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors Associated With the Intention to Use mHealth Among Thai Middle-Aged Adults and Older Adults: Cross-Sectional Study.

Background: Mobile health care (mHealth) apps are emerging worldwide as a vital component of internet health care, but there are issues, especially among older adults.

Objective: We aim to investigate the factors influencing the intention to use (ITU) mHealth apps, focusing on those with and without prior mHealth experience.

Methods: A cross-sectional study conducted from August 2022 to July 2023 included Thai citizens aged 45 years or older. Self-reported questionnaires collected data on sociodemographic information, health conditions, smartphone or tablet ownership, and mHealth usage experience. The Thai mHealth Senior Technology Acceptance Model questionnaires with a 10-point Likert scale evaluated mHealth acceptance. A multivariable logistic regression analysis, adjusted for age, gender, education, income, and living area, was performed for 2 subgroups: those who used ITU mHealth apps and those who did not.

Results: Of 1100 participants, 537 (48.8%) intended to use mHealth apps, while 563 (51.2%) did not. The ITU group had a younger average age, higher education levels, higher income, and fewer underlying diseases compared to those who did not intend to use mHealth apps. For those who had never used mHealth apps, having a smartphone was strongly associated with higher odds of ITU (adjusted odds ratio 2.81, 95% CI 1.6 to 4.93; P<.001), while having any underlying disease was associated with lower odds of ITU (adjusted odds ratio 0.63, 95% CI 0.42 to 0.97; P=.034). Higher acceptance levels, characterized by a positive attitude toward mHealth and lower fear of making mistakes, were also associated with higher ITU. For those with prior mHealth experience, acceptance in areas such as perceived ease of use, gerontechnology anxiety, and facilitating conditions was significantly associated with ITU.

Conclusions: Among inexperienced users, a positive attitude toward mHealth significantly enhanced ITU. Conversely, having an underlying disease decreased ITU, indicating a need for tailored mHealth apps. For experienced users, acceptance levels in areas such as ease of use and gerontechnology anxiety were crucial. Future research should explore specific mHealth apps for more targeted insights.

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来源期刊
JMIR Human Factors
JMIR Human Factors Medicine-Health Informatics
CiteScore
3.40
自引率
3.70%
发文量
123
审稿时长
12 weeks
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