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评估移动健康中的用户满意度与参与度:来自综合数字健康参与模型(IDHEM)的见解。

Evaluating user satisfaction and engagement in mHealth: Insights from the Integrated Digital Health Engagement Model (IDHEM).

作者信息

Alshammari Hind Mashan, Almutairi Reem Iafi, Ghazwani Asma Yahya, Aditya Ronal Surya

机构信息

General Directorate Contact Center (GDCC) Department in Riyadh, Ministry of Health (MOH), Riyadh, Saudi Arabia.

Public Health and Health Informatics College, University of Hail, Hail, Saudi Arabia.

出版信息

Digit Health. 2025 Jul 22;11:20552076251346698. doi: 10.1177/20552076251346698. eCollection 2025 Jan-Dec.

DOI:10.1177/20552076251346698
PMID:40718399
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12290358/
Abstract

INTRODUCTION

In recent years, mobile health (mHealth) applications have revolutionized healthcare by improving accessibility, boosting patient engagement, and simplifying health management processes. However, despite their increasing popularity, there is still a significant lack of understanding regarding how demographic factors shape user perceptions and interactions with these tools.

OBJECTIVE

This research aims to assess user satisfaction and the perceived value of the Sehhaty app among residents of Hail City, Saudi Arabia, while also examining how demographic variables influence user engagement. The findings emphasize the necessity of incorporating demographic insights into the design of mHealth applications and introduce the Integrated Digital Health Engagement Model (IDHEM) as a novel theoretical framework.

METHOD

A cross-sectional study design was implemented, using an electronic survey distributed to 333 users of the Sehhaty app. The survey evaluated key aspects such as ease of use, user satisfaction, system information organization, and perceived usefulness. Convenience sampling was utilized to ensure participation from a wide range of demographic groups. Descriptive statistics and Pearson correlation analysis were conducted to explore the relationships between demographic characteristics and user perceptions.

RESULTS

The study revealed high levels of user satisfaction, with 94% of participants reporting that the app was easy to use, resulting in an overall satisfaction score of 4.56 out of 5. Significant correlations were identified between demographic factors like age, gender, and employment status, suggesting that personalized development approaches can significantly enhance user engagement.

CONCLUSION

The Sehhaty app shows great promise in enhancing healthcare access and management, especially among younger and female users. The findings underscore the importance of considering demographic factors in the design of mHealth applications to better meet diverse user needs. Additionally, this study introduces the IDHEM, providing a new framework for understanding user behavior and guiding the development of future digital health solutions.

摘要

引言

近年来,移动健康(mHealth)应用通过提高可及性、增强患者参与度以及简化健康管理流程,给医疗保健带来了变革。然而,尽管它们越来越受欢迎,但对于人口统计学因素如何塑造用户对这些工具的认知和互动,仍存在严重的理解不足。

目的

本研究旨在评估沙特阿拉伯海勒市居民对Sehhaty应用的用户满意度和感知价值,同时考察人口统计学变量如何影响用户参与度。研究结果强调了将人口统计学见解纳入移动健康应用设计的必要性,并引入了综合数字健康参与模型(IDHEM)作为一个新的理论框架。

方法

采用横断面研究设计,通过电子调查向333名Sehhaty应用的用户进行发放。该调查评估了易用性、用户满意度、系统信息组织和感知有用性等关键方面。采用便利抽样以确保广泛的人口统计学群体参与。进行描述性统计和Pearson相关性分析,以探索人口统计学特征与用户认知之间的关系。

结果

研究显示用户满意度较高,94%的参与者表示该应用易于使用,总体满意度得分为4.56(满分5分)。年龄、性别和就业状况等人口统计学因素之间存在显著相关性,表明个性化的开发方法可以显著提高用户参与度。

结论

Sehhaty应用在改善医疗保健可及性和管理方面显示出巨大潜力,尤其是在年轻用户和女性用户中。研究结果强调了在移动健康应用设计中考虑人口统计学因素以更好地满足不同用户需求的重要性。此外,本研究引入了IDHEM,为理解用户行为和指导未来数字健康解决方案的开发提供了一个新的框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/a93e0216b80b/10.1177_20552076251346698-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/9897479363a9/10.1177_20552076251346698-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/cab26d5fb3e8/10.1177_20552076251346698-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/23cf61f72bb0/10.1177_20552076251346698-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/7e71a3d63c94/10.1177_20552076251346698-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/1fefb1125a3d/10.1177_20552076251346698-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/a93e0216b80b/10.1177_20552076251346698-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/9897479363a9/10.1177_20552076251346698-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/cab26d5fb3e8/10.1177_20552076251346698-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/23cf61f72bb0/10.1177_20552076251346698-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/7e71a3d63c94/10.1177_20552076251346698-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/1fefb1125a3d/10.1177_20552076251346698-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5676/12290358/a93e0216b80b/10.1177_20552076251346698-fig6.jpg

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