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移动医疗应用的功能:用户视角。

Functions of mHealth applications: A user's perspective.

机构信息

Masaryk University, Czech Republic.

出版信息

Health Informatics J. 2019 Sep;25(3):1065-1075. doi: 10.1177/1460458217740725. Epub 2017 Nov 10.


DOI:10.1177/1460458217740725
PMID:29121831
Abstract

The usage of mobile health (mHealth) applications is rapidly increasing. This research has been aimed mostly at reviewing existing mHealth apps and their functionality. However, studies from users' perspectives are rather scarce. This exploratory study addresses that gap and, using cross-sectional survey data, seeks to reveal the socio-demographic and individual characteristics of users who utilize specific functions of mHealth apps. The data were collected via an online survey through websites oriented toward eating habits, exercising, dieting, and weight loss. From the original sample (1002 users; M = 24.8, standard deviation = 6.9; 81.6% females), the final sub-sample of 406 participants aged from 13 to 39 years (M = 23.8, standard deviation = 5.3, 86.9% females) who reported usage of mHealth apps was examined. The analyses revealed demographic and individual differences in predicting usage of various functions of mHealth apps. The drive for thinness was associated with functions for weight monitoring and planning functions. Excessive exercise was associated with weight monitoring, socializing functions, and functions for planning and monitoring goals. These findings imply that mHealth apps should be individually tailored to incorporate components such as risk-specific warnings or the provision of information related to seeking professional help for at-risk audiences.

摘要

移动健康 (mHealth) 应用的使用正在迅速增加。这项研究主要集中在回顾现有的 mHealth 应用及其功能上。然而,从用户角度进行的研究却相当匮乏。这项探索性研究弥补了这一空白,通过横断面调查数据,旨在揭示使用 mHealth 应用特定功能的用户的社会人口统计学和个体特征。数据是通过针对饮食习惯、锻炼、节食和减肥的网站进行在线调查收集的。在最初的样本(1002 名用户;M = 24.8,标准差= 6.9;81.6%女性)中,最终分析了 406 名年龄在 13 至 39 岁之间(M = 23.8,标准差= 5.3,86.9%女性)的报告使用 mHealth 应用程序的参与者子样本。分析揭示了在预测使用 mHealth 应用程序的各种功能方面存在人口统计学和个体差异。对苗条的渴望与体重监测和计划功能有关。过度运动与体重监测、社交功能以及计划和监测目标的功能有关。这些发现表明,mHealth 应用程序应该根据个人情况进行定制,以纳入针对特定风险的警告或为高风险人群提供与寻求专业帮助相关的信息等组件。

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Digit Health. 2025-7-22

[2]
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[3]
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Life (Basel). 2024-9-27

[4]
Effects of a mobile health intervention based on a multitheoretical model of health behavior change on anxiety and depression, fear of cancer progression, and quality of life in patients with differentiated thyroid cancer: A randomized controlled trial.

BMC Med. 2024-10-15

[5]
Mobile App-Based Lifestyle Coaching Intervention for Patients With Nonalcoholic Fatty Liver Disease: Randomized Controlled Trial.

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[6]
Impact of a mobile health intervention based on multi-theory model of health behavior change on self-management in patients with differentiated thyroid cancer: protocol for a randomized controlled trial.

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[7]
Mobile Technology-Based Interventions for Stroke Self-Management Support: Scoping Review.

JMIR Mhealth Uhealth. 2023-12-6

[8]
Effect of exercise intervention using mobile healthcare on blood lipid level and health-related physical fitness in obese women: a randomized controlled trial.

Phys Act Nutr. 2023-9

[9]
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J Med Internet Res. 2023-6-28

[10]
Effects of a Mobile-Health Exercise Intervention on Body Composition, Vascular Function, and Autonomic Nervous System Function in Obese Women: A Randomized Controlled Trial.

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