Suppr超能文献

结合自我追踪和劝导式电子辅导以促进更健康生活方式的电子健康干预措施的关键组成部分:一项范围综述。

Key Components in eHealth Interventions Combining Self-Tracking and Persuasive eCoaching to Promote a Healthier Lifestyle: A Scoping Review.

作者信息

Lentferink Aniek J, Oldenhuis Hilbrand Ke, de Groot Martijn, Polstra Louis, Velthuijsen Hugo, van Gemert-Pijnen Julia Ewc

机构信息

Centre for eHealth & Wellbeing Research, Departement of Psychology, Health, and Technology, University of Twente, Enschede, Netherlands.

Marian van Os Centre for Entrepreneurship, Hanze University of Applied Sciences, Groningen, Netherlands.

出版信息

J Med Internet Res. 2017 Aug 1;19(8):e277. doi: 10.2196/jmir.7288.

Abstract

BACKGROUND

The combination of self-tracking and persuasive eCoaching in automated interventions is a new and promising approach for healthy lifestyle management.

OBJECTIVE

The aim of this study was to identify key components of self-tracking and persuasive eCoaching in automated healthy lifestyle interventions that contribute to their effectiveness on health outcomes, usability, and adherence. A secondary aim was to identify the way in which these key components should be designed to contribute to improved health outcomes, usability, and adherence.

METHODS

The scoping review methodology proposed by Arskey and O'Malley was applied. Scopus, EMBASE, PsycINFO, and PubMed were searched for publications dated from January 1, 2013 to January 31, 2016 that included (1) self-tracking, (2) persuasive eCoaching, and (3) healthy lifestyle intervention.

RESULTS

The search resulted in 32 publications, 17 of which provided results regarding the effect on health outcomes, 27 of which provided results regarding usability, and 13 of which provided results regarding adherence. Among the 32 publications, 27 described an intervention. The most commonly applied persuasive eCoaching components in the described interventions were personalization (n=24), suggestion (n=19), goal-setting (n=17), simulation (n=17), and reminders (n=15). As for self-tracking components, most interventions utilized an accelerometer to measure steps (n=11). Furthermore, the medium through which the user could access the intervention was usually a mobile phone (n=10). The following key components and their specific design seem to influence both health outcomes and usability in a positive way: reduction by setting short-term goals to eventually reach long-term goals, personalization of goals, praise messages, reminders to input self-tracking data into the technology, use of validity-tested devices, integration of self-tracking and persuasive eCoaching, and provision of face-to-face instructions during implementation. In addition, health outcomes or usability were not negatively affected when more effort was requested from participants to input data into the technology. The data extracted from the included publications provided limited ability to identify key components for adherence. However, one key component was identified for both usability and adherence, namely the provision of personalized content.

CONCLUSIONS

This scoping review provides a first overview of the key components in automated healthy lifestyle interventions combining self-tracking and persuasive eCoaching that can be utilized during the development of such interventions. Future studies should focus on the identification of key components for effects on adherence, as adherence is a prerequisite for an intervention to be effective.

摘要

背景

在自动化干预措施中,自我追踪与劝导式电子辅导相结合是一种全新且颇具前景的健康生活方式管理方法。

目的

本研究旨在确定自动化健康生活方式干预措施中自我追踪与劝导式电子辅导的关键组成部分,这些部分有助于提高干预措施对健康结果、可用性和依从性的影响。次要目的是确定应如何设计这些关键组成部分,以促进健康结果、可用性和依从性的改善。

方法

采用了Arskey和O'Malley提出的范围综述方法。在Scopus、EMBASE、PsycINFO和PubMed数据库中检索了2013年1月1日至2016年1月31日期间发表的文献,这些文献需包含:(1)自我追踪;(2)劝导式电子辅导;(3)健康生活方式干预。

结果

检索共得到32篇文献,其中17篇提供了关于对健康结果影响的结果,27篇提供了关于可用性的结果,13篇提供了关于依从性的结果。在这32篇文献中,27篇描述了一项干预措施。在所描述的干预措施中,最常应用的劝导式电子辅导组成部分是个性化(n = 24)、建议(n = 19)、目标设定(n = 17)、模拟(n = 17)和提醒(n = 15)。至于自我追踪组成部分,大多数干预措施使用加速度计来测量步数(n = 11)。此外,用户访问干预措施的媒介通常是手机(n = 10)。以下关键组成部分及其具体设计似乎对健康结果和可用性都有积极影响:通过设定短期目标最终实现长期目标来进行缩减、目标个性化、表扬信息、提醒将自我追踪数据输入技术设备、使用经过有效性测试的设备、自我追踪与劝导式电子辅导的整合以及在实施过程中提供面对面指导。此外,当要求参与者向技术设备输入更多数据时,健康结果或可用性并未受到负面影响。从纳入文献中提取的数据识别依从性关键组成部分的能力有限。然而,确定了一个对可用性和依从性都很关键的组成部分,即提供个性化内容。

结论

本范围综述首次概述了结合自我追踪与劝导式电子辅导的自动化健康生活方式干预措施中的关键组成部分,这些组成部分可在开发此类干预措施时加以利用。未来的研究应侧重于确定影响依从性的关键组成部分,因为依从性是干预措施有效实施的前提条件。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cca7/5558041/5f46c24e55e2/jmir_v19i8e277_fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验