van Velsen Lex, Broekhuis Marijke, Jansen-Kosterink Stephanie, Op den Akker Harm
eHealth Group, Roessingh Research and Development, Enschede, Netherlands.
Biomedical Signals and Systems Group, University of Twente, Enschede, Netherlands.
J Med Internet Res. 2019 Sep 6;21(9):11759. doi: 10.2196/11759.
Persuasive design, in which the aim is to change attitudes and behaviors by means of technology, is an important aspect of electronic health (eHealth) design. However, selecting the right persuasive feature for an individual is a delicate task and is likely to depend on individual characteristics. Personalization of the persuasive strategy in an eHealth intervention therefore seems to be a promising approach.
This study aimed to develop a method that allows us to model motivation in older adults with respect to leading a healthy life and a strategy for personalizing the persuasive strategy of an eHealth intervention, based on this user model.
We deployed a Web-based survey among older adults (aged >60 years) in the Netherlands. In the first part, we administered an adapted version of the revised Sports Motivation Scale (SMS-II) as input for the user models. Then, we provided each participant with a selection of 5 randomly chosen mock-ups (out of a total of 11), each depicting a different persuasive strategy. After showing each strategy, we asked participants how much they appreciated it. The survey was concluded by addressing demographics.
A total of 212 older adults completed the Web-based survey, with a mean age of 68.35 years (SD 5.27 years). Of 212 adults, 45.3% were males (96/212) and 54.7% were female (116/212). Factor analysis did not allow us to replicate the 5-factor structure for motivation, as targeted by the SMS-II. Instead, a 3-factor structure emerged with a total explained variance of 62.79%. These 3 factors are intrinsic motivation, acting to derive satisfaction from the behavior itself (5 items; Cronbach alpha=.90); external regulation, acting because of externally controlled rewards or punishments (4 items; Cronbach alpha=.83); and a-motivation, a situation where there is a lack of intention to act (2 items; r=0.50; P<.001). Persuasive strategies were appreciated differently, depending on the type of personal motivation. In some cases, demographics played a role.
The personal type of motivation of older adults (intrinsic, externally regulated, and/or a-motivation), combined with their educational level or living situation, affects an individual's like or dislike for a persuasive eHealth feature. We provide a practical approach for profiling older adults as well as an overview of which persuasive features should or should not be provided to each profile. Future research should take into account the coexistence of multiple types of motivation within an individual and the presence of a-motivation.
劝导式设计旨在通过技术手段改变态度和行为，是电子健康（eHealth）设计的一个重要方面。然而，为个体选择合适的劝导特征是一项微妙的任务，可能取决于个体特征。因此，在电子健康干预中对劝导策略进行个性化似乎是一种很有前景的方法。
本研究旨在开发一种方法，使我们能够针对老年人健康生活的动机进行建模，并基于此用户模型制定一种对电子健康干预的劝导策略进行个性化的策略。
我们在荷兰对老年人（年龄>60岁）开展了一项基于网络的调查。在第一部分，我们使用修订后的运动动机量表（SMS-II）的改编版作为用户模型的输入。然后，我们为每位参与者提供从总共11个中随机选择的5个原型，每个原型描绘一种不同的劝导策略。展示每种策略后，我们询问参与者对其的欣赏程度。调查最后涉及人口统计学信息。
共有212名老年人完成了基于网络的调查，平均年龄为68.35岁（标准差5.27岁）。在212名成年人中，45.3%为男性（96/212），54.7%为女性（116/212）。因子分析未能让我们复制SMS-II所针对的动机的五因素结构。相反，出现了一个三因素结构，总解释方差为62.79%。这三个因素分别是内在动机，即从行为本身获得满足感（5个项目；克朗巴哈系数=0.90）；外部调节，即由于外部控制的奖励或惩罚而行动（4个项目；克朗巴哈系数=0.83）；以及无动机，即缺乏行动意图的情况（2个项目；r=0.50；P<0.001）。根据个人动机类型的不同，对劝导策略的欣赏程度也不同。在某些情况下，人口统计学因素也起作用。
老年人的个人动机类型（内在动机、外部调节动机和/或无动机），再加上他们的教育水平或生活状况，会影响个体对劝导性电子健康特征的喜欢或不喜欢。我们提供了一种对老年人进行剖析的实用方法，以及针对每个剖析结果应提供或不应提供哪些劝导特征的概述。未来的研究应考虑个体内多种动机类型的共存以及无动机的存在。
