JMIR Publications

ABSTRACT

Background:

Persuasive design, in which the aim is to change attitudes and behaviors by means of technology, is an important aspect of eHealth design. However, selecting the right persuasive feature for an individual is a delicate matter, and is likely to depend on individual characteristics. Personalization of the persuasive strategy in an eHealth intervention therefore seems like a promising approach.

Objective:

The goals of this study are to develop a method that allows us to profile the individual older adult with respect to leading a healthy life, and to develop a strategy for personalizing the persuasive strategy of an eHealth intervention, based on this user profile.

Methods:

We deployed an online survey among older adults (60+) in the Netherlands. In the first part, we administered an adapted version of the revised Sports Motivation Scale, as input for the user models. Then, we provided each participants with a selection of five randomly chosen mock-ups (out of a total of 11), each one depicting a different persuasive strategy. After showing each strategy, we asked participants how much they appreciated it. The survey was concluded by addressing demographics.

Results:

212 older adults completed the online survey, with a mean age of 68.35 years (standard deviation 5.27 years). 96/212 were male (45.3%), 116/212 were female (54.7%). Factor analysis did not allow us to replicate the five-factor structure for motivation, as targeted by the revised Sports Motivation Scale. Instead, a three-factor structure emerged with a total explained variance of 62.79%. These three factors are intrinsic motivation, acting because of deriving satisfaction from the behavior itself (five items; Cronbach’s alpha: .90); external regulation, acting because of externally controlled rewards or punishments (four items; Cronbach’s alpha: .83); and a-motivation, a situation where there is a lack of intention to act (two items; r = .50, p <.001). Persuasive strategies were appreciated differently, depending on the type of personal motivation. For some cases, demographics played a role.

Conclusions:

The personal type of motivation of older adults (intrinsic, externally regulated and/or a-motivation), combined with their educational level strongly affects which persuasive eHealth features and an individual (dis)likes. We provide a practical approach for profiling older adults, as well as an overview of which persuasive features should (not) be provided to each profile.