Feasibility of generating structured motivational messages for tailored physical activity coaching

Tailored motivational messages are helpful to motivate people in eHealth applications for increasing physical activity, but it is not sufficiently clear how such messages can be effectively generated in advance. We, therefore, put forward a theory-driven approach to generating tailored motivational messages for eHealth applications for behavior change, and we examine its feasibility by assessing how motivating the resulting messages are perceived. For this, we designed motivational messages with a specific structure that was based on an adaptation of an existing ontology for tailoring motivational messages in the context of physical activity. To obtain tailored messages, experts in health psychology and coaching successfully wrote messages with this structure for personas in scenarios that differed with regard to the persona's mood, self-efficacy, and progress. Based on an experiment in which 60 participants each rated the perceived motivational impact of six generic and six tailored messages based on scenarios, we found credible support for our hypothesis that messages tailored to mood, self-efficacy, and progress are perceived as more motivating. A thematic analysis of people's free-text responses about what they found motivating and demotivating about motivational messages further supports the use of tailored messages, as well as messages that are encouraging and empathetic, give feedback about people's progress, and mention the benefits of physical activity. To aid future work on motivational messages, we make our motivational messages and corresponding scenarios publicly available.

Designing Personalized Persuasive Game Elements for Older Adults in Health Apps

The use of gamification elements in health apps has been shown to promote healthy behaviors. However, one-size-fits-all gamification strategy does not have the best persuasive effect. Therefore, the aim of this paper was to determine how to select personalized game elements for older adults and use them in health education app design. Firstly, based on the DMC model, the Kano model was used to identify the demand attributes of game mechanisms, and three gamification mechanisms (winning, feedback and reward) preferred by the elderly were selected. Secondly, the corresponding gamification elements were selected by the focus group method, and nine virtual products were generated. Thirdly, the virtual products were rated and conjointly analyzed to obtain the relative importance of gamification mechanisms and the utility values of gamification elements, and a comparative analysis was conducted on four characteristics of older adults: age, gender, personal income, and education. The results obtained the best combination of gamification elements chosen by the elderly under different classifications. Finally, design guidelines on persuasive gamification elements were developed based on the characteristics of older adults, and a modified gamification model was proposed. The results of this study provide suggestions and guidelines for the design of persuasive gamification in health education apps, which will help improve the satisfaction of older adults with health apps.