Khin Than Win, Madeleine R H Roberts & Harri Oinas-Kukkonen (2018) Persuasive system features in computer-mediated lifestyle modification interventions for physical activity, Informatics for Health and Social Care, DOI: 10.1080/17538157.2018.1511565
Persuasive system features in computer-mediated lifestyle modification interventions for physical activity
|Author:||Win, Khin Than1; Roberts, Madeleine R H1; Oinas-Kukkonen, Harri2|
1Unviersity of Wollongong, Australia
2University of Oulu, Finland
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe201902114514
|Publish Date:|| 2019-10-23
Objective: Increasing physical activity has been identified as one of the most important factors in lifestyle modification. Previous studies have reported the effectiveness of using the Internet in motivating behavioral modifications of physical activities. The aim of this study is to identify the persuasive system features most frequently used in computer-mediated physical activities in the current literature.
Materials and Methods: In this review, intervention studies were identified through a structured computerized search of PubMed, PsychInfo, and Web of Science. The results of the search were analyzed using the persuasive systems design (PSD) features identified by Oinas-Kukkonen and Harjumaa (2009).
Results: Thirty-eight articles were reviewed, and the features of the physical activity interventions described were mapped to the identified facets of PSD. The PSD features used most often by researchers in the studies considered in this research included tailoring, tunneling, reminders, trustworthiness, and expertise. The effectiveness of the interventions described in the studies was also compared. The stage of change theory was applied in several intervention studies, and the importance of stage of change has been identified in effectiveness of persuasion toward physical activity.
Informatics for health and social care
|Type of Publication:||
A2 Review article in a scientific journal
|Field of Science:||
113 Computer and information sciences
This is an Accepted Manuscript of an article published by Taylor & Francis in Informatics for Health and Social Care on 23 Oct 2018, available online: https://doi.org/10.1080/17538157.2018.1511565.