David Rei, Céline Clavel, Jean-Claude Martin, Brian Ravenet
{"title":"Adapting goals and motivational messages on smartphones for motivation to walk","authors":"David Rei, Céline Clavel, Jean-Claude Martin, Brian Ravenet","doi":"10.1016/j.smhl.2024.100482","DOIUrl":null,"url":null,"abstract":"<div><p>Physical activity is one of the most recognised means of disease prevention. While several studies investigated different techniques for motivating people to walk (e.g. adaptive <em>goal setting</em>), only few studies considered user profiles to personalise interactions. In this article, we propose a new interaction model which adapts walking goals and motivational messages in a static way (using the initial physical activity level) and in a dynamic way (using previous days’ performance). We explain how we implemented this model in a mobile application counting and displaying in real time the number of steps, an adapted daily goal and personalised motivational messages throughout the day. We describe two field studies conducted with 32 and 50 users over four weeks. We compare the impacts of adapted daily goals and personalised motivational messages on users’ step counts and motivation to walk. Participants using the adapted version of the mobile application displayed an increase in their motivation to walk after the intervention and were more physically active than participants using non adapted versions of the mobile application.</p></div>","PeriodicalId":37151,"journal":{"name":"Smart Health","volume":"32 ","pages":"Article 100482"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Health","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352648324000382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 0
Abstract
Physical activity is one of the most recognised means of disease prevention. While several studies investigated different techniques for motivating people to walk (e.g. adaptive goal setting), only few studies considered user profiles to personalise interactions. In this article, we propose a new interaction model which adapts walking goals and motivational messages in a static way (using the initial physical activity level) and in a dynamic way (using previous days’ performance). We explain how we implemented this model in a mobile application counting and displaying in real time the number of steps, an adapted daily goal and personalised motivational messages throughout the day. We describe two field studies conducted with 32 and 50 users over four weeks. We compare the impacts of adapted daily goals and personalised motivational messages on users’ step counts and motivation to walk. Participants using the adapted version of the mobile application displayed an increase in their motivation to walk after the intervention and were more physically active than participants using non adapted versions of the mobile application.