Abstract
A growing number of information technology systems and services have occurred to change users' attitudes or behaviors or both in the rapid development of mobile social media platforms. It is a new topic in the field of health communication whether the digitization and socialization of individual exercise behavior can stimulate health behavior. WeRun is a typical platform for the digitization and socialization of individual exercise. Based on 689 WeRun users' questionnaires, this study first repairs the missing and abnormal data by BP neural network. Then, the decision tree is used to evaluate the relationship between the perceived social support and exercise behavior under different intervention conditions, and detects the heterogeneous intervention effects for different pre-intervention profiles. In addition, this study further discusses the performances of social support features of persuasion technology in the WeRun. The data-driven method used in this study is beneficial to reducing self-selection bias and evaluate the intervention effect. The decision tree does not require decision-makers to have much expertise or to make parameter hypotheses while evaluating the intervention effect, and the results are more direct and intelligible. The results show that the decision tree can detect the heterogeneous intervention effect. In some cases, there is not a perfectly positive correlation between the degree of perceived social support and the number of average daily steps, and the relationship with friends has a great impact on the user's perceived social support. In addition, it also reveals the relationship between social comparison and perceived social support, and their interaction on exercise behavior. Finally, this study provides practical suggestions for the design and operation of e-health social network platform. The platforms are supposed to take corresponding persuasive strategies according to the various characteristics of users, so as to improve the continuous attention and participation of users.
Highlights
Along with the increasing richness of material life, people are attaching more and more importance on personal health
This study is based on the tree-based method for assessing the effects of self-selective interventions proposed by Yahav et al [52] to evaluate the differences in average daily steps between users under different intervention conditions, i.e., under varying degrees of perceived social support
Giving thumbs-up this kind of social support behavior will have a positive short-term impact on the user’s exercise behavior [30], and the results of this study indicate that social support can compensate for the lack of motivation caused by the lack of competitive consciousness
Summary
Along with the increasing richness of material life, people are attaching more and more importance on personal health. This study is based on the tree-based method for assessing the effects of self-selective interventions proposed by Yahav et al [52] to evaluate the differences in average daily steps between users under different intervention conditions, i.e., under varying degrees of perceived social support. The effect of the intervention is evaluated by comparing the average daily steps values of users with different degrees of perceived social support. In subset A (CompaFro>0.5), this positive impact is relatively low, with only 1,591.258 steps increased This means that when users lack a strong sense of competition (i.e., low possibility of comparison with top-ranked friends), perceived social support can better motivate exercise behavior. By comparing the samples of node 4 and node 5, it can be seen that users with a high probability of viewing the leaderboard every day (CheckRank) are more likely to walk than those with a low probability of viewing the leaderboard, indicating that there is an incentive relationship between the leaderboard and users’ exercise behavior
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