Towards Achieving Human Flourishing – An mHealth Application and Machine Learning Approach

<p>Although human flourishing has been studied in a wide range of fields, very little research has attempted to examine contributing factors of flourishing with the help of Machine Learning techniques. Based on relevant literature, this dissertation expands domains and measures of human flourishing and utilizes Machine Learning methods to find significant factors of flourishing, then develops a mobile application to help promote six important factors (positive mode, gratitude, contented minded, health, companionship and creativity) of flourishing. This dissertation empirically tests the effectiveness and utility of the FLOURISHING app. Data collected from 1615 survey participants revealed that a significant proportion of Americans did see their state of flourishing, life satisfaction and overall well-being through a more positive lens during the COVID-19 pandemic. The research reveals that financial stability, employment, positive mood, happiness, quality of life, fulfillment, contented mind, work satisfaction, health, gratitude, honoring commitments, companionship, creativity, friendship, religion, willingness to face challenges are key contributing components of human flourishing. A FLOURISHING app was developed to enhance flourishing. The effects of the app on flourishing was examined using a controlled effectiveness trial. 40 participants were recruited and were assigned into two groups, either received the intervention (using FLOURISHING app for 30 days) or served as a control (using a memory app, Lumosity, for 30 days). Participants completed assessments surveys prior to and again 30 days later. Results showed that there was a statistically significant increase in flourishing scores in the group of participants who used the newly developed FLOURISHING app. Therefore, the flourishing app did help promote several critical aspects of human flourishing and the effectiveness was proven. The utility of this app was measured by MARS (Mobile APP Rating Scale) Survey, which also indicated a high level of utility. This dissertation applied mixed research methods: feature selection techniques in machine learning and design science approach to better understand key determinants of human flourishing and ways to promote human flourishing. At the end of this dissertation, several implications are drawn from the finding, and future research directions are suggested.</p>

Name thesis:degree_name

Information Systems and Technology, PhD

Level thesis:degree_level

Open Access Dissertation

Discipline thesis:degree_discipline

Center for Information Systems and Technology

Year dc:date.available

2022

Author dc:creator

• Fu, Yubo

Contributors dc:contributor

• Wallace Chipidza
• Saida Heshmati

• Data Science
• Design Science
• Human Flourishing
• Machine Learning

Repository record dc:identifier

https://scholarship.claremont.edu/cgu_etd/500

OAI identifier oai:identifier

oai:scholarship.claremont.edu:cgu_etd-1531