Improving Smartphone Users' Affect and Wellbeing with Personalized Positive Psychology Interventions

Abstract

We developed a smartphone application that detects users' affect and provides personalized positive psychology interventions in order to enhance users' psychological wellbeing. Users' emotional states were measured by analyzing facial expressions and the sentiment of SMS messages. A virtual character in the application prompted users to verbally journal about their day by providing three positive psychology interventions. The system used a Markov Decision Process (MDP) model and a State-Action-Reward-State-Action (SARSA) algorithm to learn users' preferences about the positive psychology interventions. Nine participants were recruited for an experimental study to test the application. They used it daily for three weeks. The interactive journaling activity increased participants' arousal and valence levels immediately following each interaction, and we saw a trend toward improved self-acceptance levels over the three week period. The interaction duration increased significantly throughout the study as well. The qualitative analysis on journal entries showed that the application users explored and reflected on various aspects of themselves by looking at daily events, and found novel appreciation for and meanings in their daily routine.