Podium Presentation 6th World Congress on Positive Psychology 2019

Prediction Of Wellbeing Via Smartphone Experience Sampling - A Scalable Solution To Tracking Dynamic Positive Functioning Measures. (#87)

Nikki Rickard 1 , Elizabeth Seabrook 2 , David Bakker 1 , Abdullah Arjmand 1
  1. School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
  2. Swinburne University of Technology, Hawthorn, Victoria, Australia

MoodPrism is an evidence-based mood-tracking smartphone app that measures dynamic changes in positive functioning, including positive affect, connectedness, and self-esteem, and provides regular feedback on wellbeing and mental health.  The app also administers a range of psychometric questionnaires at monthly intervals, including the Warwick Edinburgh Mental Wellbeing Scale (WEMWBS) to assess wellbeing and the Patient Health Questionnaire (PHQ-9) to assess depression.  This study sampled 241 participants and evaluated whether using MoodPrism for 30 day improved wellbeing.  Whether wellbeing could be predicted by daily experience sampling method (ESM) measures of positive functioning as effectively as by longer psychometric tests was also assessed by aggregating seven positive functioning measures across 30 days.  Wellbeing scores improved significantly following MoodPrism use.  Multiple regression analyses revealed that the ESM index significantly predicted wellbeing and depression scores. Individually, daily reporting of connectedness and meaning best predicted wellbeing, while self-esteem was the only significant predictor of depression. These findings suggest that short daily measures delivered by smartphones may offer a valid and economical method for ongoing prediction of wellbeing and mental health.  The ubiquity of smartphones also suggests that this methodology is highly scalable and may support improved awareness of wellbeing at a population level.