Mobile apps for mood tracking: an analysis of features and user reviews

Many mood tracking apps are available on smartphone app stores, but little is known about their features and their users' experiences. To investigate commercially available mood tracking apps, we conducted an in-depth feature analysis of 32 apps, and performed a qualitative analysis of a set of user reviews. Informed by a widely adopted personal informatics framework, we conducted a feature analysis to investigate how these apps support four stages of selftracking: preparation, collection, reflection, and action; and found that mood tracking apps offer many features for the collection and reflection stages, but lack adequate support for the preparation and action stages. Through the qualitative analysis of user reviews, we found that users utilize mood tracking to learn about their mood patterns, improve their mood, and self-manage their mental illnesses. In this paper, we present our findings and discuss implications for mobile apps designed to enhance emotional wellness.

[1]  H. Christensen,et al.  Smartphones for Smarter Delivery of Mental Health Programs: A Systematic Review , 2013, Journal of medical Internet research.

[2]  R. Calvo,et al.  Positive Computing: Technology for Wellbeing and Human Potential , 2014, Psychology Teaching Review.

[3]  Mark Matthews,et al.  Mobile phone mood charting for adolescents , 2008 .

[4]  G. Flores Mateo,et al.  Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis , 2015, Journal of medical Internet research.

[5]  Paul Grof,et al.  Electronic monitoring of self-reported mood: the return of the subjective? , 2016, International Journal of Bipolar Disorders.

[6]  M. Seligman.  Authentic Happiness: Using the New Positive Psychology to Realize Your Potential for Lasting Fulfillment , 2002 .

[7]  Nuria Oliver,et al.  A study of mobile mood awareness and communication through MobiMood , 2010, NordiCHI.

[8]  Mark Erik Larsen,et al.  Mobile Apps for Bipolar Disorder: A Systematic Review of Features and Content Quality , 2015, Journal of medical Internet research.

[9]  Lisa P. Newmark,et al.  Many Mobile Health Apps Target High-Need, High-Cost Populations, But Gaps Remain. , 2016, Health affairs.

[10]  G. Clifford,et al.  Daily longitudinal self-monitoring of mood variability in bipolar disorder and borderline personality disorder , 2016, Journal of affective disorders.

[11]  J. Bernhardt,et al.  Behavioral Functionality of Mobile Apps in Health Interventions: A Systematic Review of the Literature , 2015, JMIR mHealth and uHealth.

[12]  Edward H. Wagner,et al.  Getting Traction When Overwhelmed: Implications for Supporting Patient-Provider Communication , 2017, CSCW Companion.

[13]  Alan Chamberlain,et al.  Emotions in context: examining pervasive affective sensing systems, applications, and analyses , 2015, Personal and Ubiquitous Computing.

[14]  Rachel Kenny,et al.  Feasibility of "CopeSmart": A Telemental Health App for Adolescents , 2015, JMIR mental health.

[15]  Jodi Forlizzi,et al.  A stage-based model of personal informatics systems , 2010, CHI.

[16]  C. Keyes,et al.  The structure of psychological well-being revisited. , 1995, Journal of personality and social psychology.

[17]  Sean A. Munson,et al.  A lived informatics model of personal informatics , 2015, UbiComp.

[18]  Oksana Zelenko,et al.  Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps , 2015, JMIR mHealth and uHealth.

[19]  David Coyle,et al.  Interaction design and emotional wellbeing , 2012, CHI EA '12.

[20]  Rafael A. Calvo,et al.  Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications , 2010, IEEE Transactions on Affective Computing.

[21]  Geri Gay,et al.  Pilot Study of Aurora, a Social, Mobile-Phone-Based Emotion Sharing and Recording System , 2011, Journal of diabetes science and technology.