Emotional wellbeing is crucial for mental health and wellbeing. People tend to prefer to manage their own emotional problems, even though they could sometimes do with some help recognizing how they feel, or how to get help when they need it to improve their emotional health. Monitoring risk in people with mental health problems is also a significant challenge for practitioners, parents and teachers.  One in five young people experience depressive symptoms, but less than half of these seek professional help.  Of those that seek assistance, ongoing monitoring for onset of relapse is a significant challenge for mental health services.

eMental Health services are beginning to erode some of the practical access barriers to mental health support by providing flexible and confidential information, support and interventions via the internet.  With smartphones penetrating 52% of the Australian population, and with 74% of users never leaving home without their mobile device [1], mobile mental health is at the forefront of this technological revolution [2].  Despite this, there is an overwhelming lack of evidence supporting the effectiveness of these apps [3] - of the few apps that are supported by hard research, none are currently available from iTunes or Google Play stores. 

An app which helps monitor changes in emotional health on a day-to-day basis would help overcome this challenge by detecting when risk increases and therefore when extra help might be needed.  With permission of the user, there is also the potential for parents, teachers or doctors to access information on how young people are travelling emotionally when they are not in contact with them.  In addition to be an easy to use and informative health app to use, this research is about gathering the evidence to confirm that such an app works and will help people in the way intended.

In this app, we harness the popularity of mobile technology to develop a sustainable and highly innovative means of monitoring and providing feedback on emotional wellbeing. Rich data on a user’s music use, physical activity and social network – each of which has been associated with changes in mental health risk [4] - will be collected anonymously via smartphones or other mobile devices.  A set of questionnaires also needs to be completed to provide a unique ‘psychological profile’ for each user. Research has shown that the relationship between smartphone use and mental health is different for different types of people [5] so this profile will also us to explore several known ‘moderators’ of this relationship. Several of these questionnaires will be repeated after a month’s use of the app – the difference between profiles before and after using the app will provide us with critical data for evaluating whether this app is improving the user’s understanding of their own emotions as well as where and how to get information about mental health if they need it. Each day for a month, the user will also complete a short mood report which provides feedback in various formats.  Research has shown that daily reporting of moods (known as ‘experience sampling methodology’) provides a richer, more reliable insight into a person’s emotional state than traditional questionnaires alone. Importantly, the app will confidentially deliver feedback about emotional wellbeing to the user’s own phone. Mental health information – developed in partnership with leading mental health organizations beyond blue and headspace - will be tailored to how they are feeling. 

 

References

1 Our Mobile Planet. (2012). Retrieved from http:// www.ourmobileplanet.com

2 Harrison, V., et al., Mobile mental health: Review of the emerging field. Journal of Mental Health, 2011. 20(6): p. 509-524;  Reid, S.C., et al., Using a mobile phone application in youth mental health. Australian Family Physician, 2012. 41(9): p. 711-714

3 Donker, T. et al. (2013).  Smartphones for smarter delivery of metnal health programs: A systematic review.  J Med Internet Res, 15(11), e247.

4 Kotikalapudi, R. et al (2012).  Associating Internet Usage with Depressive Behavior among College Students.  Technology and Society Magazine, IEEE, 31(4), 73-80; De Choudhury, M., et al, (2013). Predicting Depression via Social Media. Association for the Advancement of Artificial Intelligence Conference Proceedings.  www.aaai.org; Wang R., et al (2014).  StudentLife: Assessing mental health, academic performance and behavioral trends of college students using smartphones.  UBICOMP’14, Sep 13-17, Seatttle WA, USA.

 5 Csikszentmihalyi, M., & LeFevre, J. (1989). Optimal experience in work and leisure. Journal of Personality and Social Psychology, 56, 815-822.