Research using MoodPrism

Research is essential to make sure that health apps like MoodPrism actually help people.  We think MoodPrism will be an important and enjoyable way of monitoring emotional health, but we need your help to show this. 

Beyondblue funded a team of researchers led by Adjunct Associate Professor Nikki Rickard from Monash University to test how useful this app is for all types of users.   See Research Background below if you want to read more about this research.

You now have the opportunity to play an important part in ongoing research, which may help many people to improve their well-being and prevent mental health problems.

Want to participate?

We are often seeking participants 13 years or over, who currently use an Android or Apple smartphone for our research. If you would like to be involved, we will contact you if a study starts up in which you could take part.

You will need to download MoodPrism and use it for at least three months.  This will involve completing about an hour’s worth of surveys at the start (which you can do in several chunks if you want), and then answering short questions (2 mins) when prompted by the app daily. Surveys will again need to be completed three months later.

All information collected is de-identified and completely confidential.

Register your interest in participating:

All data will remain confidential. Responses marked with * are compulsory.

Download information about participating HERE, or if you are under 18, find information for your parents HERE.

Device *

Research Background

Mental health apps

Emotional awareness is important for mental health and wellbeing. People often want to manage their own emotional issues, but sometimes we could do with some help recognizing how we feel. It can also sometimes be difficult to know where to get help or support when we need it to improve our emotional health. Monitoring risk in people with mental health problems can also be a significant challenge for practitioners, parents and teachers. More than 1 in 10 people live with anxiety or depression, but only a third of us seek professional help [1]. Ongoing monitoring when receiving help can also be a significant challenge for mental health professionals.

eMental Health services are beginning to erode some of the access barriers to mental health support by providing flexible and confidential information, support and intervention via the internet. In 2018, two thirds of the population in over 50 countries own a smartphone [2]. Australian statistics show that in 2012, 74% of users never leave home without their mobile device [3].  Mobile mental health technology is emerging as a promising and innovative way of supporting mental health when professional services cannot be accessed [4].  There is however an overwhelming lack of evidence supporting the effectiveness of these apps [5].  Of the few apps that are supported by scientific research, few are still available from iTunes or Google Play stores. In a recent publication, we reviewed the research on mobile mental health apps and provided a list of 16 recommendations for researchers or app developers to consider when creating mental health apps [6].

MoodPrism (Version 2: Released March 2019)

In this app, we harness the popularity of mobile technology to develop a sustainable and engaging way of monitoring and providing feedback on emotional wellbeing. The updated app invites users to complete regular check-ins (daily, weekly, or on demand) on their mood.  This methodology (known as ‘experience sampling methodology’ or ‘ecological momentary assessment’ [7]) is well-established as providing a more valid and reliable insight into a person’s emotional state in real time than traditional questionnaires alone. Incorporating this into a smartphone app enhances the integrity of this information as a user can complete the check-ins quickly with minimal disruption to their daily activities, and using a device with which they are very familiar.  A full description of how the original version of MoodPrism was developed has been published [8]. 

MoodPrism provides rich feedback on a person’s emotional health as it fluctuates over time.  Providing this feedback can help users identify patterns in their moods, and the app also notes when and with whom they were at different moodpoints.  Raising emotional awareness and insight has been demonstrated to improve wellbeing [9]. For example, in a recent study we found that using MoodPrism for 30 days increased mental wellbeing, and reduced depression and anxiety in a community sample.  For people who were depressed or anxious when they began using the app, this change was partially explained by the increase in emotional awareness they reported [10]. 

MoodPrism also provides users with mental health information delivered confidentially to their own phone.  The mental health resources in the app were developed in partnership with leading mental health organizations beyond blue and headspace, and are tailored to how users report they are feeling.   

Apps like MoodPrism can help people monitor changes in their emotional health on a day-to-day basis.  By providing regular feedback, use of this app may help identify when risk of emotional illhealth increases and therefore when extra help might be needed.  With permission of the user, this information could also be shared with parents, teachers, doctors or friends to access information on how people are travelling emotionally when they are not in contact with them.  In addition to being an easy to use and informative health app to use, the research we are performing also contributes to the broader evidence about whether mental health apps work and whether they help people in the way intended by their developers.

MoodPrism's content is drawn from psychological literature with a strong evidence base, including emotion theories (e.g., Gross's emotion regulation theory, Russell's circumplex theory), positive psychology (e.g., Seligman's PERMA framework) and dual models of mental health (e.g., Keyes' Complete Mental health model).  Evidence supporting MoodPrism's sensitivity to detect meaningful changes in emotional state over time, and its potential impact on emotional health, has been published in international, peer-rviewed scientific journals: see below for list of current publications on MoodPrism.

References cited

[1] beyondblue facts. Retrieved 28/3/18 from

[2] Zenith Mobile Advertising Forecasts 2017.  Retrieved 28/3/18 from

[3] Our Mobile Planet. (2012). Retrieved 28/3/18 from  

[4] Harrison, V., et al., (2011).  Mobile mental health: Review of the emerging field. Journal of Mental Health, 20(6), 509-524.  

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

[6] Bakker, D., Kazantzis, N., Rickwood, D., & Rickard, N.S. (2016). Mental health smartphone apps: Evidence-based recommendations for future development.  JMIR – Mental Health, 3(1):e7.

[7] Csikszentmihalyi, M. (July 2014). Validity and Reliability of the Experience-Sampling Method. New York: Springer.

[8] Rickard, N.S., Arjmand, H., Bakker, D., & Seabrook, E. (2016).  Development of a mobile phone app to support self-monitoring of emotional well-being: A mental health digital innovation.  JMIR – Mental Health, 3(4), e49.

[9] Reid, S.C., Kauer, S.D., H et al. (2011).  A mobile phone application for the assessment and management of youth mental health problems in primary care: A randomised controlled trial.  BMC Family Practice, 12, 131.

[10] Bakker, D., & Rickard, N. (2017).  Engagement in a mobile phone app for self-monitoring of emotional wellbeing predicts changes in mental health: MoodPrism. Journal of Affective Disorders, 227, 432-442.


Published Research on MoodPrism and related apps

Rickard, N.S., Arjmand, H., Bakker, D., & Seabrook, E. (2016).  Development of a mobile phone app to support self-monitoring of emotional well-being: A mental health digital innovation.  JMIR – Mental Health, 3(4), e49. Access here

Seabrook, E., Kern, E., & Rickard. N. (2016).  Social Networking Sites, Depression, and Anxiety: A Systematic Review.  JMIR – Mental Health, 3(4), e50.  Access here

Bakker, D., Kazantzis, N., Rickwood, D., & Rickard, N.S. (2016). Mental health smartphone apps: Evidence-based recommendations for future development.  JMIR – Mental Health, 3(1):e7. Access here

Seabrook, E., & Rickard, N.S. (2018). Depression is predicted by emotional instability on Facebook, but by reduced emotion variability on Twitter. Journal of Medical Internet Research, accepted 17/2/2018.  Access here.

Bakker, D., & Rickard, N. (2017) Engagement in mobile phone app for self-monitoring of emotional wellbeing predicts changes in mental health: MoodPrism.  Journal of Affective Disorders, 227, 432-442.  Access here.

Bakker, D., Kazantzis, N., Rickwood, D., & Rickard, N. (2018).  A Randomized Controlled Trial of Three Smartphone Apps for Anxiety and Depression Symptoms. Behaviour Research and Therapy, Access here.  

Bakker, D., Kazantzis, N., Rickwood, D., & Rickard, N. (2017).  Development and pilot evaluation of smartphone delivered Cognitive Behavior Therapy strategies for mood and anxiety related problems: MoodMission. Cognitive and Behavioral Practice, accepted subject to minor revisions 5/1/18.  Access here.


Coming Soon

Rickard, N.S., Seabrook, E., & Bakker, D. Incorporating feedback into dynamic emotion data collection; an opportunity to enhance validity while addressing duty of care.

Seabrook, E1 & Rickard, N.  A smartphone experience sampling method for examining the coherence between emotion signals on Twitter and in self-report.

Bakker, D., & Rickard, N. (2017) Engagement with a cognitive behavioral therapy mobile phone app predicts changes in mental health and well-being: MoodMission.

Arjmand, H-A., & Rickard, N.S. (2017). Exploring the utility of a smartphone Experience-Sampling-Application (ESA) for exploring resilience to daily stressors.

Arjmand, H-A., & Rickard, N.S. (2017). The implementation of an Experience-Sampling-Method capturing trajectories of psychological responding following major daily stressors.

Arjmand, H-A., & Rickard, N.S. (2017). Influences of age, self-esteem, and perceived social support on classifications into trajectories of psychological responding following a daily major stressor.

Seabrook, E. M., Kern, M. L., Fulcher, B. D., & Rickard, N. S. (2018). Do people Tweet what they feel? A case-series exploration of daily mood ratings and the emotions expressed on Twitter.