DPsych(Clin) Candidate, Monash University
Building and evaluating mobile apps to improve mental health and well-being
The World Health Organisation lists depression as the leading cause of disability worldwide, with enormous economic and health costs. We have treatments that work, but sadly 65% of Australians who experience a mental health issue do not receive treatment. This rate is estimated to be much higher in other parts of the world where treatments are not as accessible.
To fix this growing mental health crisis, we need supports that are much easier to access. We developed MoodMission, an app for iPhone and Android, as a solution to this problem.
When you're feeling low or anxious, MoodMission can suggest you some short strategies, "Missions", to feel better again. Missions are taken from evidence-based psychotherapies and are designed to be short and easy to complete. MoodMission will intelligently suggest 5 from our database of over 200 Missions, based on how you are feeling and how you have gone in the past. A learning algorithm means that the more you use MoodMission, the better it's suggestions get.
You don't need to be experiencing a mental health issue to use MoodMission, and the app can be used to prevent problems from arising in the first place. We also designed it to be used by anyone, regardless of their age or experience with therapy.
My research has involved reviewing the evidence for computerised therapies and the existing range of available mental health apps. I am part of a team that developed another mental health app, MoodPrism, which helps users track their mood in a mood diary. After researching this app and the available evidence in the field, we designed MoodMission to be at the cutting edge. We built the app with the support of crowdfunding and released it to the public on iOS and Android app stores.
My research is now focussed on investigating the effectiveness of the app at decreasing users' depression and anxiety, and improving their positive mental wellbeing. The app has had over 40,000 downloads and we are publishing results from just over 600 users who completed a range of assessments. The app has also been used in a randomised controlled trial, and we are publishing findings from that soon too.
For more on MoodMission and research involving the app, visit www.moodmission.com
Abstract: Electronic mental health interventions for mood disorders have increased rapidly over the past decade, most recently in the form of various systems and apps that are delivered via smartphones.We aim to provide an overview of studies on smartphone-based systems that combine subjective ratings with objectively measured data for longitudinal monitoring of patients with affective disorders. Specifically, we aim to examine current knowledge on: (1) the feasibility of, and adherence to, such systems; (2) the association of monitored data with mood status; and (3) the effects of monitoring on clinical outcomes.We systematically searched PubMed, Web of Science, PsycINFO, and the Cochrane Central Register of Controlled Trials for relevant articles published in the last ten years (2007-2017) by applying Boolean search operators with an iterative combination of search terms, which was conducted in February 2017. Additional articles were identified via pearling, author correspondence, selected reference lists, and trial protocols.A total of 3463 unique records were identified. Twenty-nine studies met the inclusion criteria and were included in the review. The majority of articles represented feasibility studies (n=27); two articles reported results from one randomized controlled trial (RCT). In total, six different self-monitoring systems for affective disorders that used subjective mood ratings and objective measurements were included. These objective parameters included physiological data (heart rate variability), behavioral data (phone usage, physical activity, voice features), and context/environmental information (light exposure and location). The included articles contained results regarding feasibility of such systems in affective disorders, showed reasonable accuracy in predicting mood status and mood fluctuations based on the objectively monitored data, and reported observations about the impact of monitoring on clinical state and adherence of patients to the system usage.The included observational studies and RCT substantiate the value of smartphone-based approaches for gathering long-term objective data (aside from self-ratings to monitor clinical symptoms) to predict changes in clinical states, and to investigate causal inferences about state changes in patients with affective disorders. Although promising, a much larger evidence-base is necessary to fully assess the potential and the risks of these approaches. Methodological limitations of the available studies (eg, small sample sizes, variations in the number of observations or monitoring duration, lack of RCT, and heterogeneity of methods) restrict the interpretability of the results. However, a number of study protocols stated ambitions to expand and intensify research in this emerging and promising field.
Pub.: 26 Jul '17, Pinned: 28 Aug '17
Abstract: Unlike most other health conditions, the treatment of mental illness relies on subjective measurement. In addition, the criteria for diagnosing mental illnesses are based on broad categories of symptoms that do not account for individual deviations from these criteria. The increasing availability of personal digital devices, such as smartphones that are equipped with sensors, offers a new opportunity to continuously and passively measure human behavior in situ. This promises to lead to more precise assessment of human behavior and ultimately individual mental health. More refined modeling of individual mental health and a consideration of individual context, assessed through continuous monitoring, opens the way for more precise and personalized digital interventions that may help increase the number of positive clinical outcomes in mental healthcare. In this paper, we provide a conceptual review of such techniques for measuring, modeling, and treating mental illness and maintaining mental health.
Pub.: 01 Jul '17, Pinned: 28 Aug '17
Abstract: The rapid growth in the use of mobile phone applications (apps) provides the opportunity to increase access to evidence-based mental health care.Our goal was to systematically review the research evidence supporting the efficacy of mental health apps for mobile devices (such as smartphones and tablets) for all ages.A comprehensive literature search (2008-2013) in MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, PsycINFO, PsycTESTS, Compendex, and Inspec was conducted. We included trials that examined the effects of mental health apps (for depression, anxiety, substance use, sleep disturbances, suicidal behavior, self-harm, psychotic disorders, eating disorders, stress, and gambling) delivered on mobile devices with a pre- to posttest design or compared with a control group. The control group could consist of wait list, treatment-as-usual, or another recognized treatment.In total, 5464 abstracts were identified. Of those, 8 papers describing 5 apps targeting depression, anxiety, and substance abuse met the inclusion criteria. Four apps provided support from a mental health professional. Results showed significant reductions in depression, stress, and substance use. Within-group and between-group intention-to-treat effect sizes ranged from 0.29-2.28 and 0.01-0.48 at posttest and follow-up, respectively.Mental health apps have the potential to be effective and may significantly improve treatment accessibility. However, the majority of apps that are currently available lack scientific evidence about their efficacy. The public needs to be educated on how to identify the few evidence-based mental health apps available in the public domain to date. Further rigorous research is required to develop and test evidence-based programs. Given the small number of studies and participants included in this review, the high risk of bias, and unknown efficacy of long-term follow-up, current findings should be interpreted with caution, pending replication. Two of the 5 evidence-based mental health apps are currently commercially available in app stores.
Pub.: 19 Nov '13, Pinned: 28 Aug '17
Abstract: The number of mental health apps (MHapps) developed and now available to smartphone users has increased in recent years. MHapps and other technology-based solutions have the potential to play an important part in the future of mental health care; however, there is no single guide for the development of evidence-based MHapps. Many currently available MHapps lack features that would greatly improve their functionality, or include features that are not optimized. Furthermore, MHapp developers rarely conduct or publish trial-based experimental validation of their apps. Indeed, a previous systematic review revealed a complete lack of trial-based evidence for many of the hundreds of MHapps available.To guide future MHapp development, a set of clear, practical, evidence-based recommendations is presented for MHapp developers to create better, more rigorous apps.A literature review was conducted, scrutinizing research across diverse fields, including mental health interventions, preventative health, mobile health, and mobile app design.Sixteen recommendations were formulated. Evidence for each recommendation is discussed, and guidance on how these recommendations might be integrated into the overall design of an MHapp is offered. Each recommendation is rated on the basis of the strength of associated evidence. It is important to design an MHapp using a behavioral plan and interactive framework that encourages the user to engage with the app; thus, it may not be possible to incorporate all 16 recommendations into a single MHapp.Randomized controlled trials are required to validate future MHapps and the principles upon which they are designed, and to further investigate the recommendations presented in this review. Effective MHapps are required to help prevent mental health problems and to ease the burden on health systems.
Pub.: 05 Mar '16, Pinned: 28 Aug '17
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