Mobile Intervention for Prevention and Self-Management of Depression


Major depressive disorder is one of the most prevalent mental conditions in working-age adults, with estimates for major depression of 16.6% for lifetime occurrence and 6.7% for a one-year period.1-2 The prevalence of subclinical depression is equal to or greater than major depressive disorder, with lifetime rates up to 26% and an annual prevalence of 5-10%.3-4 Subclinical depression is associated with a two to five-fold increased risk of developing full-syndrome depressive disorders.5-­7

Depression-related costs exceed $83 billion annually in the United States, with more than half incurred by employers through lower productivity, absenteeism, and disability.8 Each year, U.S. employers lose over 27 workdays per depressed employee, totaling up to 225 million lost workdays per year.9

Interventions that reduce the performance-impairing symptoms of subclinical depression and prevent the onset of major depression can improve employee well‐being while reducing healthcare costs and improving productivity.10

MoodHacker Intervention

With the help from National Institutes of Health (NIH) funding, GlobalMed Wellness developed MoodHacker, an empirically validated approach for treating mild-to-moderate depression using a mobile application to reach a broad audience of employees through employer-sponsored benefits. MoodHacker combines critical skills from the validated Coping with Depression CBT skills-training program,11 with positive psychology strategies,12 and persuasive technology.

MoodHacker aims to activate and engage employees through positive cognitive and behavioral skills to improve their mood, reduce depressive symptoms, and prevent escalation to clinical depression. The application guides users to select mood-enhancing activities and track their mood, raising awareness of the influence of positive daily activities on their overall well-being. Notifications and inspirations encourage activity selection, mood tracking, and daily reflection, with additional tips for getting the most out of MoodHacker.  Users have access to our library of articles and videos within the application, promoting the practice of featured cognitive and behavioral skills building resiliency outside of the app.

Study Design & Methods

To test the efficacy of the MoodHacker mobile application, we conducted a two-group randomized controlled trial with 300 employed adults to assess changes in depression symptoms, behavioral activation (actively engaging in positive self-care activities), negative thinking, and knowledge.

Participants were recruited through a variety of sources, including an EAP and a variety of additional non-EAP organizations, including Hope to Cope, Esperanza, Mental Health America, the National Alliance on Mental Illness, Livestrong, eHow, and other eHealth websites, Chamber of Commerce offices, employee support organizations, among others.

Couples used the Love Every Day intervention for three weeks. Both partners independently completed online surveys before and immediately after completing the Love Every Day intervention (approximately three weeks after baseline). Primary outcomes included relationship distress, partner cohesion, relationship confidence, and relationship satisfaction. Other measures examined effects on crucial components of the NERMEM (e.g., knowledge of self and partner, care for one’s partner, shared identity, self-efficacy to manage conflicts). 

The treatment group (N = 150) had access to the MoodHacker intervention for ten weeks and received weekly emails for the first six weeks. The control group (N = 150) received an email with links to four websites with credible information about depression. Study participants in both groups completed online surveys at baseline (T1), six weeks after baseline (T2), and ten weeks after baseline (T3). Surveys assessed depression symptoms, behavioral activation, negative thoughts, worksite outcomes, knowledge, and user satisfaction and usability.

Results & Discussion

At six weeks, we found statistically significant effects on depression (PHQ-­9; = .013), behavioral activation (= .004), negative thoughts (= .014), and knowledge (= .024). Because MoodHacker was developed primarily for distribution through EAP services, we examined these analyses to determine if MoodHacker effects differed for those with EAP access versus those without EAP access. We found that MoodHacker had highly significant effects on depression (= .004) and workplace distress (= .007) for those who reported access to an EAP (N = 91) but no significant effects for those without EAP access.

We conducted a dose-response analysis to explore whether the amount of app use (dose) was related to depression scores (response) based on a composite of the number and total duration of app visits. There was a statistically significant correlation between app use and decreases in depression (r = -.20, = .018).


Treatment group participants visited MoodHacker an average of 13 times (range 0–49 times) in 6 weeks, which amounted to an average of 1 hour (range 0–6.5 hours) total time on the mobile‐web site, accumulated in multiple brief visits. These users were also exposed to educational and prompting emails, but the number read, and time spent on emails could not be determined for analysis. However, aggregated data shows that 42% of participants opened the last email, and 17% continued to access the app after program emails ended.


This study found that the MoodHacker mobile‐web self-management intervention improved behavioral activation (i.e., actively engaging in positive self-care activities), negative thoughts, and knowledge in employed adults after six weeks of use. Significant effects on depression symptoms were seen among those with access to an EAP, and among this subgroup, the intervention also improved workplace distress. The dose-response analysis and range in program use confirm that engagement is crucial to driving outcomes. 


  1. Kessler, Berglund, Demler, Jin, Koretz, Merikangas, et al. (2005). Lifetime prevalence and age of onset distributions of DSM-­‐IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 593–602.
  2. Kessler, Chiu, Demler, Merikanagas, Walters. (2005). Prevalence, severity, and comorbidity of 12-­‐ month DSM-­‐IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 617-­‐627.
  3. Cuijpers, De Graaf, & Van Dorsselaer. (2004). Minor depression: risk profiles, functional disability, health care use and risk of developing major depression. Journal of Affective Disorders, 79, 71–79.
  4. Lewinsohn, Shankman, Gau, & Klein. (2004). The prevalence and comorbidity of subthreshold psychiatric conditions. Psychological Medicine, 34, 613–622.
  5. Gotlib, Lewinsohn, & Seeley. (1995). Symptoms versus a diagnosis of depression: Differences in psychosocial functioning. Journal of Consulting and Clinical Psychology, 63, 90‐100.
  6. Fergusson, Horwood, Ridder, & Beautrais. (2005). Subthreshold depression in adolescence and mental health outcomes in adulthood. Archives of General Psychiatry, 62, 66-­‐72.
  7. Keenan, Hipwell, Feng, et al. (2008). Subthreshold symptoms of depression in preadolescent girls are stable and predictive of depressive disorders. Journal of the American Academy of Child Adolescent Psychiatry, 47, 1433­‐1442.
  8. Greenberg, Kessler, Birnbaum, et al. (2003) The economic burden of depression in the United States: How did it change between 1990 and 2000? Journal of Clinical Psychiatry, 64, 1465–1475.
  9. Kessler, Akiskal, Ames, et al. (2006) Prevalence and effects of mood disorders on work performance in a nationally representative sample of U.S. workers. American Journal of Psychiatry, 163, 1561–1568.
  10. Wang, Simon, Avorn, et al. (2007) Telephone screening, outreach, and care management for depressed workers and impact on clinical and work productivity outcomes. A randomized controlled trial. JAMA, 298, 1401-­‐1411.
  11. Lewinsohn, Antonuccio, Steinmetz, & Teri. (1984) The Coping with Depression Course: A Psychoeducational Intervention for Unipolar Depression. Eugene, OR: Castalia.
  12. Lopez & Snyder (Editors). (2009) The Oxford Handbook of Positive Psychology (2nd ed.) New York: Oxford University Press, Inc.