The Use and Effectiveness of Mobile Apps for Depression: Results From a Fully Remote Clinical Trial

Abstract

BackgroundMobile apps for mental health have the potential to overcome access barriers to mental health care, but there is little information on whether patients use the interventions as intended and the impact they have on mental health outcomes.ObjectiveThe objective of our study was to document and compare use patterns and clinical outcomes across the United States between 3 different self-guided mobile apps for depression.MethodsParticipants were recruited through Web-based advertisements and social media and were randomly assigned to 1 of 3 mood apps. Treatment and assessment were conducted remotely on each participant’s smartphone or tablet with minimal contact with study staff. We enrolled 626 English-speaking adults (≥18 years old) with mild to moderate depression as determined by a 9-item Patient Health Questionnaire (PHQ-9) score ≥5, or if their score on item 10 was ≥2. The apps were (1) Project: EVO, a cognitive training app theorized to mitigate depressive symptoms by improving cognitive control, (2) iPST, an app based on an evidence-based psychotherapy for depression, and (3) Health Tips, a treatment control. Outcomes were scores on the PHQ-9 and the Sheehan Disability Scale. Adherence to treatment was measured as number of times participants opened and used the apps as instructed.ResultsWe randomly assigned 211 participants to iPST, 209 to Project: EVO, and 206 to Health Tips. Among the participants, 77.0% (482/626) had a PHQ-9 score >10 (moderately depressed). Among the participants using the 2 active apps, 57.9% (243/420) did not download their assigned intervention app but did not differ demographically from those who did. Differential treatment effects were present in participants with baseline PHQ-9 score >10, with the cognitive training and problem-solving apps resulting in greater effects on mood than the information control app (χ22=6.46, P=.04).ConclusionsMobile apps for depression appear to have their greatest impact on people with more moderate levels of depression. In particular, an app that is designed to engage cognitive correlates of depression had the strongest effect on depressed mood in this sample. This study suggests that mobile apps reach many people and are useful for more moderate levels of depression.ClinicalTrialClinicaltrials.gov NCT00540865; https://www.clinicaltrials.gov/ct2/show/NCT00540865 (Archived by WebCite at http://www.webcitation.org/6mj8IPqQr)

Training Cognitive Functions Using Mobile Apps in Breast Cancer Patients: Systematic Review

“…Almost half of the eleven studies (5) were conducted in North America, four of them were performed in the United States of America [24,27,28,31] and one in Canada [32]. Three were conducted in Europe: -two in Italy [29,33] and one in Norway [26].…”

“…Three papers focused on healthy older adults [27,28,30] while one study chooses a population of older adults with and without Subjective Cognitive Complaints and Mild Cognitive Impairment [32]. One study focused on adults with mild to moderate depression [24], one on overweight or obese adult [25]. Just one paper from our search specified on healthy adults [26].…”

“…Only two articles [30,31] chose to describe the development and the improved design of the apps. Only one paper [24] had as the main aim to assess and improve depressive symptoms by comparing three different apps, one of which is explicitly aimed at improving depression through a cognitive control exercise. Just one study had the explicit aim of investigating the efficacy of the app in improving cognitive functioning [25].…”

“…Arean and colleagues [24] study aimed at testing the efficacy of three apps in relieving from depressive symptomatology. These three apps were called Project: EVO, iPST and Health Tips.…”

Exploring User Needs for a Mobile Behavioral-Sensing Technology for Depression Management: Qualitative Study (Preprint)

“…Some clinicians suggested using gentle reminders in the form of reflection questions to raise patients' attentions to negative data. Designers should allow for personalization [21] about whether and how to present negative behavioral target data. Preferences could be acquired from student patients about their willingness to discuss negative data with their clinicians, or their acceptance of gentle reminders without presenting the actual data if the system detects something is not going well, or their preference to dismiss any potentially negative information.…”