Exploring the features of an app-based just-in-time intervention for depression

Nicole Everitt, Jaclyn Broadbent, Ben Richardson, Joshua M. Smyth, Kristin Heron, Samantha Teague, Matthew Fuller-Tyszkiewicz

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)

Abstract

Background: Technological advancements make it possible to deliver depression interventions via smartphone applications (“Apps”), including those that deliver content “just-in-time” (e.g., in response to acute negative mood states). This study examined whether an app-based just-in-time intervention (ImproveYourMood+) decreased depressive symptoms, and whether the following features were related to symptom improvement: micro-intervention content, mood monitoring, and just-in-time prompts to use content. Methods: Participants (n = 235) from the general population who self-identified as wanting to improve their negative mood were randomised to a waitlist control group (n = 55) or one of three intervention groups: MoodTracker (monitoring-only, n = 58), ImproveYourMood (monitoring and content; n = 62), or ImproveYourMood+ (monitoring, content, and prompts; n = 60). The active intervention phase was 3 weeks. Depressive and anxiety symptoms, and negative automatic thoughts were assessed at baseline, immediately post-intervention, and one month following post-intervention. Results: Linear mixed modelling revealed greater declines over time in depressive and anxiety symptoms and negative automatic thoughts for the ImproveYourMood group (standardized mean differences [SMDs] ranged from.32 to.40) and improves for the ImproveYourMood+ group for negative automatic thoughts (SMDs ≥.37) compared to the waitlist control group. No between-group differences were observed between the MoodTracker and control groups (SMDs =.04–.23). User experience appeared to be superior in more comprehensive/multi-modal versions. Limitations: The study employed a naturalistic design, whereby participants self-selected to utilise the program, did not complete eligibility assessments, and did not receive compensation. The study therefore attained considerable drop-out rate (~50% by the follow-up timepoints), potentially reflecting the usage patterns of real-world mental health apps. Conclusions: The findings suggest that micro-interventions can be an effective way to reduce depressive symptoms both in the moment and 1–2 months later. Integration of micro-interventions with full treatment programs is a viable next step in micro-intervention research.

Original languageEnglish (US)
Pages (from-to)279-287
Number of pages9
JournalJournal of Affective Disorders
Volume291
DOIs
StatePublished - Aug 1 2021

All Science Journal Classification (ASJC) codes

  • Clinical Psychology
  • Psychiatry and Mental health

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