Exploring the features of an app-based just-in-time intervention for depression
Everitt, Nicole, Broadbent, Jaclyn, Richardson, Ben, Smyth, Joshua M., Heron, Kristin, Teague, Samantha, and Fuller-Tyszkiewicz, Matthew (2021) Exploring the features of an app-based just-in-time intervention for depression. Journal of Affective Disorders, 291. pp. 279-287.
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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.
Item ID: | 73667 |
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Item Type: | Article (Research - C1) |
ISSN: | 1573-2517 |
Copyright Information: | © 2021 Elsevier B.V. All rights reserved. |
Date Deposited: | 02 May 2022 23:33 |
FoR Codes: | 52 PSYCHOLOGY > 5203 Clinical and health psychology > 520302 Clinical psychology @ 100% |
SEO Codes: | 20 HEALTH > 2002 Evaluation of health and support services > 200208 Telehealth @ 100% |
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