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Preventing depression using a smartphone app: a randomized controlled trial

Published online by Cambridge University Press:  06 July 2020

Mark Deady*
Affiliation:
Black Dog Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
Nicholas Glozier
Affiliation:
Central Clinical School, Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
Rafael Calvo
Affiliation:
School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, Australia Dyson School of Design Engineering, Imperial College London, London, UK
David Johnston
Affiliation:
Black Dog Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
Andrew Mackinnon
Affiliation:
Black Dog Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
David Milne
Affiliation:
School of Systems Management and Leadership, Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW, Australia
Isabella Choi
Affiliation:
Central Clinical School, Brain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
Aimee Gayed
Affiliation:
School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
Dorian Peters
Affiliation:
School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, Australia Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, UK
Richard Bryant
Affiliation:
School of Psychology, University of New South Wales, Sydney, NSW, Australia
Helen Christensen
Affiliation:
Black Dog Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
Samuel B. Harvey
Affiliation:
Black Dog Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia
*
Author for correspondence: Mark Deady, E-mail: m.deady@unsw.edu.au

Abstract

Background

There is evidence that depression can be prevented; however, traditional approaches face significant scalability issues. Digital technologies provide a potential solution, although this has not been adequately tested. The aim of this study was to evaluate the effectiveness of a new smartphone app designed to reduce depression symptoms and subsequent incident depression amongst a large group of Australian workers.

Methods

A randomized controlled trial was conducted with follow-up assessments at 5 weeks and 3 and 12 months post-baseline. Participants were employed Australians reporting no clinically significant depression. The intervention group (N = 1128) was allocated to use HeadGear, a smartphone app which included a 30-day behavioural activation and mindfulness intervention. The attention-control group (N = 1143) used an app which included a 30-day mood monitoring component. The primary outcome was the level of depressive symptomatology (PHQ-9) at 3-month follow-up. Analyses were conducted within an intention-to-treat framework using mixed modelling.

Results

Those assigned to the HeadGear arm had fewer depressive symptoms over the course of the trial compared to those assigned to the control (F3,734.7 = 2.98, p = 0.031). Prevalence of depression over the 12-month period was 8.0% and 3.5% for controls and HeadGear recipients, respectively, with odds of depression caseness amongst the intervention group of 0.43 (p = 0.001, 95% CI 0.26–0.70).

Conclusions

This trial demonstrates that a smartphone app can reduce depression symptoms and potentially prevent incident depression caseness and such interventions may have a role in improving working population mental health. Some caution in interpretation is needed regarding the clinical significance due to small effect size and trial attrition.

Trial Registration Australian and New Zealand Clinical Trials Registry (www.anzctr.org.au/) ACTRN12617000548336

Type
Original Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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