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Preventing depression using a smartphone app: a randomized controlled trial.

Mark Deady1, Nicholas Glozier2, Rafael Calvo3,4

  • 1Black Dog Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.

Psychological Medicine
|July 7, 2020
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Summary
This summary is machine-generated.

A new smartphone app effectively reduced depression symptoms in Australian workers. This digital intervention shows promise for preventing depression in the working population.

Keywords:
Behavioural activationdepressioneHealthmHealthmindfulnessrandomized control trialsmartphoneworkplace mental health

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Area of Science:

  • Mental Health
  • Digital Health
  • Occupational Health

Background:

  • Traditional depression prevention methods face scalability challenges.
  • Digital technologies offer a potential scalable solution for depression prevention.
  • Effectiveness of digital interventions for depression requires further testing.

Purpose of the Study:

  • To evaluate the effectiveness of a novel smartphone application in reducing depression symptoms.
  • To assess the app's potential in preventing incident depression among Australian workers.

Main Methods:

  • A randomized controlled trial involving employed Australians without clinically significant depression.
  • Intervention group used the HeadGear smartphone app (behavioral activation and mindfulness).
  • Control group used a mood monitoring app; follow-up at 5 weeks, 3 months, and 12 months.

Main Results:

  • The HeadGear group showed significantly fewer depressive symptoms over time (p=0.031).
  • Depression prevalence over 12 months was 3.5% for HeadGear users versus 8.0% for controls.
  • Intervention group had reduced odds of depression caseness (OR=0.43, p=0.001).

Conclusions:

  • Smartphone app interventions can effectively reduce depression symptoms in the working population.
  • Digital tools may play a role in preventing depression and improving occupational mental health.
  • Further research is needed to confirm clinical significance due to effect size and attrition.