Accepted for/Published in: JMIR Research Protocols
Date Submitted: Aug 25, 2020
Date Accepted: Nov 10, 2020
Date Submitted to PubMed: Dec 28, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A text-messaging study to help cope with social distancing: clinical trial protocol for the Stay Well at Home study
ABSTRACT
Introduction: Social distancing is a crucial intervention to slow down person-to-person transmission of COVID-19. However, social distancing has negative consequences including increases in depression and anxiety. Digital interventions, like text-messaging, can provide accessible support on a population wide scale. We developed text messages in English and Spanish to help individuals manage their depressive mood and anxiety during the COVID-19 pandemic. The messages are designed within two different categories: behavioral activation and coping skills.
Methods:
In a two-arm randomized controlled trial we will examine the effect of our 60 days text-messaging intervention. Participants will be randomized into 1) a random messaging arm, where message category and timing will be chosen with equal probabilities, and 2) a reinforcement-learning arm, with a learned decision mechanism for choosing the messages. Participants in both arms will receive one message per day within four different time windows and will be asked to provide their mood rating 3 hours later. We will compare self-reported daily mood ratings, self-reported Patient Health Questionnaire depression scale 8-item (PHQ-8) and Generalized Anxiety Disorder 7-item (GAD-7) at baseline and at intervention completion.
Results:
The Institutional Review Board at the University of California Berkeley approved this study (CPHS: 2020-04-13162) in April 2020. Data collection runs from April 2020 to April 2021. As of August 24th 2020, we have enrolled 229 participants. We plan to submit manuscripts describing the main results of the trial and results from the micro-randomized trial for publication in peer-reviewed journals and presentations at (inter)-national scientific meetings. Registration: clinicaltrials.gov: NCT04473599; pre-results. Discussion: Results will contribute to our knowledge of effective psychological tools to alleviate the negative effects of social distancing, and the benefit of using machine learning to personalize digital mental health interventions.
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Copyright
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