A Text Messaging Intervention for Coping With Social Distancing During COVID-19 (StayWell at Home): Protocol for a Randomized Controlled Trial

Abstract

Background 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, such as 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. Objective In a two-arm randomized controlled trial, we aim to examine the effect of our 60-day text messaging intervention. Additionally, we aim to assess whether the use of machine learning to adapt the messaging frequency and content improves the effectiveness of the intervention. Finally, we will examine the differences in daily mood ratings between the message categories and time windows. Methods The messages were designed within two different categories: behavioral activation and coping skills. 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 three 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 depression, using the 8-item Patient Health Questionnaire; and self-reported anxiety, using the 7-item Generalized Anxiety Disorder scale at baseline and at intervention completion. Results The Committee for the Protection of Human Subjects at the University of California Berkeley approved this study in April 2020 (No. 2020-04-13162). Data collection began in April 2020 and will run to April 2021. As of August 24, 2020, we have enrolled 229 participants. We plan to submit manuscripts describing the main results of the trial and results from the microrandomized trial for publication in peer-reviewed journals and for presentations at national and international scientific meetings. Conclusions 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. Trial Registration ClinicalTrials.gov NCT04473599; https://clinicaltrials.gov/ct2/show/NCT04473599 International Registered Report Identifier (IRRID) DERR1-10.2196/23592

Cultural influence on COVID-19 cognitions and growth speed: the role of cultural collectivism

“…Our success in reducing COVID-19 transmission relies on people voluntarily adopting prevention behaviors. A number of studies have investigated messaging strategies that have potential in promoting preventive behaviors in response to COVID-19 (Everett et al, n.d.;Figueroa et al, 2021;Hacquin et al, 2020;Ma & Miller, 2021;Pink et al, 2020;Sobande, 2020). The current study highlights the importance of considering culture when designing such messages.…”

Effectiveness and implementation of a text messaging intervention to reduce depression and anxiety symptoms among Latinx and Non-Latinx white users during the COVID-19 pandemic

“…Importantly, the content is pre-established, not sent by a live therapist, and not tailored to each user. More information on the study protocol can be found in previous work ( Figueroa et al, 2021 ).…”

A Text Messaging Intervention (StayWell at Home) to Counteract Depression and Anxiety During COVID-19 Social Distancing: Pre-Post Study

“…The sample size calculation was performed in a previous protocol paper [23], which includes 2 aims. This paper only considers the primary aim.…”

“…Further studies are needed to compare the effectiveness of personalizing messages using a reinforcement learning algorithm to that of a random message condition. Other studies in progress may be better suited to answer questions related to the impact of reinforcement learning models' utility for improving personalization [23].…”

“…In April 2020, we initiated the StayWell at Home intervention (ClinicalTrials.gov, NCT04473599), a 60-day skills-based daily text messaging program in accordance with principles of CBT [23]. This paper assesses the effects of StayWell on symptoms of depression and anxiety in a broad adult population living in the United States during the COVID-19 pandemic.…”