The investigators have developed supportive text-messages in English and Spanish to help people cope with the stress and anxiety of COVID-19 social distancing. The purpose of this study is to examine if automated text-messages will improve depression and anxiety symptoms and enhance positive mood. Additionally, the investigators will compare the effectiveness of sending messages on a random schedule (using a micro-randomized trial design) or sent by a reinforcement learning policy on overall change in depression and anxiety symptoms and daily mood during the 8-week study.
The investigators will send participants supportive text-messages for a period of 2 months.
These text-messages will include tips about behavioral activation and coping skills to deal
with worries and stress. The investigators generated a message bank balanced such that 50% of
all messages are related to behavioral activation (BA) and 50% messages involve different
coping skills. Participants will receive one of these messages per day between 9:00 am and
6:00 pm. Participants will also receive a message asking them to rate their mood on a scale
of 1-9 once a day 3 hours after the BA or coping message.
Participants will be randomized to:
1. a uniform random messaging group (micro-randomized trial design).
2. a reinforcement learning group with a learned decision mechanism for the timing and type
of text-message. The algorithm learns from previous data (which messages were sent, what
was the participants' mood) to maximize an increase in participants mood. No other data
are collected from participants' phones.
The investigators will compare the effect of sending text-messages by a random schedule, and
text-messaging chosen by the RL algorithm. This allows to both evaluate the effect of the
individual intervention components over time within a micro-randomized trial design, and
assess the added value of using RL to adapt the messaging scheme.
The investigators hypothesize that:
- Participant will show improvements in depression, anxiety symptoms and mood during the
60 day study.
- The participants in the group receiving reinforcement learning will have a greater
improvement in depressive symptoms, anxiety and positive mood during the study than
participants in the micro-randomized group.
- The investigators will find differential effects on mood ratings for the two categories
of messages
Behavioral: Uniform random message delivery
In this arm, the categories and timings of text-messages will be delivered to participants using a random schedule
Behavioral: Reinforcement learning message delivery
In this arm, the categories and timings of text-messages will be chosen by a reinforcement learning algorithm
Behavioral: Mood ratings only
In this arm, participants will monitor their mood daily and receive feedback on that mood randomly
Inclusion criteria:
- Over 18 years old
- Own a mobile phone
- Speak English or Spanish
Exclusion criteria:
- Not owning a mobile phone
- Under 18 years old
University of California Berkeley
Berkeley, California, United States
Adrian Aguilera, PhD, Principal Investigator
UC Berkeley