Personnel Change

Purpose: Test the effects of using Calm for its impact on stress, anxiety, and sleep in pregnant women using the following aims:

Aim #1: Determine the feasibility of using Calm.

Aim #2: Determine the preliminary efficacy of using Calm on stress, anxiety, and sleep.

Exploratory Aim #3: Explore the preliminary efficacy of using Calm on self-reported birth outcomes

Rates of stress and poor sleep affect up to 70% of pregnant women with rates even higher in racial and ethnic minority (REM) women. Stress and poor sleep are often untreated or misdiagnosed, especially in lower income and REM populations, due to high health-related costs or lack of insurance and may underestimate the prevalence of stress and poor sleep. High stress and poor sleep increases risk of depression, anxiety, pregnancy complications, and poor birth outcomes. Research suggests that stress and poor sleep are strongly associated during pregnancy. In fact, poor sleep in pregnancy has been regarded as both an outcome of stress and a stressor in itself and improving sleep has been suggested as a strategy to protect maternal mental health. There is a need for interventions particularly among REM pregnant women to reduce stress and improve sleep.

Treatments for prenatal stress and poor sleep are inadequate in meeting the needs of pregnant women. Typical treatments are usually an aggregation of medication, interpersonal psychotherapy, and cognitive behavioral therapy. However, mental health stigma and concern with potential teratogenic effects from medication use may discourage women to seek help and many prefer non-pharmacological approaches. Mindfulness meditation (MM) is a nonpharmacological approach effective for reducing stress and improving sleep during pregnancy. MM can be described as the practice of self-regulation of attention and accepting the present moment. MM interventions may moderate the impact of poor sleep quality on stress and can have lasting effects with regular practice. Furthermore, MM is a recommended strategy for pregnant women to improve mental health. While there is evidence for the benefits of MM, many studies report high drop-out rates due to inconvenience, travel, or child care demands. Accessible, low cost, MM interventions to improve stress and sleep outcomes for pregnant women are warranted.

Delivery of MM using smartphone applications (apps) for the management of stress and sleep has dramatically increased in recent years. App-based MM can be delivered remotely, substantially increasing reach, accessibility, and scalability. Over 260 MM apps exist, but many consumer-based apps have low evidence for their efficacy among pregnant and REM users. Calm is a popular, consumer-based MM app that has over 100 million downloads, four million subscribers, and has demonstrated effects in stress and improved sleep in non-pregnant populations. In our preliminary survey data, pregnant subscribers of the Calm app most commonly used the app for sleep problems (29%; n=31) and reported the app was most helpful for improving sleep (32%; n=32) and stress (21%; n=21). Currently, the feasibility and potential impact of the Calm app to reduce stress and improve sleep in pregnant REM women is unknown.

Inclusion Criteria

• Pregnant women 14-16 or 28-30 weeks gestation
• Resident of United States
• Access to regular WiFI
• Access to a smartphone regularly
• Willing to download an app onto their smartphone
• Score of >13 on Perceived Stress Scale (PSS-10)] 31 and sleep quality [score of >5 on Pittsburgh Sleep Quality Index (PSQI)]
• Have not practiced meditation more than 60 minutes a month in the past six months
• Willing to be randomized to one of two groups.

Exclusion Criteria:

• <18 years of age
• Unable to consent
• First trimester (less than 14 weeks)

Researchers will assign participants to groups based on a randomized allocation list, which will be generated prior to the start study by a team member who is not involved in the group-assignment process. Allocation sequences will be concealed until the time of group assignment.