A Personalized Mind-Body Intervention (MBI) for Improving Sleep Among Women Working in Healthcare

The effect of the personalized MBI intervention on individual's sleep duration will be assessed in each arm separately. Participants' daily sleep duration will be measured objectively using Fitbit devices and by self-reported questionnaires. Individual changes in the average daily sleep durations between the run-in and each treatment period will be reported using means and 95% CIs. Bland-Altman plots will be constructed to visualize agreement between Fitbit reported and self-reported sleep duration. The effects of treatment on sleep duration will be assessed using GEE with an unstructured variance-covariance matrix for measures on the same day to that night's sleep. This model accounts for possible autocorrelation and linear trends between sleep duration across time.

A change between time points is reported (e.g., baseline (2 weeks) and 2 weeks for each intervention period (4 weeks per intervention)) as a value for each intervention period minus value at baseline.

Sleep latency is an important parameter in a sleep study. The duration of time between when the lights are turned off (lights out) as the patient attempts to sleep, until the time patient actually falls asleep will be reported as sleep latency and aggregated daily using Fitbit devices. The effect of the personalized MBI intervention on individual's sleep latency will be assessed in each arm separately. Individual changes in the average daily sleep latency between the run-in and each treatment period will be reported using means (95% CIs) and modeled using Generalized estimating equations (GEE).

Sleep efficiency (SE) is an indicator of sleep quality. SE is commonly defined as the ratio of total sleep time (TST) to time in bed (TIB). Values (as percentages) greater than or equal to 85% indicate good sleep quality (Ohayon et al., 2017 [PMID: 28346153]). SE will be recorded and aggregated daily using Fitbit devices. The effect of the personalized MBI intervention on individual's SE be assessed in each arm separately. Individual changes in the average daily sleep efficiency between the run-in and each treatment period will be reported using means (95% CIs) and modeled using Generalized estimating equations (GEE).

Fitbit calculates the resting heart rate by measuring the heart rate when it detects sleep, and by measuring it throughout the day while an individual is but inactive (no steps detected). Resting heart rate will be recorded and aggregated daily using Fitbit devices. The effect of the personalized MBI intervention on individual's resting heart rate will be assessed in each arm separately. Individual changes in the average resting heart rate between the run-in and each treatment period will be reported using means (95% CIs) and modeled using Generalized estimating equations (GEE).

The number of steps per day (physical activity) will be recorded and aggregated daily using Fitbit devices. The effect of the personalized MBI intervention on individual's number of steps per day will be assessed in each arm separately. Individual changes in the daily average number of steps between the run-in and each treatment period will be reported using means (95% CIs) and modeled using Generalized estimating equations (GEE).

Participant's perceived stress score will be measured using the Perceived Stress Scale (PSS) (scale 0 to 40) and the Ecological Momentary Assessment (EMA) Stress questionnaire (scale 0 to 10). PSS and EMA will be evaluated pre-intervention (run-in), bi-weekly during the intervention, and post-intervention. Individual changes in the average PSS and EMA scores between the run-in and each treatment period will be reported using means (95% CIs).

Participant's anxiety and depressive disorder scores will be assessed using the Patient Health Questionnaire (PHQ-4), a self-report version of the Primary Care Evaluation of Mental Disorders (PRIME-MD) on a scale of 0 to 3 for a total of four items. Total score will be determined by adding together the scores of each of the 4 items. Scores are rated as normal (0-2), mild (3-5), moderate (6-8), and severe (9-12). Total score ≥3 for first 2 questions suggests anxiety. Total score ≥3 for last 2 questions suggests depression. PHQ-4 will be evaluated pre-intervention (run-in), bi-weekly during the intervention, and post-intervention. Individual changes in the average PHQ-4 scores between the run-in and each treatment period will be reported using means (95% CIs). The role of anxiety and depression as a potential mediator (M) between perceived stress (X) and sleep score (Y), will be determined by mixed effects regression models.