1000 Bolstering Research Study Recruitment Speed and Retention Rate In A Nationwide Web Based Sleep Study

Abstract

Introduction: This study sought to take advantage of technological and methodological advancements in the field of Mobile Health and apply them to a large-scale longitudinal research study on sleep and activity. Large-scale studies of sleep patterns, quality, and associated characteristics substantiated by objective data are lacking. Utilizing a novel platform, we sought to gain further insights into the relationship between sleep and activity while simultaneously speeding up the recruitment process and maximizing data completeness. Method(s): A subset of Achievement community members were invited to the study and assessed for eligibility. Eligible participants completed an electronic consent process and a series of baseline questionnaires. Participants were asked to connect a wearable device through the study dashboard, which allowed objective sleep and activity data to be collected. Participants could access the study platform from any computer or connected mobile device. After successful completion of the baseline questionnaires, participants were sent a daily single-item Sleepiness Checker activity (Karolinska Sleepiness Scale) for 7 consecutive days at baseline and every 3 months thereafter for 1 year. Result(s): During a 5-day recruitment period, 1156 participants enrolled in the study. 98% of enrolled participants completed baseline questionnaires and 91% completed a baseline sleepiness checker activity. Mean days of sleepiness checker completed was 5.7+/-1.7 (1-7), with 51% of participants completing 7 consecutive days. 85% of participants provided sleep-specific wearable data, and 87% provided activity-specific wearable data. At baseline, wearable data indicated that participants slept an average of 302.8+/-98.1 minutes per night (63-576) and self-reported TST was 391.2+/-108 minutes. Participant retention at one year was 60%, with 40% of those participants completing 7/7 days of the sleepiness checker. Conclusion(s): Conducting online, community-based longitudinal studies that include objective sleep and activity data is an innovative approach to expanding sleep research. As is the case with all large community-based studies, data quality and representativeness of the sample to the overall population must be carefully examined.