Impact of Digital Monitoring, Assessment and Cognitive Behavioral Therapy on Subjective Sleep Quality, Workplace Productivity and Health Related Quality of Life: Observational Study (Preprint)
Authors: Altman Yuval , Eyal Shuli , Baharav Anda , Niejadlik Kyle 
Published: December 2018

BACKGROUND

Sleep difficulties negatively impact health, performance and quality of life, as about a third of the general population suffers from at least one insomnia symptom. Recent studies link insomnia with reduced work productivity, resulting in extensive losses for employees, employers and insurers. Cognitive behavioral therapy for insomnia (CBTi) is recommended as first-line treatment for insomnia and the ubiquity of smart mobile devices allows for promising approaches to overcome some of the limitations surrounding it.

OBJECTIVE

Our aim was to propose a comprehensive sleep solution for smart mobile devices, and to characterize the effects of this solution, while using adequate sample sizes.

METHODS

Employees of a Fortune-50 company were randomly selected, all with a Pittsburgh Sleep Quality Index (PSQI) larger than 8. Subjects were randomly assigned to either an intervention group (IG, n=247) or a control group (CG, n=249), and were asked to fill several questionnaires, in addition to the PSQI. Questionnaires were completed pre-treatment, post-treatment at six weeks and a follow-up after two months. People in the IG were provided with a sleep assessment and therapy service via a mobile app (SleepRate). De-identified objective and subjective sleep data were acquired on a nightly basis, along with a digital sleep diary. Sleep parameters included sleep onset (SO), wake after sleep onset (WASO), sleep efficiency (SE) and sleep satisfaction (SS). Sleep problems, such as symptoms of insomnia, were detected based on the sleep data and several questionnaires. Subjects in the IG were then offered treatment to address the detected sleep problems. For subjects with symptoms of insomnia, average sleep parameters during the assessment week (AW) were compared to those during the last week in treatment (LW).

RESULTS

Post-treatment average PSQI was lower for the IG (8.5), compared to that of the CG (10.9, p=.005), as were absenteeism (IG: 0.39%, CG: 1.0%, p=.06) and presenteeism (IG: 15.6%, CG: 21.4%, p=.02). The average amount of healthy days was significantly higher for the IG (22.5 days) compared to that of the CG (18.6 days, p=.005). At follow-up, average PSQI of the IG was significantly lower (7.1) than that of the CG (10.4, p=.005), as well as absenteeism (IG: 0.15%, CG: 0.84%, p=.03) and presenteeism (IG: 11.9%, CG: 23.5%, p=.005), while the average amount of healthy days was significantly higher (IG: 23.8, CG: 19.0, p=.005). For subjects in the IG, subjective SE was significantly higher at LW (89.1±12.3%, mean±SD) compared to that at the AW (87.5±9.8%, p=.025), WASO significantly shortened (AW: 25.7±27minutes, LW: 19.8±18.4minutes, p=.011), as SS increased significantly (AW: 49.2±11.5, LW: 53±15.4, p=.003).

CONCLUSIONS

The use of a mobile sleep solution improved the subjective sleep perception in the IG and facilitated a substantial increase in work productivity.