Preprint Article Version 1 This version is not peer-reviewed

Sensor-Based Sleep Quality Index (SB-SQI): A New Metric to Examine the Association of Office Workstation Type on Stress and Sleep

Version 1 : Received: 26 August 2018 / Approved: 27 August 2018 / Online: 27 August 2018 (11:33:23 CEST)

How to cite: Lee, H.; Razjouyan, J.; nguyen, H.; Lindburg, C.; Srinivasan, K.; Gilligan, B.; Canada, K.; Sharafkhaneh, A.; Mehl, M.; Currim, F.; Ram, S.; Lunden, M.; Heerwagen, J.; Kampschroer, K.; Sternberg, E.; Najafi, B. Sensor-Based Sleep Quality Index (SB-SQI): A New Metric to Examine the Association of Office Workstation Type on Stress and Sleep. Preprints 2018, 2018080457 (doi: 10.20944/preprints201808.0457.v1). Lee, H.; Razjouyan, J.; nguyen, H.; Lindburg, C.; Srinivasan, K.; Gilligan, B.; Canada, K.; Sharafkhaneh, A.; Mehl, M.; Currim, F.; Ram, S.; Lunden, M.; Heerwagen, J.; Kampschroer, K.; Sternberg, E.; Najafi, B. Sensor-Based Sleep Quality Index (SB-SQI): A New Metric to Examine the Association of Office Workstation Type on Stress and Sleep. Preprints 2018, 2018080457 (doi: 10.20944/preprints201808.0457.v1).

Abstract

Study Objective: This study examined office workstation types’ impact on objective health-related metrics including stress, physical activity (PA), and sleep quality. We propose a sensor-based sleep quality index (SB-SQI) to fill a needed gap for objective sleep quality measurement over short timescales. Methods: We monitored 231 office workers using chest-worn sensors for 72 hours, yielding 11,736 hours of usable data from 163 participants (mean age 43.4, 56% women). SB-SQI was based on a validated algorithm estimating sleep-onset latency, total sleep time, and sleep efficiency, using the scoring method from the Pittsburg Sleep Quality Index (PSQI). We examined the relationships between SB-SQI, office workstation type (open-bench seating, cubicle, and private office), work-hours stress (standard deviation of heart rate variability), and after-work PA (relative duration of moderate-to-vigorous activity). Results: The sensor-derived poor-sleep ratio of the private office workers was higher than with other office workstation types (81% vs. 66.1%, p = 0.023). PSQI revealed a similar but insignificant trend with a lower effect-size. Among good-sleepers, open-bench seating workers had 22% (p = 0.018) less stress during work hours than others. A significant association between work-hours stress and after-work hours PA (r = 0.331, p = 0.000) was observed irrespective of office workstation type, with the highest PA level observed for open-bench seating workers. Conclusions: Office workstation type had a significant impact on work-hours stress, affecting PA after work hours, which influenced sleep quality. SB-SQI could be more sensitive than PSQI in determining the impact of office workstation types on sleep quality.

Subject Areas

Sleep, Office workers, office workstation, wellbeing, stress, physical activity, wearables, digital health, sleep quality index, tracking sleep quality, workstation types, accelerometry, heart rate variability

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