Nighttime Smartphone Use: Evaluating the effect of reducing blue light emissions from smartphones on sleep onset latency and duration
type: CreativeWork
description: Insufficient sleep – in terms of both quantity and quality – is a public health concern, and a risk factor for a range of adverse physical and mental health conditions. A growing body of research points to a significant association between smartphone use and sleep impairment, with a primary hypothesized pathway being the disruptive effects of blue light upon sleep processes. New software and functional improvements to smartphones in recent years provide the opportunity to better quantify, and potentially limit, the detrimental impact that smartphones may have on sleep. The principal purpose of the current study was to examine the degree to which activating Night Shift® mode on an iPhone® before sleep onset, thereby decreasing the amount of blue light emitted from the device, improves sleep onset latency and sleep quantity. This study also examined the relationship between objectively recorded smartphone use on both previously stated sleep measures. Ninety-one undergraduates were randomized to either have their Night Shift® mode settings automatically activated from 9pm to 5am or turned off for the duration of the study. Self-reported sleep onset latency, and objectively recorded sleep quantity and smartphone use data was collected over a 7-day study period. For sleep reported to conform to regular sleep patterns, there were no significant main effects of Night Shift® condition or pre-sleep smartphone use, nor an interaction effect of these two variables, on either sleep onset latency or total sleep quantity. Exploratory analyses of the entire dataset, combining sleep data reported to both conform and not conform to regular sleep patterns, revealed a significant interaction between Night Shift® condition and quantity of smartphone use on sleep onset latency. These findings suggest future research of Night Shift® mode may be warranted.
abstract: Insufficient sleep – in terms of both quantity and quality – is a public health concern, and a risk factor for a range of adverse physical and mental health conditions. A growing body of research points to a significant association between smartphone use and sleep impairment, with a primary hypothesized pathway being the disruptive effects of blue light upon sleep processes. New software and functional improvements to smartphones in recent years provide the opportunity to better quantify, and potentially limit, the detrimental impact that smartphones may have on sleep. The principal purpose of the current study was to examine the degree to which activating Night Shift® mode on an iPhone® before sleep onset, thereby decreasing the amount of blue light emitted from the device, improves sleep onset latency and sleep quantity. This study also examined the relationship between objectively recorded smartphone use on both previously stated sleep measures. Ninety-one undergraduates were randomized to either have their Night Shift® mode settings automatically activated from 9pm to 5am or turned off for the duration of the study. Self-reported sleep onset latency, and objectively recorded sleep quantity and smartphone use data was collected over a 7-day study period. For sleep reported to conform to regular sleep patterns, there were no significant main effects of Night Shift® condition or pre-sleep smartphone use, nor an interaction effect of these two variables, on either sleep onset latency or total sleep quantity. Exploratory analyses of the entire dataset, combining sleep data reported to both conform and not conform to regular sleep patterns, revealed a significant interaction between Night Shift® condition and quantity of smartphone use on sleep onset latency. These findings suggest future research of Night Shift® mode may be warranted.
author: NAMEKATA, MICHAEL
language: en
keywords: Clinical psychology, Blue light, Night shift, Sleep, Smartphone
date published: 2020-08-31
date modified: 2026-07-24T02:45:54Z
provider: University of Kansas
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Kansas

PropertyValue
property ID: Handle
value: https://hdl.handle.net/1808/35292