Literature DB >> 30611008

Development of a mobile application (App) to delineate "digital chronotype" and the effects of delayed chronotype by bedtime smartphone use.

Yu-Hsuan Lin1, Bo-Yu Wong2, Sheng-Hsuan Lin3, Yu-Chuan Chiu4, Yuan-Chien Pan5, Yang-Han Lee6.   

Abstract

The widespread use and deep reach of smartphones motivate the use of mobile applications to continuously monitor the relationship between circadian system, individual sleep patterns, and environmental effects. We selected 61 adults with 14-day data from the "Know Addiction" database. We developed an algorithm to identify the "sleep time" based on the smartphone behaviors. The total daily smartphone use duration and smartphone use duration prior to sleep onset were identified respectively. We applied mediation analysis to investigate the effects of total daily smartphone use on sleep through pre-sleep use (PS). The results showed participants' averaged pre-sleep episodes within 1 h prior to sleep are 2.58. The duration of three pre-sleep uses (PS1∼3) maybe a more representative index for smartphone use before sleep. Both total daily duration and the duration of the last three uses prior to sleep of smartphone use significantly delayed sleep onset, midpoint of sleep and reduced total sleep time. One hour of increased smartphone use daily, delays the circadian rhythm by 3.5 min, and reduced 5.5 min of total sleep time (TST). One hour of increased pre-sleep smartphone use delayed circadian rhythm by 1.7 min, and reduced 39 s of TST. The mediation effects of PS1∼3 significantly impacted on these three sleep indicators. PS1∼3 accounted for 14.3% of total daily duration, but the proportion mediated of delayed circadian rhythm was 44.0%. We presented "digital chronotype" with an automatic system that can collect high temporal resolution data from naturalistic settings with high ecological validity. Smartphone screen time, mainly mediated by pre-sleep use, delayed the circadian rhythm and reduced the total sleep time.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Chronotype; Circadian rhythm; Digital chronotype; Digital footprint; Mediation analysis; Mobile application (App)

Mesh:

Year:  2018        PMID: 30611008     DOI: 10.1016/j.jpsychires.2018.12.012

Source DB:  PubMed          Journal:  J Psychiatr Res        ISSN: 0022-3956            Impact factor:   4.791


  10 in total

Review 1.  Development of Digital Biomarkers of Mental Illness via Mobile Apps for Personalized Treatment and Diagnosis.

Authors:  I-Ming Chen; Yi-Ying Chen; Shih-Cheng Liao; Yu-Hsuan Lin
Journal:  J Pers Med       Date:  2022-06-06

2.  Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning-Based Exploratory Study.

Authors:  Tahsin Mullick; Ana Radovic; Sam Shaaban; Afsaneh Doryab
Journal:  JMIR Form Res       Date:  2022-06-24

3.  The Association Between Temperament and Characteristics, Smartphone App Use Patterns and Academic Performance of University Students.

Authors:  Jea Woog Lee; Sung Je Park; Soyeon Kim; Un Sun Chung; Doug Hyun Han
Journal:  J Korean Med Sci       Date:  2022-05-02       Impact factor: 5.354

4.  Temporal Stability of Smartphone Use Data: Determining Fundamental Time Unit and Independent Cycle.

Authors:  Yuan-Chien Pan; Hsiao-Han Lin; Yu-Chuan Chiu; Sheng-Hsuan Lin; Yu-Hsuan Lin
Journal:  JMIR Mhealth Uhealth       Date:  2019-03-26       Impact factor: 4.773

5.  Validation of the Mobile App-Recorded Circadian Rhythm by a Digital Footprint.

Authors:  Yu-Hsuan Lin; Bo-Yu Wong; Yuan-Chien Pan; Yu-Chuan Chiu; Yang-Han Lee
Journal:  JMIR Mhealth Uhealth       Date:  2019-05-16       Impact factor: 4.773

6.  Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations.

Authors:  Alina Trifan; Maryse Oliveira; José Luís Oliveira
Journal:  JMIR Mhealth Uhealth       Date:  2019-08-23       Impact factor: 4.773

7.  Tracking Subjective Sleep Quality and Mood With Mobile Sensing: Multiverse Study.

Authors:  Koen Niemeijer; Merijn Mestdagh; Peter Kuppens
Journal:  J Med Internet Res       Date:  2022-03-18       Impact factor: 7.076

8.  Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review.

Authors:  Abinaya Gopalakrishnan; Revathi Venkataraman; Raj Gururajan; Xujuan Zhou; Rohan Genrich
Journal:  PeerJ Comput Sci       Date:  2022-08-02

9.  Assessing User Retention of a Mobile App: Survival Analysis.

Authors:  Yu-Hsuan Lin; Si-Yu Chen; Pei-Hsuan Lin; An-Shun Tai; Yuan-Chien Pan; Chang-En Hsieh; Sheng-Hsuan Lin
Journal:  JMIR Mhealth Uhealth       Date:  2020-11-26       Impact factor: 4.773

10.  Two-dimensional taxonomy of internet addiction and assessment of smartphone addiction with diagnostic criteria and mobile apps.

Authors:  Yi-Lun Wu; Sheng-Hsuan Lin; Yu-Hsuan Lin
Journal:  J Behav Addict       Date:  2021-01-06       Impact factor: 6.756

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.