Literature DB >> 24746375

What's the healthiest day?: Circaseptan (weekly) rhythms in healthy considerations.

John W Ayers1, Benjamin M Althouse2, Morgan Johnson3, Mark Dredze4, Joanna E Cohen5.   

Abstract

BACKGROUND: Biological clocks govern numerous aspects of human health, including weekly clocks-called circaseptan rhythms-that typically include early-week spikes for many illnesses.
PURPOSE: To determine whether contemplations for healthy behaviors also follow circaseptan rhythms.
METHODS: We assessed healthy contemplations by monitoring Google search queries (2005-2012) in the U.S. that included the word healthy and were Google classified as health-related (e.g., healthy diet). A wavelet analysis was used in 2013 to isolate the circaseptan rhythm, with the resulting series compared by estimating ratios of relative query volume (healthy versus all queries) each day (e.g., (Monday-Wednesday)/Wednesday).
RESULTS: Healthy searches peaked on Monday and Tuesday, thereafter declining until rebounding modestly on Sunday. Monday and Tuesday were statistically indistinguishable (t=1.22, p=0.22), but their combined mean had 30% (99% CI=29, 32) more healthy queries than the combined mean for Wednesday-Sunday. Monday and Tuesday query volume was 3% (99% CI=2, 5) greater than Wednesday, 15% (99% CI=13, 17) greater than Thursday, 49% (99% CI=46, 52) greater than Friday, 80% (99% CI=76, 84) greater than Saturday, and 29% (99% CI=27, 31) greater than Sunday. We explored media-based (priming) motivations for these patterns and they were consistently rejected.
CONCLUSIONS: Just as many illnesses have a weekly clock, so do healthy considerations. Discovery of these rhythms opens the door for a new agenda in preventive medicine, including implications for hypothesis development, research strategies to further explore these rhythms, and interventions to exploit daily cycles in healthy considerations.
Copyright © 2014 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2014        PMID: 24746375     DOI: 10.1016/j.amepre.2014.02.003

Source DB:  PubMed          Journal:  Am J Prev Med        ISSN: 0749-3797            Impact factor:   5.043


  14 in total

1.  Revisiting the Rise of Electronic Nicotine Delivery Systems Using Search Query Surveillance.

Authors:  John W Ayers; Benjamin M Althouse; Jon-Patrick Allem; Eric C Leas; Mark Dredze; Rebecca S Williams
Journal:  Am J Prev Med       Date:  2016-02-11       Impact factor: 5.043

2.  Monday-focused tailored rapid interactive mobile messaging for weight management 2 (MTRIMM2): results from a randomized controlled trial.

Authors:  Anna Y Kharmats; Chan Wang; Laura Fuentes; Lu Hu; Tina Kline; Kevin Welding; Lawrence J Cheskin
Journal:  Mhealth       Date:  2022-01-20

3.  Campaigns and counter campaigns: reactions on Twitter to e-cigarette education.

Authors:  Jon-Patrick Allem; Patricia Escobedo; Kar-Hai Chu; Daniel W Soto; Tess Boley Cruz; Jennifer B Unger
Journal:  Tob Control       Date:  2016-03-08       Impact factor: 7.552

4.  Is There a Weekly Pattern for Health Searches on Wikipedia and Is the Pattern Unique to Health Topics?

Authors:  Elia Gabarron; Annie Y S Lau; Rolf Wynn
Journal:  J Med Internet Res       Date:  2015-12-22       Impact factor: 5.428

5.  The Seasonal Periodicity of Healthy Contemplations About Exercise and Weight Loss: Ecological Correlational Study.

Authors:  Kenneth Michael Madden
Journal:  JMIR Public Health Surveill       Date:  2017-12-13

6.  Relationship Between Weekly Patterns of Caloric Intake and Reported Weight Loss Outcomes: Retrospective Cohort Study.

Authors:  Christine Hill; Brian W Weir; Laura W Fuentes; Alicia Garcia-Alvarez; Danya P Anouti; Lawrence J Cheskin
Journal:  JMIR Mhealth Uhealth       Date:  2018-04-16       Impact factor: 4.773

7.  Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data.

Authors:  Jonas Christoffer Tana; Jyrki Kettunen; Emil Eirola; Heikki Paakkonen
Journal:  JMIR Ment Health       Date:  2018-05-23

8.  Posting behaviour patterns in an online smoking cessation social network: implications for intervention design and development.

Authors:  Benjamin Healey; Janet Hoek; Richard Edwards
Journal:  PLoS One       Date:  2014-09-05       Impact factor: 3.240

9.  Leveraging Big Data to Improve Health Awareness Campaigns: A Novel Evaluation of the Great American Smokeout.

Authors:  John W Ayers; J Lee Westmaas; Eric C Leas; Adrian Benton; Yunqi Chen; Mark Dredze; Benjamin M Althouse
Journal:  JMIR Public Health Surveill       Date:  2016-03-31

10.  Weekly enrollment and usage patterns in an Internet smoking cessation intervention.

Authors:  Kevin Welding; Elaine De Leon; Sarah Cha; Morgan Johnson; Joanna E Cohen; Amanda L Graham
Journal:  Internet Interv       Date:  2017-07-28
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.