Literature DB >> 28293577

Do as I tweet, not as I do: comparing physical activity data between fitness tweets and Healthy People 2020.

Ted Vickey1, John G Breslin2.   

Abstract

BACKGROUND: The goal of this research was to compare the self-reported estimates of daily physical-activity data provided to the Healthy People 2020 research team via a telephone survey to the mobile fitness app real-time reporting of physical activity using Twitter.
METHODS: The fitness tweet classification data set was collected from mobile fitness app users who shared their physical activity over Twitter. Over 184 days, 2,856,534 tweets were collected in 23 different languages. However, for the purposes of this study, only the English-language tweets were analysed, resulting in a total of 1,982,653 tweets by 165,768 unique users. The information and data gleaned from this data set, which reflected 184 days of continuous data collection, were compared to the results from the Healthy People survey, which were compiled using telephone interviews of self-reported physical activity from the previous week.
RESULTS: The data collected from fitness tweets using the five mobile fitness apps suggest lower percentages of people achieving both the 150 to 300 and 300+ min levels than is reflected in the Healthy People survey results. While employing Twitter and other social media as data-collection tools could help researchers obtain information that users might not remember or be willing to disclose face-to-face or over the telephone, further research is needed to determine the cause of the lower percentages found in this study.
CONCLUSIONS: Though some challenges remain in using social media like Twitter to glean physical-activity data from the public, this approach holds promise for yielding valuable information and improving outcomes.

Entities:  

Keywords:  Twitter; mHealth; mobile fitness apps; physical activity

Year:  2015        PMID: 28293577      PMCID: PMC5344139          DOI: 10.3978/j.issn.2306-9740.2015.11.01

Source DB:  PubMed          Journal:  Mhealth        ISSN: 2306-9740


  11 in total

Review 1.  Limits to the measurement of habitual physical activity by questionnaires.

Authors:  R J Shephard
Journal:  Br J Sports Med       Date:  2003-06       Impact factor: 13.800

2.  Trend and prevalence estimates based on the 2008 Physical Activity Guidelines for Americans.

Authors:  Susan A Carlson; Janet E Fulton; Charlotte A Schoenborn; Fleetwood Loustalot
Journal:  Am J Prev Med       Date:  2010-10       Impact factor: 5.043

3.  Twitter classification model: the ABC of two million fitness tweets.

Authors:  Theodore A Vickey; Kathleen Martin Ginis; John G Breslin; Maciej Dabrowski
Journal:  Transl Behav Med       Date:  2013-09       Impact factor: 3.046

4.  Measurement error of self-reported physical activity levels in New York City: assessment and correction.

Authors:  Sungwoo Lim; Brett Wyker; Katherine Bartley; Donna Eisenhower
Journal:  Am J Epidemiol       Date:  2015-04-08       Impact factor: 4.897

5.  Increasingly mobile: How new technologies can enhance qualitative research.

Authors:  Carrie Ann Moylan; Amelia Seraphia Derr; Taryn Lindhorst
Journal:  Qual Soc Work       Date:  2015-01

6.  How many days of monitoring predict physical activity and sedentary behaviour in older adults?

Authors:  Teresa L Hart; Ann M Swartz; Susan E Cashin; Scott J Strath
Journal:  Int J Behav Nutr Phys Act       Date:  2011-06-16       Impact factor: 6.457

7.  Reliability and validity of the Activity Questionnaire for Adults and Adolescents (AQuAA).

Authors:  Mai J M Chinapaw; Sander M Slootmaker; Albertine J Schuit; Mariska van Zuidam; Willem van Mechelen
Journal:  BMC Med Res Methodol       Date:  2009-08-10       Impact factor: 4.615

8.  Objective vs. self-reported physical activity and sedentary time: effects of measurement method on relationships with risk biomarkers.

Authors:  Carlos A Celis-Morales; Francisco Perez-Bravo; Luis Ibañez; Carlos Salas; Mark E S Bailey; Jason M R Gill
Journal:  PLoS One       Date:  2012-05-09       Impact factor: 3.240

9.  Emerging technologies for assessing physical activity behaviors in space and time.

Authors:  Philip M Hurvitz; Anne Vernez Moudon; Bumjoon Kang; Brian E Saelens; Glen E Duncan
Journal:  Front Public Health       Date:  2014-01-28

10.  Emerging technologies to promote and evaluate physical activity: cutting-edge research and future directions.

Authors:  Dan J Graham; J Aaron Hipp
Journal:  Front Public Health       Date:  2014-06-27
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  1 in total

1.  Tweeting about physical activity: can tweeting the walk help keeping the walk?

Authors:  Janice Y Tsoh
Journal:  Mhealth       Date:  2016-03-02
  1 in total

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