Literature DB >> 28931147

The quantified self during travel: mapping health in a prospective cohort of travellers.

Andrea Farnham1,2, Reinhard Furrer3,4, Ulf Blanke5, Emily Stone1, Christoph Hatz1,2,6,7, Milo A Puhan1.   

Abstract

BACKGROUND: Travel medicine research has remained relatively unchanged in the face of rapid expansion of international travel and is unlikely to meet health challenges beyond infectious diseases. Our aim was to identify the range of health outcomes during travel using real-time monitoring and daily reporting of health behaviours and outcomes and identify traveller subgroups who may benefit from more targeted advice before and during travel.
METHODS: We recruited a prospective cohort of travellers ≥ 18 years and planning travel to Thailand for <5 weeks from the travel clinics in Zurich and Basel (Switzerland). Participants answered demographic, clinical and risk behaviour questionnaires pre-travel and a daily health questionnaire each day during travel using a smartphone application. Environmental and location data were collected passively by GPS. Classification trees were used to identify predictors of health behaviour and outcomes during travel.
RESULTS: Non-infectious disease events were relatively common, with 22.7% (17 out of 75 travellers) experiencing an accident, 40.0% ( n  = 30) a wound or cut and 14.7% ( n  = 11) a bite or lick from an animal. Mental health associated events were widely reported, with 80.0% ( n  = 60) reporting lethargy, 34.7% ( n  = 26) anxiety and 34.7% ( n  = 26) feeling tense or irritable. Classification trees identified age, trip length, previous travel experience and having experienced a sports injury in the past year as the most important discriminatory variables for health threats.
CONCLUSIONS: Our study offers a revolutionary look at an almost real-time timeline of health events and behaviours during travel using mHealth technology. Non-infectious disease related health issues were common in this cohort, despite being largely unaddressed in traditional travel medicine research and suggest a substantial potential for improving evidence-based travel medicine advice. © International Society of Travel Medicine, 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Entities:  

Keywords:  epidemiology; health behaviour; mHealth; travel medicine

Mesh:

Year:  2017        PMID: 28931147     DOI: 10.1093/jtm/tax050

Source DB:  PubMed          Journal:  J Travel Med        ISSN: 1195-1982            Impact factor:   8.490


  7 in total

1.  Development and validation of a questionnaire to evaluate the knowledge, attitude and practices regarding travel medicine amongst physicians in an apex tertiary hospital in Northern India.

Authors:  Arvind Kumar; Anand Rajendran; Mohd Usman; Jatin Ahuja; Sameer Samad; Ankit Mittal; Prerna Garg; Upendra Baitha; Piyush Ranjan; Naveet Wig
Journal:  Trop Dis Travel Med Vaccines       Date:  2022-06-01

Review 2.  Measuring mobility, disease connectivity and individual risk: a review of using mobile phone data and mHealth for travel medicine.

Authors:  Shengjie Lai; Andrea Farnham; Nick W Ruktanonchai; Andrew J Tatem
Journal:  J Travel Med       Date:  2019-05-10       Impact factor: 8.490

3.  Research data management in health and biomedical citizen science: practices and prospects.

Authors:  Ann Borda; Kathleen Gray; Yuqing Fu
Journal:  JAMIA Open       Date:  2019-12-09

4.  Evaluation of a web-based self-reporting method for monitoring international passengers returning from an area of emerging infection.

Authors:  B Lefèvre; T Blanchon; P Saint-Martin; P Tattevin; D Che; E Caumes; T Pitel; L Rossignol; N Dournon; X Duval; B Hoen
Journal:  Infect Dis Now       Date:  2020-06-18

Review 5.  Possibilities, Problems, and Perspectives of Data Collection by Mobile Apps in Longitudinal Epidemiological Studies: Scoping Review.

Authors:  Florian Fischer; Sina Kleen
Journal:  J Med Internet Res       Date:  2021-01-22       Impact factor: 5.428

6.  The COVID-19 pandemic offers a key moment to reflect on travel medicine practice.

Authors:  Christoph Hatz; Silja Bühler; Andrea Farnham
Journal:  J Travel Med       Date:  2020-12-23       Impact factor: 8.490

Review 7.  SleepOMICS: How Big Data Can Revolutionize Sleep Science.

Authors:  Nicola Luigi Bragazzi; Ottavia Guglielmi; Sergio Garbarino
Journal:  Int J Environ Res Public Health       Date:  2019-01-21       Impact factor: 3.390

  7 in total

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