Literature DB >> 25851185

Assessing work-asthma interaction with Amazon Mechanical Turk.

Philip Harber1, Gondy Leroy.   

Abstract

OBJECTIVES: To illustrate the utility of crowdsourcing for occupational health surveillance.
METHODS: Amazon Mechanical Turk was used to recruit and obtain information from employed persons with asthma, who answered questions about work-asthma interactions.
RESULTS: Data collection from 60 subjects required only a few hours. Participants spent on average 7 minutes responding to seven questions (one optional) and used an average of 708 words. Work exacerbation, interference of asthma with work, and suggested workplace accommodation are frequent (83% reported at least one interaction).
CONCLUSIONS: The full spectrum of work-asthma interactions should be considered. Modern crowdsourcing methods have considerable potential as occupational health surveillance tools because of their effectiveness; efficiency and financial viability are additional important advantages.

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Mesh:

Year:  2015        PMID: 25851185     DOI: 10.1097/JOM.0000000000000360

Source DB:  PubMed          Journal:  J Occup Environ Med        ISSN: 1076-2752            Impact factor:   2.162


  5 in total

Review 1.  Comparing Amazon's Mechanical Turk Platform to Conventional Data Collection Methods in the Health and Medical Research Literature.

Authors:  Karoline Mortensen; Taylor L Hughes
Journal:  J Gen Intern Med       Date:  2018-01-04       Impact factor: 5.128

2.  Sun Protection Belief Clusters: Analysis of Amazon Mechanical Turk Data.

Authors:  Marimer Santiago-Rivas; Julie B Schnur; Lina Jandorf
Journal:  J Cancer Educ       Date:  2016-12       Impact factor: 2.037

Review 3.  The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations.

Authors:  Laura M Schwab-Reese; Wendy Hovdestad; Lil Tonmyr; John Fluke
Journal:  Child Abuse Negl       Date:  2018-02-01

4.  Temporal preference in individuals reporting chronic pain: discounting of delayed pain-related and monetary outcomes.

Authors:  D Andrew Tompkins; Patrick S Johnson; Michael T Smith; Eric C Strain; Robert R Edwards; Matthew W Johnson
Journal:  Pain       Date:  2016-08       Impact factor: 7.926

5.  Mapping of Crowdsourcing in Health: Systematic Review.

Authors:  Perrine Créquit; Ghizlène Mansouri; Mehdi Benchoufi; Alexandre Vivot; Philippe Ravaud
Journal:  J Med Internet Res       Date:  2018-05-15       Impact factor: 5.428

  5 in total

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