Crowdsourcing novel childhood predictors of adult obesity.

Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study exa...

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Autores principales:	Kirsten E Bevelander, Kirsikka Kaipainen, Robert Swain, Simone Dohle, Josh C Bongard, Paul D H Hines, Brian Wansink
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/288fe59f4c1e4124aa8db93b9e917359
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spelling	oai:doaj.org-article:288fe59f4c1e4124aa8db93b9e9173592021-11-18T08:33:43ZCrowdsourcing novel childhood predictors of adult obesity.1932-620310.1371/journal.pone.0087756https://doaj.org/article/288fe59f4c1e4124aa8db93b9e9173592014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24505310/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study examined whether crowdsourcing could generate well-documented predictors in obesity research and, moreover, whether new directions for future research could be uncovered. Participants were recruited through social media to a question-generation website, on which they answered questions and were able to pose new questions that they thought could predict obesity. During the two weeks of data collection, 532 participants (62% female; age = 26.5±6.7; BMI = 29.0±7.0) registered on the website and suggested a total of 56 unique questions. Nineteen of these questions correlated with body mass index (BMI) and covered several themes identified by prior research, such as parenting styles and healthy lifestyle. More importantly, participants were able to identify potential determinants that were related to a lower BMI, but have not been the subject of extensive research, such as parents packing their children's lunch to school or talking to them about nutrition. The findings indicate that crowdsourcing can reproduce already existing hypotheses and also generate ideas that are less well documented. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity. The questions generated by participants also suggest new ways to express known predictors.Kirsten E BevelanderKirsikka KaipainenRobert SwainSimone DohleJosh C BongardPaul D H HinesBrian WansinkPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 2, p e87756 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kirsten E Bevelander Kirsikka Kaipainen Robert Swain Simone Dohle Josh C Bongard Paul D H Hines Brian Wansink Crowdsourcing novel childhood predictors of adult obesity.
description	Effective and simple screening tools are needed to detect behaviors that are established early in life and have a significant influence on weight gain later in life. Crowdsourcing could be a novel and potentially useful tool to assess childhood predictors of adult obesity. This exploratory study examined whether crowdsourcing could generate well-documented predictors in obesity research and, moreover, whether new directions for future research could be uncovered. Participants were recruited through social media to a question-generation website, on which they answered questions and were able to pose new questions that they thought could predict obesity. During the two weeks of data collection, 532 participants (62% female; age = 26.5±6.7; BMI = 29.0±7.0) registered on the website and suggested a total of 56 unique questions. Nineteen of these questions correlated with body mass index (BMI) and covered several themes identified by prior research, such as parenting styles and healthy lifestyle. More importantly, participants were able to identify potential determinants that were related to a lower BMI, but have not been the subject of extensive research, such as parents packing their children's lunch to school or talking to them about nutrition. The findings indicate that crowdsourcing can reproduce already existing hypotheses and also generate ideas that are less well documented. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity. The questions generated by participants also suggest new ways to express known predictors.
format	article
author	Kirsten E Bevelander Kirsikka Kaipainen Robert Swain Simone Dohle Josh C Bongard Paul D H Hines Brian Wansink
author_facet	Kirsten E Bevelander Kirsikka Kaipainen Robert Swain Simone Dohle Josh C Bongard Paul D H Hines Brian Wansink
author_sort	Kirsten E Bevelander
title	Crowdsourcing novel childhood predictors of adult obesity.
title_short	Crowdsourcing novel childhood predictors of adult obesity.
title_full	Crowdsourcing novel childhood predictors of adult obesity.
title_fullStr	Crowdsourcing novel childhood predictors of adult obesity.
title_full_unstemmed	Crowdsourcing novel childhood predictors of adult obesity.
title_sort	crowdsourcing novel childhood predictors of adult obesity.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/288fe59f4c1e4124aa8db93b9e917359
work_keys_str_mv	AT kirstenebevelander crowdsourcingnovelchildhoodpredictorsofadultobesity AT kirsikkakaipainen crowdsourcingnovelchildhoodpredictorsofadultobesity AT robertswain crowdsourcingnovelchildhoodpredictorsofadultobesity AT simonedohle crowdsourcingnovelchildhoodpredictorsofadultobesity AT joshcbongard crowdsourcingnovelchildhoodpredictorsofadultobesity AT pauldhhines crowdsourcingnovelchildhoodpredictorsofadultobesity AT brianwansink crowdsourcingnovelchildhoodpredictorsofadultobesity
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Crowdsourcing novel childhood predictors of adult obesity.

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