Crowdsourcing childhood predictors of adult obesity
Number of pages
SourceAppetite, 101, (2016), pp. 228
Article / Letter to editor
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SW OZ BSI CW
SubjectCommunication and Media
The 39th Annual Meeting of the British Feeding and Drinking Group. What would happen if you asked real, non-expert people what factors they believed most contributed to how slim or overweight they are as adults? Would the answers provide insights into eating behaviors that experts may not have considered? 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 that was developed for the study, 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: M = 26.5, SD = 6.7; BMI: M = 29.0 SD = 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 yet been the subject of extensive research, such as parents packing their children's lunch to school or talking to them about nutrition. The findings indicated that crowdsourcing can reproduce already existing hypotheses. Moreover, it has the potential to identify new areas of study that may need more attention among experts in the future. The crowdsourced predictors discovered in this study emphasize the importance of family interventions to fight obesity.
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