A computer-based incentivized food basket choice tool: Presentation and evaluation
To develop and evaluate a low-cost computer-based tool to elicit dietary choices in an incentive compatible manner, which can be used on-line or as part of a laboratory study. The study was conducted with around 255 adults. Respondents were asked to allocate a fixed monetary budget across a choice o...
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description | To develop and evaluate a low-cost computer-based tool to elicit dietary choices in an incentive compatible manner, which can be used on-line or as part of a laboratory study.
The study was conducted with around 255 adults. Respondents were asked to allocate a fixed monetary budget across a choice of around a hundred grocery items with the prospect of receiving these items with some probability delivered to their home by a real supermarket. The tool covers a broad range of food items, allows inference of macro-nutrients and calories, and allows the researcher to fix the choice set participants can choose from. We compare the information derived from our incentivized tool, and compare it to alternative low-cost ways of measuring dietary intake, namely the food frequency questionnaire and a one-shot version of the 24-hour dietary recall, which are both based on self-reports. We compare the calorie intake indicators derived from each tool with a number of biometric measures for each subject, namely weight, body-mass-index (BMI) and waist size.
The results show that the dietary information collected is only weakly correlated across the three methods. We find that only the calorie intake measure from our incentivized tool is positively and significantly related to each of the biometric indicators. Specifically, a 10% increase in calorie intake is associated with a 1.5% increase in BMI. By contrast, we find no significant correlations for either of the two measures based on self-reports.
The computer-based tool is a promising new, low-cost measure of dietary choices, particularly in one-shot situations where such behaviours are only observed once, whereas other tools like 24-hour dietary recalls and food frequency questionnaires may be more suited when they are administered repeatedly. The tool may be useful for research conducted with limited time and budget. |
doi_str_mv | 10.1371/journal.pone.0210061 |
format | Article |
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The study was conducted with around 255 adults. Respondents were asked to allocate a fixed monetary budget across a choice of around a hundred grocery items with the prospect of receiving these items with some probability delivered to their home by a real supermarket. The tool covers a broad range of food items, allows inference of macro-nutrients and calories, and allows the researcher to fix the choice set participants can choose from. We compare the information derived from our incentivized tool, and compare it to alternative low-cost ways of measuring dietary intake, namely the food frequency questionnaire and a one-shot version of the 24-hour dietary recall, which are both based on self-reports. We compare the calorie intake indicators derived from each tool with a number of biometric measures for each subject, namely weight, body-mass-index (BMI) and waist size.
The results show that the dietary information collected is only weakly correlated across the three methods. We find that only the calorie intake measure from our incentivized tool is positively and significantly related to each of the biometric indicators. Specifically, a 10% increase in calorie intake is associated with a 1.5% increase in BMI. By contrast, we find no significant correlations for either of the two measures based on self-reports.
The computer-based tool is a promising new, low-cost measure of dietary choices, particularly in one-shot situations where such behaviours are only observed once, whereas other tools like 24-hour dietary recalls and food frequency questionnaires may be more suited when they are administered repeatedly. The tool may be useful for research conducted with limited time and budget.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0210061</identifier><identifier>PMID: 30629643</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adults ; Analysis ; Biology and Life Sciences ; Body mass ; Calories ; Choice (Psychology) ; Computational Biology - methods ; Cost-Benefit Analysis ; Diet ; Diet Records ; Diet Surveys - economics ; Diet Surveys - methods ; Dietary intake ; Economics ; Energy Intake - physiology ; Epidemiology ; Food ; Food intake ; Food Preferences - physiology ; General practitioners ; Health care ; Humans ; Indexing ; Indicators ; Laboratories ; Low cost ; Low income groups ; Management ; Medical research ; Medical sciences ; Medicine and Health Sciences ; Methods ; Nutrients ; Nutrition research ; Obesity ; Practice ; Preventive medicine ; Public health ; Reproducibility of Results ; Research and Analysis Methods ; Research methodology ; Researchers ; Supermarkets ; Weight</subject><ispartof>PloS one, 2019-01, Vol.14 (1), p.e0210061-e0210061</ispartof><rights>COPYRIGHT 2019 Public Library of Science</rights><rights>2019 Spiteri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2019 Spiteri et al 2019 Spiteri et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-655c88a1ab5f2c9577c06c59ac50c21596e32a90745b0336088125d70b7a7ac03</citedby><cites>FETCH-LOGICAL-c692t-655c88a1ab5f2c9577c06c59ac50c21596e32a90745b0336088125d70b7a7ac03</cites><orcidid>0000-0002-8206-1637</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328152/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328152/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30629643$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Buckland, Nicola</contributor><creatorcontrib>Spiteri, Jonathan</creatorcontrib><creatorcontrib>James, Jonathan</creatorcontrib><creatorcontrib>Belot, Michèle</creatorcontrib><title>A computer-based incentivized food basket choice tool: Presentation and evaluation</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>To develop and evaluate a low-cost computer-based tool to elicit dietary choices in an incentive compatible manner, which can be used on-line or as part of a laboratory study.
The study was conducted with around 255 adults. Respondents were asked to allocate a fixed monetary budget across a choice of around a hundred grocery items with the prospect of receiving these items with some probability delivered to their home by a real supermarket. The tool covers a broad range of food items, allows inference of macro-nutrients and calories, and allows the researcher to fix the choice set participants can choose from. We compare the information derived from our incentivized tool, and compare it to alternative low-cost ways of measuring dietary intake, namely the food frequency questionnaire and a one-shot version of the 24-hour dietary recall, which are both based on self-reports. We compare the calorie intake indicators derived from each tool with a number of biometric measures for each subject, namely weight, body-mass-index (BMI) and waist size.
The results show that the dietary information collected is only weakly correlated across the three methods. We find that only the calorie intake measure from our incentivized tool is positively and significantly related to each of the biometric indicators. Specifically, a 10% increase in calorie intake is associated with a 1.5% increase in BMI. By contrast, we find no significant correlations for either of the two measures based on self-reports.
The computer-based tool is a promising new, low-cost measure of dietary choices, particularly in one-shot situations where such behaviours are only observed once, whereas other tools like 24-hour dietary recalls and food frequency questionnaires may be more suited when they are administered repeatedly. The tool may be useful for research conducted with limited time and budget.</description><subject>Adults</subject><subject>Analysis</subject><subject>Biology and Life Sciences</subject><subject>Body mass</subject><subject>Calories</subject><subject>Choice (Psychology)</subject><subject>Computational Biology - methods</subject><subject>Cost-Benefit Analysis</subject><subject>Diet</subject><subject>Diet Records</subject><subject>Diet Surveys - economics</subject><subject>Diet Surveys - methods</subject><subject>Dietary intake</subject><subject>Economics</subject><subject>Energy Intake - physiology</subject><subject>Epidemiology</subject><subject>Food</subject><subject>Food intake</subject><subject>Food Preferences - physiology</subject><subject>General practitioners</subject><subject>Health care</subject><subject>Humans</subject><subject>Indexing</subject><subject>Indicators</subject><subject>Laboratories</subject><subject>Low cost</subject><subject>Low income groups</subject><subject>Management</subject><subject>Medical research</subject><subject>Medical sciences</subject><subject>Medicine and Health Sciences</subject><subject>Methods</subject><subject>Nutrients</subject><subject>Nutrition research</subject><subject>Obesity</subject><subject>Practice</subject><subject>Preventive medicine</subject><subject>Public health</subject><subject>Reproducibility of Results</subject><subject>Research and Analysis Methods</subject><subject>Research 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computer-based incentivized food basket choice tool: Presentation and evaluation</title><author>Spiteri, Jonathan ; James, Jonathan ; Belot, Michèle</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-655c88a1ab5f2c9577c06c59ac50c21596e32a90745b0336088125d70b7a7ac03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adults</topic><topic>Analysis</topic><topic>Biology and Life Sciences</topic><topic>Body mass</topic><topic>Calories</topic><topic>Choice (Psychology)</topic><topic>Computational Biology - methods</topic><topic>Cost-Benefit Analysis</topic><topic>Diet</topic><topic>Diet Records</topic><topic>Diet Surveys - economics</topic><topic>Diet Surveys - methods</topic><topic>Dietary intake</topic><topic>Economics</topic><topic>Energy Intake - physiology</topic><topic>Epidemiology</topic><topic>Food</topic><topic>Food intake</topic><topic>Food Preferences - 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Presentation and evaluation</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2019-01-10</date><risdate>2019</risdate><volume>14</volume><issue>1</issue><spage>e0210061</spage><epage>e0210061</epage><pages>e0210061-e0210061</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>To develop and evaluate a low-cost computer-based tool to elicit dietary choices in an incentive compatible manner, which can be used on-line or as part of a laboratory study.
The study was conducted with around 255 adults. Respondents were asked to allocate a fixed monetary budget across a choice of around a hundred grocery items with the prospect of receiving these items with some probability delivered to their home by a real supermarket. The tool covers a broad range of food items, allows inference of macro-nutrients and calories, and allows the researcher to fix the choice set participants can choose from. We compare the information derived from our incentivized tool, and compare it to alternative low-cost ways of measuring dietary intake, namely the food frequency questionnaire and a one-shot version of the 24-hour dietary recall, which are both based on self-reports. We compare the calorie intake indicators derived from each tool with a number of biometric measures for each subject, namely weight, body-mass-index (BMI) and waist size.
The results show that the dietary information collected is only weakly correlated across the three methods. We find that only the calorie intake measure from our incentivized tool is positively and significantly related to each of the biometric indicators. Specifically, a 10% increase in calorie intake is associated with a 1.5% increase in BMI. By contrast, we find no significant correlations for either of the two measures based on self-reports.
The computer-based tool is a promising new, low-cost measure of dietary choices, particularly in one-shot situations where such behaviours are only observed once, whereas other tools like 24-hour dietary recalls and food frequency questionnaires may be more suited when they are administered repeatedly. The tool may be useful for research conducted with limited time and budget.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>30629643</pmid><doi>10.1371/journal.pone.0210061</doi><orcidid>https://orcid.org/0000-0002-8206-1637</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adults Analysis Biology and Life Sciences Body mass Calories Choice (Psychology) Computational Biology - methods Cost-Benefit Analysis Diet Diet Records Diet Surveys - economics Diet Surveys - methods Dietary intake Economics Energy Intake - physiology Epidemiology Food Food intake Food Preferences - physiology General practitioners Health care Humans Indexing Indicators Laboratories Low cost Low income groups Management Medical research Medical sciences Medicine and Health Sciences Methods Nutrients Nutrition research Obesity Practice Preventive medicine Public health Reproducibility of Results Research and Analysis Methods Research methodology Researchers Supermarkets Weight |
title | A computer-based incentivized food basket choice tool: Presentation and evaluation |
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