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Characteristics of smartphone-based dietary assessment tools: a systematic review.

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cam.depositDate2021-12-16
cam.issuedOnline2021-12-21
cam.orpheus.success2022-01-18 - Embargo set during processing via Fast-track
dc.contributor.authorKönig, Laura M
dc.contributor.authorVan Emmenis, Miranda
dc.contributor.authorNurmi, Johanna
dc.contributor.authorKassavou, Aikaterini
dc.contributor.authorSutton, Stephen
dc.contributor.orcidKönig, Laura M [0000-0003-3655-8842]
dc.contributor.orcidVan Emmenis, Miranda [0000-0002-4717-6746]
dc.contributor.orcidNurmi, Johanna [0000-0001-8414-3444]
dc.contributor.orcidKassavou, Aikaterini [0000-0002-6562-4143]
dc.contributor.orcidSutton, Stephen [0000-0003-1610-0404]
dc.date.accessioned2022-01-19T00:30:13Z
dc.date.available2022-01-19T00:30:13Z
dc.date.issued2022-12
dc.date.updated2021-12-16T08:01:06Z
dc.description.abstractSmartphones have become popular in assessing eating behaviour in real-life and real-time. This systematic review provides a comprehensive overview of smartphone-based dietary assessment tools, focusing on how dietary data is assessed and its completeness ensured. Seven databases from behavioural, social and computer science were searched in March 2020. All observational, experimental or intervention studies and study protocols using a smartphone-based assessment tool for dietary intake were included if they reported data collected by adults and were published in English. Out of 21,722 records initially screened, 117 publications using 129 tools were included. Five core assessment features were identified: photo-based assessment (48.8% of tools), assessed serving/ portion sizes (48.8%), free-text descriptions of food intake (42.6%), food databases (30.2%), and classification systems (27.9%). On average, a tool used two features. The majority of studies did not implement any features to improve completeness of the records. This review provides a comprehensive overview and framework of smartphone-based dietary assessment tools to help researchers identify suitable assessment tools for their studies. Future research needs to address the potential impact of specific dietary assessment methods on data quality and participants' willingness to record their behaviour to ultimately improve the quality of smartphone-based dietary assessment for health research.
dc.format.mediumPrint-Electronic
dc.identifier.doi10.17863/CAM.80209
dc.identifier.eissn1743-7202
dc.identifier.issn1743-7199
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/332773
dc.language.isoeng
dc.publisherInforma UK Limited
dc.publisher.departmentDepartment of Public Health And Primary Care, The Primary Care Unit
dc.publisher.urlhttp://dx.doi.org/10.1080/17437199.2021.2016066
dc.rightsAll Rights Reserved
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserved
dc.subjectEcological momentary assessment
dc.subjectdiet
dc.subjectdietary assessment
dc.subjecteating behaviour
dc.subjectmhealth
dc.subjectsmartphone
dc.subjectAdult
dc.subjectHumans
dc.subjectSmartphone
dc.subjectDiet
dc.subjectEating
dc.titleCharacteristics of smartphone-based dietary assessment tools: a systematic review.
dc.typeArticle
prism.endingPage99
prism.publicationDate2021
prism.publicationNameHealth Psychol Rev
prism.startingPage1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement
pubs.licence-identifierapollo-deposit-licence-2-1
rioxxterms.typeJournal Article/Review
rioxxterms.versionAM
rioxxterms.versionofrecord10.1080/17437199.2021.2016066

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