Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review
BackgroundPoor diet, alcohol use, and tobacco smoking have been identified as strong determinants of chronic diseases, such as cardiovascular disease, diabetes, and cancer. Smartphones have the potential to provide a real-time, pervasive, unobtrusive, and cost-effective way t...
| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2022-02-01
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| Series: | JMIR mHealth and uHealth |
| Online Access: | https://mhealth.jmir.org/2022/2/e27337 |
| _version_ | 1827858629501386752 |
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| author | Louise Thornton Bridie Osman Katrina Champion Olivia Green Annie B Wescott Lauren A Gardner Courtney Stewart Rachel Visontay Jesse Whife Belinda Parmenter Louise Birrell Zachary Bryant Cath Chapman David Lubans Tim Slade John Torous Maree Teesson Pepijn Van de Ven |
| author_facet | Louise Thornton Bridie Osman Katrina Champion Olivia Green Annie B Wescott Lauren A Gardner Courtney Stewart Rachel Visontay Jesse Whife Belinda Parmenter Louise Birrell Zachary Bryant Cath Chapman David Lubans Tim Slade John Torous Maree Teesson Pepijn Van de Ven |
| author_sort | Louise Thornton |
| collection | DOAJ |
| description |
BackgroundPoor diet, alcohol use, and tobacco smoking have been identified as strong determinants of chronic diseases, such as cardiovascular disease, diabetes, and cancer. Smartphones have the potential to provide a real-time, pervasive, unobtrusive, and cost-effective way to measure these health behaviors and deliver instant feedback to users. Despite this, the validity of using smartphones to measure these behaviors is largely unknown.
ObjectiveThe aim of our review is to identify existing smartphone-based approaches to measure these health behaviors and critically appraise the quality of their measurement properties.
MethodsWe conducted a systematic search of the Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsycINFO (EBSCOhost), CINAHL (EBSCOHost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost), and IEEE Xplore Digital Library databases in March 2020. Articles that were written in English; reported measuring diet, alcohol use, or tobacco use via a smartphone; and reported on at least one measurement property (eg, validity, reliability, and responsiveness) were eligible. The methodological quality of the included studies was assessed using the Consensus-Based Standards for the Selection of Health Measurement Instruments Risk of Bias checklist. Outcomes were summarized in a narrative synthesis. This systematic review was registered with PROSPERO, identifier CRD42019122242.
ResultsOf 12,261 records, 72 studies describing the measurement properties of smartphone-based approaches to measure diet (48/72, 67%), alcohol use (16/72, 22%), and tobacco use (8/72, 11%) were identified and included in this review. Across the health behaviors, 18 different measurement techniques were used in smartphones. The measurement properties most commonly examined were construct validity, measurement error, and criterion validity. The results varied by behavior and measurement approach, and the methodological quality of the studies varied widely. Most studies investigating the measurement of diet and alcohol received very good or adequate methodological quality ratings, that is, 73% (35/48) and 69% (11/16), respectively, whereas only 13% (1/8) investigating the measurement of tobacco use received a very good or adequate rating.
ConclusionsThis review is the first to provide evidence regarding the different types of smartphone-based approaches currently used to measure key behavioral risk factors for chronic diseases (diet, alcohol use, and tobacco use) and the quality of their measurement properties. A total of 19 measurement techniques were identified, most of which assessed dietary behaviors (48/72, 67%). Some evidence exists to support the reliability and validity of using smartphones to assess these behaviors; however, the results varied by behavior and measurement approach. The methodological quality of the included studies also varied. Overall, more high-quality studies validating smartphone-based approaches against criterion measures are needed. Further research investigating the use of smartphones to assess alcohol and tobacco use and objective measurement approaches is also needed.
International Registered Report Identifier (IRRID)RR2-10.1186/s13643-020-01375-w |
| first_indexed | 2024-03-12T12:56:55Z |
| format | Article |
| id | doaj.art-db20f24a18d84e2d9d804da3a768e29b |
| institution | Directory Open Access Journal |
| issn | 2291-5222 |
| language | English |
| last_indexed | 2024-03-12T12:56:55Z |
| publishDate | 2022-02-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR mHealth and uHealth |
| spelling | doaj.art-db20f24a18d84e2d9d804da3a768e29b2023-08-28T20:49:46ZengJMIR PublicationsJMIR mHealth and uHealth2291-52222022-02-01102e2733710.2196/27337Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic ReviewLouise Thorntonhttps://orcid.org/0000-0001-7705-833XBridie Osmanhttps://orcid.org/0000-0002-4286-6844Katrina Championhttps://orcid.org/0000-0001-8319-9366Olivia Greenhttps://orcid.org/0000-0002-3412-260XAnnie B Wescotthttps://orcid.org/0000-0001-7458-3251Lauren A Gardnerhttps://orcid.org/0000-0002-8592-6691Courtney Stewarthttps://orcid.org/0000-0002-7713-9524Rachel Visontayhttps://orcid.org/0000-0002-0693-1012Jesse Whifehttps://orcid.org/0000-0003-1951-5365Belinda Parmenterhttps://orcid.org/0000-0001-8013-5658Louise Birrellhttps://orcid.org/0000-0002-1335-1382Zachary Bryanthttps://orcid.org/0000-0002-2115-1516Cath Chapmanhttps://orcid.org/0000-0002-2460-6862David Lubanshttps://orcid.org/0000-0002-0204-8257Tim Sladehttps://orcid.org/0000-0002-1725-9188John Toroushttps://orcid.org/0000-0002-5362-7937Maree Teessonhttps://orcid.org/0000-0002-6744-463XPepijn Van de Venhttps://orcid.org/0000-0003-3321-450X BackgroundPoor diet, alcohol use, and tobacco smoking have been identified as strong determinants of chronic diseases, such as cardiovascular disease, diabetes, and cancer. Smartphones have the potential to provide a real-time, pervasive, unobtrusive, and cost-effective way to measure these health behaviors and deliver instant feedback to users. Despite this, the validity of using smartphones to measure these behaviors is largely unknown. ObjectiveThe aim of our review is to identify existing smartphone-based approaches to measure these health behaviors and critically appraise the quality of their measurement properties. MethodsWe conducted a systematic search of the Ovid MEDLINE, Embase (Elsevier), Cochrane Library (Wiley), PsycINFO (EBSCOhost), CINAHL (EBSCOHost), Web of Science (Clarivate), SPORTDiscus (EBSCOhost), and IEEE Xplore Digital Library databases in March 2020. Articles that were written in English; reported measuring diet, alcohol use, or tobacco use via a smartphone; and reported on at least one measurement property (eg, validity, reliability, and responsiveness) were eligible. The methodological quality of the included studies was assessed using the Consensus-Based Standards for the Selection of Health Measurement Instruments Risk of Bias checklist. Outcomes were summarized in a narrative synthesis. This systematic review was registered with PROSPERO, identifier CRD42019122242. ResultsOf 12,261 records, 72 studies describing the measurement properties of smartphone-based approaches to measure diet (48/72, 67%), alcohol use (16/72, 22%), and tobacco use (8/72, 11%) were identified and included in this review. Across the health behaviors, 18 different measurement techniques were used in smartphones. The measurement properties most commonly examined were construct validity, measurement error, and criterion validity. The results varied by behavior and measurement approach, and the methodological quality of the studies varied widely. Most studies investigating the measurement of diet and alcohol received very good or adequate methodological quality ratings, that is, 73% (35/48) and 69% (11/16), respectively, whereas only 13% (1/8) investigating the measurement of tobacco use received a very good or adequate rating. ConclusionsThis review is the first to provide evidence regarding the different types of smartphone-based approaches currently used to measure key behavioral risk factors for chronic diseases (diet, alcohol use, and tobacco use) and the quality of their measurement properties. A total of 19 measurement techniques were identified, most of which assessed dietary behaviors (48/72, 67%). Some evidence exists to support the reliability and validity of using smartphones to assess these behaviors; however, the results varied by behavior and measurement approach. The methodological quality of the included studies also varied. Overall, more high-quality studies validating smartphone-based approaches against criterion measures are needed. Further research investigating the use of smartphones to assess alcohol and tobacco use and objective measurement approaches is also needed. International Registered Report Identifier (IRRID)RR2-10.1186/s13643-020-01375-whttps://mhealth.jmir.org/2022/2/e27337 |
| spellingShingle | Louise Thornton Bridie Osman Katrina Champion Olivia Green Annie B Wescott Lauren A Gardner Courtney Stewart Rachel Visontay Jesse Whife Belinda Parmenter Louise Birrell Zachary Bryant Cath Chapman David Lubans Tim Slade John Torous Maree Teesson Pepijn Van de Ven Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review JMIR mHealth and uHealth |
| title | Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review |
| title_full | Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review |
| title_fullStr | Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review |
| title_full_unstemmed | Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review |
| title_short | Measurement Properties of Smartphone Approaches to Assess Diet, Alcohol Use, and Tobacco Use: Systematic Review |
| title_sort | measurement properties of smartphone approaches to assess diet alcohol use and tobacco use systematic review |
| url | https://mhealth.jmir.org/2022/2/e27337 |
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