Image-Based Dietary Assessment and Tailored Feedback Using Mobile Technology: Mediating Behavior Change in Young Adults

Charlene L Shoneye¹, Satvinder S Dhaliwal², Christina M Pollard^{3

4}, Carol J Boushey^{5

6}, Edward J Delp⁷, Amelia J Harray⁸, Peter A Howat⁹, Melinda J Hutchesson¹⁰, Megan E Rollo¹¹, Fengqing Zhu¹², Janine L Wright¹³, Iain S Pratt^{14

15}, Jonine Jancey¹⁶, Rhiannon E Halse¹⁷, Jane A Scott¹⁸, Barbara Mullan¹⁹, Clare E Collins²⁰, Deborah A Kerr²¹

Affiliations

¹ School of Public Health, Curtin University, Perth, WA 6845, Australia. charlene.shoneye@curtin.edu.au.
² School of Public Health, Curtin University, Perth, WA 6845, Australia. S.Dhaliwal@curtin.edu.au.
³ School of Public Health, Curtin University, Perth, WA 6845, Australia. c.pollard@curtin.edu.au.
⁴ East Metropolitan Health Service, Perth, WA 6845, Australia. c.pollard@curtin.edu.au.
⁵ Epidemiology Program, University of Hawaii Cancer Centre, Honolulu, HI 96813, USA. cjboushey@cc.hawaii.edu.
⁶ Department of Nutrition, Purdue University, West Lafayette, IN 47907, USA. cjboushey@cc.hawaii.edu.
⁷ School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA. ace@ecn.purdue.edu.
⁸ School of Public Health, Curtin University, Perth, WA 6845, Australia. amelia.harray@curtin.edu.au.
⁹ School of Public Health, Curtin University, Perth, WA 6845, Australia. p.howat@curtin.edu.au.
¹⁰ School of Health Sciences and Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2308, Australia. melinda.hutchesson@newcastle.edu.au.
¹¹ School of Health Sciences and Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2308, Australia. megan.rollo@newcastle.edu.au.
¹² School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA. zhu0@ecn.purdue.edu.
¹³ School of Public Health, Curtin University, Perth, WA 6845, Australia. J.Wright@exchange.curtin.edu.au.
¹⁴ Cancer Council Western Australia, Subiaco, WA 6008, Australia. SPratt@cancerwa.asn.au.
¹⁵ Western Australian Cancer Prevention Research Unit (WACPRU), School of Psychology, Curtin University, Perth, WA 6845, Australia. SPratt@cancerwa.asn.au.
¹⁶ School of Public Health, Curtin University, Perth, WA 6845, Australia. J.Jancey@curtin.edu.au.
¹⁷ School of Public Health, Curtin University, Perth, WA 6845, Australia. rhiannon.halse@curtin.edu.au.
¹⁸ School of Public Health, Curtin University, Perth, WA 6845, Australia. jane.scott@curtin.edu.au.
¹⁹ Health Psychology & Behavioural Medicine Research Group, School of Psychology, Curtin University, Perth, WA 6845, Australia. Barbara.mullan@curtin.edu.au.
²⁰ School of Health Sciences and Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2308, Australia. clare.collins@newcastle.edu.au.
²¹ School of Public Health, Curtin University, Perth, WA 6845, Australia. d.kerr@curtin.edu.au.

PMID: 30791502
PMCID: PMC6412987
DOI: 10.3390/nu11020435

Image-Based Dietary Assessment and Tailored Feedback Using Mobile Technology: Mediating Behavior Change in Young Adults

Charlene L Shoneye et al. Nutrients. 2019.

. 2019 Feb 19;11(2):435.

doi: 10.3390/nu11020435.

Authors

Affiliations

¹ School of Public Health, Curtin University, Perth, WA 6845, Australia. charlene.shoneye@curtin.edu.au.
² School of Public Health, Curtin University, Perth, WA 6845, Australia. S.Dhaliwal@curtin.edu.au.
³ School of Public Health, Curtin University, Perth, WA 6845, Australia. c.pollard@curtin.edu.au.
⁴ East Metropolitan Health Service, Perth, WA 6845, Australia. c.pollard@curtin.edu.au.
⁵ Epidemiology Program, University of Hawaii Cancer Centre, Honolulu, HI 96813, USA. cjboushey@cc.hawaii.edu.
⁶ Department of Nutrition, Purdue University, West Lafayette, IN 47907, USA. cjboushey@cc.hawaii.edu.
⁷ School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA. ace@ecn.purdue.edu.
⁸ School of Public Health, Curtin University, Perth, WA 6845, Australia. amelia.harray@curtin.edu.au.
⁹ School of Public Health, Curtin University, Perth, WA 6845, Australia. p.howat@curtin.edu.au.
¹⁰ School of Health Sciences and Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2308, Australia. melinda.hutchesson@newcastle.edu.au.
¹¹ School of Health Sciences and Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2308, Australia. megan.rollo@newcastle.edu.au.
¹² School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA. zhu0@ecn.purdue.edu.
¹³ School of Public Health, Curtin University, Perth, WA 6845, Australia. J.Wright@exchange.curtin.edu.au.
¹⁴ Cancer Council Western Australia, Subiaco, WA 6008, Australia. SPratt@cancerwa.asn.au.
¹⁵ Western Australian Cancer Prevention Research Unit (WACPRU), School of Psychology, Curtin University, Perth, WA 6845, Australia. SPratt@cancerwa.asn.au.
¹⁶ School of Public Health, Curtin University, Perth, WA 6845, Australia. J.Jancey@curtin.edu.au.
¹⁷ School of Public Health, Curtin University, Perth, WA 6845, Australia. rhiannon.halse@curtin.edu.au.
¹⁸ School of Public Health, Curtin University, Perth, WA 6845, Australia. jane.scott@curtin.edu.au.
¹⁹ Health Psychology & Behavioural Medicine Research Group, School of Psychology, Curtin University, Perth, WA 6845, Australia. Barbara.mullan@curtin.edu.au.
²⁰ School of Health Sciences and Priority Research Centre in Physical Activity and Nutrition, Faculty of Health and Medicine, University of Newcastle, Newcastle, NSW 2308, Australia. clare.collins@newcastle.edu.au.
²¹ School of Public Health, Curtin University, Perth, WA 6845, Australia. d.kerr@curtin.edu.au.

PMID: 30791502
PMCID: PMC6412987
DOI: 10.3390/nu11020435

Abstract

Assessing the implementation of nutrition interventions is important to identify characteristics and dietary patterns of individuals who benefit most. The aim was to report on young adults' experiences of receiving dietary feedback text messaging intervention. Diet was captured using an image-based 4-day mobile food record^TM application (mFR^TM) and assessed to formulate two tailored feedback text messages on fruit and vegetables and energy-dense nutrient-poor (EDNP) foods and beverages. At 6-months 143 participants completed a second mFR^TM and a questionnaire evaluating the dietary feedback. Participants who agreed the text messages made them think about how much vegetables they ate were more likely to increase their intake by at least half a serve than those who disagreed [odds ratio (OR) = 4.28, 95% Confidence Interval (CI): 1.76 to 10.39]. Those who agreed the text messages made them think about how much EDNP foods they ate, were twice as likely to decrease their intake by over half a serve (OR = 2.39, 95%CI: 1.12 to 5.25) than those who disagreed. Undertaking detailed dietary assessment ensured the tailored feedback was constructive and relevant. Personal contemplation about vegetable and EDNP food intake appears to be a mediator of dietary change in young adults.

Keywords: alcohol; image-based dietary assessment; junk food; mobile food record; sugar-sweetened beverages; tailored feedback; tailoring; technology intervention; text messaging; vegetables; young adult.

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Conflict of interest statement

The authors do not have any competing interests. The study was funded by Healthway who did not have any role in the study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication.

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Image-Based Dietary Assessment and Tailored Feedback Using Mobile Technology: Mediating Behavior Change in Young Adults

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Image-Based Dietary Assessment and Tailored Feedback Using Mobile Technology: Mediating Behavior Change in Young Adults

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