Effects of Recording Food Intake Using Cell Phone Camera Pictures on Energy Intake and Food Choice

Doumit, Rita; Long, JoAnn D.; Kazandjian, Chant; Gharibeh, Nathalie; Karam, Lina; Song, Huaxin; Boswell, Carol; Zeeni, Nadine

doi:10.1111/wvn.12123

Cited by 15 publications

(16 citation statements)

References 25 publications

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“…A sub-theme that arose from survey responses was that the act of keeping a dietary record increased participants’ awareness of the food they ate. The findings of DBBB are mirrored in other studies where participants have reported increased awareness of foods or portion sizes consumed as a result of capturing images of food intake [ 40 ]. Participation in the DietBytes study may have created a teachable moment, by motivating women to consider dietary changes, and previous research has demonstrated that pregnancy is a time period when women may gain an increased awareness of their dietary intake [ 41 ] and be more receptive towards engaging in healthy eating behaviors [ 42 ].…”

Section: Discussionsupporting

confidence: 67%

Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

Ashman

Collins

Brown³

et al. 2017

Nutrients

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Image-based dietary records could lower participant burden associated with traditional prospective methods of dietary assessment. They have been used in children, adolescents and adults, but have not been evaluated in pregnant women. The current study evaluated relative validity of the DietBytes image-based dietary assessment method for assessing energy and nutrient intakes. Pregnant women collected image-based dietary records (via a smartphone application) of all food, drinks and supplements consumed over three non-consecutive days. Intakes from the image-based method were compared to intakes collected from three 24-h recalls, taken on random days; once per week, in the weeks following the image-based record. Data were analyzed using nutrient analysis software. Agreement between methods was ascertained using Pearson correlations and Bland-Altman plots. Twenty-five women (27 recruited, one withdrew, one incomplete), median age 29 years, 15 primiparas, eight Aboriginal Australians, completed image-based records for analysis. Significant correlations between the two methods were observed for energy, macronutrients and fiber (r = 0.58–0.84, all p < 0.05), and for micronutrients both including (r = 0.47–0.94, all p < 0.05) and excluding (r = 0.40–0.85, all p < 0.05) supplements in the analysis. Bland-Altman plots confirmed acceptable agreement with no systematic bias. The DietBytes method demonstrated acceptable relative validity for assessment of nutrient intakes of pregnant women.

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Section: Discussionsupporting

confidence: 67%

Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

Ashman

Collins

Brown³

et al. 2017

Nutrients

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“…Recent studies using RFPM conducted in pregnant women and preschoolers with obesity found that this method was not accurate in estimating energy intake compared to doubly labeled water [29,30]. Doumit et al conducted a cross-over study in college students, mostly of normal weight, to examine the effects of recording food intake from memory or with the aid of cell phone photos on energy intake and food choices [31]. They reported a nonsignificant trend for lower energy intake in the group using cell phone photos, suggesting increased awareness of food choice and portion size.…”

Section: Introductionmentioning

confidence: 99%

Weight Loss Following Use of a Smartphone Food Photo Feature: Retrospective Cohort Study

Neriah

Geliebter

2019

JMIR Mhealth Uhealth

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Background Tracking of dietary intake is key to enhancing weight loss. Mobile apps may be useful for tracking food intake and can provide feedback about calories and nutritional value. Recent technological developments have enabled image recognition to identify foods and track food intake. Objective We aimed to determine the effectiveness of using photography as a feature of a smartphone weight loss app to track food intake in adults who were overweight or obese. Methods We analyzed data from individuals (age, 18-65 years; body mass index≥25 kg/m2; ≥4 days of logged food intake; and ≥2 weigh-ins) who used a mobile-based weight loss app. In a retrospective study, we compared those who used the photo feature (n=9871) and those who did not use the feature (n=113,916). Linear regression analyses were used to assess use of the photo feature in relation to percent weight loss. Results Weight loss was greater in the group using the photo feature (Δ=0.14%; 95% CI 0.06-0.22; P<.001). The photo feature group used the weight loss app for a longer duration (+3.5 days; 95% CI 2.61-4.37; P<.001) and logged their food intake on more days (+6.1 days; 95% CI 5.40-6.77; P<.001) than the nonusers. Mediation analysis showed that the weight loss effect was absent when controlling for either duration or number of logged days in the program. Conclusions This study was the first to examine the effect of a food photo feature to track food intake on weight loss in a free-living setting. Use of photo recognition was associated with greater weight loss, which was mediated by the duration of app use and number of logged days in the program.

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“…Of the remaining 15 studies, four (27%) explicitly discuss dropout, reporting dropout rates of 7% (Epstein, Cordeiro, Bales, Fogarty, & Munson, 2014), 17% (Khovanskaya et al, 2013), 19% (Doumit et al, 2015), and 44% (Park et al, 2015). In nine studies (60%), dropout rates were not explicitly reported, but results imply that all participants completed the study (i.e., 0% dropout).…”

Section: Study Duration Dropout and System Usagementioning

confidence: 99%

“…Most systems provided anywhere, anytime access to data and feedback via a mobile app, whereas others used an application intended for desktop use (e.g., Collins, Cox, Bird, & Cornish-Tresstail, 2014;Doumit et al, 2015;Khovanskaya, Baumer, Cosley, Voida, & Gay, 2013). How and when data were accessible in the systems used by existing PI users was generally not reported on.…”

Section: Features and Use Of Evaluated Systemsmentioning

confidence: 99%

“…Similarly, some of De Maeyer and Jacobs's (2013) participants became aware of how active they were, in either a positive (more than they thought) or negative (less than they thought) sense. In the study by Doumit et al (2015), participants became aware of portion sizes of food consumed through food tracking. Hori et al (2013) also noted that most of their participants became aware of the parameter that was being tracked-in this case, smiling.…”

Section: Consciousness Raisingmentioning

confidence: 99%

See 1 more Smart Citation

Personal Informatics, Self-Insight, and Behavior Change: A Critical Review of Current Literature

Dijk

Westerink

Beute

et al. 2017

Human–Computer Interaction

117

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Personal informatics (PI) systems allow users to collect and review personally relevant information. The purpose commonly envisioned for these systems is that they provide users with actionable, data-driven selfinsight to help them change their behavioral patterns for the better. Here, we review relevant theory as well as empirical evidence for this selfimprovement hypothesis. From a corpus of 6,568, only 24 studies met the selection criteria of being a peer-reviewed empirical study reporting on actionable, data-driven insights from PI data, using a "clean" PI system with no other intervention techniques (e.g., additional coaching) on a nonclinical population. First results are promising-many of the selected articles report users gaining actionable insights-but we do note a number of methodological issues that make these results difficult to interpret. We conclude that more work is needed to investigate the self-improvement hypothesis and provide a set of recommendations for future work.

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Effects of Recording Food Intake Using Cell Phone Camera Pictures on Energy Intake and Food Choice

Abstract: Cell phone pictures may be an easy, relevant, and accessible method of diet self-monitoring when aiming at dietary changes. Future trials should combine this technique with healthy eating education.

Cited by 15 publications

References 25 publications

Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

Weight Loss Following Use of a Smartphone Food Photo Feature: Retrospective Cohort Study

Personal Informatics, Self-Insight, and Behavior Change: A Critical Review of Current Literature

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