Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study

May combine two claims.

Half (50.45%) of users with Strict diets were Semi-active or Active, a significantly higher proportion than among users who had not defined their diets.

“A similar trend was observed when Semi-active users were included in the comparisons: half (50.45%, 3174/6291) of the users with Strict diets were Semi-active or Active, a significantly higher proportion than among users who had not defined their diets.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Of all ratings given, users in the Not defined diet group gave 21.81%, the Everything group 52.83%, the Strict group 20.70%, and the Other group 4.66%.

“users in the “Not defined” diet group gave 21.81% (1,732,976/7,946,447) of all ratings, users in the “Everything” group gave 52.83% (4,198,272/7,946,447), users with Strict diets gave 20.70% (1,645,134/7,946,447), and users with some Other diet gave 4.66% (370,065/7,946,447) of all ratings.”

May combine two claims.

Active users had a higher average healthiness rating and a higher proportion of pictures with comments and likes than less active users.

“Small but significant differences were found between Active and less active users for all variables: the average healthiness rating was higher and the proportion of pictures having comments and likes was higher.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The average healthiness rating of valid pictures was 0.58, slightly above the midpoint of the fat-fit scale from 0 to 1.

“Their average healthiness rating, 0.58, was slightly above the midpoint of the fat-fit scale from 0 to 1.”

May combine two claims.

Most users did not take any pictures (69%) or took only one picture (17%).

“Most of the users did not take any pictures (69%) or took only one picture (17%), which means that they only downloaded the app and experimented with it once without starting dietary self-monitoring.”

May combine two claims.

Almost 190,000 people downloaded The Eatery between October 2011 and April 2012, but less than 3% were active users (used the app for more than a week and took 10 or more food pictures).

“Almost 190,000 people downloaded the app, The Eatery, between October 2011 and April 2012, but attrition was very high: less than 3% were active users, that is, used the app for more than a week and took 10 or more food pictures.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Most common dietary preferences reported by users during first use were "I eat everything" (46.33%) or undefined (42.22%).

“Most common dietary preferences (see Table 2) reported by users during the first use of the app were “I eat everything” (46.33%) or undefined (42.22%).”

May combine two claims.

Initiation of self-monitoring in the middle of the week during daytime and the amount of feedback from peers were connected to higher adherence.

“Moreover, initiation of self-monitoring in the middle of the week during daytime and the amount of feedback from peers were connected to higher adherence.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Differences in users' ideas about what healthy or fit food is do not seem to have influenced adherence in this study.

“People may also have very different ideas about what healthy or “fit” food is, but these differences do not seem to have influenced adherence in this study.”

May combine two claims.

More than half of active users (53%) gave a textual description for their first picture whereas less than one-fifth of non-active users (18%) did so.

“This is supported by the finding that more than half of the active users (53%) gave a textual description for their first picture whereas less than one-fifth of the non-active users (18%) did so.”

May combine two claims.

Although active users obtained more comments and likes than those who took only few pictures, the total percentage of pictures with comments (4%) and likes (15%) was quite low.

“Although active users obtained more comments and likes for their pictures from peers than those who took only few pictures, the total percentage of pictures with comments (4%) and likes (15%) was quite low.”

May combine two claims.

Users with strict diets gave 21% of all ratings although only 9% of all users belonged to the strict group.

“They also gave 21% of all ratings, although only 9% of all users belonged to the strict group.”

• AssumptionRests on an assumption: Users' self-reported dietary preferences accurately reflect their actual diets.

Probably not a substantial claim: may not pass S4 (based).

As with most mobile apps, the majority of users tried the dietary self-monitoring app only once.

“As with most mobile apps, the majority of users tried the dietary self-monitoring app only once.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Although the difference between the user's own rating and average peer ratings was highest among active users, in practice this difference was very small.

“Although the difference between the user’s own rating and average peer ratings was highest among active users, in practice this difference was very small.”

Probably not a substantial claim: may not pass S2 (checkable).

Self-monitoring of food intake is a recommended behavioral strategy in weight control and improvement of dietary habits.

“On an individual level, one behavioral strategy recommended in weight control and improvement of dietary habits is self-monitoring of food intake [2,3].”

• cites [2] National Institute of Health (NIH)Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report19982013-11-04Bethesda, MDNational Heart, Lung, and Blood Institutehttp://www.nhlbi.nih.gov/guidelines/obesity/prctgd_c.pdf6KsKK0SU3Not checked yet

  Not checked in the free run.

• cites [3] sourceNot checked yet

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Classified as probably not a substantial claim.

Knowledge about healthy eating is not sufficient on its own to change eating behavior.

“Knowledge about healthy eating is not sufficient on its own to change eating behavior [1].”

• cites [1] Contento, I, 1995, Journal of Nutrition EducationNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

Smartphones and photography can be used to make self-monitoring easy and convenient.

“Smartphones and photography can be used to make self-monitoring easy and convenient [6-9].”

• cites [6] sourceNot checked yet

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• cites [7] Glanz, K, 2006, Am J Health Promot sourceNot checked yet

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• cites [8] sourceNot checked yet

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• cites [9] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

In a free online weight loss program, more frequent weight monitoring was associated with greater weight loss.

“Another study on members of a free online weight loss program found that more frequent weight monitoring was associated with greater weight loss, but no association was found between dietary monitoring frequency and weight loss [13].”

• cites [13] sourceNot checked yet

  Not checked in the free run.

May combine two claims.

Traditional dietary self-monitoring methods suffer from underreporting and recall issues.

“These methods can be burdensome to people [6,7,15-17] and suffer from underreporting and recall issues [15-19].”

• cites [15] sourceNot checked yet

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• cites [16] sourceNot checked yet

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• cites [17] sourceNot checked yet

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• cites [18] Frobisher, C, 2003, J Hum Nutr Diet sourceNot checked yet

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• cites [19] Lee, CD, 2012, J Diabetes Sci Technol sourceNot checked yet

  Not checked in the free run.

Classified as probably not a substantial claim.

Individualized feedback has been found to be associated with higher adherence to online interventions promoting healthy lifestyles.

“Individualized feedback has been found to be associated with higher adherence to online interventions promoting healthy lifestyles [22,23].”

• cites [22] sourceNot checked yet

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• cites [23] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Although it is still difficult to estimate food ingredients and portion sizes from a photograph, efforts to develop estimation algorithms based on image processing or crowdsourcing are underway.

“Although it is still difficult to estimate food ingredients and portion sizes from a photograph, efforts to develop estimation algorithms based on image processing or crowdsourcing are underway [6,16].”

• cites [6] sourceNot checked yet

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• cites [16] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The duration of the monitoring period has varied from eight weeks to two years in different studies.

“The degree of monitoring is typically reported as the number of food diaries/entries completed per day and/or week, and the duration of the monitoring period has varied from eight weeks to two years in different studies [3].”

• cites [3] sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

Reviews on Web-based interventions have found that adherence is generally lower outside randomized controlled trials.

“Little research exists about usage behavior of health-promoting apps, but reviews on Web-based interventions have found that adherence is generally lower outside randomized controlled trials and some observational studies have reported adherence rates as low as 1% [29].”

• cites [29] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Some observational studies have reported adherence rates as low as 1%.

“Little research exists about usage behavior of health-promoting apps, but reviews on Web-based interventions have found that adherence is generally lower outside randomized controlled trials and some observational studies have reported adherence rates as low as 1% [29].”

• cites [29] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

A pilot study using disposable cameras suggests that recording food before eating can lead to increased consideration of dietary habits and alter food choices better than written diaries.

“A pilot study using disposable cameras suggests that recording food before eating can lead to increased consideration of dietary habits and alter food choices better than written diaries [21].”

• cites [21] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Traditional methods for dietary self-monitoring include more or less detailed food diaries and calorie counting.

“Traditional methods for dietary self-monitoring include more or less detailed food diaries and calorie counting [14].”

• cites [14] Thompson, FE, 2008, Nutrition in the Prevention and Treatment of DiseaseNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

In a six-month intervention study, greater weight loss was associated with more frequent monitoring.

“For example, a six-month intervention study found that the average number of food records per week was 3.7 and greater weight loss was associated with more frequent monitoring [12].”

• cites [12] sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

In weight loss studies, consistent recording of food intake appears to be one of the most effective methods.

“In weight loss studies, consistent recording of food intake appears to be one of the most effective methods [3,11].”

• cites [3] sourceNot checked yet

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• cites [11] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Feedback on performance is a self-regulation technique that either reinforces the current behavior or creates a discrepancy between current and ideal behavior.

“Feedback on performance is a self-regulation technique that either reinforces the current behavior or creates a discrepancy between current and ideal behavior [4].”

• cites [4] Carver, CS, 1982, Psychol Bull sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

In a free online weight loss program, no association was found between dietary monitoring frequency and weight loss.

“Another study on members of a free online weight loss program found that more frequent weight monitoring was associated with greater weight loss, but no association was found between dietary monitoring frequency and weight loss [13].”

• cites [13] sourceNot checked yet

  Not checked in the free run.

Classified as probably not a substantial claim.

The percentage of food records made within 15 minutes of eating has been found to be associated with weight loss.

“Methods that can minimize the temporal distance between eating and recording food intake are likely to improve outcomes; the percentage of food records made within 15 minutes of eating has been found to be associated with weight loss [20].”

• cites [20] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Beyond nutritional assessments, technology can be used to share advice and feedback on healthy eating between users.

“Beyond nutritional assessments, technology can be used to share advice and feedback on healthy eating between users [27].”

• cites [27] Parker, A, 2012, CHI'12 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems sourceNot checked yet

  Not checked in the free run.

Classified as probably not a substantial claim.

In terms of the content of feedback, encouraging reflection and self-monitoring may be more important than detailed analysis of nutritional contents when the target is to change eating behavior.

“In terms of the content of feedback, encouraging reflection and self-monitoring may be more important than detailed analysis of nutritional contents when the target is to change eating behavior [10,24,25].”

• cites [10] sourceNot checked yet

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• cites [24] sourceNot checked yet

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• cites [25] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Mobile apps can provide automated feedback on the healthiness of the food based on the photo and also leverage other users to provide feedback through crowdsourcing.

“Mobile apps can provide automated feedback on the healthiness of the food based on the photo and also leverage other users to provide feedback through crowdsourcing [6].”

• cites [6] sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

Dietary self-monitoring prompts people to reflect on their current behavior and compare it to ideal behavior.

“Dietary self-monitoring prompts people to reflect on their current behavior and compare it to ideal behavior [4,10].”

• cites [4] Carver, CS, 1982, Psychol Bull sourceNot checked yet

  Not checked in the free run.

• cites [10] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Capturing images of food may improve adherence and accuracy in some groups, such as among adolescents who may be less motivated to keep detailed food diaries.

“Capturing images of food may improve adherence and accuracy in some groups, such as among adolescents who may be less motivated to keep detailed food diaries [8].”

• cites [8] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

In a six-month intervention study, the average number of food records per week was 3.7.

“For example, a six-month intervention study found that the average number of food records per week was 3.7 and greater weight loss was associated with more frequent monitoring [12].”

• cites [12] sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Evaluation of PlateMate suggested that crowd-generated assessments were almost as accurate as those done by professional nutritionists, although pictures containing ambiguous items such as beverages or salad dressing received inaccurate ratings.

“Evaluation of the app suggested that these crowd-generated assessments were almost as accurate as those done by professional nutritionists, although pictures containing ambiguous items such as beverages or salad dressing received inaccurate ratings [26].”

• cites [26] Noronha, J, 2011, Proceedings of the 24th Annual ACM Symposium on User Interface Software and TechnologyNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

The degree of monitoring is typically reported as the number of food diaries/entries completed per day and/or week.

“The degree of monitoring is typically reported as the number of food diaries/entries completed per day and/or week, and the duration of the monitoring period has varied from eight weeks to two years in different studies [3].”

• cites [3] sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Bonferroni correction was used to adjust for multiple comparisons, with adjusted significance level P=.0014.

“Bonferroni correction was used to adjust for multiple comparisons and the adjusted significance level was set at P=.0014.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

Dietary self-monitoring for about 1.5 months would be enough to lead to increased awareness of eating habits and changes in behavior, if done diligently.

“Dietary self-monitoring for this amount of time would be enough to lead to increased awareness of eating habits and changes in behavior, if done diligently.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Registration time was not available for 1.49% of the users.

“Registration time was not available for 1.49% of the users (2837/189,770).”

Classified as probably not a substantial claim.

Changes in healthiness ratings were analyzed only among Active users who had at least one valid picture among the first two pictures they had taken (99.35% of Actives).

“Changes in healthiness ratings were analyzed only among Active users who had at least one valid picture among the first two pictures they had taken (99.35% of Actives, 4863/4895).”

Probably not a substantial claim: may not pass S3 (load-bearing).

The study found that sessions with apps were short, averaging a little more than a minute.

“The study found that sessions with apps were short, averaging a little more than a minute, and that different types of apps were used during different times of the day.”

• cites [30] Böhmer, M, 2011, MobileHCI'11 Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Communication apps were the most frequently used, 49.50% of app launches, whereas the proportion of health apps was only 0.26% of all app launches.

“Communication apps were the most frequently used, 49.50% of app launches, whereas the proportion of health apps was only 0.26% of all app launches [30].”

• cites [30] Böhmer, M, 2011, MobileHCI'11 Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Given the short usage period for the majority of users, many probably tried out the application for fun.

“Given the short usage period for majority of the users, many probably tried out the application for fun.”

Classified as probably not a substantial claim.

People's eating patterns and daily routines vary over the week.

“Considering that people’s eating patterns and daily routines vary over the week [31,32], analyzing the temporal context of app usage may help identify the best times to start using an app that promotes lifestyle changes.”

• cites [31] sourceNot checked yet

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• cites [32] sourceNot checked yet

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May combine two claims.

Users did not photograph only healthy foods and there was room for improvement.

“Hence, users did not photograph only healthy foods and there was room for improvement.”

• AssumptionRests on an assumption: The crowdsourced healthiness ratings validly reflect the healthiness of the photographed foods.

Probably not a substantial claim: may not pass S3 (load-bearing).

The pattern of easy joining and trying out without serious intention or commitment is similar to most free apps.

“This is similar to most free apps, which are easy to join and try out even if there is no serious intention or commitment to start using the app [13,25].”

• cites [13] sourceNot checked yet

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• cites [25] sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The positive trend among some users could also mean that they started gaming the system by selectively photographing their foods to get better ratings and comments.

“Thus, the positive trend among some users could also mean that they started “gaming the system” by selectively photographing their foods to get better ratings and comments.”

Classified as probably not a substantial claim.

The Eatery was not marketed as a weight loss app but as a method to eat healthier (Stop counting calories, start eating better).

“The Eatery was not marketed as a weight loss app but instead as a method to eat healthier (“Stop counting calories, start eating better”), and hence may have attracted a large number of users with no real interest in dietary improvements and thus lacking motivation for dietary self-monitoring.”

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

The Eatery may have attracted a large number of users with no real interest in dietary improvements and thus lacking motivation for dietary self-monitoring.

“The Eatery was not marketed as a weight loss app but instead as a method to eat healthier (“Stop counting calories, start eating better”), and hence may have attracted a large number of users with no real interest in dietary improvements and thus lacking motivation for dietary self-monitoring.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The proportion of users who had downloaded the app less than one week before the sampling period ended was 2.01%, and they were still included in the analyses due to their small number.

“The proportion of users who had downloaded the app less than one week before the sampling period ended (on March 28, 2012 or later) was 2.01% (3812/189,770). Hence, they could not be classified as Actives. They were still included in the analyses due to their small number.”

May combine two claims.

Improvers used the app for a longer time and did dietary self-monitoring more frequently than other Actives.

“In other words, they used the app for a longer time and did dietary self-monitoring more frequently.”

Probably not a substantial claim: may not pass S3 (load-bearing).

One of the few articles published about mobile app usage examined data that was collected from 4125 users between August 2010 and January 2011.

“One of the few articles published about mobile app usage examined data that was collected from 4125 users between August 2010 and January 2011 [30].”

• cites [30] Böhmer, M, 2011, MobileHCI'11 Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services sourceNot checked yet

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Classified as probably not a substantial claim.

Pictures with fewer than 10 ratings were excluded as invalid, based on manual inspection.

“By manual inspection, the threshold of a valid picture was adjusted to 10 ratings: if the first picture taken by a user had received less than 10 ratings, the picture information was excluded and the second picture was used instead.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Different types of apps were used during different times of the day.

“The study found that sessions with apps were short, averaging a little more than a minute, and that different types of apps were used during different times of the day.”

• cites [30] Böhmer, M, 2011, MobileHCI'11 Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

The overall quality and content of the pictures was screened by the researchers by examining a random sample of pictures.

“The overall quality and content of the pictures was screened by the researchers by examining a random sample of pictures.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Practical advice for healthy eating could have been given by formation of implementation intentions through if-then planning, which has been shown to increase effectiveness of healthy eating interventions.

“Practical advice for healthy eating could also have been given by formation of implementation intentions through if-then planning, which has been shown to increase effectiveness of healthy eating interventions [10].”

• cites [10] sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

The most significant limitation of the study is the lack of information about user demographics, behavioral outcomes, and initial motives.

“The most significant limitation of the study is the lack of information about user demographics, behavioral outcomes, and initial motives.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

General statistics about smartphone users in early 2012 suggest that iPhone users were slightly older than Android users and downloaded more apps in a month than users of other smartphone systems.

“The general statistics about smartphone users in early 2012 suggest that iPhone users were slightly older than Android users and downloaded more apps in a month than users of other smartphone systems [37].”

• cites [37] Alexander A2014-03-31Smartphone usage statistics 2012 (infographic)http://ansonalex.com/infographics/smartphone-usage-statistics-2012-infographic/6OTvN95oZNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

Crowdsourced ratings can be biased, resulting from cultural differences or the rater's own food preferences.

“Crowdsourced ratings can be biased, resulting from cultural differences [26] or rater’s own food preferences.”

• cites [26] Noronha, J, 2011, Proceedings of the 24th Annual ACM Symposium on User Interface Software and TechnologyNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Dietary decisions are often unconscious and affected by environmental factors more than people believe.

“Dietary decisions are often unconscious and affected by environmental factors more than people believe [39].”

• cites [39] sourceNot checked yet

  Not checked in the free run.

May combine two claims.

Even though the app reached a large number of people, its actual impact among users remained small because most did not even start dietary self-monitoring with the app.

“Even though the findings show that the app reached a large number of people, its actual impact among users remained small because most did not even start dietary self-monitoring with the app.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Implementing these techniques could have given users a more specific purpose for using the app.

“Implementing these techniques could have given users a more specific purpose for using the app.”

May combine two claims.

The app did not prompt users to set specific goals or review behavioral goals and only implicitly prompted intention formation (eat healthy).

“The app did not prompt users to set specific goals or review behavioral goals and only implicitly prompted intention formation (“eat healthy”).”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

In this study, the location information of where the pictures were taken was available but was not exploited.

“In this study, the location information of where the pictures were taken was available, but was not exploited, although dietary behaviors are likely to be linked with locations.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Prior studies have found that diet quality is generally poorer during weekends than on weekdays and calorie intake is higher, especially in the form of fat and alcohol.

“Prior studies have found that diet quality is generally poorer during weekends than on weekdays and calorie intake is higher, especially in the form of fat and alcohol [31,32,35]”

• cites [31] sourceNot checked yet

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• cites [32] sourceNot checked yet

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• cites [35] sourceNot checked yet

  Not checked in the free run.

May combine two claims.

The app utilized self-regulation techniques of self-monitoring and feedback but lacked other techniques derived from control theory.

“Finally, the app utilized self-regulation techniques of self-monitoring and feedback, but lacked other techniques derived from control theory [4,5].”

• cites [4] Carver, CS, 1982, Psychol Bull sourceNot checked yet

  Not checked in the free run.

• cites [5] sourceNot checked yet

  Not checked in the free run.

May combine two claims.

Because a higher proportion of active users first used the app during weekdays and daytime, the food they chose to photograph first was probably their workday lunch, which is often healthier than foods eaten during weekends.

“Because a higher proportion of active users also used the app for the first time during weekdays and daytime, the food that they chose to photograph first was probably their workday lunch, which is often healthier than foods that are eaten during weekends [35].”

• cites [35] sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

The app did not implement all self-regulation techniques that could have strengthened its impact and it lacked means to track changes in eating behavior systematically.

“Still, the app did not implement all self-regulation techniques that could have strengthened its impact and it lacked means to track changes in eating behavior systematically.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The association between outcomes and adherence to dietary self-monitoring has been found to differ between race and gender groups in weight loss interventions.

“the association between outcomes and adherence to dietary self-monitoring has been found to differ between race and gender groups in weight loss interventions [12]”

• cites [12] sourceNot checked yet

  Not checked in the free run.

Classified as probably not a substantial claim.

The app itself did not offer explicit advice on what to do to improve eating habits or what constitutes a healthy diet.

“The app itself did not offer explicit advice on what to do to improve eating habits or what constitutes a healthy diet.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

This could mean that this kind of application attracts users with special diets and/or those interested in food.

“This could mean that this kind of an application attracts users with special diets and/or those interested in food.”

Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

If people used the app as intended for dietary self-monitoring on a regular basis, they could experience some benefits through heightened awareness of their eating habits.

“If people would use the app as intended for dietary self-monitoring on a regular basis, they could experience some benefits through heightened awareness of their eating habits.”

May combine two claims.

Users did not photograph everything they ate, so there is no way of knowing how healthily people ate in general and whether the observed positive trend in healthiness ratings among 10% of active users meant anything in practice.

“Moreover, users did not photograph everything they ate so there is no way of knowing how healthily people ate in general and whether the observed positive trend in healthiness ratings among 10% of active users meant anything in practice.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Someone who downloads a healthy eating app in the middle of the week during daytime probably has the intention to start keeping track of their eating.

“In contrast, someone who downloads a healthy eating app in the middle of the week during daytime probably has the intention to start keeping track of their eating.”

Probably not a substantial claim: may not pass S3 (load-bearing).

It is possible that users with strict diets were already most interested in healthy eating.

“Hence, it is possible that users with strict diets were already most interested in healthy eating.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Portion size estimation is difficult even when measurement aids are present in the picture.

“Portion size estimation is difficult even when measurement aids are present in the picture [18,19,38].”

• cites [18] Frobisher, C, 2003, J Hum Nutr Diet sourceNot checked yet

  Not checked in the free run.

• cites [19] Lee, CD, 2012, J Diabetes Sci Technol sourceNot checked yet

  Not checked in the free run.

• cites [38] sourceNot checked yet

  Not checked in the free run.

May combine two claims.

The timing of initial use of the dietary self-monitoring app may be important both for users' pre-existing motivation and the type of reinforcing feedback generated by the app.

“Hence, the timing of the initial use of the dietary self-monitoring app may be important both in terms of the users’ pre-existing motivation and the type of reinforcing feedback generated by the app.”

May combine two claims.

The social network formed in this way is very loose: users neither know whose pictures they rate nor who rates their pictures.

“The social network formed in such a way is very loose: users neither know whose pictures they rate nor have any knowledge of who rates their pictures.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Some updates were released to the app during the six-month data collection; they consisted of minor modifications and fixes to the user interface and were not included in the analyses since the main features and functions remained the same.

“Some updates were released to the app during the six-month timeframe of data collection. These updates consisted of minor modification and fixes in the user interface of the app. They may have had a minor influence on the user experience of the app, but they were not included in the analyses since the main features and functions remained the same.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

If users are merely told that their meal is unhealthy but not given advice on how to make it better, they do not get enough value out of the experience and subsequently lack motivation to continue using the app.

“It may be that if users are merely told that their meal is unhealthy but not given any advice on what to do to make it better, they do not get enough value out of the experience and subsequently lack motivation to continue using the app [36].”

• cites [36] sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

Engaging in giving ratings for a long time might require an existing community or formation of stronger ties between users.

“However, engaging in this activity for a long time might require an existing community or formation of stronger ties between users [27].”

• cites [27] Parker, A, 2012, CHI'12 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

One explanation for participation in giving ratings is reciprocity: when a user rates someone else's pictures, they also get ratings for their own.

“One explanation is the reciprocity of the action: when a user rates someone else’s pictures, they also get ratings for their own.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Users of The Eatery owned an iPhone, so it is possible that their characteristics followed the same pattern as other iPhone users.

“Users of The Eatery owned an iPhone so it is possible that their characteristics followed the same pattern.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

The middle of the week during daytime could be a fruitful time to suggest initiation of lifestyle changes.

“This time period could also be a fruitful time to suggest initiation of lifestyle changes, although everyone does not have the same work schedules.”