SmartAPPetite For Youth: pilot and feasibility study of an adolescent smartphone nutrition intervention

Abstract

Background

Canadian adolescents report poor dietary quality. Smartphone-based nutrition interventions have the potential to improve adolescent diets through food knowledge and purchasing. “SmartAPPetite for Youth” is a smartphone-based nutrition intervention for adolescents that addresses key gaps in the literature. The study objective is to evaluate the intervention for feasibility, acceptability, and usability before undertaking a full-scale randomized controlled study.

Methods

The study was conducted in March–June 2016, among adolescents aged 14 years attending a secondary school in London, Ontario. Participants received the SmartAPPetite application on their phones, which sent time-based healthy eating messages (max 3/day) and location-based “nudge” messages (max 5/day) for 8 weeks. To evaluate recruitment methods, performance of app features, suitability of study instruments, and overall feasibility (measured by the rate of study retention, with a target of 70%), data was collected via the following: (1) a pre-post youth survey; (2) assessing participant experience; and (3) researcher observations. The youth survey included demographic questions, and questions about nutrition perceptions, food intake behaviors, food knowledge, and food purchasing behaviors. Questions about participant experiences included how often they interacted with the app, what they liked, and what they thought should be improved.

Results

Of 108 eligible adolescents, 59 consented to participate and 54 completed the follow-up survey. Most participants reported that the app benefitted them and stated that they would recommend the app to a friend. Results from the youth survey show that SmartAPPetite has the potential to influence food knowledge, food purchasing, and food intake behaviors. The implementation review identified some changes to our intervention study design, tools, and the app that are required for it to have the greatest impact in a scaled-up scientifically rigorous randomized controlled study.

Conclusions

The results of this pilot study show that the project is feasible, and that adolescents will accept the intervention and enjoy engaging with the app. The app was well accepted, and participants perceived that it was helpful in improving their food knowledge and health behaviors. The primary objective of this study identified some key lessons that can be built upon for a larger study. The impact of the app needs to be properly tested in a full-scale trial.

Key messages regarding feasibility

• Results show that the project is feasible, as retention rates with complete data were high. Our target retention rate was 70%, and we achieved a rate of 91.5%.

• Participants perceived that the app was helpful in improving food knowledge and health behaviors. Participants reported enjoying engaging with the app and requested the addition of recipes related to message content.

• This study provided suggestions for improving the intervention study protocol and suitability of study instruments, such as food purchasing and food knowledge questions.

Introduction

Unhealthy diets are primary risk factors for many non-communicable diseases, such as obesity, cardiovascular disease, and cancer [1–3]. Consumption of foods high in sugar [4–6] and sodium [7] is associated with disease, while frequent vegetable and fruit consumption can reduce disease risk [8–12]. National survey data shows that only one in ten Canadian adolescents in grades 6 through 12 meet the minimum recommended daily intake of fruits and vegetables [13]. Additionally, Canadian adolescents report that ultra-processed foods contribute to over half of total daily energy [14], frequent intake of sugar-sweetened beverages [15], and an overall low diet quality [15]. Identifying effective strategies to improve dietary intake among adolescents is an important public health goal given that food habits established during this life stage have been shown to affect food behaviors in later life [16].

Adolescence is associated with increasing levels of independent mobility and freedom to travel without parental supervision [17, 18], and is also a time at which many young people begin their first paid employment. Increased independence often translates to increased intake of fast food [19], especially when youth walk to or from school [20]. Moreover, close proximity to and high density of fast food outlets around schools is associated with increased purchasing among adolescents when a parent or guardian is not present [21]. Many traditional nutrition interventions succeed by increasing adolescent nutrition-related knowledge, but fall short of actual behavior change [16], or addressing the environmental contexts in which individuals make food choices [22].

Food literacy encompasses knowledge, food skills, attitudes, self-efficacy, behaviors, and food security [23]. Food literacy has been identified as a promising intervention point [16], and food literacy programs are associated with positive food behavior changes that may be sustained into adulthood [19, 24].

Food literacy interventions have expanded to include recent technological advancements. As of 2021, 97.9% of Canadian youth (ages 15 through 24 years) report owning or having access to a smartphone [25]. Acknowledging the ubiquitous role that smartphones play in society, many researchers have developed smartphone health interventions to improve individual health [26, 27]. The relatively low cost of smartphones and minimal participant burden make them an ideal medium for delivering health interventions [28], and particularly useful in reaching adolescents [29].

Existing smartphone nutrition interventions targeted at adolescents typically focus on weight loss or weight management rather than dietary behaviors or food literacy [30, 31], and many include other intervention components such as in-person counselling or school-based education sessions [27, 30–32]. Smartphone software applications (“apps”) and text messaging are often used to keep participants on track with their dietary and physical activity goals. Many studies differ in their study design and app functionalities, making it difficult to compare the effectiveness of different interventions on dietary-related behaviors and outcomes. Some interventions send users text messages asking them to submit goals and follow-up questions to gauge progress [29, 33–35]. Many interventions require participants to keep a food diary or track dietary intake as part of the intervention [36], and include features such as recipe banks, goal setting, and physical activity trackers [29, 35, 37–39]. Studies that include food literacy interventions were often text messaging-based, use text messaging as an element of a larger multicomponent intervention [34, 38, 40, 41], or provide personalized feedback to participants [42–45]. Many apps include other intervention components, so it is difficult to infer the effect of the app [35], but smartphone nutrition apps do show potential as a feasible and acceptable form of intervention [28, 35]. A recent systematic review on smartphone app-based nutrition interventions in adolescents reported that nutrition apps as stand-alone treatments have the potential to impact adolescents’ dietary intake. This review concluded that more interventions using validated dietary outcome tools, as well as interventions that collect app analytic data, are needed to better understand the potential impact of these interventions [36].

Despite the technological advances in nutrition interventions, peer-reviewed literature on smartphone-based food literacy interventions for adolescents is still lacking. Currently, some apps available on the Apple and Android App Stores provide users with nutrition information, but the accuracy of this nutrition information and its effectiveness has not been rigorously studied. A literature review evaluating mobile technology for nutrition education found that credible and evidence-based apps are still lacking [46].

This paper reports on the pilot and feasibility study of “SmartAPPetite for Youth”, a smartphone-based nutrition intervention for adolescents that addresses key gaps in the literature, namely the use of validated dietary outcome tools and inclusion of accurate nutrition information and data on app engagement. The primary objective of this study was to evaluate the feasibility of the SmartAPPetite for Youth intervention prior to undertaking a full-scale randomized controlled study. A secondary objective was to examine potential differences in food knowledge, food purchasing, and food intake behaviors using an uncontrolled pre-post study design.

Methods

The intervention: SmartAPPetite

The SmartAPPetite app is a product of a cross-sector collaboration between academic researchers, registered dietitians, and community stakeholders, designed to help address the rising rates of obesity and revitalize the local food economy. The app is a multi-dimensional intervention that uses nudge theory to improve food knowledge and encourage users to make healthier food choices [47–50]. Dietary interventions based on nudge theory have shown some positive improvements in dietary choice, usually via changes in the food environment such as product placement or nutrition education at the point of purchase [51]. Such interventions can be limited by influencing dietary choices in that one food environment. SmartAPPetite integrates nudges across food environments and at different times of the day by sending users personalized messages to inform and subsequently ‘nudge’ them towards making healthier food choices and purchases at pre-screened local vendors [52].

All messages provided by the SmartAPPetite app are evidence-based and approved by a registered dietitian to ensure the information is scientifically rigorous and based on best practices as recommended by Dietitians of Canada. SmartAPPetite users receive two types of messages: time-based messages and location-based messages. Time-based messages are food tips about nutrition, seasonal availability, healthy behaviors, and food handling, that connect the food featured in the message to related recipes that use the ingredient and a list of nearby vendors selling the ingredient. Location-based messages are tied to the location of individual vendors and are delivered to users based on their minute-by-minute GPS logging. Location logging is accomplished through the WiFi-Assisted GPS chip built into smartphone devices. When a user is located within a pre-defined distance (i.e., 500 m) of a healthy local food vendor, the user receives a message providing information about healthy local products sold by the vendor. The database of vendors was created from public health food safety inspection records. These records are the most accurate official dataset available in Ontario, Canada for geolocating food vendors [53].

App users receive their messages through push notifications that arrive on a smartphone (or tablet device running Apple iOS or Android operating systems). If the user clicks on the short message (indicating interest), the full-screen app appears with more extensive information and links. Underlying the app’s time-based messages is an algorithm that determines which food tips are most suitable to the individual user. The algorithm’s recommendations are based on responses to a brief survey of food preferences, goals, and dietary restrictions, which is completed by the user upon initial setup of the app (see Fig. 1). At the time of the pilot and feasibility study, the SmartAPPetite database contained approximately 750 messages, categorized as healthy local food, location-based, lifestyle, or adolescent health. Within healthy local food, sub-groups included availability, nutritional benefits, varieties and flavors, selection, preparation, and storage. Table 1 shows sample messages from each category.

Fig. 1.

Screenshots of SmartAPPetite application features

Table 1.

Example SmartAPPetite messages by category

Message categories	Short tip	Full message
Location-based messages
Local vendors	You are close to the Covent Garden Market. Open Year Round!	Covent Garden Market began in 1835! It continues to build upon a long history of selling fresh produce & gourmet foods offering a family atmosphere. It has an ice rink in the winter and a seasonal farmers' market in the summer months. In the Public Square, you will find many public events, such as music & theater festivals. Don’t miss it! Open: Mon-Thurs 8am-6 pm; Fri 8am-7:30 pm, Sat 8am-6 pm, Sun 11am-4 pm
Time-based messages
Lifestyle	Are you a mindless eater? Find out why and what you can do!	Sometimes we eat, not because we are hungry, but because we are bored, sad, excited, distracted, stressed or even thirsty. This can cause us to eat without thinking about it, and it can lead to overeating. Next time you reach for a cookie, stop and ask yourself if you are actually hungry. Check out the links below to learn some great ways you can become a more mindful eater!
Adolescent health	Do you know how much sugar is in one can of pop?	One can of pop contains about 10 teaspoons of sugar. Drinking one can of pop is about 75% of a person’s recommended daily limit of sugar! Next time try a beverage with little or no added sugar, like water or unsweetened fruit juice. Or, check the nutrition facts table to help choose options with less sugar
Healthy Local Food
Availability	Tis the season for Ontario-grown nectarines!	August marks the beginning of Ontario-grown nectarine season! Make sure to grab some delicious nectarines this month from a local vendor
Nutritional benefits	Powerful and purple! Do you know the health benefits of this fruit?	Grapes are a delicious snack packed with nutrients. Purple grapes contain thousands of phytonutrients, a compound in plants, which can help maintain a healthy heart! Grapes also contain Vitamin C, an important antioxidant that helps to maintain your teeth and skin
Varieties and flavors	Did you know cantaloupes are actually muskmelons?	The “cantaloupes” grown in Ontario are actually muskmelons. Although true cantaloupes evolved from the muskmelon species, they are mainly only found in Europe. Muskmelons and true cantaloupes differ in appearance. True cantaloupes are smaller with deep grooves and muskmelons found in North America are larger and have the familiar netted outer skin
Selection	Follow these simple tips for picking the freshest celery	When buying celery, look for stalks that are straight and firm. Fresh stalks should not appear to be limp, soft or damaged. The stalks should have a bright color and fresh green leaves attached. Try not to choose celery that smells musty, instead, it should have a fresh scent
Preparation	Remove bitterness out of Kale with this tip	Did you know that you can get the slight bitterness out of kale by simply rubbing its leaves together? This process will also make the leaves a bit more tender. This makes including kale in your salads easy, even for picky eaters
Storage	How to store cucumbers to preserve freshness	Cucumbers can be kept for up to 10 days if properly stored. Store in a cool, dry place such as the fridge. To prevent early spoilage, do not wash your cucumber until right before eating. If you don't use the entire cucumber, wrap it with plastic wrap before storing in the fridge and eat within 5 days

Topics for the messages included in the SmartAPPetite for Youth pilot and feasibility study were developed through focus groups with adolescents to determine what aspects of nutrition and healthy living they found most interesting, useful, and engaging. For the pilot and feasibility study, we set a maximum of three time-based messages to be sent daily at participant-defined times, typically before mealtimes. We also set a maximum of five location-based messages to be sent to participants each day.

Participant recruitment and study design

The SmartAPPetite for Youth pilot and feasibility study was approved by Western University’s Non-Medical Research Ethics Board (REB#: 107034) and the local school board ethics committee. This study was completed in one secondary school located in London, Ontario, Canada between March and June of 2016. The recruitment of the school began in March 2016, where the school principal was contacted by the school board ethics officer with the request to participate in the study. The principal agreed, and the school’s student success coordinator invited nine classes, a total of 239 students 14 to 17 years of age, to participate in the project.

Each class selected received a short presentation about SmartAPPetite, including an explanation of how to use the app and the details of the SmartAPPetite for Youth pilot and feasibility study. As the pilot and feasibility study version of the app was only available through the App Store, only students with an Apple device (e.g., iPhone, iPod touch, iPad) were eligible to participate in this study. Eligible students were provided with a letter of information and parental consent form to bring home. Once students received parental consent, they were asked to provide their own assent prior to completing the baseline survey and downloading the app from the App Store. During the intervention, participants were sent up to three time-based and five location-based messages each day. At the conclusion of the eight-week intervention, participants completed a follow-up survey. Participants received a $15 (CAD) gift card for each survey they completed, for a maximum of $30 in incentives for participating in the study.

Representatives of the SmartAPPetite team consulted with the school student council, who recommended four key strategies to engage the student body during the study: having a display booth during the lunch period, circulating a study poster in all the classrooms, advertising on televisions in the hallways, and offering monetary incentives.

Data collection methods

Our primary objective was to assess the feasibility of implementing the intervention as a foundation for a larger, rigorously designed experimental study. Feasibility was measured by the study retention rate, specifically the proportion of participants who completed the study with full data. Recruitment and retention were assessed pragmatically by inviting approximately 100 eligible students and reporting the proportion who consented; we set a target retention rate of 70%. Of the 59 participants recruited at baseline, 54 remained at follow-up, yielding a retention rate of 91.5%. With this sample size, the 95% confidence interval for the retention rate is approximately 84% to 99%, providing a reasonable degree of precision for informing the design of a future full-scale trial.

Our secondary objective was to explore potential changes in food knowledge, purchasing habits, and dietary behaviors. This was evaluated using three independent methods: (1) a youth survey; (2) analysis of the in-app experience; and (3) direct observations by researchers.

These methods were combined and triangulated to better understand the acceptability and usability of our study instruments.

The youth survey was completed at baseline and again at follow-up by each participant. The survey asked questions about demographics, followed by five categories of questions to understand the ability of SmartAPPetite to change food-related behaviors: (a) individual/family characteristics (e.g., age, gender, ethnicity, household size); (b) food preferences measure the type of foods participants like; (c) nutrition perceptions gauge participants’ interest in overall health and nutrition (e.g., level of agreement with statements such as “Eating healthy is important to me” and “I like to cook”); (d) food intake behaviors are a modified food frequency questionnaire to determine how often participants consumed fruits and vegetables, common energy-dense nutrition-poor foods, and beverages; (e) food knowledge consisted of six questions used to assess the participants’ level of knowledge and perceptions of nutrition and healthy eating [54, 55] (e.g., match nutrients to their benefit, identify the recommended number of Canada’s Food Guide servings for their age group); and (f) food purchasing behaviors were asked based on the frequency of times each participant purchased food from different types of vendors around their school by day of the week.

Participant experiences with the app were collected through nine open-ended questions at the end of the follow-up survey that asked participants to reflect upon their experience using the app. Questions asked participants how often they interacted with the app, what they liked, and what they thought should be improved. This feedback was combined with observations from the research team that were collected throughout the duration of the study to better understand the process of how the intervention was implemented, and what changes should be made to improve the food knowledge, food purchasing choices, and consumption of healthy foods among this population.

Data analysis

We used a mixed methods approach to address the primary objective of this study. Quantitative data were analyzed using descriptive statistics in SPSS (IBM, SPSS Statistics 24), qualitative data were coded and analyzed with theme-based analysis in NVivo (version 11), and spatial data was analyzed using ArcGIS (version 10.5, ESRI, Redlands, California). Data from the youth survey, participant experience, and observations from the research team were triangulated to better understand the recruitment and retention, suitability of study instruments, and performance of app features.

To address the secondary study objective, potential changes in food knowledge, food purchasing, and food intake behaviors were examined by comparing baseline and follow-up youth survey measures. Since this is a pilot study with a small sample size that is not representative of a broader population, no conclusions regarding the effectiveness of SmartAPPetite in changing behavior are drawn [56].

Results

Implementation

Recruitment and retention

Recruitment for our pilot and feasibility study started with a hands-up survey asking students in the nine selected classrooms to report whether they had an Android, Apple, or other smartphone device. Of the 239 students, 108 had Apple iPhones (45.5%), 78 had Android devices (32.5%), 1 had another type of smartphone (0.2%), and 52 did not have a smartphone (21.8%). Of the 108 iPhone users eligible for the study, 59 students received parental consent and gave personal assent to participate in the study, representing a participation rate of 54.6%. All 59 participants completed the baseline survey and 54 out of the 59 completed the post-intervention survey (91.5%). The five participants who did not complete the follow-up survey were absent both days we visited the school to administer the follow-up survey. All five participants lost to follow-up were male; two were in grade ten and three were in grade eleven.

The characteristics of the sample are described in Table 2. The average age of participants was 15 years, and 56% of participants were female. Most participants were in grade ten (61%), with almost equal numbers in grades nine and eleven. Nearly one-third (32.2%) of participants were visible minorities, and three-quarters (74.6%) reported living in a household of four or more people. In addition to being smartphone owners, about half (52.5%) of the participants stated that they owned a tablet (e.g., iPad) or another handheld device (e.g., iPod). Most participants (86%) reported that they did not use any other food, nutrition, or health apps on their smartphone or other handheld devices.

Table 2.

Characteristics of study participants (n = 59)

	All participants, n (%)
Sex
Male	26 (44.1)
Female	33 (55.9)
Age (mean, SD)	15.4, 0.8
Ethnicity
White/European	40 (67.8)
Racialized groups	19 (32.2)
Grade
9	11 (18.6)
10	36 (61.0)
11	12 (20.6)
Household size
2	4 (6.8)
3	11 (18.6)
4	25 (42.4)
5	13 (22.0)
6 or more	6 (10.2)
Mobile device ownership
Smartphone	59 (100.0)
Other (e.g., tablet/touch/.mp3)	31 (52.5)
Current use of any food, nutrition, or health apps
Yes	14 (13.6)
No	45 (86.4)

Suitability of study instruments

Survey completion rates and response rates were calculated to determine if participants had any issues answering questions or survey sections. Overall, the results showed that participants were willing to complete the entire survey. Almost all participants completed the sections about demographics (98.8% completion rate), food preferences (93.2% completion rate), nutrition perceptions (100% complete at both survey times), food intake behaviors (survey one 99.8% complete; survey two 98.9% complete), and participant experience (94.7% complete).

The two sections that had lower completion rates were those sections focused on food knowledge and food purchasing. The food knowledge section had an overall completion rate of 85% (84.5% at survey one and 85.6% at survey two); however, when administering the survey, our team noticed participants had difficulty understanding how to respond to two questions that required a ranked response (i.e., rank a list of three food items from unhealthy [1] to healthy [3]). This was supported by the survey results, which showed that many of the participants who did complete the question did not complete it properly. This made it difficult to assess the results of the food knowledge section. In the food purchasing section, we asked participants to indicate how many times they visited a selection of food vendors located around the school. In the first survey, 83.8% of participants filled out this section completely; however, this figure dropped to 76.5% for the second survey. We divided the food purchasing section into questions about purchasing on weekdays versus weekends. The weekend data had noticeably lower response rates, with only 67.5% completed responses on the first survey and 51.7% in the second survey; our observations found that many participants raised questions about whether they were supposed to complete both sections.

Performance of app features

The performance of the app and app features was assessed with the experience survey. Of the 54 participants who remained at follow-up, 53.7% of participants stated that they interacted with the app at least once a week, while 38.9% of participants stated they clicked on links within the app once a week or more. Most follow-up participants (74.1%) stated that the app benefitted them in some way, and 92.6% stated that they would recommend the app to a friend. When asked why they would recommend SmartAPPetite to a friend, participants stated they “enjoyed the experience”, they found it “easy & beneficial”, and “my friends need to be more aware of what they eat”. Like these responses, the participants had many comments about their interest and experience with the app overall, indicating they were generally pleased with SmartAPPetite.

We also asked participants how SmartAPPetite could be improved, with two-thirds of participants (67.4%) identifying that there were some features that could be made better. The most common suggestion participants had to improve the app was to provide more recipes, and to allow SmartAPPetite to be more integrated with “social media… where you can share and compare with friends.” Some participants also suggested to add more adolescent-specific messages, with one student saying they would remove messages “about adults because it doesn’t apply to us and are not that helpful”. Additionally, some participants identified that they received too many notifications per day.

Almost one-third of participants (31%) stated that what they liked most about SmartAPPetite was the information the app provided. Participants liked that it was, “relate-able [sic] to people who are around my age” and that “the information was useful, and educational for teens”. The participants also noted that “the information was concise and to the point, so you aren’t overloaded with information” and “it came up in your notifications so that it was easy to access.” Many participants liked receiving recipes and that the app provided “good recipes that were both healthy and tasted good.”

Preliminary impact

The pre-post study design allowed some assessment of how perceptions and behaviors changed between baseline and follow-up surveys, including nutrition perceptions, food intake behavior, food knowledge, and food purchasing behaviors before and after the intervention. Results of the comparative analyses are described in Tables 3 and 4.

Table 3.

Comparison of baseline and follow-up participant perceptions on nutrition and cooking behaviors

	Baseline, n (%)				Follow-up, n(%)
	Strongly Agree	Agree	Disagree	Strongly Disagree	Strongly Agree	Agree	Disagree	Strongly Disagree
“Eating healthy is important to me”	29 (49.2)	29 (49.2)	1 (1.7)	0 (0.0)	37 (68.5)	17 (31.5)	0 (0.0)	0 (0.0)
“I like to cook”	13 (22.0)	32 (54.2)	9 (15.3)	5 (8.5)	17 (31.5)	30 (55.6)	4 (7.4)	3 (5.6)
“Cooking or preparing meals helps me eat more healthy”	14 (23.7)	38 (64.4)	7 (11.9)	0 (0.0)	18 (33.3)	30 (55.6)	5 (9.3)	1 (1.9)
“Cooking or preparing meals at home helps me save money”	29 (49.2)	28 (47.5)	2 (3.4)	0 (0.0)	25 (46.3)	25 (46.3)	3 (5.6)	1 (1.9)
“Cooking or preparing lunch to take to school takes too much time”	12 (20.3)	18 (30.5)	21 (35.6)	8 (13.6)	10 (16.9)	23 (42.6)	18 (33.3)	3 (5.6)
“I feel comfortable reading food labels”	20 (33.9)	31 (52.5)	6 (10.2)	2 (3.4)	21 (38.9)	27 (50.0)	5 (9.3)	1 (1.9)

Table 4.

Descriptive comparison of meal routines and food intake at baseline and follow-up (n = 54)

Variables	Baseline Mean (SD)	Follow-up Mean (SD)
During a typical day…
How many meals do you eat?	2.9 (0.7)	3.3 (0.8)
How many snacks do you eat?	2.8 (1.3)	2.7 (1.3)
During a typical week, how many days do you…
Eat breakfast	4.5 (2.6)	4.9 (2.3)
Make your own breakfast	3.2 (2.7)	3.6 (2.6)
Buy breakfast	0.5 (1.3)	0.3 (0.8)
Eat lunch	4.9 (1.7)	5.1 (1.6)
Make your own lunch	2.6 (2.3)	2.8 (2.4)
Eat a lunch from home	3.7 (2.1)	4.0 (1.9)
Buy lunch	1.0 (1.6)	0.9 (1.2)
Eat dinner	6.4 (1.5)	6.7 (0.9)
Make your own dinner	2.6 (2.6)	2.7 (2.6)
Prepare or help prepare dinner	3.2 (2.2)	3.2 (2.1)
During a typical week, how many evenings do you eat…
Pre-made dinners (e.g., frozen food, microwave dinner)	1.1 (1.5)	1.1 (1.4)
Eat out or take-out food from a restaurant	0.9 (0.8)	0.8 (0.7)
Over the past week, how many times per day did you typically eat…
Fruit	3.5 (1.4)	3.5 (1.2)
Vegetables	3.0 (1.3)	3.1 (1.2)
Over the past week, how many times per day did you typically drink…
Water	2.7 (0.6)	2.9 (0.3)
Juice	1.4 (1.0)	1.3 (1.1)
Milk	1.4 (1.2)	1.4 (1.2)
Chocolate milk	0.4 (0.8)	0.3 (0.7)
Regular pop	0.4 (0.7)	0.4 (0.6)
Diet pop	0.1 (0.5)	0.1 (0.3)
Sports drinks	0.6 (0.9)	0.4 (0.8)
Coffee	0.3 (0.7)	0.3 (0.6)
Over the past week, how many times did you eat…
Chips	1.2 (1.3)	1.3 (1.4)
French fries	0.6 (0.8)	0.9 (1.3)
Candy/chocolate bars	1.8 (1.5)	1.0 (1.3)
Cookies, cakes, brownies, or doughnuts	1.5 (1.6)	1.3 (1.4)
Ice cream	1.1 (1.7)	1.3 (1.4)
Sweetened cereals	0.9 (1.5)	0.9 (1.6)

Nutrition perceptions

Reported nutrition perceptions were quite high at baseline, with 98% of participants strongly agreeing or agreeing that healthy eating was important to them. The only perception that showed no trends was the 50% split of those who agreed/disagreed that cooking or preparing lunch for school takes too much time. Despite these already high numbers of positive perceptions on nutrition, our preliminary analysis found higher agreement in participants’ perception of eating healthy food is important and liking to cook. There were no pre-post differences with the remaining nutrition perceptions.

Eating habits and food intake

Participants reported significant changes in breakfast eating habits, while snacks, lunch, and dinner habits appeared to remain stable. There was an increase in the number of days participants ate breakfast and made their own breakfast between baseline and follow-up, which led to an increase in the number of meals that participants reported eating on a typical day.

While meal and snack habits remained stable over time, 30% of participants self-reported that the app altered their food intake. One participant noted, “It makes you rethink your food choices,” and they provided examples of how they used the information learned through the app to directly change their own behaviors, such as eating less junk food and applying their knowledge of nutrition while shopping at the grocery store. Other participants highlighted that the app helped them experience an increase in intake of local foods and gain more awareness about healthy recipes, such as the example provided by one participant: “I now eat more local foods and I eat more variety.”

Following the same trends as our participant experience data, the consumption of healthy and unhealthy foods of our participants showed positive trends in the pre-post comparison, suggesting SmartAPPetite has the potential to positively impact food intake. The greatest increase in frequency of consumption was found with water, which increased from 2.7 to 2.9 instances per day. In contrast, participants less frequently consumed sports drinks and candy/chocolate per day.

Food purchasing

Figure 2 illustrates the distribution of how food purchases varied across the school neighborhood on weekdays. The neighborhood included three strip malls and a large regional mall. While there was a cluster of purchases that happened close to the school (within 1500 m of the school), there was also a large cluster at the regional mall on the western edge of the map (located within 3500 m of the school). Observations by research staff showed that participants with access to a car at school went there at lunch, but younger students walked or bused to the mall after school.

Fig. 2.

Vendor locations and frequency of self-reported food purchasing by study participants during weekdays*. Note: All participant (n = 59) self-reported food purchasing responses were aggregated by vendor and illustrated based on vendor type and frequency. Frequency values therefore represent totals by all 59 participants

To better understand the potential of SmartAPPetite to influence food purchasing, the difference in means testing compared the number of students making purchases at different types of food vendors and the number of purchases made at these vendors between baseline and follow-up. The results of this analysis are shown in Table 5 and show a decrease between baseline and follow-up in the number of participants that made at least one purchase on weekdays, as well as the number of purchases made on weekdays. However, the results showed no difference in purchasing behavior on weekends.

Table 5.

Comparison of baseline and follow-up purchases by vendor type and distance: weekday and weekend data

	Weekday (N = 52)		Weekend (n = 32)
	Baseline	Follow-up	Baseline	Follow-up
At least 1 purchase, n (%)
All vendors	53 (91.4)	46 (79.3)	27 (84.4)	26 (81.3)
By store type:
Variety stores	26 (44.8)	23 (39.7)	12 (37.5)	8 (25.0)
Grocery stores	44 (75.9)	35 (60.3)	18 (56.3)	17 (53.1)
Table service restaurants	18 (31.0)	8 (13.8)	9 (28.1)	7 (21.9)
Fast food restaurants	50 (86.2)	43 (74.1)	24 (75.0)	23 (71.9)
By distance:
Less than 1500 m	46 (88.5)	39 (75.0)	25 (78.1)	20 (62.5)
1501 to 2500 m	16 (30.8)	15 (28.8)	7 (21.9)	8 (25.0)
2501 to 3500 m	27 (51.9)	20 (38.5)	15 (46.9)	8 (25.0)
3501 m or more	52 (100)	52 (100)	19 (59.4)	21 (65.6)
# of purchases, mean (SD)
All vendors	4.7 (6.2)	2.9 (4.7)	5.8 (5.1)	4.5 (5.7)
By store type:
Variety stores	0.9 (1.6)	0.8 (1.1)	0.6 (0.9)	0.5 (1.1)
Grocery stores	2.6 (2.8)	2.0 (2.3)	0.9 (1.0)	0.9 (1.3)
Table service restaurants	0.5 (1.1)	0.3 (0.9)	0.6 (1.1)	0.4 (1.0)
Fast food restaurants	6.6 (6.5)	5.5 (6.9)	3.8 (3.9)	2.8 (3.4)
By distance:
Less than 1500 m	3.9 (3.3)	2.6 (3.1)	1.8 (1.6)	1.5 (1.8)
1501 to 2500 m	0.6 (1.2)	0.4 (0.8)	0.3 (0.6)	0.3 (0.6)
2501 to 3500 m	1.8 (2.4)	1.0 (1.8)	0.9 (1.3)	0.4 (0.8)
3501 m or more	4.7 (5.7)	3.7 (5.3)	2.8 (3.4)	2.3 (3.6)

We also considered food purchasing in the environment surrounding the school. At baseline, 88.5% of all participants reported making at least one purchase in the previous week at a vendor located within 1.5 km from the school; however, this declined to 75.0% of participants at follow-up. Furthermore, at baseline, participants made an average of 3.9 purchases per week at vendors located within 1.5 km of the school, compared to only 2.59 purchases at follow-up. There were similar decreases in purchasing trends when examining purchasing behaviors at vendors located between 2.5 and 3.5 km from the school.

We also analyzed the difference between baseline and follow-up data by vendor type. Findings suggest that the number of people who made at least one purchase in the previous week from grocery stores, table service restaurants, and fast-food restaurants decreased from baseline to follow-up. In addition, there was a decrease in the number of purchases made at grocery stores from baseline to follow-up, but not for the other food vendor types.

Food knowledge

As described above, the food knowledge questions in the youth survey were problematic, which resulted in poor quality data that we do not report on in this study. Nevertheless, on the participant experience survey, questions were asked about the perceived impact of the app-based intervention on food knowledge. From this evaluation, almost half of the participants (49.1%) noted that the app helped improve their knowledge about food and nutrition. For example, one participant stated, “a lot of information on the internet is not accurate. It was helpful to know that the information about health and eating habits was true and reliable”. Additionally, another participant mentioned that SmartAPPetite “helped me be more aware of what I’ve been putting into my body and made me more likely to read the nutrition label on the back of the package.” Another participant noted, “I started to be even more aware and had a healthier perception on the types of food that I am eating. I am also more focused and dedication [sic] in actually caring about my own health rather than what I physically look like”.

Discussion and conclusion

This pilot and feasibility study provided an excellent opportunity to investigate the feasibility, acceptability, and usability of implementing the SmartAPPetite smartphone-based intervention with adolescents, and to start understanding its potential to change food knowledge, food purchasing, and food intake behaviors. The results of this pilot study show that the project is entirely feasible, as our retention rates with complete data were high, and adolescents appeared to accept the intervention and enjoy engaging with the app. Our results also show that SmartAPPetite has the potential to influence food knowledge, food purchasing, and food intake behaviors. Additionally, our implementation review of the study shows that changes to our intervention study design, tools, and the app are required for it to have the greatest impact on a scaled-up scientifically rigorous randomized controlled study.

The primary objective of this study, to investigate the feasibility of the SmartAPPetite app for a randomized controlled study with youth, identified some key lessons that can be built upon for a larger study. Recruitment of our one school and students was successful due to our strong pre-existing relationship with the school board. Our study goals closely aligned with the priorities of the school and their healthy school program, which increased the eagerness of administrative staff and teachers to encourage students to participate. Our high recruitment (54.6%) and subsequent retention rates (91.6%) were aided by strong school champions who encouraged students to participate and engage in the project. We can further build on these strong recruitment rates by engaging with student leadership within schools to formulate engagement strategies for their school, and ensuring that data collection avoids key school events, such as field trips, major school events, and academic milestones (e.g., exams).

Recruitment can also be improved upon by increasing the diversity of app availability. At the time of this study, SmartAPPetite was only available on the Apple iOS platform, limiting the number of students eligible for participation (45.5%) from the selected classes. As a result, our full study will ensure that an Android version of the app is developed. This cross-platform access will mean that virtually all students would have an eligible device, allowing us to improve recruitment, while increasing sample size and generalizability [57–59].

Participants seemed very positive about their experience with the app: most reported that the app benefitted them and that they would recommend it to a friend. Offering adolescent-specific messages helped them relate to the information presented, and ultimately allowed the information to resonate, although they believed even more could be done to develop messages on topics that would interest adolescents. Similar to the literature about nutrition messaging [28, 37, 41], the adolescents in this study were very receptive to SmartAPPetite’s use of short messages with just enough information and the user-friendly design features, which made it easy for the participants to engage with the app. Consequently, our full study will include more recipes and allow participants to engage through social media. While our experience data was important to understand the impact of the study and level of engagement, there is also a need for the app to provide performance indicators through app analytics. Therefore, our full study will adapt the app to access data about participant engagement via more detailed app analytics. This information is imperative to understand how the level of engagement with the app moderates the impact of the messaging on behavior.

The high completion rates of our data collection tools suggest that participants were able to complete the surveys relatively easily, except for the food purchasing and food knowledge sections. As most of the issues with our tools were related to formatting, moving the evaluation tools to an online platform would provide participants with a more accessible format to complete the surveys and ensure that the questions are answered correctly. It will also be possible to increase the validity of data such as food purchasing by using the GPS device on a participant’s smartphone to objectively measure which food vendors they visit daily. So, our full study will adjust the formatting of the surveys and move them online. We will also endeavor to incorporate smartphone GPS devices into the app, to objectively track exposure to food vendors.

While the food knowledge tool had been adapted from previously used tools [54, 55], it did not meet the needs of our project; this seems to be a problem across much of the current literature [60]. This leaves researchers to develop their own tool to evaluate the specific measures of food literacy they are trying to change, such as knowledge, food skills, attitudes, self-efficacy, behaviors, and food security [61]. SmartAPPetite focused primarily on the food knowledge component of food literacy but is also working toward changing attitudes and self-efficacy around choosing healthier foods. Consequently, our full study will adopt the General Nutrition Knowledge Questionnaire, a reliable and valid measure of food knowledge that addresses the needs of this study [62].

While the modified food frequency questionnaire (FFQ) used to assess food intake with minimal participant burden was well completed, there are concerns with the quality of data provided by the tool. The FFQ was used as it makes collecting instances of food types much easier for adolescents than a serving size [63], but the resulting measures are less sensitive to behavior change and are difficult to compare with national averages. A 24-hour recall would be much more appropriate to adequately determine what and how much adolescents are eating at baseline and follow-up. A validated 24-hour recall survey, such as ASA24-Canada, can be conducted online, thereby appealing to the adolescent demographics, provide accurate portion sizes, and prompt participants to ensure no required information is missing [64, 65]. Thus, our full study will assess dietary intake using the ASA24-Canada, as collecting dietary data using this tool will enable us to identify any changes in dietary behaviors and overall nutrition.

The secondary objective of this pilot and feasibility study was to understand the preliminary impact of the app on food knowledge, food purchasing, and food intake behaviors. While we do not have the power or generalizability of a large-scale sample, we were able to garner trends in how the app influences behavior. The preliminary impact evaluation shows that the trends in behavior are moving in a positive direction. For instance, participants do feel eating healthily is more important to them and that they like to cook more after participating in SmartAPPetite. Meal routines show that participants are more likely to eat breakfast after engaging with the app, while food intake reporting shows increases in instances of water consumed while decreases in instances of sports drinks and candy/chocolate bars consumed. Similarly, there were decreases in both the number of people who make purchases and the number of purchases they make on a weekday. All these findings show that SmartAPPetite does have the potential to change behavior among this population group.

The trends in food intake showed no discernable changes in fruit and vegetable intake over the intervention period, which is a little surprising given how many messages were about fruits and vegetables. In contrast, there were increases in water consumption and decreases in energy-dense nutrition-poor foods (i.e., sports drinks, candy and chocolate bars), which is consistent with what has been found in other studies [41]. These are important changes to note as many of our adolescent-specific messages focused on drinking water instead of sugary sweetened beverages, sports and energy drinks, and how to choose healthier snacks. These findings and participant suggestions highlight that our more general fruits and vegetables messages are not as engaging as adolescent-specific messages. By targeting messages directly to adolescents, we should enhance participant experience and increase engagement, which may lead to improving the nutritional quality of adolescents’ diets and have positive implications on their health.

As indicated from the food purchasing questions, the adolescents participating in this study frequently purchased food in their school neighborhood. About one-third of all purchases were within 1.5 km of school, or a 15-minute walk. Based on the literature, we had anticipated that adolescents would have high levels of food purchasing close to their school [21], and the proximity of a strip mall helped to facilitate this pattern. However, there was also a large proportion of purchases made farther than 3.5 km from the school, which is where a large regional mall is located. Unfortunately, time was not considered when collecting the food purchasing data in this survey, so it is unclear when these purchases were made. Based on the distance from the school as well as our observations during data collection, it is possible that many students are frequenting the mall at the end of the school day when they have more time to bus, walk, or drive to the farther location. Overall, when assessing adolescents’ food purchasing, it is important to consider large plazas and malls not near the schools since adolescents with their own vehicles may be purchasing in those areas during their lunch breaks or after school.

Most purchases were made at fast food restaurants; however, based on our limited information, we are uncertain as to what was purchased at these vendors (e.g., drinks, meals, snacks). The volume of purchases made at fast food restaurants indicates the need to provide adolescents with messages when they are around these food vendors to help guide them to healthier food choices. However, a decrease in overall purchases and purchases made at fast food restaurants between baseline and follow-up surveys suggests that SmartAPPetite can help participants make their own lunch and possibly decrease their purchasing of unhealthy foods from fast food establishments.

Although there were many inaccuracies in the food knowledge survey responses, the open-ended responses revealed that many participants perceived that SmartAPPetite helped them to expand their knowledge about nutrition; many noted that engagement with the app helped shape their food behaviors. Participants also valued knowing that the information was credible and used this information to help motivate them to change their behaviors. More profound than gaining knowledge and changing behavior, some adolescents mentioned a change in perspective, that SmartAPPetite helped them to gain a new outlook on healthy living. Other participants commented that their engagement encouraged them to eat more local food and learn about new recipes.

Conclusions

In conclusion, this pilot and feasibility study provides the opportunity to learn many important lessons that may ultimately improve future iterations of SmartAPPetite and other nutrition and/or health apps. The SmartAPPetite app was well accepted by adolescents, and the participants perceived that it was helpful in improving their food knowledge and health behaviors. The impact of the app needs to be properly tested in a full-scale trial.

Through an evaluation of the recruitment and retention procedures, performance of app features, and the suitability of the study instruments, this pilot and feasibility study provided substantial methodological contributions, as well as suggestions for improving the app and intervention study protocol for the full randomized controlled study as mentioned in detail above.

This study demonstrated the feasibility of conducting a full-scale SmartAPPetite for Youth randomized controlled study on a larger population. This study demonstrates that the app has the potential to reach many adolescents within and beyond Southwestern Ontario. Providing this education at such a crucial phase in life could help shape the food knowledge, food purchasing, and dietary behaviors of Canadians into adulthood. Moreover, adding this educational and interactive technology into high school health curriculum could be an efficient way to ensure that all students receive evidenced-based nutrition education.

Authors’ contributions

JG is the investigator for the study and conceived the idea for the SmartAPPetite project and adolescent intervention. DB, SC, NW, and AW completed data collection and data analysis. SC wrote the first draft of this study with proofreading and edits from all other authors. LWM is the project coordinator of SmartAPPetite. Each co-author is a member of the SmartAPPetite team and assisted in the development of the study design.

Funding

This study was funded by grants from the Canadian Institute of Health Research (#399384), Heart and Stroke Foundation of Canada (G-17-0018327) and the Children’s Health Foundation (2015–2017).

Data availability

The datasets generated and analysed during the current study are not publicly available due to restrictions from the Western University’s Non-Medical Research Ethics Board but may be available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The SmartAPPetite for Youth pilot and feasibility study was approved by Western University’s Non-Medical Research Ethics Board (REB#:107034) and the local school board ethics committee.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.