The Effectiveness of Interventions Delivered Using Digital Food Environments to Encourage Healthy Food Choices: A Systematic Review and Meta-Analysis
2. Materials and Methods
2.1. Study Selection Criteria
2.1.1. Types of Studies
2.1.2. Type of Participants
2.1.3. Types of Interventions
- The intervention was delivered primarily via an online food ordering system (i.e., >50% of the intervention strategies were delivered via the online food ordering system). Online food ordering systems of interest included (but were not limited to) online supermarkets and grocery stores, online restaurants, cafes and canteens; and online food and meal delivery services.
- The intervention aimed to encourage the purchase of healthier foods/beverages and/or reduce the purchase of less-healthy foods/beverages via strategies employed within the online food ordering platform.
- The intervention involved an actual online transaction, where money or equivalent (i.e., credit/voucher) was directly or indirectly (i.e., in the form of free or subsidized meal programs) exchanged for foods or beverages. This was to ensure that the consumer purchasing behaviors were generalizable to real-world contexts.
- Translating information: translating existing, decision-relevant information by changing the format or presentation of the information, but not the context.
- Making information visible: making external information, that is normally invisible, visible (e.g., daily calories allowances).
- Providing a social reference point: role modelling, or referring to the behavior of peer groups.
- Changing choice defaults: setting no-action defaults, or the use of prompted choice (e.g., nudge).
- Changing option related effort: changing the physical or financial effort to encourage or discourage certain choices.
- Changing the range or composition of options: changing categories or changing the grouping of options.
- Changing option consequences: changing the social consequences of certain decisions, or connecting decisions to benefits or costs (e.g., price promotions or discounts).
- Providing decision assistance: providing reminders, or facilitating commitment (e.g., self or public commitment).
2.1.4. Types of Comparison
2.1.5. Types of Outcomes
- The contents of food/beverage purchases according to food groups (e.g., servings of fruits and vegetables), food categories (e.g., the proportion of ‘healthy’ items and ‘less healthy’ items), or the presence of target items (e.g., sugar sweetened beverages).
- The macronutrient and micronutrient content of food/beverage purchases (e.g., mean energy, saturated fat, total sugar or sodium; or % energy contributed from fat or sugar; or energy density).
2.2. Search Strategy
2.3. Data Collection and Analysis
2.3.1. Selection of Studies
2.3.2. Data Extraction and Management
- Study characteristics: first author, publication year, country, study design, study aim, funding source and sample size.
- Participant characteristics: age, gender and ethnicity.
- Intervention characteristics: provider of the online food ordering platform, food ordering environment (e.g., school canteen, restaurant, or supermarket), intervention description, intervention strategies (as per Mȕnscher et al.  Choice architecture taxonomy), duration and intensity of the intervention.
- Outcome characteristics: definitions, methods of outcome assessment, and time points of outcome measurements.
- Study results relevant to the review primary outcome: e.g., food and beverage purchases/selection.
- Study results relevant to the review secondary outcomes: e.g., unintended adverse events, economic data/evaluation.
- Conflict of interest: using the Tool for Addressing Conflicts of Interest in Trials (https://tacit.one/, accessed on 7 August 2020).
2.3.3. Study Risk of Bias Assessment
2.3.4. Data Synthesis
3.1. Study Selection
3.2. Study Characteristics
3.2.5. Comparison Group
3.2.6. Primary Outcomes
3.2.7. Secondary Outcomes
3.3. Risk of Bias
3.4. Intervention Effects: Meta-Analysis
3.4.1. Energy Content of Purchases
3.4.2. Total Fat and Saturated Fat Content of Purchases
3.4.3. Sodium Content of Purchases
3.5. Intervention Effects: Narrative Synthesis
3.5.1. ‘Other’ Nutrient Content of Purchases
3.5.2. ‘Healthiness’ or ‘Nutritional Quality’ of Purchases
3.5.3. Cost of Interventions Delivered via Online Food Ordering Systems
3.5.4. Unintended Adverse Events
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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|Author, Year; Study Design, Country||Online Food Ordering Environment; Participant Characteristics||Sample Size *||Intervention Description [Choice Architecture Strategies] †||Duration of Intervention||Control Description||Dietary Outcomes Assessed: Primary Outcomes||Adverse Events/Costs: Secondary Outcomes|
|Coffino , 2020;|
Adults (mean age 46.6 years; 76% male) with food insecurity from a single-person household
|n = 50||Participants were presented with a prefilled online grocery shopping cart containing groceries selected to meet nutrition requirements based on participant sex and age. [Changing choice defaults].|
Participants were free to delete, add, exchange or keep items in their cart prior to finalizing their purchase. [Changing option-related effort].
|Participants exposed to intervention in a single online grocery shop||Alternative intervention: Participants read nutrition education handout prior to completing their purchase.||Average daily food and nutrient content of purchases: Wholegrain (serves/d); Fruit (serves/d); Vegetable (serves/d); Calories (kCal/d);|
Fat (g/d); Saturated Fat (g/d);
Sodium (mg/d); Cholesterol (mg/d); Fibre (mg/d)
|Doble , 2020;|
Adults (mean age 35.6 years, 49% male), and were Singapore residents.
|n = 941||20% of products with the highest calories per serving (excluding fruit and vegetables) had a price rise of 20%. There were 3 intervention arms:|
(1) Implicit Tax: High calorie products labelled with ‘raised price’ only (no explaination)
(2) Fake tax: Shows price pre and post the price rise and falsely indicates that the product will incur a 20% price rise due to high calorie content
(3) Explicit tax: Shows the same label as fake tax group, but the 20% price rise is actually applied.
[Changing option consequences; Making information visible]
|Participants exposed to intervention in a single online grocery shop||True control: No labels or price manipulation strategy applied||The proportion of taxed (i.e., high calorie) products purchased;|
The kCal per serve purchased;
The Alternative Healthy Eating Index Score of purchases.
The kCal per $ spent.
|The average total cost per shop.|
|Finkelstein , 2020;|
Adults (mean age 35 years, 21% male), who were the primary shopper for their household and were a registered shopper with RedMart (the online food ordering platform provider)
|n = 146||For each shop participants could spend between SG$50–250, and asked to complete a typical weekly grocery shop for 3 weeks (3 shops in total).|
2 online labelling intervention arms, both applied a ‘Lower calorie’ label:
[Making information visible].
(1) Within category labels applied: 20% of products within each product category that were lowest in calories per serve were labelled *
(2) Across category labels applied: 20% of all products that were lowest in calories per serve were labelled.
|Participants shopped once a week for 3 weeks (exposed to a different intervention group each week in random order).||True control: no online intervention applied to online supermarket.||The proportion of low calorie products purchased per shop.|
The total calories (kCal) per serve purchased;
total calories (kCal) purchased per shop;
and total calories purchased per $ spent
|Total cost of the shop|
|Finkelstein , 2019;|
Adults (mean age 34.7 years, 31% male), who were Singapore residents and were a registered shopper with RedMart (the online food ordering platform provider)
|n = 147||For each shop participants could spend between SG$50–100, and asked to complete a typical weekly grocery shop for 3 weeks (3 shops in total).|
2 online labelling intervention arms:
[Making information visible]
(1) Multiple Traffic Light (MTL) labels were applied to all products *
(2) Nutri-score (NS) labels were applied to all products.
Prior to each shopping trip, a 60 s video briefly explained how to use the labels that had been applied (MTL or NS).
|Participants shopped once a week for 3 weeks (exposed to a different intervention group each week in random order).||True control: no online intervention applied to online supermarket.||Diet quality per shopping trip using the AHEI-2010.|
Average Nutri-Score of the shopping basket, weighted by serve size.
The total calories, saturated fat, total fat, sodium and sugar per serve purchased.
Calories per $ spent.
|Total cost of the shop|
|Sacks , 2011;|
Customers of online supermarket (participant demographics not further specified)
|NA||A set of four traffic light labels to show relative levels of fat, saturated fat, sugar and sodium, were applied to products of the retailer’s own brand (including, milk, bread, breakfast cereals, biscuits and frozen meals) [Making information visible], as there were commercial constrains around labelling branded products.|
On the home page of the intervention store, and on each of the selected category and product pages, a link was provided to a page providing information about the trial, an explanation of the traffic light indicators, how to interpret them, and general nutrition advice (e.g., Australian dietary guidelines).
|Intervention was active for 10 weeks.||True control: no nutrition information was provided on the comparison store site during the trial period.||Change in sales by healthiness of products.||Nil|
|Huang , 2006;|
Adult (mean age 40 years, 12% male) customers of an online supermarket service.
|n = 456||383 commonly purchased pre-packaged food items that contained >1% saturated fat were selected, and a suitable lower-fat alternative was identified for each (524 foods were identified). Participants assigned to the intervention received advice tailored to the food items they had selected for purchased. This was done automatically by a computer program, and for each items that had >1% saturated fat, participants were presented with the opportunity to retain or swap the item for an alternative, lower saturated fat item (using a side by side comparison of the products).|
[Making information visible, Changing choice defaults/Prompted choice]
|Participants were offered the same form of advice each time that they used the online supermarket during the 5 month recruitment and follow-up period.||Alternative intervention: Participants directed to the National Heart Foundation webpage, then prompted to make changes to their purchases.||Mean % saturated fat in the purchased items among the 524 foods studied.||The mean cost per 100 g for the swapped items.|
|Wyse , 2019;|
|Online School Canteen;|
Primary schools students (kindergarten to grade 6) attending government schools with an online canteen ordering system.
Online canteen user might include parents of schools students
|6 schools, and 1903 students||Online canteen menus were redesigned so that fruit and vegetable snack items were positioned first and last on the menu|
[Changing the range or composition of options].
Target items included fruit or vegetable items (fresh, frozen, tinned or dried) that the children could consume as a snack. Target items were grouped together in a single category titled “fruit and veggie snacks”, which were displayed in 2 places, first and last categories on the online menu. Within this category, items were listed in the following order: whole fresh fruit, cut-up fresh fruit, frozen fruit, tinned fruit, dried fruit, fruit with accompaniments, fresh salad vegetable, cooked vegetables, vegetables with accompaniments.
|4 week intervention||True control: no changes were made to the online menus.||The proportion of all online orders that contained at least one fruit or vegetable snack food.|
The proportion of all individual items within all online lunch orders that are a fruit or vegetable snack food.
|Average lunch time weekly revenue|
|Delaney , 2017;|
|Online School Canteen;|
Primary schools students (kindergarten to grade 6) attending included government schools.
Online canteen user might include parents of schools students.
|10 schools, and 2371 students.||Intervention schools were provided a canteen menu feedback report to improve the availability of healthy foods (strategy not delivered online).|
Menu labels (traffic light labels) were applied to online menu items. [Making information visible].
Healthy menu items were listed in the main website display, while users had to click and explore the less healthy menu items.
[Changing option related effort].
When users chose unhealthy items, they were prompted to add a healthy item.
Healthy items were displayed in bold font, image and positive food prompt “this is a good choice”, [Changing option consequence].
|2 month intervention||True control: Schools with online canteen did not receive any of the interventions strategies.||The mean energy (kj); saturated fat (g), sugar (g), and sodium (mg) content of student online lunch orders.|
The mean % energy of student online lunch orders derived from saturated fat and sugar.
The mean % of student online lunch orders that were classified as “high nutritional value” and “low nutritional value”.
|Canteen weekly revenue|
|Miller , 2016;|
|Online school food service;|
Elementary or middle school students (5th–6th grade), receiving the National School Lunch Program.
|n = 71||While pre-ordering lunch online, students received nudges if their meal did not contain all five meal components (i.e., meat/alternative, grain, fruit, vegetables, and dairy). The nudge, “Your meal does not look like a balanced meal” would appear, and a plate was shown as a visual representation and highlight areas of the meal that the student had not selected, and were provided the option to change their orders [Making information visible]. Nudges were primarily provided for fruit, vegetable and/or dairy. Students who selected all 5 components received positive feedback consisting of a smiley face and message “You have ordered a balanced meal”. If a meal remained unbalanced after receiving the nudge, students received a message stating “Please select a fruit, vegetable or dairy. Otherwise you will be charged for each item separately”. Students that did not select these 3 components were charged for each item separately. [Changing option consequence]||Intervention was delivered to students for 2 weeks.||True control: Students pre-ordered lunch online, and did not receive nudges. If they had not selected fruit, vegetable or dairy they received: “Please select a fruit, vegetable or dairy. Otherwise you will be charged for each item separately”.||The % of vegetables, fruit and low fat dairy in meals ordered.||Nil.|
|VanEpps , 2016;|
|Online workplace cafeteria;|
Adults (mean age 40 years, 39% male) employed at a large health care company, and placed at least one online order during the intervention period.
|n = 249||Using an online based system, participants were required to select exactly one meal for lunch, and had the option to add as many drinks, snacks and desserts that they wanted.|
There were 13 meal, 23 snack/dessert and 30 drink options. Participants were assigned to 1 of 3 menu labelling options: [Making information visible].
(1) Traffic light labels (green, yellow, red: based on calorie content);
(2) Calorie information appeared next to each menu item.
(3) Combined Traffic light and calorie labelling
On Monday and Wednesday morning, participants received an email reminding them of the study, and the discount (providing in a link to the website).
|4 week intervention||True control: no online menu labels||Total lunch calories purchased.||Nil.|
|Stites , 2015;|
|Online workplace (hospital) food service;|
Adult (mean age 44.9 years, 11.5% male) employees who worked full-time at the study hospital and were overweight (BMI > 25 kg/m2).
|n = 26||An online pre-ordering system was developed, to allow participants to order their lunches and view the nutrient content of their choices (calorie and fat content, plus ingredients) [Making information visible]. The system selected the version of the food selected with the least calories and fat by default [Changing choice defaults].|
This intervention included Mindful eating training (90 min session) that was delivered offline. 20 × US$1.25 lunch order vouchers were provided to all participants (intervention and control), to encourage the use of the online ordering system.
|4 week intervention||Delayed intervention group||Average kilocalories and grams of fat in purchased meals.||Nil.|
|Cost of the Intervention to the Consumer|
|Huang, 2006||Mean cost per 100 g of foods purchased:|
Intervention: AUD $0.63 [0.58–0.68]/100 g
Control: AUD $0.62 [0.58–0.067]/100 g
|Finkelstein, 2019||Difference in mean total expenditure per shop vs. control:|
Nutri-Score labels: S$0.90 [SE: 0.98]
Multi-Traffic-Light labels: S$1.13 [SE: 1.06]
|Finkelstein, 2020||Difference in mean total expenditure per shop vs. control:|
Within-category labels: S$0.11 [−0.40, 0.63]
Across-category labels: S$0.18 [−0.33, 0.70]
|Doble, 2020||Difference in mean total expenditure per shop vs. control:|
Implicit tax: S$1.86 [−1.38, 5.39]
Fake tax: −S$0.32 [−3.40, 2.82]
Explicit tax: −S$0.79 [−3.83, 2.34]
|Cost of the Intervention to the Foodservice|
|Wyse, 2019||Weekly revenue per school (Relative Mean Difference):|
AUD $180 [−16, 376], p = 0.07
|Delaney, 2017||Weekly revenue per school (Relative Mean Difference):|
AUD −$62.33 [−212.36, 87.68], p = 0.41
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Wyse, R.; Jackson, J.K.; Delaney, T.; Grady, A.; Stacey, F.; Wolfenden, L.; Barnes, C.; McLaughlin, M.; Yoong, S.L. The Effectiveness of Interventions Delivered Using Digital Food Environments to Encourage Healthy Food Choices: A Systematic Review and Meta-Analysis. Nutrients 2021, 13, 2255. https://doi.org/10.3390/nu13072255
Wyse R, Jackson JK, Delaney T, Grady A, Stacey F, Wolfenden L, Barnes C, McLaughlin M, Yoong SL. The Effectiveness of Interventions Delivered Using Digital Food Environments to Encourage Healthy Food Choices: A Systematic Review and Meta-Analysis. Nutrients. 2021; 13(7):2255. https://doi.org/10.3390/nu13072255Chicago/Turabian Style
Wyse, Rebecca, Jacklyn Kay Jackson, Tessa Delaney, Alice Grady, Fiona Stacey, Luke Wolfenden, Courtney Barnes, Matthew McLaughlin, and Sze Lin Yoong. 2021. "The Effectiveness of Interventions Delivered Using Digital Food Environments to Encourage Healthy Food Choices: A Systematic Review and Meta-Analysis" Nutrients 13, no. 7: 2255. https://doi.org/10.3390/nu13072255