Summary: A new brain training app helps people to make healthier food choices and assists in weight-loss regimes, a new study reports.
Source: University of Exeter
Using a brain-training app helps people eat less junk food and lose weight, new research suggests.
The Food Trainer (FoodT app) trains people to tap on images of healthy foods – but to stop when they see unhealthy snacks, creating an association between these foods and stopping.
The new study, by the universities of Exeter and Helsinki, found that playing the game about once a day for a month led to an average one-point reduction of junk food consumption on an eight-point scale (the scale ranges from four or more items per day, to one or zero items per month).
Overall, people who used the app more also reported larger changes in their food intake.
About half of the study’s 1,234 participants followed the recommendation and played the game at least 10 times.
Across all participants, an average weight loss of half a kilogram (just over a pound) and a small increase in healthy food eaten was seen.
“As an example, someone who ate each junk food two to four times a week reduced this to once a week after using the app regularly for a month,” said Professor Natalia Lawrence, of the University of Exeter.
“Overall, the findings are really encouraging. The app is free and it only takes about four minutes per day – so it’s something people realistically can do – and our results suggest it is effective. “There’s some evidence that the benefits were stronger for people who were more overweight.
“We would expect to see this, because the app targets mechanisms that lead people to become overweight, such as the strong urges to approach and consume tempting junk foods.”
Dr Matthias Aulbach, of the University of Helsinki, added: “For anyone with unhealthy eating habits – perhaps developed during lockdown – FoodT might be helpful.”
The study used FoodT usage data, and the app also periodically asks questions about how often users eat certain foods, along with other information such as their age and weight.
The findings suggest that using the app regularly was linked with bigger changes in eating habits.
“If you’re trying to teach the brain something new, it’s a good idea to space out the learning over multiple sessions,” said Dr Aulbach.
“It may be helpful to do the training in different contexts – not just at home but at work and elsewhere, so the associations you learn don’t just relate to one location.
“From our results it seems important that you do the training regularly and don’t just stop. So keep it interesting and relevant for yourself so you won’t get bored with it: personalise the app as far as possible and pick the foods that you find really hard to resist.”
The researchers stress that their findings should be interpreted cautiously, because there was no control (comparison) group and other factors (such as the possibility that people who did more training were also separately more motivated to lose weight) could play a part in the results.
Leaving a review on Google Play, one app user wrote: “Really useful. Seems to work on different levels whether it’s the green/red circle association of stop/go which psychologically makes you more aware, I’m not sure – but my cravings have reduced dramatically and I no longer eat in the evening mindlessly.”
Development of the app was made possible by donations to a crowdfunding campaign, and app users who consent for their data to be used – anonymously – have enabled this research and app improvements to be made.
App-based food Go/No-Go training: User engagement and dietary intake in an opportunistic observational study
Food Go/No-Go training aims to alter implicit food biases by creating associations between perceiving unhealthy foods and withholding a dominant response. Asking participants to repeatedly inhibit an impulse to approach unhealthy foods can decrease unhealthy food intake in laboratory settings. Less is known about how people engage with app-based Go/No-Go training in real-world settings and how this might relate to dietary outcomes.
This pragmatic observational study investigated associations between the number of completed app-based food Go/No-Go training trials and changes in food intake (Food Frequency Questionnaire; FFQ) for different healthy and unhealthy food categories from baseline to one-month follow-up. In total, 1234 participants (m(BMI) = 29 kg/m2, m(age) = 43years, 69% female) downloaded the FoodT app and completed food-Go/No-Go training at their own discretion (mean number of completed sessions = 10.7, sd = 10.3, range: 1–122).
In pre-registered analyses, random-intercept linear models predicting intake of different foods, and controlled for baseline consumption, BMI, age, sex, smoking, metabolic syndrome, and dieting status, revealed small, significant associations between the number of completed training trials and reductions in unhealthy food intake (b = -0.0005, CI95= [-0.0007;-0.0003]) and increases in healthy food intake (b = 0.0003, CI95 = [0.0000; 0.0006]). These relationships varied by food category, and exploratory analyses suggest that more temporally spaced training was associated with greater changes in dietary intake.
Taken together, these results imply a positive association between the amount of training completed and beneficial changes in food intake. However, the results of this pragmatic study should be interpreted cautiously, as self-selection biases, motivation and other engagement-related factors that could underlie these associations were not accounted for.
Experimental research is needed to rule out these possible confounds and establish causal dose-response relationships between patterns of engagement with food Go/No-Go training and changes in dietary intake.