Researchers tested two different ways to track what young adults eat using phone surveys. One method sent surveys at times matched to each person’s usual eating schedule, while the other sent surveys at the same times every day. Both methods worked about equally well, with people answering about two-thirds of the surveys. However, neither method perfectly captured what people ate, especially drinks. The study suggests that future tracking apps might need to use wearable devices or photos to get more accurate information about eating habits.

The Quick Take

  • What they studied: Whether sending food-tracking surveys at times matched to a person’s eating schedule works better than sending them at fixed times throughout the day
  • Who participated: 24 young adults (ages 18-30, about half male and half female) who had irregular eating patterns. Participants were randomly assigned to try one method first, then switch to the other method after a break.
  • Key finding: Both methods had similar response rates (about 65-66% of people answered the surveys) and similar accuracy (about 50% of answers matched what people actually ate). Personalizing the timing didn’t make a meaningful difference.
  • What it means for you: If you use a food-tracking app, it probably doesn’t matter much whether it sends you reminders at set times or tries to guess when you eat. The bigger challenge is that apps struggle to capture drinks and getting people to respond to every survey. This suggests future apps should use photos or wearable devices for better accuracy.

The Research Details

This was a carefully controlled experiment where 24 young adults tested two different survey methods. Before the study started, participants took photos of their food for a few days so researchers could figure out their typical eating times. Then, half the group started with personalized surveys (timed to their usual eating schedule) while the other half got surveys at fixed times (like 8am, 11am, 2pm, etc.). After two weeks, they switched methods and tried the other approach. Neither the participants nor the researchers knew which method was which until the end (this is called “double-blinded” and makes the results more trustworthy). Researchers compared the survey answers to the food photos and to what people remembered eating in 24-hour recalls.

Traditional food diaries require people to remember everything they ate at the end of the day, which is often inaccurate. This study tested whether sending quick surveys right around eating times could capture more accurate information. The crossover design (where everyone tries both methods) is especially strong because it controls for individual differences—each person serves as their own comparison.

This study has several strengths: it used a randomized design, was double-blinded to prevent bias, and had participants try both methods. However, the sample size was small (only 24 people), which limits how much we can generalize the findings. The study was also short-term (just a few weeks), so we don’t know if results would hold up over months or years. The researchers were transparent about limitations and didn’t overstate their findings.

What the Results Show

The main finding was that personalizing survey timing didn’t improve how many surveys people completed. The fixed-time method had 65.7% adherence (meaning people answered about two-thirds of surveys), while the personalized method had 66.3% adherence—essentially the same. This happened because even though researchers tried to time surveys to match each person’s eating schedule, people’s eating times varied so much day-to-day that the personalized schedule ended up sending about the same number of surveys as the fixed schedule. Agreement with actual food intake was also similar between methods: 52% for fixed timing and 47.7% for personalized timing. This means that even when people answered the surveys, their answers matched what they actually ate only about half the time.

Several other important findings emerged: First, beverages were the most commonly missed items—people frequently forgot to report what they drank. Second, participants found the survey length acceptable and didn’t mind the time it took to record their food. However, more people in the fixed-interval group complained about receiving too many surveys per day. This suggests there’s a tradeoff: personalized timing might reduce survey fatigue, but it doesn’t necessarily improve accuracy or response rates in practice.

This study builds on earlier research showing that traditional food diaries have problems with memory bias and burden. Previous studies suggested that sending surveys closer to eating times might help, but this research shows that benefit may be smaller than expected. The findings align with other recent research indicating that the biggest challenge in dietary tracking isn’t timing—it’s getting people to accurately report everything they eat, especially drinks and snacks.

The study was small (only 24 people) and short-term (a few weeks), so results may not apply to larger populations or longer tracking periods. All participants were young adults with irregular eating patterns, so findings may differ for older adults or people with more regular schedules. The study didn’t test whether adding photos or other features might improve accuracy. Additionally, the personalization strategy was relatively simple—it only looked at past eating times and didn’t adjust based on real-time factors like hunger or location.

The Bottom Line

If you’re using a food-tracking app, don’t worry too much about whether it sends reminders at fixed times or personalized times—both approaches work similarly. Instead, focus on: (1) reporting everything you eat and drink, especially beverages, (2) responding to surveys promptly when they arrive, and (3) being as accurate as possible. Apps that use photos or connect to wearable devices may be more accurate than text-based surveys alone. Confidence level: Moderate (based on a small study, but well-designed).

Young adults with irregular eating patterns who want to track their diet accurately should find this helpful. Researchers and app developers should use these findings to improve food-tracking tools. People with very regular eating schedules might not see much difference between methods. This research is less relevant for older adults or people with structured meal times.

You should expect to see the benefits of food tracking (like awareness of eating patterns) within 1-2 weeks of consistent use. However, achieving high accuracy in capturing everything you eat typically takes 2-4 weeks as you develop the habit of reporting immediately after eating.

Want to Apply This Research?

  • Set a specific goal to report all beverages consumed each day (coffee, tea, juice, soda, water, alcohol). Track the percentage of beverages successfully logged daily. This addresses the study’s finding that drinks are most commonly missed.
  • Enable push notifications at times you typically eat (breakfast, lunch, dinner, snacks) and commit to responding within 5 minutes of receiving each notification. Include a photo of your food when possible, as the study suggests images improve accuracy.
  • Weekly review: Check your app’s adherence rate (percentage of surveys completed) and accuracy rate (how often your logged foods match your actual intake). If accuracy is low, focus on responding faster and including more detail. Monthly: Identify which meal times or food types you most frequently miss and adjust your tracking strategy.

This research is for educational purposes and should not replace professional medical or nutritional advice. If you have specific dietary concerns, eating disorders, or medical conditions affecting nutrition, consult a registered dietitian or healthcare provider. The findings apply specifically to young adults with irregular eating patterns and may not generalize to other populations. Always discuss any major dietary changes with your healthcare team.