An analysis of the Carbsnap data shows that people tend to overestimate the carb count of meats. We first see this by looking at the average error patients make in meat pictures, shown in Figure 1.
Ideally, the mean error across all images should round to 0, an indication of a balanced spread between underestimates and overestimates of carbs in meats. However, our data indicates that on average, individuals estimated pictures as containing roughly 2.5 grams more carbs than factual. Though a deviation of 2.5 grams might seem insignificant initially, it's crucial to recall that these numbers are reflective of averages across multiple evaluations of numerous images.
To illustrate this, we can look at specific pictures of meat and how patients and dietitians are rating them, shown in the box plots next to each dish.
There is a clear disconnect in these figures: patients generally estimate carbohydrate counts much higher than dietitians for the same meats. Be mindful that these are general trends. While individual patients may not undervalue carbohydrates, our data reveals that many do.
Please make sure patients understand the relatively small amount of carbohydrates present in meats.
Keep using Carbsnap
Don't forget, these Insights are only as good as the data we receive from Carbsnap usage. So, please continue using the platform and advocate its merits to anyone you believe could benefit from honing their carbohydrate counting skills.
Box Plots
These statistics are available in the form of a box plot, showing the selected carbohydrate counts by dietitians and patients. Remember that at least 50 percent of the data points falls within the box in a box plot. For instance, in the first meat figure above, at least 50% of dietitians picked a range between 0 and 5 grams, while at least 50% of patients picked 12 to 40 grams (with a median of 20). A more thorough guide on interpreting box plots can be found here.