Jul 28 2014
Readers of this blog know my feelings concerning the recent PLOS study on the blood type diet. You can read them here and here. As these previous articles demonstrate, the problem was no so much the study’s methodology, but rather with its criteria, i.e. the assignment of blood type diet values to foods that had no actual value in the blood type diet, such as ‘hamburger,’ ‘beans, all kinds,’ and ‘Mac and Cheese.’
However, the PLOS study did point to a simple way that the theory could be tested: assigning a value to the consumption of beneficial and avoid foods and tracking the subject’s activity over time to see if changes in basic biomarkers (such as lab tests) correlate with adherence.
With this in mind, I began to consult with some colleagues about the possibility of developing a specific research tracking program that would allow us to collect data on dietary adherence that truly reflected whether or not the subject was following the BTD –or even some variant of it- or in fact if they did none of it at all. As I’ve already written a slew of programs of a sort similar to this, I began to go to work.
We wanted the program (now called Traktion) to fill a variety of needs. We aim to use anonymized data from Tracktion to see what kind of difference a high or low compliance level makes to people following the BTD. It also takes into account secretor status (if known), a major factor which the PLOS study overlooked.
An simple registration process and easy start-up: After an email verification (to screen out bots) users are initially required to provide only some very basic information, such as age, gender and ABO blood group. Traktion is freeware; there is no charge for its use.
A simplified way for users to input data: After testing a variety of human/computer interfaces it was clear that the best way to input diet diary information was what is known as a tagged-auto-complete form. Users simply type in the first few letters of the food they wish to add to the diary and select from the pull-down choices. The choices are from the official list of BTD value foods. This specificity requires a bit more work, since there are no foods such as ‘pizza’: instead, the user would input ‘wheat, whole wheat’, ‘tomato’, ‘mozzarella cheese,’ etc. However, it allows much more flexibility, since, for example, in our house we make pizza with spelt pizza dough.
Traktion’s diet diary entry screen. Click the image to see a larger version in a new window.
Feedback, Stickiness and ‘Easter Eggs’: I would be nice to depend on the altruism of the user to consistently put in data day after day, but we know that the more ‘sticky’ the application, the more repeat usage it receives. So I developed an entire ‘dashboard’ that presents the user with infographic-type feedback: charts and graphs that show them just how they are doing. Users can customize their dashboard to show different info-graphics, such as diet compliance, exercise activity, etc. Also, there is a neat ‘Easter Egg’ feature called ‘How Do You Feel Today?’ that records day-to-day ‘soft dimensions’, such as ‘energy’, ‘concentration,’ etc. When the user adds this information, they receive simple suggestions of beneficial foods for their type they may wish to increase their daily usage of.
Traktion’s Dashboard screen. Click the image to see a larger version in a new window.
Expandability: Although the basic requires for getting started in Traktion are minimal, users can also supply additional information, such as SNP data from 23 And Me; additional blood type related data, such as their secretor status; information on supplements, OTC medications and drugs they are taking, lab values, and specific exercises and length of time exercising. This will give us the opportunity to do additional data-mining.
Traktion’s Exercise screen. Click the image to see a larger version in a new window.
Traktion’s Health Data screen. Click the image to see a larger version in a new window.
Traktion’s Supplements and Medications screen. Click the image to see a larger version in a new window.
Traktion’s Profile Development screen. Click the image to see a larger version in a new window.
Support: Users can avail themselves of several support functions. A ‘Live Chat’ window is available for technical support and they can avail themselves of support forums, etc.
Anonymity and Security: Traktion uses SSL (secure sockets layer). All data is further encrypted on the server. On registration everyone must agree to a basic end user license agreement (EULA) that also clearly explains what the data that is being collected is to be used for. Other than the initial email, users are only identified by their chosen username.
At this point in time the basic user interface and data-gathering scripts are largely complete. I need to complete a few more dashboard plugins and finalize the data structures, and then Traktion can go into beta testing. I suspect we can have a real-world working version by September. The admin back-end can be developed over time.
What do users get out of it?
A way to track their BTD compliance level alongside other factors such as exercise, and correlate this with their wellbeing. Users may be able to work out factors that affect their personal state of health such as specific foods or exercise levels that might make them feel better or worse.
What do I get out of it?
A way to see aggregated anonymized data from large numbers of people and their compliance levels to the BTD on a custom-designed tracking system which takes the latest BTD food values into account. I hope to combine this data with other influences to get an overall picture of how well the BTD works for specific groups of people using Tracktion. For those who enter GenoTypes, lab values, medication or SNPs this may lead to new discoveries and open up possibilities for future areas of research. In the long run it will be of great benefit to the whole nutrition community.
As Traktion gets closer to completion, I’ll update this blog with further details, so stay tuned.