US20140180700A1

US20140180700A1 - System and method for increasing compliance with a health plan

Info

Publication number: US20140180700A1
Application number: US14/053,668
Authority: US
Inventors: Robert Schwarzberg; Marion Zabinski; Rene Melton; Timothy J. Dion
Original assignee: Humana Innovations Enterprises Inc
Current assignee: Humana Innovations Enterprises Inc
Priority date: 2007-09-18
Filing date: 2013-10-15
Publication date: 2014-06-26
Also published as: US8560336B2; US20090076335A1

Abstract

System and method to determine user compliance with personalized diet and exercise plans by analyzing responses to messages about the plans. An expert system has a number of stored messages and display characteristics from which it chooses. The expert system generates message relating to the user's diet or physical activity that are sent to a user's mobile device and analyzes responses. Display characteristics change periodically and compliance data relating to the user's adherence to the plan when certain display characteristics are used is stored (e.g., meal plan adherence, acceptance of specific food selections, and adherence to instructions and advice in messages). The expert system then determines which messages and display characteristics achieve the greatest compliance to the dietary and physical activity schedule and goals.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 12/118,939, filed May 12, 2008 and titled SYSTEM AND METHOD FOR INCREASING COMPLIANCE WITH A HEALTH PLAN, now U.S. Pat. No. 8,560,336, issued Oct. 15, 2013, which is incorporated herein by reference. U.S. patent application Ser. No. 12/118,939 is a continuation-in-part of U.S. patent application Ser. No. 12/117,190, filed May 8, 2008 and titled METHOD FOR TAILORING STRATEGY MESSAGES FROM AN EXPERT SYSTEM TO ENHANCE SUCCESS WITH MODIFICATIONS TO HEALTH BEHAVIORS, now U.S. Pat. No. 8,463,618, issued Jun. 11, 2013, which is incorporated herein by reference. U.S. patent application Ser. No. 12/118,939 is also a continuation-in-part of U.S. patent application Ser. No. 11/856,917 filed Sep. 18, 2007 and titled SYSTEM AND METHOD FOR REWARDING USERS FOR CHANGES IN HEALTH BEHAVIORS, which is incorporated herein by reference.

TECHNICAL FIELD

The present invention relates generally to systems and methods for assisting with the maintenance of healthy lifestyle habits. More particularly, the present invention is a system and method for track, monitoring, and analyzing data to improve user compliance with personalized diet and exercise plans.

BACKGROUND OF THE INVENTION

The present invention relates generally to systems that promote healthy lifestyles and, more particularly, to weight loss systems. The present invention is an improvement upon existing weight loss systems in that it tracks, monitors, and analyzes data to improve compliance with a personalized health plan. The present invention may be used to motivate dieters as well as keep them on a healthy diet while at the same time allowing flexibility in different dieting aspects including, but not limited to, types of food, amount of food, types of food preparation, and amount of exercise.
Dieting has become an extremely popular activity resulting from people's awareness of the health risks of becoming overweight or obese, a desire to improve one's appearance, and an aspiration to achieve the sense of accomplishment that comes from setting a difficult goal and accomplishing it. However, there is no singular method of dieting that works for every person. Body types, weight loss goals, and preferences vary greatly depending on the individual. Every dieter has individual likes and dislikes as to types of food, times and places to eat, type and length of exercise, eating habits, etc. Due to these differences, many dieters become frustrated with rigid, impersonal diets, and often quit the diet after a short time.
Furthermore, dieters differ on how well they can motivate themselves to continue to adhere to certain dietary guidelines. For example, a dieter who is supposed to only eat a cup of pasta and a vegetable for lunch, but instead decides to eat an ice cream cone as well may be unable to justify such a decision within the diet and decide to give up the diet for the rest of the day. Because such “splurges” are detrimental to the dieter's physical and mental progress, the dieter may find the diet unsustainable.
Many diet plans fail to allow for individualized exercise schedules. Typically, the diet plans suggest the same workout schedule for every person on the diet. For example, the diet plan may incorporate a workout of a half hour, two to three times a week. Such a generalized workout schedule has a number of weaknesses. First, it fails to factor in the type of activity the person is performing. The effectiveness of the exercise depends on what exercise is performed as well as the intensity. A half hour of strolling through a park is simply not as effective as a half hour of running.
Second, it does not allow for individualized ability. For some people, working out for half an hour, two to three times a week, may be physically impossible given their current condition. It may be possible for them in the future, but the person may to a 15 minute workout for until his or her health improves. Other individuals may have the desire and ability to work out for a longer period of time or a greater number of times per week.
Another problem with a general workout schedule is that it fails to factor in the individual's likes and dislikes as to type of activity and time of day to perform the activity. A plan that proposes exercise two to three times a week is easily put aside when the person is busy and distracted by other activities. A person is much more likely to perform an activity that is scheduled or better yet, for which a reminder is provided telling the person to perform a certain activity at a certain time.
Finally, existing diet plans often fail to take into account details regarding the user's dietary information. The two parts of the diet plan—the intake of food and exercise—are generally treated as separate parts of the plan. However, the two are related in that they both have an impact on caloric intake. The more one exercises, the more one can eat. Accounting for both activities allows the impact of one to be applied to the other. For example, a person may eat a large lunch one day and reduce the impact of the lunch by including an extra work out later in the week. Likewise, a person could miss a scheduled workout and compensate for it by eating a smaller meal later in the day.
A highly effective solution to many diet program problems is found through the use of coaching. Research has shown that dieting and weight loss is more successful when the dieter is coached throughout the process. Coaching keeps the dieter motivated, provides positive reinforcement, and introduces a narrowly-tailored plan for each individual participant. However, obtaining a reliable human coach is difficult and prohibitively expensive such that relatively few dieters are actually able to use one.

SUMMARY OF THE INVENTIVE CONCEPT

The present invention addresses the diet plan programs identified above by providing personalized plans to meet the needs and requirements of individual users and determining users' compliance with the plans. It uses tailored messages to “coach” individuals in following their personalized plans. An expert system uses information about an individual's diet and exercise preferences to provide tailored messages related to the plan. The expert system further receives from individuals' responses to messages and other information to determine compliance with personalized plans. Additional tailored messages are designed to increase compliance. As a result, individuals receive personalized instruction in the fields of dieting and exercise without paying the prohibitively expensive fees that are typically associated with personalized instruction. Exemplary embodiments allow the individual to use mobile or portable devices and technology, such as cell phones, PDA's, Blackberrys™, iPhones™, and others, so that the individual has constant access to personalized instruction regarding his or her personalized diet and exercise plan.
The personalized instruction is based on an individual's diet plan preferences, food preferences, meal preparation preferences, and exercise preferences. Behavior challenges are identified and target goals are set. Once the user's plan has been established, typically by providing the preference and other information through an online website, the user is never required to access the site again as the personalized instruction is given through the user's mobile device. The prior art is known to center around “pull” technology, where the user must reach out to the system for the information, and if there is inaction by the user, the instruction will stop. The present invention uses “push” technology, where the instruction is sent to the user, and inaction by the user prompts the system to reach out to the user for corrective actions and encouragement.
It has been found, through the study of behavior informatics, that the use of technology can help people make significant changes in their health. Gradual change, over a longer period of time, is more effective for long-term health solutions, rather than behavior changes that are expected to take place rapidly, over a short period of time. Further, many dieters are more comfortable using familiar technology to assist them with their dieting, as opposed to unfamiliar and possibly uncomfortable office and training room sessions with an actual dietitian and trainer. The present invention incorporates these concepts into a diet and exercise instructional platform based on individuals' preferences to increase the likelihood that individuals will adopt and follow a plan that helps them reach their personal goals.
An expert system determines user compliance with personalized diet and exercise plans and determines appropriate content and display characteristics for messages sent to a user's mobile device such that the user's compliance with the diet and exercise plan is increased. A number of message and display characteristics are monitored for groups of individuals to determine which ones the individuals respond to in a positive manner. Such display characteristics include text messages, pictures, voice patterns, etc. For text messages, the display characteristics may differ from each other in font, size of message, or tone of message.
In one embodiment, the expert system has a number of stored messages and display characteristics from which it may choose. Every time a message relating to the user's diet or physical activity is sent to the user by the expert system, a set of display characteristics is chosen to display the message. The initial set of display characteristics may be randomly chosen or there may be a pre-loaded initial set to be used for every user. The display characteristics are changed periodically and compliance data relating to whether the user was able to adhere to the plan when certain display characteristics are used is stored. This compliance data is stored in a personal profile, unique to each user. Compliance data can be measured in many different ways including, but not limited to, meal plan adherence, acceptance of specific food selections, and adherence to instructions and advice in messages. The expert system then determines which messages and display characteristics achieve the greatest compliance to the dietary and physical activity schedule and goals. These display characteristics are then used when subsequent messages are sent.
In addition to the novel features and advantages mentioned above, other features and advantages will be readily apparent from the following descriptions of the drawings and exemplary embodiments

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow chart of a process for determining message effectiveness according to an example embodiment;

FIG. 2 is an illustration of a process for generating a message by selecting message content and display characteristics according to an example embodiment; and

FIG. 3 is an illustration of a physical structure for an example embodiment.

DETAILED DESCRIPTION

Exemplary embodiments provide a predictive modeling system that determines a set of display characteristics to maximize a user's compliance to a personalized diet and exercise program.
Referring to Table 1, data that is tracked and stored for compliance analysis according to an example embodiment is shown. Data may be captured during a user enrollment process and during a user's interactions with the system. Data categories include: customer (data provided by customer related to customer's background or profile, financial, nutrition/diet, behaviors, physical activities, and messages), general (data related to user interactions with website), mobile (data about customers mobile device and its use), marketing (data about customer's introduction to system) and call center (data about customer's interaction with call center). Customer data includes initial profile data as well as diet and exercise plan and behavioral data. Initial profile data is data entered by the user during an enrollment process and may be changed by the user at any time. It may include such information as age, gender, income, height, weight, etc. Nutrition and diet data includes the user's diet plan selection, meal preparation and meal time preferences, preferred foods and substitutions, adherence data, and restaurant and shopping list data. Behavioral data includes identification of problem behaviors and strategies. Physical activity data include preferred activities and current activity level. Message data includes data regarding messages sent and received as well as related timing data.

TABLE 1

Category	Subcategory	Data Elements	Element Details

Customer	Profile	age
		gender
		income
		height
		weight	history
		state
		BMI	history
		education level
		ethnicity
		number in household
		children in household
		date of enrollment
		marital status
		time zone
		goal weight
		rate of weight loss selected	history
	Financial	household income
		occupation
	Nutrition/Diet	meal plan	calorie level
			name
			change date
			time on plan
		program	duration
			start date
			end date
			cancel date
			cancel reason
		meal preparation
		meal times	breakfast
			lunch
			snack
			dinner
		food eaten most frequently
		count of suggested menu opt-
		out
		substitution	made (in)
			what was substituted (out)
			meal
			meal item
			meal prep
		foods not selected (don't	at enrollment
		want)	ongoing
		recipes selected
		adherence (food diary)	breakfast
			lunch
			dinner
			snack
		restaurant
		shopping list
	Behaviors	problem behaviors
		strategies
		strategy success
		community involvement	member of forum
			posts
			response/guidance
	Physical Activity	participate
		current activity level
		activities	selected
			schedule
			level
			history
			calories expended
		smoke
	Messages	Messages sent	time
			time before response
		message type
		responses
General	website	page views
		time spent on page
		repeat views
		unique visitor
		returning visitor
		page before	website
			search engine
			city
		number of emails
		recipe views	download
		article views	downloads
		coupon use	Printed
			redeemed
		shopping list views	downloads
Mobile		mobile phone number
		mobile phone model
		mobile phone manufacturer
		wireless provider
		data plan
		cell phone use	frequency
			# of times per day
			times during day
			average call time
		geo code	lat or UTM (Universal Transverse
			Mercator Grid)
			long (or UTM)
		messaging plan
Marketing		heard about
		email provider
		preferred communication
		IM provider
Call center		use
		# calls to RD
		type of call
		call status
		customer data	name
			mobile number
		length of call
		resolution

As Table 1 indicates, user interactions may be monitored and data may be tracked according to each user's involvement with the system and participation in a diet and exercise program. Information about the frequency and nature of a user's interaction with the system such as the number of messages sent and received by the user over a period of time, the frequency and nature of responses to messages, and the frequency and nature of interaction with a website is collected to later determine user compliance levels.
Table 2 identifies queries that may be performed against the data that is tracked and stored. Queries related to navigation, performance, and operations may be performed. The queries provide an indication of the overall effectiveness of the system and may also be used to determine the effectiveness of individual aspects of the system. For example, various “campaigns” may be developed and promoted to all users or groups of users. User interactions may be monitored and tracked as described previously to determine the effectiveness of the various campaigns.

TABLE 2

Navigation	Performance	Operations

Count of active customers	Percent increase/decrease in	Customer acquisition cost per
compared to goal	number of active customers per	customer segment
	segment (by day/week/month)
Count of active customers	Number of active customers per	Number of net new prospects
per account (business) or	account or household	(by campaign)
household (consumer)
compared to goal
Count of products &	Number of customer referrals	Conversion rate of prospects to
services used by	by customer segment	customers (by campaign)
customers per segment
compared to goal
Percent share of wallet,	Percent increase/decrease in	Up-sell/cross-sell success rate
account or household per	number of products used by	by customer segment for
segment compared to	customers per segment (by	additional products and
goal	week/month)	services
Percent retention/	Percent increase/decrease in	Win/loss ratio per account or
renewal of active	share of wallet, account, or	household per segment
customers by segment	household per segment
compared to goal
Average tenure of	Customer loyalty ratings per	Customer retention cost per
customers by segment	segment	segment
compared to goal
Number of repeat orders	Customer loyalty ratings per	Number of “winback” customers
by segment compared to	distribution channel &	per segment
goal	interaction touch point
Number of product or	Increase/decrease in repeat	Percent of customers by
service upgrades by	orders/by segment	segment who have interacted
segment compared to		with us (with our partners)
goal		within the last quarter
Percent of customer	Increase/decrease in upgrades	Percent of active customers
outcomes met per	per segment	enrolled in/with activity in
segment		customer loyalty program per
		segment
Customer satisfaction	Customer satisfaction ratings	Number of customers “likely to
ratings per segment	per customer scenario &	defect”
	segment
Average time to complete	Task-specific customer	Product feature- or attribute-
key customer scenarios	satisfaction ratings per	specific customer satisfaction
compared to goals	interaction touch-point &	ratings
	channel
Percent of customer	Average time to complete key	Critical cycle times
responsiveness	tasks (e.g. Return the correct
objectives met compared	search result)
to goals for critical
customer-impacting tasks
Revenues per customer	Percent accuracy of information	Timeliness (as measured by
		customer)
Profitability per customer	Delivery timeliness and	Complexity of interactions (# of
by segment	accuracy	steps, # of interactions)
Average order size by	Percent cancellations	Inventory availability
customer segment
Average spending per	End-to-end transaction	Rates of returns, claims,
customer by customer	execution accuracy and speed	abandonment,
segment
Customer lifetime value	Growth of customer spending	Defect rates
by customer segment	by segment
	Customer acquisition and	Number of customer support
	retention costs by segment	requests
	Costs-to-serve by segment	Percent customer support
		interactions with 1-touch
		resolution
	Increase/decrease in sales	Early buying signals by
	from new products by segment	customer segment
	Increase/decrease in repeat	Costs-to-serve by channels,
	sales by segment	and touch points

The present invention may be used to increase compliance by measuring the effectiveness of various messages that are sent to users. Messages may be varied by content and presentation and then sent to different groups of users with similar personal profiles. Within a group, each member may receive identical or similar messages. After a set period of time, compliance data can be calculated for each group. Different messages can then be sent to the same groups or to newly formed groups. Continuing this process creates a comprehensive set of compliance data for a variety of message types and formats. The approach allows numerous data points to be collected for various types and formats of messages and allows an analyst to determine the effectiveness of various messages. More effective messages may be deployed to larger groups of users to increase overall compliance.
In order to build groups of similarly situated individuals, data may be purchased from other parties. Users may be placed into different test groups based upon similarities in their user profiles. Each member of a group may receive at least one message with similar display characteristics. For a period of time, different compliance measures may be recorded for each member in the group. Compliance measures for aggregate groups may be calculated as well. These compliance measures include, but are not limited to, percent increase/decrease in number of active customers, percent increase/decrease in number of products used by customers, and increase/decrease in repeat orders of product or service upgrades. These compliance measures may be based on a large sample size, and allow an analyst to test different display characteristics based on the type of compliance it seeks.
FIG. 1 is a flow chart of a process for determining message effectiveness according to an example embodiment. Once a user group is defined 10, the expert system determines if the time period for measuring message effectiveness has started 11. If the period has started, the expert system determines the substance of the message to be sent 12 to the users. Messages may relate to user goals, meal plans, diet and exercise activity reminders, and requests for responses or input related to an applicable diet and exercise plan. For example, if at least some of the users have accomplished their dietary goals for the week, the expert system may send a positive reinforcement message to the appropriate users. Other users may be asked to provide a current weight or to provide input regarding an activity performed recently. Then, the expert system chooses a set of display characteristics to use with the message based on such information as users' personal profiles 13. The messages are then transmitted for display on the mobile devices using the set of display characteristics 14. The user profiles are updated to indicate what messages were sent and received.
A message characteristics data store for tracking the messages that are sent may also be updated at this time 15. The message characteristics data store may track messages and related display characteristics that are currently in use or have been used for each user, the time period in which they were used, and the resulting changes to each user's personal profile during this time. Once the period for using the specified message characteristics has passed 16, the expert system calculates and analyzes the compliance data for the message 17. The compliance data may be based on the queries identified in Table 2. Messages that result in a greater level of compliance may be used more frequently and adapted for use in other groups or for other purposes.
FIG. 2 is an illustration of a process for generating a message by selecting message content and display characteristics according to an example embodiment. In this example, the expert system chooses one of each of the following display characteristics to form a set: message tone (e.g., positive, negative, neutral) 20, an avatar 21, a font 22, and a border 23. The display characteristics are not limited to those shown, but may also include other graphics, certain words, certain sentences, voice tones, etc. The message characteristics are then combined to create a message for display on the mobile device. In this example, a congratulatory message with the positive phrases underlined 24, a black border 25, and a young woman avatar 26 are displayed on a cellular phone 27.
FIG. 3 shows an embodiment of the physical structure of the system. Each of the connections mentioned here permit data to flow in both directions. A laptop or desktop personal computer 100 is connected to the server 120 through the internet 110. The user may connect to a website to create an account and enter personal information and preferences for creating a profile. The server 120 is connected to one or more databases 122, 124 comprising user data, nutrition provider data (nutritional data related to meals offered by a plurality of meal providers), diet, and exercise data, message data, progress data, compliance data, restaurant, shopping, and entertainment establishment data, reward data, and other data as may be required to provide the features and functionality of the present invention. The server 120 is connected to communication networks 130 (comprising various data transmitters and receivers) through the internet 110. The various data transmitters and receivers of the communication networks 130 facilitate communications with the user's portable technology 140 which includes cellular or mobile phones, personal digital assistants, or any other portable device capable of sending and receiving communications through the communication networks 130 and displaying them for a user. An expert system at the server uses the individual's account information, including information about the individual's mobile phone, to tailor and send to the individual messages to reinforce and motivate healthy habits.
In an example embodiment, the expert system is constructed using the J2EE programming language in conjunction with a SQL based database (like Microsoft SQL Server or Oracle DB). AJAX, Active X, and Java components may also be used to handle various aspects of the system. The mobile component of the overall system is constructed using the J2ME programming language sending wireless requests to the expert system over common carrier communication protocols. Communication between the mobile component and the expert system is constructed using XML language structures.
Any embodiment may include any of the optional or preferred features of the other embodiments. The exemplary embodiments herein disclosed are not intended to be exhaustive or to unnecessarily limit the scope of the invention. The exemplary embodiments were chosen and described in order to explain the principles so that others skilled in the art may practice the invention. Having shown and described exemplary embodiments, those skilled in the art will realize that many variations and modifications may be made to affect the described invention. Many of those variations and modifications will provide the same result and fall within the spirit of the claimed invention. It is the intention, therefore, to limit the invention only as indicated by the scope of the claims.

Claims

1. A computerized method for tracking, monitoring, and analyzing message data to increase compliance with personalized diet and exercise plans, comprising at least one server executing programming instructions for:

(a) storing in at least one user profile database for a plurality of users profile data comprising:

(1) contact information for said users;

(2) personal information for said users;

(3) dietary and exercise plan data for said users; and

(4) compliance data for said users;

(b) storing in at least one message database:

(1) message content data for communicating messages to said users;

(2) display characteristics data for formatting said messages;

(c) identifying a group of users selected from said plurality of users according to similarities in said profiles for said users;

(d) selecting for said group of users:

(1) a plurality of messages from said message content data; and

(2) display characteristics from said display characteristics data for formatting said plurality of messages;

(e) setting a time period for transmitting said plurality of messages and said plurality of display characteristics;

(f) during said time period,

(1) transmitting to mobile devices for said group of users said messages with at least a portion of said display characteristics; and

(2) receiving from mobile devices for said group of users responses to said messages formatted with said display characteristics;

(g) after said time period, calculating a plurality of compliance measures for said messages and said display characteristics based on said responses from said group of users; and

(h) transmitting to said mobile devices for said group of users additional messages with display characteristics determined from said compliance measures to result in positive responses from said group of users.

2. The computerized method of claim 1, further comprising updating said compliance data for said group of users according to said compliance measures.

3. The computerized method of claim 1, wherein said compliance measures comprise calculating for each of said users a number of messages received and acknowledged over said time period.

4. The computerized method of claim 1, wherein said compliance measures comprise a number of users who have responded to said transmitted messages, a number of users who have not responded to said transmitted messages, and a number of users who have quit a respective diet and exercise plan within said time period.

5. The computerized method of claim 1, wherein said compliance measures are selected from the group consisting of:

meal plan adherence, acceptance of food selections, and instruction adherence, user frequency of responses, user nature of responses, user frequency of interaction with a web site, and user nature of interaction with a web site.

6. The computerized method of claim 1, wherein transmitting said messages with at least a portion of said display characteristics to mobile devices for said group of users comprises transmitting at least one identical message to each user in said group of users.

7. The computerized method of claim 1, wherein selecting a plurality of messages for said group of users comprises selecting messages from the group consisting of: diet goals, diet reminders, activity goals, and activity reminders.

8. The computerized method of claim 1, wherein said display characteristics are selected from the group consisting of: text font, text size, text underlining, border, graphic, and voice pattern.

9. A computerized system for tracking, monitoring, and analyzing message data to increase compliance with personalized diet and exercise plans, comprising:

(a) at least one user profile database storing for a plurality of users profile data comprising:

(1) contact information for said users;

(2) personal information for said users;

(3) dietary and exercise plan data for said users; and

(4) compliance data for said users;

(b) at least one message database storing:

(1) message content data for communicating messages to said users;

(2) display characteristics data for formatting said messages;

(c) at least one server executing programming instructions to:

(1) identify a group of users selected from said plurality of users according to similarities in said profiles for said users;

(2) select for said group of users:

(i) a plurality of messages from said message content data; and

(ii) display characteristics from said display characteristics data for formatting said plurality of messages;

(3) set a time period for transmitting said plurality of messages and said plurality of display characteristics;

(4) during said time period,

(i) transmit to mobile devices for said group of users said messages with at least a portion of said display characteristics; and

(ii) receive from mobile devices for said group of users responses to said messages;

(5) after said time period, calculate a plurality of compliance measures for said messages and said display characteristics based on said responses from said group of users; and

(6) transmit to said mobile devices for said group of users additional messages with display characteristics determined from said compliance measures to result in positive responses from said group of users.

10. The computerized system of claim 9, wherein said server further executes instructions to update said compliance data for said group of users according to said compliance measures.

11. The computerized system of claim 9, wherein said compliance measures comprise calculating for each of said users a number of messages received and acknowledged over said time period.

12. The computerized system of claim 9, wherein said compliance measures comprise a number of users who have responded to said transmitted messages, a number of users who have not responded to said transmitted messages, and a number of users who have quit a respective diet and exercise plan within said time period.

13. The computerized system of claim 9, wherein said compliance measures are selected from the group consisting of:

14. The computerized system of claim 9, wherein transmitting said messages with at least a portion of said display characteristics to mobile devices for said group of users comprises transmitting at least one identical message to each user in said group of users.

15. The computerized system of claim 9, wherein selecting a plurality of messages for said group of users comprises selecting messages from the group consisting of: diet goals, diet reminders, activity goals, and activity reminders.

16. The computerized system of claim 9, wherein said display characteristics are selected from the group consisting of: text font, text size, text underlining, border, graphic, and voice pattern.

17. A computerized method for tracking, monitoring, and analyzing message data to increase compliance with personalized diet and exercise plans, comprising at least one server executing programming instructions for:

(1) contact information for said users;

(2) personal information for said users;

(3) dietary and exercise plan data for said users; and

(4) compliance data for said users;

(b) storing in at least one message database:

(1) message content data for communicating messages to said users;

(2) display characteristics data for formatting said messages;

(c) transmitting to a group of users selected from said plurality of users according to similarities in said profiles for said users:

(1) a plurality of messages selected from said message content data; and

(2) display characteristics for formatting said plurality of messages selected from said display characteristics data;

(d) setting a time period for:

(1) transmitting to mobile devices for said group of users said plurality of messages and at least a portion of said display characteristics; and

(e) after said time period, calculating a plurality of compliance measures for said messages and said display characteristics based on said responses from said group of users to determine which messages and display characteristics result in positive responses from said group of users.

17. The computerized method of claim 16, further comprising updating said compliance data for said group of users according to said compliance measures.

18. The computerized method of claim 17, further comprising transmitting to each of said users in said group of users additional messages and display characteristics for formatting said additional messages selected for each of said users according to said compliance data for said user.

19. The computerized method of claim 16, wherein said compliance measures are selected from the group consisting of:

20. The computerized method of claim 16, wherein said display characteristics are selected from the group consisting of: text font, text size, text underlining, border, graphic, and voice pattern.