METHOD FOR PROVIDING HEALTH THERAPEUTIC INTERVENTIONS TO A USER

1 . A system for automatically promoting an outcome to a user, the system comprising:

a client application executable on a mobile computing device associated with the user, wherein the mobile computing device comprises a sensor, wherein the mobile computing device collects a set of datasets, the set of datasets comprising:

a first passive dataset associated with digital patterns of the user at the mobile computing device;

a second passive dataset collected from the sensor;

a first active dataset collected from the client application, wherein the first active dataset comprises a set of inputs from the user;

a set of trained models; and

a computing system comprising the set of trained models and in communication with the mobile computing device, wherein the computing system:

generates a dynamic plan for the user with the set of trained models and based on the set of datasets, wherein the dynamic plan comprises a first output to the user, wherein the first output is conveyable at the mobile computing device;

automatically promotes the first output to the user at the mobile computing device;

receives a second set of inputs from the user in response to the first output;

with the set of trained models, automatically generates a second dynamic plan for the user based on the second set of inputs; and

automatically promotes a second output to the user at the mobile computing device in accordance with the second dynamic plan.

2 . The system of claim 1 , wherein the first output to the user is provided at a first time period, wherein the first time period is determined based on a set of time periods associated with the set of datasets.

3 . The system of claim 2 , wherein the first time period is determined with the set of trained models.

4 . The system of claim 1 , wherein the set of digital patterns comprises at least one of: a frequency of messages sent by the user from the mobile computing device, a length of messages sent by the user from the mobile computing device, and a ratio of inbound messages received at the mobile computing device versus outbound messages sent from the mobile computing device.

5 . The system of claim 1 , wherein the computing system further determines a set of feature vectors based on the first and second passive datasets and the first active dataset, wherein the set of feature vectors is determined based on a factor analysis approach with a linking analysis

6 . The system of claim 1 , wherein the computing sys tem comprises a remote computing subsystem in communication with the mobile computing device.

7 . A method for automatically promoting an outcome to a user, the method comprising:

receiving a first passive dataset from a mobile computing device of the user, wherein the first passive dataset comprises a log of use dataset associated with digital behavior of the user at the mobile computing device, wherein the log of use dataset corresponds to a first time period;

receiving a second passive dataset from the mobile computing device, wherein the second passive dataset is collected from a sensor of the mobile computing device, wherein the second passive dataset corresponds to a second time period;

receiving a first active dataset from a client application executable on the mobile computing device, wherein the first active dataset comprises a set of entries from the user, wherein the first active dataset corresponds to a third time period;

with a set of trained models, generating a dynamic plan for the user, comprising determining a first output for the user based on processing the first passive dataset, the second passive dataset, and the first active dataset;

automatically promoting the first output to the user at the mobile computing device at a fourth time period, wherein the fourth time period is determined based on the first, second, and third time periods;

receiving a set of inputs from the user in response to the first output;

with the set of trained models, automatically generating a second dynamic plan for the user based on the set of inputs; and

automatically promoting a second output to the user at the mobile computing device in accordance with the second dynamic plan.

8 . The method of claim 7 , wherein the trained model comprises a machine learning model.

9 . The method of claim 7 , further comprising determining a set of feature vectors based on the first and second passive datasets and the first active dataset, wherein the set of feature vectors is determined based on a factor analysis approach with a linking analysis

10 . The method of claim 7 , further comprising receiving a second active dataset from a second user, wherein the dynamic plan, for the user is further determined based on the second active dataset.

11 . The method of claim 10 , wherein the first user is assigned to the second user as a part of a program.

12 . The method of claim 7 , wherein the fourth time period is further determined with the set of trained models.

13 . The method of claim 12 , wherein the fourth time period is further determined based on historical information associated with the user.

14 . The method of claim 13 , wherein the historical information comprises a set of interactions of the user with the client application.

15 . The method of claim 7 , wherein the log of use dataset comprises a number of inbound messages received at the mobile computing device and a number of outbound messages sent from the mobile computing device.

16 . The method of claim 7 , wherein the set of entries is collected from a set of digital surveys.

17 . The method of claim 16 , wherein the dynamic care plan comprises a second set of digital surveys.

18 . A method for automatically promoting an outcome to a user, the method comprising:

receiving a set of datasets from a mobile computing device of the user, wherein the set of datasets comprises:

a first passive dataset associated with digital behavior of the user at the mobile computing device;

a second passive dataset from a sensor of the mobile computing device;

an active dataset from a client application executable on the mobile computing device, wherein the first active dataset comprises a set of entries from the user;

with a set of trained models, generating a dynamic plan for the user, comprising determining a first output for the user based on processing the set of datasets;

automatically promoting the first output to the user at the mobile computing device at a particular time period, wherein the particular time period is determined based on a set of time periods associated with the set of datasets;

receiving a set of inputs from the user in response to the first output;

with the set of trained models, automatically generating a second dynamic plan for the user based on the set of inputs; and

automatically promoting a second output to the user at the mobile computing device in accordance with the second dynamic plan.

19 . The method of claim 18 , further comprising receiving a second active dataset from a second user, wherein the dynamic plan for the user is further determined based on the second active dataset.

20 . The method of claim 19 , wherein the first user is assigned to the second user as a part of a program.