Abstract: A network computing system receives local device data from a mobile computing device of a person within a vehicle. The local device data may include sensor data from one or more sensors of the mobile computing device, and location data determined from a position-determination resource of the mobile computing device. The network computing system may detect a vehicle collision event based on the local device data. Additionally, the network computing system may determine a classification of the vehicle collision event based on the local device data.

Abstract: Embodiments of a method and system for improving sleep characterization and/or a sleeping-related disorder for a user associated with a sleep session can include receiving a log of use dataset corresponding to user digital communication behavior at a mobile device, the log of use dataset associated with the sleep session; receiving a supplementary dataset characterizing activity of the user and/or mobile device, the supplementary dataset associated with the sleep session; characterizing a sleep-related parameter for the user based on at least one of the log of use dataset and the supplementary dataset; determining a sleep care plan for the user based on the sleep-related parameter, the sleep care plan including a therapeutic intervention; and promoting a therapeutic intervention to the user according to the sleep care plan.

Abstract: A method and system for providing patient indications to an entity, the method comprising: for each of a set of patients: by way of an application executing at a mobile computing device, accessing a sensor system and a log of use of a communication application executing on the mobile computing device; receiving a survey response dataset; generating a behavioral dataset, derived from the sensor system and the log of use; generating a predictive model derived from at least one of the survey response dataset and the behavioral dataset; generating comparisons of outputs of blocks of the method to threshold conditions; producing a set of indications corresponding to the set of patients, derived from generation of, for each of the set of patients, an indication in response to the comparisons; and transmitting a portion of the set of indications to the entity according to a resource constraint of the entity.

Abstract: A method and system for modeling behavior and a psychotic disorder-related state of a patient, the method comprising: receiving a log of use dataset associated with communication behavior of the patient during a time period; receiving a supplementary dataset characterizing mobility-behavior of the patient during the time period; generating a predictive model based upon a passive dataset derived from the log of use dataset and the supplementary dataset; transforming at least one of the passive dataset and an output of the predictive model into an analysis of a psychotic episode-risk state of the individual associated with at least a portion of the time period; and upon detection that parameters of the psychotic episode-risk state satisfy at least one threshold condition, automatically initiating provision of a therapeutic intervention for the individual by way of at least one of the computing system and the mobile communication device.

Abstract: A method and system for modeling behavior and depression state of an individual, the method comprising: receiving a log of use dataset associated with communication behavior of the individual during a time period; receiving a supplementary dataset characterizing activity of the individual during the time period; receiving a survey dataset including responses, to at least one of a set of depression-assessment surveys, associated with a set of time points of the time period; generating a predictive analysis of a depression-risk state of the individual associated with at least a portion of the time period, from at least one of the log of use dataset, the supplementary dataset, and the survey dataset; and generating an alert upon detection that a set of parameters from the predictive analysis of the depression-risk state satisfy a threshold condition.