[Researchers] Summary Statistics

Domain	Variable Name	Description of Variable	Description of What it Measures
GPS
	Observed duration	The total time when the GPS is on.	This variable quantifies the missingness and the uncertainty in all other estimates.
	Observed duration in day	The total time when the GPS is on from 8AM to 8PM.	This variable quantifies the missingness in daytime and the majority of uncertainty in all other estimates.
	Observed duration at night	The total time when the GPS is on from 8PM to 8AM.	This variable quantifies the missingness at night and the minority of uncertainty in all other estimates since the user is most likely at home.
	Home time	Time spent at home over the course of a day (in hours).	“Home” is the most frequently visited significant location for a person between the hours of 8pm and 8am each day over the course of follow up.
	Distance traveled	Total distance travelled over the course of a day (in km).	The sum of lengths of all flights. A flight is defined to be a longest straight-line trip of a particle from one location to another without a directional change or pause.
	Radius of gyration	Average radius that a person travels from their center over the course of a day (in km).	Centroid = the average of each ‘place visited’ (see definition ‘significant location’) over the course of a day, with weights proportional to the amount of time spent in the location. The radius of gyration is calculated using a time-weighted average of the distance between each place and the centroid, where weights are measured in the same way.
	Maximum diameter	Largest distance between any two places that a person visited in a day (in km).
	Maximum distance from home	Largest distance between any places that a person visited in a day and their home (in km).
	Number of significant locations	Number of significant visited at any point over the course of a day.	Significant locations are distinct pauses which are at least 15 minutes long and 50 meters apart. They are determined using K-means clustering on locations that a patient visits over the course of follow up. Set K=K+1 and repeat clustering until two significant locations are within 100 meters of one another. Then use the results from the previous step (K-1) as the total number of significant locations.
	Total flight time	Total time spent in flight over the course of a day (in hours).	A flight is defined to be a longest straight-line trip of a particle from one location to another without a directional change or pause.
	Average flight length	Average of the length of all flights (straight line movement) that took place over the course of a day (in km).	GPS is converted into a sequence of flights (straight line movement) and pauses (time spent stationary). A flight is defined to be a longest straight-line trip of a particle from one location to another without a directional change or pause. Note that a long flight could be composed of several short flights with different directions, but when calculating the average, it is the mean of those short flights.
	Standard deviation of flight length	Standard deviation of the length of all flights (straight line movement) that took place over the course of a day (in km).	GPS is converted into a sequence of flights (straight line movement) and pauses (time spent stationary). The standard deviation of flights of the day is reported.
	Average flight duration	Average of the duration of all flights (straight line movement) that took place over the course of a day (in hours).	GPS is converted into a sequence of flights (straight line movement) and pauses (time spent stationary). The average of the duration of flights of the day is reported.
	Standard deviation of flight duration	Standard deviation of the duration of all flights (straight line movement) that took place over the course of a day (in hours).	GPS is converted into a sequence of flights (straight line movement) and pauses (time spent stationary). The standard deviation of the duration of flights of the day is reported.
	Total pause time	Total time spent in pause over the course of a day (in hours).	A pause is defined to be a longest time spent stationary without a directional change or flight.
	Average pause duration	Average of the duration of all pauses that took place over the course of a day (in hour).	We consider that a participant has a pause if the distance that he has moved during a 30-s period is less than r m. By default, r=10..
	Standard deviation of pause duration	Standard deviation of the duration of all pauses that took place over the course of a day (in hour).	GPS is converted into a sequence of flights (straight line movement) and pauses (time spent stationary). The standard deviation of duration of pauses over the course of a day is reported.
	Significant location entropy	Entropy measure based on the proportion of time spent at significant locations over the course of a day.	Letting p_i be the proportion of the day spent at significant location I, significant location entropy is calculated as -\sum_{i} p_i\log(p_i), where the sum occurs over all non-zero p_i for that day.
	Physical circadian rhythm	A continuous measurement of routine in the interval [0,1] that scores a day with 0 if there was a complete break from routine and 1 if the person followed the exact same routine as have in every other day of follow up.	For a detailed description of how this measure is calculated, see Canzian and Musolesi's 2015 paper in the Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, titled "Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis." Their procedure was followed using 30-min increments as a bin size.
	Physical circadian rhythm stratified	A continuous measurement of routine in the interval [0,1] that scores a day with 0 if there was a complete break from routine and 1 if the person followed the exact same routine as have in every other day of follow up.	Calculated in the same way as Physical circadian rhythm, except the procedure is repeated separately for weekends and weekdays.
Texts
	Number of outgoing texts	The total number of texts sent by the subject.	Measured in counts.
	Total outgoing text length	The total number of characters texted by the subject.	Measured in characters.
	Texting out-degree	The total number of unique subjects to which the subject sent texts.	Measured in unique counts.
	Number of incoming texts	The total number of texts received by the subject.	Measured in counts.
	Total incoming text length	The total number of characters of text received by the subject.	Measured in characters.
	Texting in-degree	The total of unique individuals who texted to the subject.	Measured in unique counts.
	Texting reciprocity	The total number of times a text is received or sent to a unique person and day without response.	The reciprocity of incoming texts is the number of texts sent from a unique individual to the subject, which is next followed up on the same day with at least one more text sent from that same individual without a response from the subject. The reciprocity of outgoing texts is the number of texts received by the subject from a unique individual, which is next followed up on the same day with at least one more text sent by the subject to that same individual without a response from that individual. Texting reciprocity is the sum of these totals.
	Texting responsiveness	The mean time before sending a text after a text is received.	Measured in hours.
Calls
	Number of outgoing calls	The total number of outgoing calls initiated by the subject.	Measured in counts.
	Total outgoing call duration	The total amount of time spent on calls initiated by the subject.	Measured in minutes.
	Call out-degree	The total number of unique calls initiated by the subject.	Measured in unique counts.
	Number of incoming calls	The total number of calls received by the subject.	Measured in counts.
	Total incoming call durations	The total amount of time spent on calls received by the subject.	Measured in minutes.
	Call in-degree	The total number of unique calls received by the subject.	Measured in unique counts.
	Call reciprocity	The total number of times a call is received or sent to a unique person and day without response.	The reciprocity of incoming calls is the number of calls sent from a unique individual to the subject, which is next followed up on the same day with at least one more call sent from that same individual without a response from the subject. The reciprocity of outgoing calls is the number of calls received by the subject from a unique individual, which is next followed up on the same day with at least one more call sent by the subject to that same individual without a response from that individual. Call reciprocity is the sum of these totals.
	Call responsiveness	The mean time before initiating a call after receiving a call.	Measured in hours.
Accelerometer
	Accelerometer coverage fraction	Fraction of a participant's follow-up time during which accelerometer measurements have been recorded.	Follow-up time is divided into windows of uniform length (e.g. minutes or hours).  The fraction of windows with more than a set minimum number of accelerometer measurements is reported.
	Accelerometer univariate summaries	A single accelerometer observation consists of three measurements, one for each axis of the device.  A univariate summary combines these measurements into a single interpretable number.  Univariate summaries include the Signal Magnitude Area (SMA), the Vector Magnitude (VM), and the Sum of Amplitudes (SA).	Given an accelerometer observation (x, y, z), the univariate summaries are calculated as SMA = |x| + |y| + |z|, VM = (x2 + y2 + z2)1/2, and SA = x + y + z.  The unit for each of these summaries is meters-per-second-squared (m/s2).
	Accelerometer signal variability	A measure of the variability of consecutive accelerometer measurements during a given time window.	For the given window of accelerometer observations, univariate summaries are computed and the corresponding sample variance is reported.
	Acceleration direction (Device orientation)	An estimate of the direction (x, y, z) in which the phone is accelerating during a given time window, with respect to the phone's frame of reference.  In many circumstances (e.g. when the phone is at rest), this direction is directly upward in the Earth's frame of reference.	For accelerometer observations {(xi, yi, zi)} from the given time window, the normalized vector of (median{xi}, median{yi}, median{zi}) is reported.
	Device proximity classification	A binary classifciation corresponding to whether the phone is "on-person" or "off-person" during a window of time.  A phone is considered "on-person" if the user is carrying it (e.g. in a pocket or handbag) or if the user is physically interacting with it (e.g. making a phone call or playing a game) at any point during the window; otherwise the phone is considered "off-person."	The given window of observations is classified as "on-person" when the accelerometer signal variability exceeds the variability that is expected from sensor noise.  The window is classified as "off-person" when the signal variability may be attributed to sensor noise alone.
Power State or OS
	Total screen events	The total number of times the screen has been turned on during a given observation window.	A record of times when the phone screen has been turned on or off is obtained from the phone's operating system.  A "screen event" occurs when the screen is turned on and subsequently turned off; the number of such events during the given window is reported.
	Total unlock events	The total number of times the phone has been unlocked during a given observation window.	A record of times when the phone has been unlocked is obtained from the phone's operating system; the number of such events during the given window is reported
	Total power events	The total number of discreet periods that the phone has been connected to a power supply during a given observation window.	A record of times when the phone has been connected or disconnected from a power source is obtained from the phone's operating system.  A "power event" occurs when the phone is connected and subsequently disconntected; the number of such events during the given window is reported.
Multiple Domains
	Sleep onset time		A longitudinal model computes the distribution of sleep onset timing per day according to a parametric model. This model is then combined with daily activity data to compute the most likely time for that day's sleeping onset.
	Awake onset time		A longitudinal model computes the distribution of awaking onset timing per day according to a parametric model. This model is then combined with daily activity data to compute the most likely time for that day's waking onset.
	Sleep duration	The total amount of time estimated to be asleep.	The sleep awake time subtracted by the sleep onset time.